Dynamic Advancements in Teaching and Learning Based Technologies: New Concepts (Premier Reference Source)

Dynamic Advancements in Teaching and Learning Based Technologies: New Concepts

Eugenia M.W. Ng The Hong Kong Institute of Education, Hong Kong Nikos Karacapilidis University of Patras, Greece Mahesh S. Raisinghani TWU School of Management, USA

INFORMATION SCIENCE REFERENCE Hershey • New York

Director of Editorial Content: Director of Book Publications: Acquisitions Editor: Development Editor: Publishing Assistant: Typesetter: Production Editor: Cover Design:

Kristin Klinger Julia Mosemann Lindsay Johnston Michael Killian Casey Conapitski Casey Conapitski Jamie Snavely Lisa Tosheff

Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2011 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Dynamic advancements in teaching and learning based technologies : new concepts / Eugenia M.W. Ng, Nikos Karacapilidis and Mahesh S. Raisinghani, Editors. p. cm. Includes bibliographical references and index. Summary: "This book explores the impact of Web-based technology on the design, implementation and evaluation of the learning and teaching process, as well as the development of new activities, relationships, skills, and competencies for the various actors implied in such processes"--Provided by publisher. ISBN 978-1-60960-153-9 (hardcover) -- ISBN 978-1-60960-155-3 (ebook) 1. Web-based instruction. I. Ng, Eugenia M. W., 1959- II. Karacapilidis, Nikos, 1967- III. Raisinghani, Mahesh S., 1967- IV. Title. LB1044.87.D96 2011 378.1'7344678--dc22 2010047284 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher.

Table of Contents

Preface . ................................................................................................................................................ xv Section 1 Chapter 1 The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System...................................... 1 Mei-Yu Chang, National Hsinchu University of Education, Taiwan Wernhuar Tarng, National Hsinchu University of Education, Taiwan Fu-Yu Shin, Chien-Kuo Elementary School, Taiwan Chapter 2 Student and Teacher Perspectives Testing a System for Adaptive e-Learning...................................... 16 Carla Limongelli, Roma Tre University, Italy Filippo Sciarrone, Open Informatica, Italy Marco Temperini, Sapienza University of Rome, Italy Giulia Vaste, Roma Tre University, Italy Chapter 3 A Case-Based Approach to Adaptive Hypermedia Navigation............................................................. 46 Alessandro Micarelli, Roma Tre University, Italy Filippo Sciarrone, Roma Tre University, Italy Fabio Gasparetti, Roma Tre University, Italy Chapter 4 Animated Pedagogical Agents: The Effect of Visual Information on a Historical Figure Application................................................................................................................. 66 R. Heller, Athabasca University, Canada M. Procter, Athabasca University, Canada

Chapter 5 A Case Study of Ontology-Driven Development of Intelligent Educational Systems.......................... 79 Gordon Deline, CBC/Radio-Canada, Canada Fuhua Lin, Athabasca University, Canada Dunwei Wen, Athabasca University, Canada Dragan Gaševic, Athabasca University, Canada Kinshuk, Athabasca University, Canada Section 2 Chapter 6 Learning with Online Activities: What Do Students Think About Their Experience?.......................... 96 Salam Abdallah, Abu Dhabi University, UAE Chapter 7 Minimal Functionalities of Course Management Systems: A Faculty Perspective............................. 122 V. Adlakha, University of Baltimore, USA A. Aggarwal, University of Baltimore, USA Chapter 8 Α Learning Platform for the Introduction of Remote Sensing Principles in Higher Education in a Blended Learning Collaborative Environment............................................................ 142 Nektaria Adaktilou, University of Athens, Greece Costas Cartalis, University of Athens, Greece George Kalkanis, University of Athens, Greece Chapter 9 An Evaluation of Blending Technology with Pedagogy for Teacher Education and its Implication for their Classroom Teaching........................................................................................... 162 Carol Kahan Kennedy, Fordham University, USA Maureen Hinkley, Fairfield University, USA Section 3 Chapter 10 Redefining Web Users’ Optimal Flow Experiences in Online Environments: An Empirical Analysis......................................................................................................................... 181 Anshu Saxena Arora, Savannah State University-Savannah, USA Mahesh S. Raisinghani, TWU School of Management, USA

Chapter 11 Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!.......... 199 Nikos Karacapilidis, University of Patras & Research Academic Computer Technology Institute, Greece Manolis Tzagarakis, University of Patras & Research Academic Computer Technology Institute, Greece Nikos Karousos, Hellenic Open University, Greece George Gkotsis, University of Patras, Greece Vassilis Kallistros, Research Academic Computer Technology Institute, Greece Spyros Christodoulou, Research Academic Computer Technology Institute, Greece Christos Mettouris, Research Academic Computer Technology Institute, Greece Dora Nousia, Research Academic Computer Technology Institute, Greece Chapter 12 Integrating XML Technologies and Open Source Software for Personalization in E-Learning.............................................................................................................. 216 Hsun-Ming Lee, Texas State University-San Marcos, USA Robert Davis, Texas State University-San Marcos, USA Yu-Liang Chi, Chung Yuan Christian University, Taiwan Chapter 13 Autism and Family Interventions Through Technology: A Description of a Web-Based Tool to Educate Fathers of Children with Autism............................................................ 232 Richard E. Ferdig, Kent State University, USA Hilary G. Amberg, University of Florida, USA Jennifer H. Elder, University of Florida, USA Susan A. Donaldson, University of Florida, USA Gregory Valcante, University of Florida, USA Roxanna Bendixen, University of Florida, USA Section 4 Chapter 14 Learner-Centered Teaching and the Use of Technology...................................................................... 248 Annette Greer, East Carolina University, USA Vivian Mott, East Carolina University, USA Chapter 15 Effective Teaching with Technology in Adult Education.................................................................... 264 Victor C. X. Wang, North Central University, USA

Chapter 16 The Role of Adult Education in Online Delivery of Career and Technical Education........................ 280 Victor M. Hernández-Gantes, University of South Florida, USA Chapter 17 The Role of Learning Styles and Technology...................................................................................... 299 Royce Collins, Kansas State University, USA Chapter 18 CTowards an Effective ICT-based University Learning. The tacit and the Interaction Dimensions........................................................................................................................ 316 Manuel Ahedo, Rovira i Virgili University, Spain Chapter 19 What can we learn from the Past about Future Technological Trends in Adult Education?................ 333 John Hope, University of Auckland, New Zealand Compilation of References ............................................................................................................... 354 About the Contributors .................................................................................................................... 395 Index.................................................................................................................................................... 405

Detailed Table of Contents

Preface . ................................................................................................................................................ xv Section 1 Chapter 1 The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System...................................... 1 Mei-Yu Chang, National Hsinchu University of Education, Taiwan Wernhuar Tarng, National Hsinchu University of Education, Taiwan Fu-Yu Shin, Chien-Kuo Elementary School, Taiwan This study combined ideas from learning hierarchy and scaffolding theory to design a web-based, adaptive learning system to investigate the effectiveness of scaffolding for elementary school students having different levels of learning achievement. The topic chosen for learning was the Three States of Water. A quasi-experiment was conducted. In this experiment, students were divided into three groups: control group (without scaffolds), experimental group A (scaffolds providing by on-line conversation) and experimental group B (scaffolds providing by face-to-face conversation). The experimental results showed significant improvement for students after they had studied using the web-based, adaptive learning system. Specifically, scaffolds in the form of face-to-face conversations greatly enhanced the learning of high-achievement students. However, there were no significant differences between the low-achievement students with or without the provision of scaffolds. It was also discovered that the web-based, adaptive learning system could help students develop their learning responsibility. Chapter 2 Student and Teacher Perspectives Testing a System for Adaptive e-Learning...................................... 16 Carla Limongelli, Roma Tre University, Italy Filippo Sciarrone, Open Informatica, Italy Marco Temperini, Sapienza University of Rome, Italy Giulia Vaste, Roma Tre University, Italy Personalization is becoming a mandatory requirement in Web-based Education and long distance learning in general, representing a flexible way of learning the exact amount of knowledge to reach a given learning goal. This approach saves time and money and it is particularly suited for life-long learning.

The drawback is that the teacher has to produce some effort to prepare didactic material and while research in this field proposes several intelligent systems providing personalization with advanced didactic strategies, teacher’s point of view is less considered. In this chapter we extend our previous work that aimed to build an adaptive system for education called LS-Plan, taking into account both teacher’s and student’s needs. In particular we carried out a comprehensive evaluation of the system embedded into an Adaptive Educational Hypermedia called Lecomps5, in order to experiment and prove the added value of the system. Chapter 3 A Case-Based Approach to Adaptive Hypermedia Navigation............................................................. 46 Alessandro Micarelli, Roma Tre University, Italy Filippo Sciarrone, Roma Tre University, Italy Fabio Gasparetti, Roma Tre University, Italy Hypermedia, with its combination of multimedia and non-linear organization of links among informative nodes, provides a highly interactive environment. In structured domains such as Web-based Educational Systems, the complexity of the learning domain often requires a large set of learning nodes and conceptual interrelationships that can cause several issues, e.g.: lack of comprehension, disorientation and inefficacious learning strategies. In this chapter we propose a new approach to guided navigation in hypermedia-based domains, suitable for helping users in structured and complex learning environments such as cultural heritage domains. Our proposal draws inspiration from the Case-Based Reasoning paradigm associated with a hypermedia structural analysis. In particular, our presentation highlights the use of a hybrid architecture for Adaptive Navigation Support, where the indexing problem of the casebased reasoner is solved by way of a sub-symbolic approach. A case study in the Neo-Realist Italian Cinema domain is discussed along with a formal and controlled evaluation that proves the advantages of the proposed approach. Chapter 4 Animated Pedagogical Agents: The Effect of Visual Information on a Historical Figure Application................................................................................................................. 66 R. Heller, Athabasca University, Canada M. Procter, Athabasca University, Canada The role of Animated Pedagogical Agents (APAs) depends on an understanding of the persona effect as a mechanism for increasing student engagement and motivation. We argue that historical figure applications of APAs may be helpful to identify the parameters that give rise to a persona effect. Given the importance of visual information, an experimental approach was used to examine how different image conditions would affect perception of a historical figure APA interaction. Eighty-eight participants were randomly assigned to one of three conditions; no image, static image, or animated image. Contrary to expectations, the no image condition was associated with significantly higher ratings for 6 of the 12 measures, including 3 measures of social presence. These findings stand in contrast to previous research and suggest that historical figure applications may be unique in their evocation of a persona effect and valuable for understanding the nature of the persona effect.

Chapter 5 A Case Study of Ontology-Driven Development of Intelligent Educational Systems.......................... 79 Gordon Deline, CBC/Radio-Canada, Canada Fuhua Lin, Athabasca University, Canada Dunwei Wen, Athabasca University, Canada Dragan Gaševic, Athabasca University, Canada Kinshuk, Athabasca University, Canada This chapter presents a case study of ontology-driven development of intelligent educational systems. Following a review of literature related to ontology development, ontology-driven software development, and traditional software engineering, we developed an ontology-driven software development methodology appropriate for intelligent ontology-driven systems which have ontologies as key execution components, such as e-Advisor, and which is biased toward an integration of incremental and iterative ontology development and downstream Model Driven Architecture for development of software components. Section 2 Chapter 6 Learning with Online Activities: What Do Students Think About Their Experience?.......................... 96 Salam Abdallah, Abu Dhabi University, UAE Learning through social interactions and critical thinking is becoming a fundamental teaching approach, especially for adult students. This approach promotes holistic and deeper understanding for the subject being learned. Online technologies are offering us new opportunities to create communities of inquiry that allow for more active learning that enhances students’ critical thinking. This chapter introduces an exploratory case in a Middle Eastern context that uses multiple online activities to supplement and strengthen the students’ face-to-face learning environment. This interpretive case discusses the students’ perceptions of their experience when using online activities. The case indicates that students improved their learning, are very positive about their first interaction with online activities and would like to see it as a standard practice to supplement their face-to-face learning. Chapter 7 Minimal Functionalities of Course Management Systems: A Faculty Perspective............................. 122 V. Adlakha, University of Baltimore, USA A. Aggarwal, University of Baltimore, USA In this chapter the authors offer a faculty perspective on desirable features of a Course Management System (CMS) to teach a course efficiently. This paper is the result of our Web teaching experiences over a period of ten years using three different CMS platforms. We develop a list of necessary functionalities that a CMS must provide web-based or web-enhanced learning. The authors anticipate that this paper could help guide software developers in developing appropriate CMS tools and would help institutions to gain greater insight into the selection of an appropriate CMS for effective Web-based or web-

enhanced education (WBE). The discussion could also assist current and future Web course instructors by increasing their awareness to take advantage of many features that might exist in their CMS. Chapter 8 Α Learning Platform for the Introduction of Remote Sensing Principles in Higher Education in a Blended Learning Collaborative Environment............................................................ 142 Nektaria Adaktilou, University of Athens, Greece Costas Cartalis, University of Athens, Greece George Kalkanis, University of Athens, Greece The purpose of this study was the creation of a pedagogy inclusive electronic platform for the introduction of Remote Sensing principles to University students. In Universities throughout the world, there is a constant research about new and more flexible ways of teaching and organizing learning in all thematic areas. Environmental Remote Sensing is the measurement from a distance, of all the spectral features of the Earth’s surface and the atmosphere. These measurements are usually made by instruments carried by satellites and they are processed to create information concerning regional and global environmental issues. Remote Sensing is an interdisciplinary thematic area that evolves in a very fast manner. This course has been taught at the Physics Department of the University of Athens in the traditional lecture-based manner until now. This study describes the design, development, pilot application and formative evaluation of the learning platform proposed. The indices derived for the educational proposal’s evaluation demonstrated that the platform has a very good potential to support learning in the area of Remote Sensing and act as an interactive digital repository of knowledge that may enhance students’ learning and facilitate the organization and management of the course. Chapter 9 An Evaluation of Blending Technology with Pedagogy for Teacher Education and its Implication for their Classroom Teaching........................................................................................... 162 Carol Kahan Kennedy, Fordham University, USA Maureen Hinkley, Fairfield University, USA Although research has been conducted on the benefits and drawbacks of online courses, more is specifically needed in teacher-education to increase understanding of the transfer process from technology integration learning to the classroom. This study was designed to evaluate a model for blending technology with traditional classroom methods in preparing teachers to do the same. A combination of qualitative and quantitative methods was used to examine the collaborative and scaffolding approaches to the teacher learners construction of meaning in the online discourse. Data has been collected from blended graduate level courses taught in the area of educational technology for in-service and preservice teachers from 2001 through 2006. These findings will be used to help identify best-practices for technology integration with teacher-education through informed applied research, and to create a new model for more comprehensive future blended course design.

Section 3 Chapter 10 Redefining Web Users’ Optimal Flow Experiences in Online Environments: An Empirical Analysis......................................................................................................................... 181 Anshu Saxena Arora, Savannah State University-Savannah, USA Mahesh S. Raisinghani, TWU School of Management, USA The chapter highlights a research study on consumer navigation behavior through the Web users’ optimal Flow experiences in the online environments. The research study establishes the empirical groundwork for measuring Web users’ Flow experiences in the Web environment. The chapter proposes a comprehensive definition of Flow on the basis of Comprehensive Process (Flow) Model of Network Navigation, considering that the Flow concept is a multidimensional concept in the “multi-activity” medium of the Web. Flow has been defined as a multi-dimensional and context-specific concept. Furthermore, the research chapter proposes that there are 10 Flow constructs (also called “the antecedents of Flow”) along with the three states of Flow, namely, Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow. Consumer Behavior on the Web is studied using the Flow concept for three categories of Flow users, namely, Perfect and Imperfect-Intensive Flow (PIIF) users, Imperfect Flow (IF) users, and Non-Flow (NF) users. These users achieve Flow depending on 10 Flow-constructs and three Flow states. Empirical results suggest a direct relationship between the Flow states and the Flow user categories and between expected Web user in the future (EXPUSE) and the Flow user categories. This research study provides a basis for future researchers to study consumer navigation behavior on the Web using the Flow concept for three categories of Flow users through 10 Flow constructs and three Flow states. The research has significant implications for theory and practice. Chapter 11 Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!.......... 199 Nikos Karacapilidis, University of Patras & Research Academic Computer Technology Institute, Greece Manolis Tzagarakis, University of Patras & Research Academic Computer Technology Institute, Greece Nikos Karousos, Hellenic Open University, Greece George Gkotsis, University of Patras, Greece Vassilis Kallistros, Research Academic Computer Technology Institute, Greece Spyros Christodoulou, Research Academic Computer Technology Institute, Greece Christos Mettouris, Research Academic Computer Technology Institute, Greece Dora Nousia, Research Academic Computer Technology Institute, Greece In this chapter, we demonstrate how CoPe_it! – a web-based argumentative collaboration support tool – enables one to manage cognitively-complex collaboration settings, that is settings characterized by big volumes of interrelated data obtained from diverse sources and knowledge expressed by diverse participants. The CoPe_it! approach focuses on issues related to the representation of such settings and aims at making it easier for participants to follow the evolution of a collaboration, comprehend it in its entirety, and meaningfully aggregate data in order to resolve the issue under consideration.

Chapter 12 Integrating XML Technologies and Open Source Software for Personalization in E-Learning.............................................................................................................. 216 Hsun-Ming Lee, Texas State University-San Marcos, USA Robert Davis, Texas State University-San Marcos, USA Yu-Liang Chi, Chung Yuan Christian University, Taiwan E-learning that emphasizes learner-centered activity and system interactivity provides a pedagogic opportunity to deliver a context for individual learning options. In the past decade, e-catalog standards based on learning object models have facilitated the design of e-learning systems. This study addresses issues for e-learning in a professional setting to foster the development of computer skills in students. In particular, personalized templates generated according to student and learning object models are proposed for instructors to provide practice exercises. Standardized XML technologies and open source software are integrated to create information filters and user interfaces to achieve personalization. The students use open source software that acts as a new type of Web client other than a browser. A case study that applies personalized templates for the learning of computer programming students with different skill levels is presented. Chapter 13 Autism and Family Interventions Through Technology: A Description of a Web-Based Tool to Educate Fathers of Children with Autism............................................................ 232 Richard E. Ferdig, Kent State University, USA Hilary G. Amberg, University of Florida, USA Jennifer H. Elder, University of Florida, USA Susan A. Donaldson, University of Florida, USA Gregory Valcante, University of Florida, USA Roxanna Bendixen, University of Florida, USA Most research on family interventions of children with autism has focused on the role of the mother, and little is known about the effects of training fathers. Through a series of National Institutes of Health–funded studies we have demonstrated treatment success by focusing on fathers who are trained at home. Although our research has been successful, this work introduces questions related to how best to train fathers when on-site, in-home training is not a viable option due to geographical distance or a variety of other logistical constraints. This chapter describes the development and initial use of an Internet-based tool to offer this training more broadly. We briefly describe past research as well as the need for the implementation of an Internet-based tool. We then describe the system, document early indicators of success, and discuss metrics we are using with our fathers. The chapter concludes with a discussion of future goals and research needs.

Section 4 Chapter 14 Learner-Centered Teaching and the Use of Technology...................................................................... 248 Annette Greer, East Carolina University, USA Vivian Mott, East Carolina University, USA This chapter explores the use of various learning technologies as tools for facilitating learner-centered teaching. The chapter offers another perspective on the scholarship of teaching with technology— through discussion of various theoretical models of learner-centered teaching, the role of technology on the student/instructor relationships, the impact on technology in different educational settings and contexts, and learners’ cultural differences. The chapter concludes with a brief discussion of future trends, cautions, and speculations related to technology use in learner-centered teaching. Chapter 15 Effective Teaching with Technology in Adult Education.................................................................... 264 Victor C. X. Wang, North Central University, USA Effective teaching with technology in adult education stems from many factors. Technology is only used to enhance learning. Not only are teachers of adult learners required to study the tools related to the use of technology, but are also required to study the nature of knowledge, the nature of learning, constructivism and various kinds of teaching philosophies. Without thorough knowledge of these factors, effective teaching with technology cannot occur in adult education, let alone other educational fields. This chapter is comprehensive concerning effective teaching with technology in adult education because it also addresses the interrelationships between the use of technologies and the teaching and learning process. Chapter 16 The Role of Adult Education in Online Delivery of Career and Technical Education........................ 280 Victor M. Hernández-Gantes, University of South Florida, USA As online education continues to grow, there is a consensus that online courses and programs should be designed based on the needs of adult learners. This premise is also relevant to growing career and technical education (CTE) programs offered online. However, much of the literature in online CTE lacks implicit connections to emerging notions of adult development and learning. This chapter provides an overview of the status of online education in CTE offered in higher education, and discusses adult learning development as a means to inform curriculum design and instruction. The chapter concludes with an outline of emerging trends bridging adult learning and online education relevant to career and technical education. Chapter 17 The Role of Learning Styles and Technology...................................................................................... 299 Royce Collins, Kansas State University, USA

Learning style research has informed effective classroom teaching strategies for decades. Technology has allowed faculty and students to move the learning environment from the four-walled classroom to a fluid global virtual space. Knowledge gained through the application of learning style research to online instruction has enhanced practice; however, research demonstrating the alignment of learning styles with current technological resources has been limited. Learning styles and their interrelationship with technology and adult learners is as important today as initial learning style research was in the six decades after its beginnings in the 1940s. Education today must meet the needs of students who are more comfortable in electronic environments, as well as those who need the four-walled classroom. The ability to use learning style research to accomplish both will lead to enhanced student learning and a more productive experience. Chapter 18 CTowards an Effective ICT-based University Learning. The tacit and the Interaction Dimensions........................................................................................................................ 316 Manuel Ahedo, Rovira i Virgili University, Spain The principles and practices of university learning are being subject to critical reconsideration from new approaches to adult teaching and a growing use of information and communication technologies (ICTs). ICTs in adult learning have an ambivalent effect. On the one hand, they offer potential improvement in on-line communicative activities and the transmission of codified or explicit knowledge. On the other hand, they can reduce socially- and interactive-mediated tacit teaching and learning. Thus, the crucial criterion for effective and complementary use of ICTs in adult andragogy is whether they enable time and interactive social space for the tacit dimension of teaching and learning. This chapter analyzes these issues by comparing how two young universities in Spain have dealt with these effects of ICTs in relation to the tacit and interaction challenging dimensions of learning and teaching. Chapter 19 What can we learn from the Past about Future Technological Trends in Adult Education?................ 333 John Hope, University of Auckland, New Zealand The purpose of this chapter is to examine the past two decades of technology use in adult education with the intention of providing a critical lens with which to view future technological trends in adult education. The chapter begins with a brief summary of technological trends, such as the introduction of the Internet and the World Wide Web, that have influenced adult education over the past two decades. Political, economic, social, and pedagogical issues that have influenced the use of technology in adult education are also discussed and possible solutions to these issues are outlined. The chapter concludes with an attempt to extrapolate future technological trends that could influence the direction of adult education in the decade to come. Compilation of References ............................................................................................................... 354 About the Contributors .................................................................................................................... 395 Index.................................................................................................................................................... 405

xv

Preface

ABSTRACT Collaboration can facilitate and augment learning in many ways. At the same time, information technology plays a more and more important role in supporting collaborative learning globally. Aiming at further contributing to this directive, this chapter elaborates a series of issues related to the current state, objectives and future trends of collaborative learning. Particular attention is given to design issues as well as to different opportunities for researchers to tap into the Web 2.0 tools to foster collaborative learning. Keywords: computer-supported collaboration, technology-enhanced learning, social networking, Web 2.0, blog, wiki.

INTRODUCTION The changing nature of our society and organizations, being more and more knowledge-based (Holsapple & Joshi, 2002), has a major impact on how individual and organizational learning is - and will be - delivered or experienced. In this evolving context, it is broadly considered that collaboration is a highly desirable and effective action towards learning. David Johnson and Roger Johnson are probably the most consistent advocates of cooperative learning. They found that social skills and competencies tended to increase more within cooperative situations as working together increases students’ abilities to provide leadership, build and maintain trust, communicate effectively and manage conflicts constructively (Johnson & Johnson, 1989). More specifically, argumentative collaboration, conducted by a group of people working towards solving a problem, can admittedly facilitate and augment learning in many ways, such as in explicating and sharing individual representations of the problem, maintaining focus on the overall process, maintaining consistency, increasing plausibility and accuracy, as well as in enhancing the group’s collective knowledge (Koschmann, 1999; Andriessen et al., 2003; Ravenscroft & McAlister, 2006). Information technology takes an important role in supporting learning such as providing information in multiple modes, using technologies as mindtools, and scaffolding conversations virtually with anyone in the world (Jonassen, 2000; Jonassen, Peck, & Wilson, 1999). Leveraging Web-based technologies towards building responsive environments that motivate, engage and inspire learners (these environments are embedded in the business processes and human resources management systems of organizations) is highly critical. Accordingly, the research field of technology-enhanced learning continues to receive increasing attention. However, as widely admitted, learning evolves, and this is only partly due to the

xvi

reduced cost of the related software and hardware. Learning and teaching technologies should further focus on (i.e. exploit and augment) the collaboration among learners. The related technologies should support self-directed and personalized learning through the engagement of learners in collaborative learning settings and scenarios (Dillenbourg, 1999; Stahl et al., 2006). Formal and informal learning should be considered in parallel, together with the overall social and organizational context. The appropriate management of the related knowledge resources and user-generated content is another critical issue to be addressed during the development of the contemporary collaborative learning technologies. In any case, these technologies should make it easier for learners to follow the evolution of an ongoing collaboration, comprehend it in its entirety, and meaningfully aggregate data in order to resolve the issue under consideration. In the context sketched above, this chapter elaborates a series of issues related to the current state, objectives and future trends of collaborative learning. Particular attention is given to the identification of requirements imposed by contemporary communities and learning contexts, as well as to the consideration of approaches that could significantly contribute to their fulfillment.

SUPPORTING COLLABORATION AND OPTIMIZING THE LEARNING EXPERIENCE Learning is best accomplished when the individual needs of learners are established well in advance. These needs include the learners’ prior knowledge, learning styles, and cognitive traits. The learning environment (whether classroom traditional teaching, virtual Web world, or any form of hybrid learning structures) and collaboration tools must support the learners’ needs to facilitate and enhance their learning experience. Web Based Learning Environments (WBLE) - also known as Web Based Learning Systems (WBLS) - incorporate the process of ‘adaptation’ and address rightly the cognitive traits and learning styles. The ‘adaptation’ process includes detecting the individual learning needs of learners and then adapting courses according to the identified needs (Kinshuk & Graf, 2007). There is a wide range of free software and/or open source learning management systems (e.g., eFront) and course management systems (e.g., Dokeos, ILIAS, Moodle, and so forth). Many well-known virtual learning environments are available to facilitate the creation of virtual class rooms (e.g., Blackboard, FirstClass, Desire2Learn, CyberExtension , It's Learning, WebTrain, and so forth). For designing and adapting courses in WBLS, it is important to understand the learners’ skills and match them with the right challenges through the right level of courses targeted at them. It is beneficial to incorporate the differences in cognitive architecture based on psychology related theories/models such as Kolb’s Experiential Learning Theory, Felder-Silverman learning model, Theory of Multiple Intelligences, Myer-Briggs Type Indicator, and so forth, in order to avoid cognitive overload and facilitate learning for students with weak cognitive abilities. Research has pointed out that learners with strong learning preference for a specific learning style might experience difficulties in learning if their learning style is not supported by the appropriate teaching environment. Cognitive traits do not change with time and remain more or less stable. Changing learning styles requires training for the weak learning preferences in order to enhance them; which means even learning style is stable over time. Developing a proper technology enhanced learning environment is a key to enhance learning and making learning accessible to all learners by incorporating their individual cognitive traits and learning styles through the concept of ‘adaptation’.

xvii

Recent advances in computing and Internet technologies, together with the advent of the Web 2.0 era, resulted to the development of a plethora of online, publicly available environments such as blogs, discussion forums, wikis, and social networking applications (Summerford, 2008). These offer people an unprecedented level of flexibility and convenience to participate in complex collaborative activities, such as long online debates of public interest about the greening of our planet through renewable energy sources or the design of a new product in a multinational company. Information found in these environments is considered as a valuable resource for individuals and organizations to solve problems they encounter or get advice towards making a decision. In any case, people have to go through some type of sorting, filtering, ranking and aggregation of the existing resources in order to facilitate sensemaking. Yet, these activities are far from being easy. This is because collaboration settings are often associated with ever-increasing amounts of multiple types of data, obtained from diverse sources that often have a low signal-to-noise ratio for addressing the problem at hand. In turn, these data may vary in terms of subjectivity, ranging from individual opinions and estimations to broadly accepted practices and indisputable measurements and scientific results. Their types can be of diverse level as far as human understanding and machine interpretation are concerned. They can be put forward by people having diverse or even conflicting interests. At the same time, the associated data are in most cases interconnected, in a vague or explicit way. Data and their interconnections often reveal social networks and social interactions of different patterns. The above bring up the need for innovative software tools that can appropriately capture, represent and process the associated data and knowledge. Such tools should shift in focus from the collection and representation of information to its meaningful assessment and utilization. They should facilitate argumentation, i.e. discussion in which reasoning and disagreements exist, not only discourse for persuasion, logical proof and evidence-based belief (Kunz & Rittel, 1970), the ultimate aim being to support collaborative sense-making (and/or decision-making), and accordingly enhance learning. This can be seen as a special type of social computing where various computations concerning the associated context and group’s behavior need to be supported. Designing software systems that can adequately address users’ needs to express, share, interpret and reason about knowledge during an argumentative collaboration session has been a major research and development activity for more than twenty years. Technologies supporting argumentative collaboration usually provide the means for discussion structuring and visualization, sharing of documents, and user administration. They support argumentative collaboration at various levels and have been tested through diverse user groups and contexts. Furthermore, they aim at exploring argumentation as a means to establish a common ground between diverse stakeholders, to understand positions on issues, to surface assumptions and criteria, and to collectively construct consensus. While helpful in particular settings, the above solutions prove to be inadequate in cognitively-complex situations. Apple, Microsoft, Frog Design and Canesta are creating technology and products/devices based on human-computer interaction, human factors and human-gesture interface design that respond to people’s physical movements by using sensors to recognize natural gestures. For example, a television that can be turned on and off by waving at it. Andrew McAfee, principal research scientist at the Center for Digital Business in the Massachusetts Institute of Technology’s Sloan School of Management, suggests the use of Enterprise 2.0 as new collaborative tools for an organization (McAfee, 2009; Gaudin, 2010). He defines Enterprise 2.0 as the business use of an emergent social platform and the design and implementation of intelligent tools that allow people to interact as they want to. For example, the Central Intelligence Agency (CIA) is using this technology to broadcast an individual’s expertise to people inside the intelligence

xviii

community. This allows them to find the candidate(s) with the appropriate background not only within CIA but also in the Federal Bureau of Investigations (FBI) and the National Security Agency (NSA).

DESIGN ISSUES The ever-growing influence of Internet in our everyday life has implied a paradigm shift in terms of relationships between customers and companies. New interaction means in Web 1.0 have undergone a dramatic change in quantity and quality with the advent of the so-called Web 2.0, the Social Web. The upcoming Web 3.0, the Semantic Web, will also impact the design of collaborative learning solutions tremendously. This section elaborates a series of issues to be thoroughly considered during the design of contemporary collaborative learning solutions. These concern diverse collaboration aspects and should be taken into account together with the overall collaboration context.

Incremental Formalization When engaged in the use of existing technologies and systems supporting argumentative collaboration, users have to follow a specific formalism. More specifically, their interaction is regulated by procedures that prescribe and - at the same time - constrain their work. This may refer to both the system-supported actions a user may perform (e.g. types of discourse or collaboration acts), and the system-supported types of argumentative collaboration objects (e.g. one has to strictly characterize a collaboration object as an idea or a position). In many cases, users have also to fine-tune, align, amend or even fully change their usual way of collaborating in order to be able to exploit the system’s features and functionalities. Such formalisms are necessary towards making the system interpret and reason about human actions (and the associated resources), thus offering advanced computational services. However, there is much evidence that sophisticated approaches and techniques often resulted in failures (Shipman & Marshall, 1994; Shipman & McCall, 1994). This is often due to the extra time and effort that users need to spend in order to get acquainted with the system, the associated disruption of the users’ usual workflow (Fischer et al., 1991), as well as to the “error prone and difficult to correct when done wrong” character of formal approaches (Halasz, 1988). Complex contexts imply additional disadvantages when using formal approaches. Such approaches impose a structure which is not mature enough to accommodate the management of huge amounts of data coming from diverse sources. They do not allow users to elaborate and digest these data at their own pace, according to the evolution of the collaboration. Instead, a varying level of formality should be considered. This variation may either be imposed by the nature of the task at hand (e.g. decision making, deliberation, persuasion, negotiation, conflict resolution), the particular context of the collaboration (e.g. medical decision making, public policy making), or the group of people who collaborate each time (i.e. how comfortable people feel with the use of a certain technology or formalism). The above advocate an incremental formalization approach. In other words, formality and the level of knowledge structuring should not be considered as a predefined and rigid property, but rather as an adaptable aspect that can be modified to meet the needs of the tasks at hand. By the term formality, we refer to the rules enforced by the system, with which all user actions must comply. Allowing formality to vary within the collaboration space, incremental formalization, i.e. a stepwise and controlled evolution from a mere collection of individual ideas and resources to the production of highly contextualized and interrelated knowledge artifacts, can be achieved.

xix

Visualization and Reasoning It has been widely argued that visualization of argumentation conducted by a group of experts working collaboratively towards solving a problem can facilitate the overall process in many ways, such as in explicating and sharing individual representations of the problem, in maintaining focus on the overall process, as well as in maintaining consistency and in increasing plausibility and accuracy (Kirschner et al., 2003). Moreover, it leads to the enhancement of the group’s collective knowledge. For the above reasons, visualization issues should receive much attention while shaping the proposed innovative collaborative learning solutions. Alternative projections of a virtual collaboration space may constitute the ‘vehicle’ that permits incremental formalization of argumentative collaboration (Karacapilidis & Tzagarakis, 2007). A projection can be defined as a particular representation of the collaboration space, in which a consistent set of abstractions able to solve a particular organizational problem during argumentative collaboration is available. With the term abstraction, we refer to the particular data and knowledge items, relationships and actions that are supported through a particular projection, and with which a particular problem can be represented, elaborated and be solved. The foreseen solutions should enable switching from one projection to another, during which abstractions of a certain formality level are transformed to the appropriate abstractions of another formality level. This transformation should be rule-based (and context-specific); such rules can be defined by users and/or the facilitator of the collaboration and reflect the evolution of a community’s collaboration needs. It should be up to the community to exploit one or more projections of a collaboration space (upon users’ needs and expertise, as well as the overall collaboration context). Each projection of the collaboration space should provide the necessary mechanisms to support a particular level of formality (e.g. projection-x may cover only needs concerning collection of knowledge items and exploitation of legacy resources, whereas projection-y may provide decision making functionalities). The more informal a projection is, the more easiness-of-use is usually implied; at the same time, the actions that users may perform are intuitive and not time consuming (e.g. drag-and-drop a document to a shared collaboration space). Informality is associated with generic types of actions and resources, as well as implicit relationships between them. However, the overall context is more human (and less system) interpretable. As derives from the above, the aim of an informal projection of the collaboration space should be to provide users the means to structure and organize data and knowledge items easily, and in a way that conveys semantics to them. Generally speaking, informal projections may support an unbound number of data and knowledge item types. Moreover, users may create any relationship among these items; hence, relationship types may express agreement, disagreement, support, request for refinement, contradiction etc. While such a way of dealing with data and knowledge resources is conceptually close to practices that humans use in their everyday environment, it is inconvenient in situations where support for advanced decision making processes must be provided. Such capabilities require resources and structuring facilities with fixed semantics, which should be understandable and interpretable not only by the users but also by the tool. Hence, decision making processes can be better supported in environments that exhibit a high level of formality. The more formal projections of a collaboration space come to serve such needs. The more formal a projection is, easiness-of-use is usually reduced; actions permitted are less intuitive and more time consuming. Formality is associated with fixed types of actions, as well as explicit relationships between them. However, a switch to a more formal projection is highly desirable when (some members of) a community need to further elaborate the data and knowledge items con-

xx

sidered so far. Such functionalities are provided by projections that may enable the formal exploitation of collaboration items patterns and the deployment of appropriate formal argumentation and reasoning mechanisms. A switch to a projection of a higher level of formality should disregard less meaningful data and knowledge items, resulting to a more compact and tangible representation of the collaboration space. This effect is highly desirable in cognitively-complex situations.

Information Triage Concepts originally coming from the area of spatial hypertext and the information triage process (Marshall & Shipman, 1997), i.e. the process of sorting and organizing through numerous relevant materials and organizing them to meet the task at hand, should be also exploited towards the proposed collaborative learning solutions. According to the above, users must effortlessly scan, locate, browse, update and structure knowledge resources that may be incomplete, while the resulting structures may be subject to rapid and numerous changes. Information triage related functionalities enable users to meaningfully organize the big volumes of data and knowledge items in a collaborative setting. Spatial hypertext is admittedly a promising approach to address issues in argumentative collaboration environments, as it introduces a visual language in an attempt to take advantage of the humans’ visual memory and their ability to recognize patterns. Exploiting these human capabilities can greatly reduce the negative impacts of cognitively-complex environments. Spatial hypertext removes the barrier between reading and writing processes enabling articulation of tacit knowledge and ambiguity, as well as establishment of emerged problem-solving strategies. Thus, users are incrementally processing information and are not forced to predefined structural commitments. The corresponding features and functionalities should enable users to create and organize information by making use of spatial relationships and structures, giving them the freedom to express relationships among information items through spatial proximity and visual cues. Such cues could be related to the linking of collaboration items (e.g. coloring and thickness of the respective links) and the drawing of colored rectangles to cluster related items. As highlighted above, the foreseen solutions should permit an ordinary and unconditioned evolution of data and knowledge structures. Such solutions should also provide abstraction mechanisms that allow the creation of new abstractions out of existing ones. Abstraction mechanisms may include:    

annotation and metadata (i.e. the ability to annotate instances of various knowledge items and add or modify metadata); aggregation (i.e. the ability to group a set of data and knowledge items so as to be handled as a single conceptual entity); generalization/specialization (i.e. the ability to create semantically coarse or more detailed knowledge items in order to help users manage information pollution of the collaboration space); patterns (i.e. the ability to specify instances of interconnections between knowledge items of the same or a different type, and accordingly define collaboration templates).

Exploitation of Legacy Resources The foreseen solutions should also reduce the overhead of entering information by allowing the reuse of existing resources. Generally speaking, when legacy resources have to be reused during a collaborative session, complexity is increased. This is not only due to the additional amount of data involved, but

xxi

also to the conceptual overhead and distractions imposed to the user from switching among applications and environments. One way of dealing with this situation is to enable the ubiquitous access of legacy resources from within the collaboration environment by seamlessly integrating the systems involved. Towards this direction, interoperability among various applications should be carefully considered.

Social Networking Management of social structures, interactions and relationships is also critical in a contemporary collaborative learning framework. Applications and projects dealing with social relationships mainly support explicit and abstract structures. However, social structures may gain from the expertise of structure domain research, including various structure abstractions or ways for implicit structuring. Another issue to be addressed concerns the elaboration of social relationships in their contexts, that is, how they relate to assets, locations, or change over time. Social network analysis (Castells, 2004) has to be extensively used to find who is depending on whom in a network. Such an analysis will also help to detect hidden hierarchy of social networks. Other requirements of this category concern the (semi)automatic rolespecific cognitive mapping for each participant based on his/her overall behavior and the development of artifacts-related collaboration metrics. The foreseen solutions should integrate a sophisticated user and role modeling module to tackle the above issues. This module should build on an explicit representation of the notion of user/group, which in turn should be based on a predefined attribute hierarchy. The associated attributes can be domainspecific. They can be categorized, depending on how they are populated and who may modify them, as explicit (their values are provided by users themselves and include personal data such as name, address, birth date, preferences, competencies, skills etc.) or implicit (their values are not provided by users explicitly, but implicitly, by observing their behavior within the system). User/group modeling should be also associated with mechanisms for the acquisition of the abovementioned implicit information of users/groups. These mechanisms will observe and log the operations and discourse moves of users within the system and record them in the user’s profile. Finally, such a sophisticated user and role modeling module should integrate an inference engine. The role of such an engine is to analyze all data present in the profile, together with data from the collaborative workspaces, in order to extract meaningful information about social structures, interactions and relationships. Contrary to most user modeling approaches, this approach pays much attention to community-related aspects (i.e. relationships between individual users and relationships between users and artifacts).

DEVELOPING ADAPTIVE COURSES THROUGH WEB BASED LEARNING ENVIRONMENTS There are many ways of simulating the different intelligences of Multiple Intelligences (MI) theory with the use of the software programs where these programs act as triggers of MI. A MI theory based WBLE, supported by interactive e-books, eText, word puzzles, word games, word meanings, thesaurus, spell checks, electronic libraries, electronic essays and paragraphs, word restricted short and long answer type questions, and word processing software can help in activating Verbal-Linguistic Intelligence. Critical thinking programs, quizzes, webquests, scientific demonstrations, mathematical exercises, problemsolving, true-false questions, questions with direct answers and logical reasoning software programs

xxii

and activities will stimulate Logical-Mathematical Intelligence. The use of PowerPoint Presentations, virtual reality programming, draw and paint programs, clip-arts, collaborative writing projects, and all kinds of graphics can stimulate a learner, who is driven by Visual-Spatial Intelligence. A web based course using software programs of virtual reality, hands-on construction kits and simulation software, interactive modules, videoconferencing, and interactive games can lead to Bodily-Kinesthetic Intelligence. Musical-Rhythmic Intelligence can be enhanced by using ‘music’ as a part of course development where musical digital interfaces are used and question-answer format questions where musical sound represents correct and wrong choices. A musical-oriented learner will answer questions with a view of hitting the right answer leading to an appropriate musical note. Audio lectures can be a great tool for enhancing Musical Intelligences. Such a WBLE supported by musical recognition and interface will be both challenging and enterprising for the musical oriented learner. Electronic bulletin boards, interactive gaming technologies, chat sessions, discussion forums, information sharing via computer/Internet, class Web sites, videoconferencing, email, and collaborative e-Projects in Web based courses will lead to a development of Interpersonal Intelligence where information is shared among individuals in different locations, areas or even different parts of the world supported by use of computer technologies. Learning supported by self-paced presentations, flexibility, personal choice software, and self-mode selection and presentation will fulfill the needs of Intrapersonal Intelligence. For strengthening and stimulating Naturalist Intelligence, WBLE can use creative multimedia presentations software, creation of tables, graphical displays, chat sessions, videoconferencing, email, discussion forums and class Web sites. All these elements and characteristics can be added to Web based online courses (integrating Web with classroom environments). A WBLE based on Multiple Intelligences will be directed towards satisfying and stimulating 7-11 intelligences as defined by the instructor. A requirement for providing adaptation in Web based courses through WBLE is to know the learners’ characteristics. Instructors play an important role in the development of such a WBLE and the environment helps in prioritizing the levels and kinds of intelligences deemed fit for a particular course. The first and best online instruction is the creation of a class Web site in which learners share information with all class participants (Gardner, 1993; Gallagher, 2003). The website design and pedagogy can be refined by the instructors based on the learners’ motivation levels and intelligences. Instructors can visit each learner’s interactions with WBLE and interpret their learning actions performed on various knowledge objects. This will help the instructors to understand the learning styles and preferences of all learners and will lead to the course adaptation and customization by improving significant areas of MI theory. We believe that the adaptive Web based courses using WBLE can support various learning formats, i.e. either in a face-to-face classroom environment or a Web based online course with class Web sites, multimedia presentations, audio lectures, chat sessions, discussion forums, interactive programming, virtual reality, videoconferencing, graphical displays, email, listservs, and the use of hypermedia. Hence, we offer the following propositions: •

WBLE development based on Multiple Intelligences catering to Verbal-Linguistic Intelligence, Logical-Mathematical Intelligence, Visual-Spatial Intelligence, Bodily-Kinesthetic Intelligence, Musical-Rhythmic Intelligence, Interpersonal Intelligence, Intrapersonal Intelligence, and Naturalist Intelligence and the subsequent use of matching Web-based learning tools and activities (class Web sites, multimedia presentations, audio lectures, chat sessions, discussion forums, interactive programming, virtual reality, videoconferencing, graphical displays, email, listservs, and the use of hypermedia) should result in higher levels of adult student satisfaction with the learning in a course.

xxiii

•

•

•

WBLE development based on Multiple Intelligences and the subsequent use of matching Webbased learning tools and activities should result in higher levels of academic performance by adult students in a course. WBLE development based on Multiple Intelligences and the subsequent use of matching Webbased learning tools and activities should result in deeper, more lasting adult student learning in a course and beyond the course (in other courses as well as their professional career). WBLE development based on Multiple Intelligences and the subsequent use of matching Webbased learning tools and activities should increase the ability of adult students to learn in a course and beyond the course (in other courses as well as their professional career).

USING WEB 2.0 TO ENHANCE COLLABORATIVE LEARNING Web 2.0 is broadly defined as a second generation or more personalized communication mode that emphasizes active participation via the World Wide Web. Users of Web 2.0 not only create and own data but also mix, amend and recombine content and are relatively more “open to the world”, welcoming comments and revisions (McLoughlin & Lee, 2007). Many of us collaborate, create and share new information on the Web through various Web 2.0 tools such as social bookmarking systems, blogs, wikis, and video sharing platforms. Commonly used Web 2.0 platforms include Twitter, Facebook, Wikipedia and Youtube. Blog is a text-based online environment which enable creators to publish in the Internet. The creators can embed pictures, videos and other online resources whilst the viewers can make comments. The difference between publishing as web pages and blogs is that blogs preserve old postings and the new creations are shown in reverse chronological order (Viégas, 2005). Wikis are also widely adopted as a Web 2.0 tool which facilitate collaborative work. Users can publish their products on the Internet easily without knowing how to write HTML codes (Heafner & Friedman, 2008). The history features of wikis are particularly helpful for users to trace the content and timing of the revision. Educators must rethink how Web 2.0 technology can help students collaborate. Oliver (2007) points out the necessity to redesign technology integration courses to leverage new Web 2.0 tools. Barlow (2008) also argues that Web 2.0 tools also offer an exciting opportunity to create a classroom without walls, as they provide a huge and untapped resource for educators, while Klamma et al. (2007) suggest that Web 2.0 concepts and technologies could support lifelong learning communities. Ducate and Lomicka (2008) found that students were more motivated to complete their foreign language writing tasks when using blogs as there were audiences. Goldman, Cohen & Sheahan (2008) also found that blogging helped their students understand other environment health issues. Similarly, there are a number of studies which report wikis can foster collaborative learning, in particular, writing English from primary to university levels (Mak & Coniam, 2008; Wang, 2010; Wilkoff, 2007). Wikis are also useful in fostering deep understanding of social studies (Heafner & Friedman, 2008) and enhance pre-service teachers to produce high quality learning materials (Lai & Ng, in press; Nicholas & Ng, 2009). However, using blogs and wikis might not always generate positive results, for example, some students did not found peer’s comments useful (Ellison & Wu, 2008; Haltic, Lee, Paulus, & Spence, in press; Xie, Ke, & Sharma, 2008). There are two broad future research directions; one is calling for more research into how to integrate Web 2.0 into pedagogy, whilst another one is conducting research on the impact of Web 2.0 tools on the learning outcomes. As for investigating the learning process, we could use Web 2.0 environments to

xxiv

facilitate group projects which require different experts and perhaps learners of different backgrounds. This kind of findings would be more convincing and authentic if learners are to collaborate with heterogeneous learners of different locations so that the flexibility and convenience of the Internet can be fully capitalized. Longitudinal research is inevitably considered necessary to examine the potential of using Web 2.0 tools for various learning activities for different disciplines. There are also various ways to investigate the learning outcomes. Firstly, we could conduct pre-tests and post-tests to find out the subject knowledge of learners. Secondly, to have control groups of using and not using Web 2.0 environments as collaborative learning tools. Thirdly, it is equally important to measure the learning process and learning outcome. Web 2.0 environments are rather different from traditional computer tools due to their user-friendliness and the needs for social interaction. It would be interesting to examine if there is any gender difference in terms of their performances (females were slower to adopt Internet than males (Weil & Rosen, 1995, 1997), and females reported higher levels of discomfort and incompetence of using computers (Schumacher & Morahan-Martin, 2001)). It is imperative to re-design assessment criteria so that assessment should be designed to support learning (Biggs, 1996) and reflect generic skills (such as collaboration, creativity and other information technology related skills) that learners developed.

CONCLUSION This chapter has elaborated a series of issues related to the collaborative learning paradigm, the ultimate aim being to sketch the appropriate tools and technologies that will facilitate and augment it. A series of critical requirements imposed by contemporary communities and learning contexts have been identified, while approaches that could significantly contribute to their fulfillment have been discussed. We argue that the proper tuning and integration of these approaches is able to fully support the evolution of a cognitively complex (and/or data intensive) collaboration, while it provides the means for addressing the issues related to formality in collaborative knowledge building and learning systems. Ideas of how to develop adaptive courses through Web Based Learning Environments were also elaborated. The value and opportunities of using Web 2.0 environments to conduct research on learning process and learning outcomes were finally discussed. By no means, one would argue that the list of issues discussed in this chapter covers fully the diversity and complexity of the research field under consideration. Related works, derived from other perspectives, should be also taken into account during the development of innovative collaborative learning systems (see, for instance, (Amy, 2003), (Dimitracopoulou, 2005) and (Kamtsiou et al., 2006)). Furthermore, the improvement of collaboration among learners should not be considered as the sole research direction towards further enhancing web-based learning. The augmentation of the quality (not the quantity) of e-learning material and the establishment (and global adoption) of e-learning standards consist two other essential directions to be thoroughly investigated.

xxv

REFERENCES Amy, W. (2003). Supporting Electronic Discourse: Principles of Design from a Social Constructivist Perspective. Journal of Interactive Learning Research, 14(2), pp. 167-184. Andriessen, J., Baker, M., & Suthers, D. (2003). Argumentation, computer support, and the educational context of confronting cognitions. In J. Andriessen, M. Baker, & D. Suthers (Eds.), Arguing to learn: confronting cognitions in computer-supported collaborative learning environments (pp. 1-25). Dordrecht, The Netherlands: Kluwer Academic Publishers. Barlow, T. (2008). Web 2.0: Creating a classroom without walls. Teaching Science, 54(1), pp. 46-48. Biggs, J. (1996). Assessing learning quality: Reconciling institutional, staff and educational demands. Assessment & Evaluation in Higher Education, 21, pp. 5-15. Castells, M. (2004). The Network Society: A Cross-cultural Perspective. Northampton, MA: Edward Elgar. Conklin, J., & Begeman, M. (1989). gIBIS: A tool for all reasons. Journal of the American Society for Information Science, 40(3), 200-213. Conklin, J., Selvin, A.M., Buckingham Shum, S. & Sierhuis, M. (2001). Facilitated hypertext for collective sense-making: 15 years on from gIBIS. In Proc. of the 12th ACM Conference on Hypertext and Hypermedia, ACM Press, pp. 123-124. de Moor, A., & Aakhus, M. (2006). Argumentation support: from technologies to tools. Communications of ACM, 49(3), pp. 93-98. Dillenbourg P. (1999). What do you mean by ‘collaborative learning’? In P. Dillenbourg (Ed.), Collaborative Learning: Cognitive and Computational Approaches (pp. 1-19). Oxford: Elsevier. Dimitracopoulou, A. (2005). Designing collaborative learning systems: current trends and future research agenda. In Proc. of the 2005 Conference on Computer Support for Collaborative Learning, Taipei, Taiwan, May 30-June 4, 2005, pp. 115-124. Ducate, L. C., & Lomicka, L. L. (2008). Adverntures in the blogosphere; from blog readers to blog writers. Computer Assisted Language Learning, 2(1), pp. 9-28. Ellison, N. B., & Wu, Y. (2008). Blogging in the classroom: A preliminary exploration of student attitudes and impact on comprehension. Journal of Multimedia and Hypermedia, 17(1), pp. 99-122. Fischer, G., Lemke, A.C., McCall, R., & Morch, A. (1991). Making Argumentation Serve Design. Human Computer Interaction, 6(3-4), pp. 393-419. Gallagher, B. J. (2003). Multile Intelligences and Online Instructional Design. 2003. Gardner, H. (1993). Multiple intelligences: The theory in practice. New York: Basic Books. Gaudin S. (2010). The Grill: Andrew McAfee. ComputerWorld, April 5, pp. 12-14. Goldman, R. H., Cohen, A. P., & Sheahan, F. (2008). Using seminar blogs to enhance student participation and learning in public health school classes. American Journal of Public Health, 98(9), 1658-1663.

xxvi

Halasz, F. (1988). Reflections on NoteCards: Seven Issues for the Next Generation of Hypermedia Systems. Communications of the ACM, 31(7), 836-852. Haltic, O., Lee, D., Paulus, T., & Spence, M. (In press). Blog effectiveness to support learning. Internet and Higher Education. Heafner, T. L., & Friedman, A., M. (2008). Wikis and constructivism in secondary social studies: fostering a deeper understanding. Computers in the Schools, 35(3-4), 288-302. Holsapple, C. W., & Joshi, K. D. (2002). Knowledge management: A threefold framework. The Information Society, 18, 47-64. Jonassen, D. H. (2000). Computers as mindtools for schools. Upper Saddle River, N.J.: Merrill. Jonassen, D. H., Peck, K. L., & Wilson, B. G. (1999). Learning with technology: a constructivist perspective. Upper Saddle River, N.J.: Merrill. Kamtsiou, V., Naeve, A., Stergioulas, L., & Pappa, D. (2006). Future Visions of Technology-Enhanced Professional Learning. In Proc. of the ICALT-2006 Conference, Kerkrade, The Netherlands, 5-7 July, 2006, pp. 542-543. Karacapilidis, N., & Papadias, D. (2001). Computer supported argumentation and collaborative decision making: The HERMES System. Information Systems, 26(4), 259-277. Karacapilidis, N., & Tzagarakis, M. (2007). Supporting Incremental Formalization in Collaborative Learning Environments. In E. Duval, R. Klamma, & M. Wolpers (Eds.), Proceedings of the 2nd European Conference on Technology Enhanced Learning (EC-TEL 2007), Crete, Greece, September 17-20, 2007, Lecture Notes in CS, Vol. 4753, pp. 127–142, Berlin: Springer-Verlag. Kinshuk and Sabine Graf (2007). Considering Cognitive Traits and Learning Styles to Open Web-Based Learning to a Larger Student Community, Proceedings of the International Conference on Information and Communication Technology and Accessibility (ICTA 2007), Hammamet , Tunisia, April 2007, pp. 21-26. Kirschner, P., Buckingham Shum, S., & Carr, C. (2003). Visualizing Argumentation: Software Tools for Collaborative and Educational Sense-Making. London: Springer. Klamma, R., Chatti, M. A., Duval, E., Hummel, H., Hvannberg, E. H., Kravcik, M., et al. (2007). Social software for life-long learning. Educational Technology & Society, 10(3), pp. 72-83. Retrieved from http://www.ifets.info/journals/10_3/6.pdf Koschmann, T. D. (1999). Toward a dialogic theory of learning: Bakhtin’s contribution to understanding learning in settings of collaboration. In C.M. Hoadley & J. Roschelle (Eds.), Proc. of the CSCL’99 Conference (pp. 308-313). Mahwah, NJ: Lawrence Erlbaum Associates. Kunz, W., & Rittel, H. (1970). Issues as Elements of Information Systems. Technical Report 0131, Universität Stuttgart, Institut für Grundlagen der Planning. Lai, Y. C., & Ng, E. M. W. (in press). Using Wikis for Developing Student Teachers’ Learning, Teaching and Assessment Capabilities. The Internet and Higher Education (Special Edition).

xxvii

Mak, B., & Coniam, D. (2008). Using wikis to enhance and develop writing skills among secondary school students in Hong Kong. System, 36, 437-455. Marshall, C., & Shipman, F.M. (1997). Spatial Hypertext and the Practice of Information Triage. In Proc. of the 8th ACM Conference on Hypertext, pp. 124-133. McAfee, S. (2009). Enterprise 2.0: New Collaborative Tools for your Organization’s Toughest Challenges. Harvard Business Publishing. McLoughlin, C., & Lee, M. J. W. (2007, 2-5 December). Social software and participatory learning: pedagogical choices with technology affordances in the Web 2.0 era. Paper presented at the ICT: Providing choices for learners and learning. Proceedings ascilite Singapore 2007, Singapore. Nicholas, H., & Ng, W. (2009). Fostering online social construction of science knowledge with primary pre-service teachers working in virtual teams. Asia-Pacific Journal of Teacher Education, 37(4), 379-398. Oliver, K. (2007). Leveraging Web 2.0 in the redesign of a graduate-level technology integration course. TechTrends, 51(5), 55-61. Ravenscroft, A., & McAlister, S. (2006). Designing interaction as a dialogue game: Linking social and conceptual dimensions of the learning process. In C. Juwah (Ed.), Interactions in Online Education: implications for theory and practice (pp. 73-90). Routledge. Reed, C.A., & Rowe, G.W.A. (2004). Araucaria: Software for Argument Analysis, Diagramming and Representation. International Journal of AI Tools, 14(3-4), 961-980. Schumacher, P., & Morahan-Martin, J. (2001). Gender, Internet and computer attitudes and experiences Computers in Human Behavior, 17, 95-110. Shipman, F.M., & Marshall, C.C. (1994). Formality Considered Harmful: Issues, Experiences, Emerging Themes, and Directions. Technical Report ISTL-CSA-94-08-02, Xerox Palo Alto Research Center. Shipman, F.M., & McCall, R. (1994). Supporting knowledge-base evolution with incremental formalization. In Proc. of the CHI ’94 Conference, 285-291. Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. Keith Sawyer (Ed.), Cambridge Handbook of the Learning Sciences (pp. 409–425). New York: Cambridge University Press. Summerford, S. (2008). Web 2.0 for the Classroom Teacher: An Internet Hotlist on Web 2.0. Retrieved Dec. 17, 2008, from http://www.kn.pacbell.com/wired/fil/pages/listweb20s.html Suthers, D., Weiner, A., Connelly, J., & Paolucci, M. (1995). Belvedere: Engaging students in critical discussion of science and public policy issues. In Proc. of the 7th World Conference on Artificial Intelligence in Education, 266-273. van Gelder, T.J. (2002). Argument mapping with Reason!Able. The American Philosophical Association Newsletter on Philosophy and Computers, 2(1), 85-90. Verheij, B. (2003). Artificial argument assistants for defeasible argumentation. Artificial Intelligence, 150(1-2), 291-324.

xxviii

Viégas, F. B. (2005). Bloggers' Expectations of Privacy and Accountability:An Initial Survey. Journal of Computer-Mediated Communication, 10(3), article 12. Retrieved from http://jcmc.indiana.edu/vol10/ issue3/viegas.html. Wang, L. (2010). Implementing and promoting blended learning in higher educaiton and institutions: Comparing different approaches. In E. M. W. Ng (Ed.), Comparative blended learning practices and environments (pp. 70-87). Hershey, PA: Information Science Reference. Weil, M., & Rosen, L. (1995). The psychological impact of technology from a global perspective: a study of technological sophistication and technophobia. Computers in Human Behavior, 11, 95-133. Weil, M., & Rosen, L. (1997). Technostress: Coping with technology @ work, @ home, @ play. New York: Wiley. Wilkoff, B. (2007). Discourse about discourse: Safety vs. panic. Retrieved from http://bhwilkoff.podomatic.com/ Xie, Y., Ke, F., & Sharma, P. (2008). The effect of peer feedback for blogging onn college students' reflective learning processes. Internet and Higher Education, 11, 18-25.

Eugenia M. W. Ng The Hong Kong Institute of Education, Hong Kong Nikos Karacapilidis University of Patras, Greece Mahesh Raisinghani TWU School of Management, USA

Section 1

1

Chapter 1

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System Mei-Yu Chang National Hsinchu University of Education, Taiwan Wernhuar Tarng National Hsinchu University of Education, Taiwan Fu-Yu Shin Chien-Kuo Elementary School, Taiwan

ABSTRACT This study combined ideas from learning hierarchy and scaffolding theory to design a web-based, adaptive learning system to investigate the effectiveness of scaffolding for elementary school students having different levels of learning achievement. The topic chosen for learning was the Three States of Water. A quasi-experiment was conducted. In this experiment, students were divided into three groups: control group (without scaffolds), experimental group A (scaffolds providing by on-line conversation) and experimental group B (scaffolds providing by face-to-face conversation). The experimental results showed significant improvement for students after they had studied using the web-based, adaptive learning system. Specifically, scaffolds in the form of face-to-face conversations greatly enhanced the learning of high-achievement students. However, there were no significant differences between the low-achievement students with or without the provision of scaffolds. It was also discovered that the web-based, adaptive learning system could help students develop their learning responsibility.

INTRODUCTION The purpose of science education is to provide students with scientific knowledge, concepts, attitudes and methods for application in their daily

lives. The role of a teacher is to assist students in learning and solving problems. At the beginning, students are usually interested in learning science, but to some extent, they lose it or become confused, especially when learning abstract concepts. The Three States of Water is a learning unit

DOI: 10.4018/978-1-60960-153-9.ch001 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

containing abstract and complicated concepts for elementary students. Use of the Internet and instructional technology can help teachers and students in many ways. It is easier for students to understand abstract concepts if their learning process is assisted by instructional technology. This study combined with ideas of learning hierarchy and scaffolding theory to the design of a web-based, adaptive learning system to improve the quality of web-based learning. The major purpose of this study was to investigate students’ learning via a web-based, adaptive learning system where scaffolds were provided to help the students to study the concept of the Three States of Water. This study also tried to find out whether students’ learning responsibility was being developed during their learning process. The concept of scaffolding is based on Vygotsky’s social constructivist view of learning (1978). Vygotsky proposed that there were two major factors, i.e., culture and social context, which influence learning. He claimed that every mental function in a child’s development first came from the social interaction with an adult. This kind of interaction provides a supportive environment in which children can extend their current knowledge and skills. The supported situation occurs in what Vygotsky referred to as the zone of proximal development. That is the area between what children can do independently and what they can do with assistance, such as they get from teachers and other students. The assistance that other people provide is a scaffold for a child. Given repeated experiences, children can internalize the supported situation of the mental processes, and can engage in them in new contexts (Clark & Graves, 2005). Two sources of knowledge are suggested by Vygotsky. The first is everyday knowledge, i.e., gut knowledge, instinctive knowledge and spontaneous knowledge. This type of knowledge is influenced by peer interaction, language and experience of the individual who tries to understand his or her environment. The second is from

2

formal education in the classroom, which is called formal knowledge and it possesses strict logic and clear definitions. Therefore, learners construct meaningful knowledge through both their daily lives and school experiences. However, some scientific concepts are very abstract and difficult for students to grasp. In addition, they may often be influenced by different cultural and social environments. For example, the concept of “The sun rises in the east and falls in the west” generally exists in textbooks and daily communication, and students have this misconception before they are educated with formal knowledge. Students may think the experiences they have in daily life constitute their full knowledge base. Therefore, it is important for them to know if the knowledge they have received is formally right or not. According to scaffolding theory, teachers should hold continuous and active conversations with students to find out the possible levels of their potential development (where they are) and to control their learning environments (where they should be) by providing proper support to make the concepts they acquire consistent with scientists’ current definitions.

Empirical Studies on Related Topics Osbome and Cosgrove (1983) discovered in their study that students lacked the support of substantial scientific concepts when they explained changes in the states of water. The finding was that they had only superficial knowledge of the terms and expressions. For example, some students would think that a solid changing into a liquid will lose weight or condensation will make particles more compacted. Bar and Travis (1991) investigated the concepts of liquid and gas as possessed by Israeli children and they found that most children had misconceptions about evaporation and condensation, suggesting that it was more difficult for the children to understand these abstract concepts.

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

The curriculum for science and technology in elementary schools in Taiwan includes the learning about substances and energy, natural environments, ecological conservation and information technology. The learning unit chosen in this study was focused on the important concepts of the Three States of Water and changes such as solidification, melting, condensation and evaporation, because it is related directly or indirectly to most of the subjects mentioned above. Although most of the phenomena can widely be seen in our daily lives, students may still have misconceptions due to their own mis-understanding and mis-reasoning. After reviewing related research conducted in this area, the authors found that most children do have misconceptions about the states of water. Only a few of them think that vapor can also become water at a low temperature. Very few of them discover that wind blowing can make water evaporate more easily. Senior students in elementary schools know much about evaporation, but they know little about condensation as a formal scientific concept. Many children think condensation is solidification. In general, condensation is a more difficult concept than evaporation for students to understand. Most students do not know the white smoke above boiling water is a gas or vapor; they think of it as smoke. Again, some students believe the weight of water changes after it becomes ice. This study therefore designed diagnostic tools and adaptive learning mechanisms to correct the students’ misconceptions that often occur.

Current Status of Adaptive ↜Learning Electronic Learning (or e-Learning), sometimes provided as online learning or web-based learning, means learning through digital content to reach the goal of learning anytime and anywhere. In general, e-Learning includes any means of delivering teaching materials through networks (Whittington, 2000). Since 1990, the Internet has developed rapidly. After the establishment of the

World Wide Web (WWW), many educational websites emerged (Berge & Collins, 1995; Cahoon, 1998; Collis, 1996; Porter, 1997). Digital content may consist of multimedia as well as online interactions, allowing learners to play a more active role in the process of learning (Aivazidis, Lazaridou & Hellden, 2006). Learners’ locations are no longer limited to classrooms, and they can learn anytime they want. In addition to a variety of teaching materials, e-Learning has gradually become the most convenient way for students to access new information and knowledge. Since traditional ways of learning can not meeting the needs of individual learners, an increasing number of researches in adaptive learning systems have been conducted in recent years. An adaptive learning system can provide suitable contents for different learners according to their backgrounds, prior knowledge, individual demands and learning statuses (Papanikolaou et al. 2002). Atkinson (1976) suggested that an efficient instructional strategy must be adaptive. Therefore, an adaptive learning system must change instructional strategy according to learners’ situations during a learning process under teacher’s control to enhance learning and achieve the expected instructional objectives. Besides, the system can collect some features of learners and store them in certain learning modules, which can be used to provide suitable contents for different learners (Brusilovsky,1996). Web-based learning has become more and more popular today. A web-based learning system is accessible by a large number of students at the same time according to individual necessity and learning pace, and it is not limited by time or space. Therefore, it is suitable for the development of adaptive learning environments (Chang, 2005). According to Lin’s study (1998), an adaptive learning system can achieve the goal of teaching students according to their aptitudes in a normal class grouping environment, and it makes learning more active and efficient.

3

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

A personalized web-based learning system was proposed by Chang et al. (2006) based on item response theory (IRT). The system was aimed at providing a suitable learning environment by considering the learning portfolios of content difficulty, learner’s ability and conceptual coherence. Lin and Kuo (2005) developed a virtual learning environment based on the theory of learning objects and constructivism. The learning contents and statuses of learners on the system can be individualized to achieve the goal of adaptive learning. Also, learners can cooperate in the inhabited virtual world to increase learning effectiveness during their learning processes. Because e-Learning systems are usually developed in accordance with learners’ requirement in terms of platforms, materials, presentation styles and virtual communities, it often occurs that some systems are only suitable for certain users. If a system is transferred to another environment, for some other people, tremendous manpower and costs must be spent in making changes (Dodds, 2001a; 2001b). To solve this problem, international standard organizations have specified e-Learning standards. E-Learning systems such as SCORM, AICC, IEEE, IMS, IEEELOM, ARIADNE, and Microsoft promulgate these standards (Hodgins & Conner, 2000). Among them, SCORM has now become an important standard for e-Learning content (Chang, Hsu, Smith & Wang, 2004). Learning contents that conform to SCORM standards have reusable and sharable features. However, there are still some disadvantages, such as complicated definitions for the rules of learning activity and huge frameworks for learning contents, making it difficult to manage, reuse and combine these with traditional educational theories. E-Learning does need a good system to support online services, such as course design, learning resource delivery, integration of courses and teaching methods (Suthers, Johnson & Tillinghast, 2002), etc. For this reason, the Graduate School of Online Learning Applications, National Chiao Tung University, Hsinchu, Taiwan devel-

4

oped their Object Oriented Learning Activity System (OOLAS) based on the standards of SCORM, Learning Design Specification, Knowledge Tree and Multibook. In the SCORM standards, most metadata models were used to define learning materials (Su, Tseng, Lin & Lu, 2005). Chang et al. proposed in their study (2004) a metadata model to define online assessment. OOLAS is composed of an authoring system and a learning system. In addition to a simple process for editing materials, it presents the contents of curricula easily and allows teachers to plan related programs to assist students with learning effectively. OOLAS also allows teachers to design the related tests of concepts. In this study, the authors used OOLAS to develop a web-based, adaptive learning system that was integrated with scaffolding to improve the learning efficiency of students. They also developed teaching materials for the concepts of the Three States of Water. The system modules were: diagnostic tools, a test-item database, adaptive learning modules and learning contents for the scientific concepts in the Three States of Water (Figure 1). The diagnostic tools were designed using twotiered test items to identify the prior misconceptions of students. After detecting their misconceptions, an adaptive learning module was initiated by a rule-based inference engine to generate individualized learning content for students according to the particular misconceptions of the particular student.

RESEARCH DESIGN This study was conducted using a quasi-experimental design. A total of 200 students belonging to two elementary schools in Taipei County were chosen for the experiment. The authors divided the students into a control group and experimental groups to investigate the learning of students with or without scaffolds. The authors also measured

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

Figure 1. The operation of the web-based, adaptive learning system

the changes in their learning responsibility after the e-Learning. For the control group, the students studied using the web-based, adaptive learning system by themselves without the provision of any scaffolds. For the experimental groups, the students could ask teachers for help if they had questions during the learning processes and after the diagnostic tests. There were two experimental groups, provided with scaffolds in different ways. For experimental group A, the scaffolds were provided in the form of online conversation between the teachers and students. For experimental group B, the scaffolds were provided in the form of face-to-face conversations between the teachers and students. For both media of communication, teachers provided scaffolds by discussing with the students to find out their problems and correct their misconceptions.

Research Procedure This study selected the Three States of Water as the topic of learning. Therefore, the authors first analyzed the related concepts covered by textbooks of elementary schools, and then developed a learning hierarchy according to these concepts. Based on the learning hierarchy, the authors used the diagnostic tools of the web-based, adaptive learning system to find out the misconceptions of students. The authors developed the adaptive learning modules by using a rule-based inference engine to provide remedial instructions for students according to a categorization of the types of their misconceptions. After that, the authors

conducted a quasi-experiment to find out the influence of scaffolding on students when they were learning using the system.

Research Samples The samples in this study were 5th and 6th grade students, randomly selected from two elementary schools in Taipei County. Because these students had already taken computer courses during their 3rd grade year, by the time of this experiment, they had two to three years of experience in using computers and the Internet. This reduced the influence of computer skills on the effectiveness of e-Learning. As stated, the students were divided into the control group (without scaffolds) and the experimental groups (with scaffolds). The experimental groups consisted of group A (providing scaffolds via online conversation) and group B (providing scaffolds via face-to-face conversation). According to a pretest, students with scores above the first 50% were classified as high achievement students while the remaining 50% were classified as low achievement students. In the control group, there were 33 high-achievement students and 33 low-achievement students, making a total of 66 students. In the experimental group A, there were 33 high-achievement students and 32 low-achievement students, making a total of 65 students. In the experimental group B, there were 35 high-achievement students and 34 lowachievement students, making a total of 69 students (as listed in Table 1).

5

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

Table 1. The number of students in each group Content

Three States of Water

Groups

Scaffolds

Control Group

None

Achievement

Number of Students

High

33

Low

33 33

Experimental Group A

Online Conversation

High Low

32

Experimental Group B

Face-to-Face Conversation

High

35

Low

34

Total Number of Students

Diagnostic Tools The questions to diagnose misconceptions about the Three States of Water in this study were modified from the paper-based test questions designed by Chang (2003), who analyzed the misconceptions that students in elementary schools often have. Since two-tier test items have been used widely and efficiently in discovering misconceptions and conceptual changes (Tsai & Chou, 2002), the authors thus used them to develop the diagnostic tools based on the empirical study of Lin (1995). The authors consulted three science teachers and two experts in science education about the validity of the test items and diagnostic tools. Finally, the two-tier test items were uploaded and stored in the test-item bank by using authoring tools of the system. An example of the two-tiered question follows: There are two identical wet towels. One is spread and the other is folded. Which one do you think will dry first? Answer: (A) Folded one. (B) Both at the same time. (C) Spread one. (D) I don’t know. Explain your reason:.

Pretest and Posttest Limited by the sampling method and number of samples, we adopted a non-equivalent group pretest-posttest design in our experiment, and adjusted the difference in students’ background

6

200

using an analysis of covariance (ANCOVA) to investigate the influence of scaffolding on the students with different levels of achievement. The questions in the pretest and posttest were designed based on the learning contents and related concepts of the Three States of Water. The reliability of the achievement test was verified by an internal-consistency reliability test with Cronbach α=0.71. After removing the inappropriate questions, there were 113 multiple-choice questions left. Among them, 37 questions were selected to form the pretest and posttest, and the remaining questions were used as diagnostic test items. The scores of the pretest were used to measure the students’ levels of achievement. The questions in the posttest were similar to that of the pretest, enabling the authors to compare the experimental and control group results. An example of a question follows: Which of the following is the correct description for the speed of evaporation? (A) The more humid the environment is, the faster the evaporation is. (B) The hotter the environment is, the faster the evaporation is. (C) The more airtight the environment is, the faster the evaporation is.

Measurement of Learning Responsibility In this study, the authors used a questionnaire to measure the development of self-learning responsibility after the web-based learning. The ques-

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

tionnaire was developed by the researchers and verified by three elementary school teachers and two experts in the research area of science education. It contained 18 questions. Each question had five scales in its answer: 5 points for very likely, 4 points for likely, 3 points for no opinion, 2 points for not likely, and 1 point for not likely at all (as shown in Appendix I). This is an indicator for the degree of development of the students’ learning responsibility. All questions in this measurement were positive-response designed. Thus, the more points a student gained, the more responsible and active he or she was in learning. The reliability of this measurement was verified by testing on 32 6th grade students and the total internal consistency was calculated as Cronbach α=0.89.

INSTRUCTIONAL DESIGN The principle of instructional design in this study was based on Gagne’s learning hierarchy (1985). The major concepts of the Three States of Water were analyzed to form a hierarchical diagram. The learning hierarchy was constructed according to competence indicators for the curriculum of science and technology in elementary schools in Taiwan. For example, the concepts of the Three States of Water are based on solidification, melting, evaporation and condensation. Deeper, the concept of solidification contains the lower-level concepts of water changing from liquid to solid, increasing volume, and mass conservation. Because condensation, solidification, melting and evaporation are the major concepts for the Three States of Water in elementary science courses, a number of teaching activities were designed to introduce these concepts. The authors encoded all concepts in the learning hierarchy by number to simplify the diagnostic sequences. A student with a misconception at a high level implies that he or she may have misconceptions at lower levels and thus requires further diagnostic processes. Generally, the higher the

hierarchical level is, the smaller the number is. For example, the highest-level concept is “three states of water”, which was encoded as 1. The secondlevel concepts are “solidification”, “melting”, “evaporation”, “condensation”, and which were encoded as 2, 3, 4, and 5. The concept of “solidification” (2) contains the lower-level concepts of water changing from “liquid to solid” (6), “mass conservation” (7), and “increasing volume” (8) as shown in Figure 2. Because experiments and observation are very important for the establishment of scientific concepts, the authors designed several online experiments to simulate the phenomena of the Three States of Water to help students develop their scientific concepts (Figure 3). The experiments were designed using Flash to provide an interactive user interface, animations for the simulation of the phenomena and concepts in the Three States of Water. In this study, there were four lessons for all students to complete. After each one, the students did a diagnostic test to see if they had completely understood the scientific concepts. The design of diagnostic tests followed the sequence of solidification, melting, evaporation and condensation. After students had completed a learning activity, they were directed to the diagnostic tests to see if their understanding about the related concepts was correct. If the concepts of students were valid according to the diagnostic results, they could keep on learning the remaining concepts. Otherwise, the students had to proceed with remedial instruction to correct their misconceptions. For example, if students passed the tests on the concept of solidification, they could move to the next stage to start the learning activities on the concept of condensation. Otherwise, they were directed to the remedial instructions for the correction of previous misconceptions, followed by formative evaluations to guarantee the conceptual changes had been internalized. When all misconceptions were corrected after remedial

7

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

Figure 2. Hierarchy of scientific concepts in the three states of water

learning activities, they could start learning the contents for the next stage (Figure 4).

RESULTS AND DISCUSSIONS The major purpose of this experiment was to investigate students’ learning enhancement on the web-based, adaptive learning system and the development of learning responsibility after the

e-Learning. In addition, the learning statuses of students, such as misconceptions and conceptual changes, were also studied by analyzing learning records. Students’ scores in the pretest and posttest were analyzed using statistical software SPSS to calculate the mean and standard deviation for each group.

Figure 3. The online experiments incorporated in the learning content

8

The Effectiveness of Scaffolding in a Web-Based, Adaptive Learning System

Figure 4. Learning diagnosis design of the system

Learning Effectiveness Based on the analysis of the T-test, all students performed very well on the web-based, adaptive learning system, no matter whether they were highachievement (t=7.27, p θA, being θA and θB respectively the medians of the statistical distributions LA and LB to which the stochastic variable L belongs. •

Question 2:

two samples of users who navigated according to modalities A and C, are due to chance and the two groups of users belong to the same population. Alternative Hypothesis H1: The population yielding the sample that navigated according to modality C, is different from the population that navigated according to modality A. Hence, in statistical terms: H0: θC = θA and H1: θC > θA, being θA and θC respectively the medians of the statistical distributions LA and LC to which the stochastic variable L belongs. •

Question 3:

Null Hypothesis H0: The differences observed in the measures of the statistical parameters of the two samples that navigated according to modalities B and C, are due to chance and the two groups of users belong to the same population. Alternative Hypothesis H1: The population yielding the sample that navigated according to modality C, is different from the population that navigated according to modality B. In statistical terms: H0: θC = θB and H1: θC > θB being θA and θB respectively the medians of the statistical distributions LB and LC to which the stochastic variable L belongs

The Statistical Sample For our experiment, we formed a sample of 30 users, with a homogeneous starting knowledge on the domain of interest, as measured by means of a pre-test questionnaire. This sample was randomly selected among students of our university. Within this group, three groups were randomly formed: 10 users navigated according to modality A, 10 according to modality B and 10 according to modality C for a total of 120 minutes each. All users were trained on the procedure to be followed before starting the experiment.

Null Hypothesis H0: The differences observed in the measures of the statistical parameters of the 59

A Case-Based Approach to Adaptive Hypermedia Navigation

Hypothesis Testing

fact, the last column of Table 1 shows the lowest and the highest values for the distribution translation due to the navigation. As already stated in the previous section, it turns out that all the three null hypotheses must be rejected. This supports all three of our alternative hypotheses, because in all three cases we have: p-value < α = 0.05. The sample navigating according to modality C is very different from sample A. In addition, modality B is between modalities A and C. This is meaningful because it implies that even when the topological and semantic orientation provided by the system is static, i.e., maintaining the same node as root, (higher GW parameter), it nevertheless promotes the learning process by means of a less chaotic and a more guided navigation. If we want to estimate the added value provided by the two types of help, static (modality B) and dynamic (modality C), compared to the navigation performed without any type of help, we must first compute the statistical parameters of the three samples, i.e., their median θ. We can thus express the estimated added value by computing the ratios between the modalities, i.e., the ratios between the medians of the shifted statistical distributions. The results are shown in Table 2. As we can see from the last column of Table 2, the added value of the navigation, effected by means of the “intelligent help” module is well-

We report in Table 1 the WMW test results, together with the results for the confidence interval of the variable Δ, obtained by means of the Hodges and Lehmann procedure (Hodges & Lehmann, 1963), with a level of significance α = 0.05.

Discussion The first column of Table 1 shows the tested comparisons. In all cases we obtained: p-value < α. Consequently, we must reject all the Null Hypothesis H0. This means that after navigating, the three samples of users belong to different distributions from the original ones due to a translation estimated to be towards higher values. The estimated translation Δ, shown in the fourth column needs to be considered: it is different in all three WMW tests. Table 1 highlights that the translation, estimated in an exact way for the testing of hypothesis 1 was: Δ = 27, whereas it was Δ = 38 in the case of testing hypothesis 2 and finally it was Δ = 68 for the testing of hypothesis 3. These scores undoubtedly strengthen the alternative hypotheses H1. The last column of Table 1 shows the results obtained by means of the Hodges and Leheman procedure applied to the samples, for the confidence interval estimation of Δ at 95%. In Table 1. WMW test results Comparison

p-value

H0

∆

[α,β]

1. (A vs. B)

0.0262

Rejected

∆1 = 27

[0,40]

2. (B vs. C)

0.0116

Rejected

∆2 =38

[0,68]

3. (A vs. C)

0.001

Rejected

∆3 = 68

[14,75]

Table 2. Comparison among A, B and C navigation modalities

60

Comparison

Ratio

Added Value

B vs. A

= = 1.71

71%

C vs. B

= = 1.66

66%

C vs. A

= = 2.85

185%

A Case-Based Approach to Adaptive Hypermedia Navigation

evident: it can be up to 185% higher than the value obtained from a non-assisted navigation and 71% higher than the one drawn from a navigation with a static, topological-oriented help module. The inferential statistical model based on a non-parametric hypothesis testing, calculated on the score obtained in the output test, confirmed the correlation in its different combinations, at different levels. In particular, it strengthens the hypothesis that the proposed adaptive help, obtained by way of AI techniques, will effectively find the learning goal of the user or, at least, the related aim and thematic path best suited to the user’s learning purposes. Moreover, the knowledge that HyperCase infers about the user’s learning goal is of great advantage to user disorientation problems, since it enables the construction of the most appropriate help service to bring the user `back on track’.

Related Work We shall now present an overview of some of the more significant proposals regarding adaptive educational hypermedia, developed during past years in order to face the disorientation problem of navigation in closed-corpus hypermedia domains, such as guided tours in museums, galleries or monuments or cultural heritage information. In particular, we will focus on approaches based on adaptive navigation, that is, the manipulation of links that are presented within pages (Brusilovsky & Millan, 2007). The reader is referred to (Kobsa, Koenemann, & Pohl, 2001; Brusilovsky & Maybury, 2002; Brusilovsky & Millan, 2007) for a more in depth description of the various adaptive hypermedia systems proposed in the literature. In (Funk & Conlan, 2002), the authors study how feedback helps authoring and improves personalization in a education environment. The feedback may be gathered implicitly by analysis and evaluation of the learner’s progress, or requested explicitly from the user. The learning content may be structured at runtime in different ways, e.g.

text documents, slides, animation, simulation, interactive, according to the learner preferences. Clustering techniques group learners with similar preferences and needs into sets of stereotypes. This is particular useful when the learner models are sparse and incomplete. A case-based reasoner is employed to sequence learning objects by means of required competence and additional competence achieved according to prerequisite requirements, in terms of knowledge or competencies the learner is supposed to have. The work does not provide details on the implementation or any evaluation. Fink et al. (Fink, Kobsa & Nill, 1998) focus on adapting hypermedia for elderly and disabled users. User models are acquired through interviews, inference and stereotypes and are hierarchically organized including the respective handicap and the ability to use complex user interfaces. The adaptivity is mostly based on stereotypes of users with similar handicaps, simplifying the GUI according to the abilities of current users and suggesting information related to their needs. The evaluation involves a small group of users and does not include a formal empirical methodology to prove the efficacy. From a different prospective, Interbook (Seeberg, Reichenberger, Fischer, Steinmetz & Steinacker, 1999) provides guided tours in form of tables of contents organizing the most relevant subset of the material to the user through conceptual networks. Each link between learning objects is tagged with one the following educational states: ready to be learnt, recommended, not ready to be learnt. Interbook is based on the domain modelling approach of ELM-ART (Weber & Brusilovsky, 2001), an intelligent interactive educational system that supports teaching of programming languages. In order to sequence the available content, the system provides adaptive navigation support in terms of suggested links connected to the most relevant next unit for the current user. Each learning unit is represented as an object containing text unit and information that can be used to relate units and concepts to each other. The learners are evaluated

61

A Case-Based Approach to Adaptive Hypermedia Navigation

with tests, i.e. a sequence of questions that examine the knowledge of the user about the concepts explained in that unit. The effectiveness of Interbook is yet to be evaluated, while the evaluation of the user knowledge based on explicit tests does not suggest a feasible adaptation of ELM-ART in our domains. Further systems in literature follow different approaches. Exploiting the Web to deliver information to different devices is the goal of the system described in (Wilkinson, Lu, Paradis, Paris, Wan & Wu, 2000). A discourse planner with a Web query and document synthesis technology answer user queries generating hypertext that is appropriate to the desired medium for delivery. The described adaptivity is location-dependent. The same adaptivity is used in the GUIDE project (Cheverst, Davies, Mitchell & Smith, 2000), where personal context, i.e., current location, preferred reading language, etc. is used to tailor the information presented to the visitor. The domain representation allows for setting relationships between informative objects in order to determine optimal routes between attractions. Special tags in HTML pages are replaced with personalized information. The NAUTILUS architecture (Gori, Maggini, Martinelli & Scarselli, 2000) consists of user profile updated by relevance feedback provided by the users. The users profiles are employed to perform a focused autonomous navigation by following only the hyperlinks that were evaluated as more promising. A Java graphical interface provides the NAUTILUS recommendations to the user. User profiles are built by means of TFxIDF and expected information gain. Recursive neural networks are employed to score and recommend links. A collaborative approach is employed by Bollen (Bollen, 2000). It generates navigation path based recommendations for individual users according to group user models. A further work (Marucci & Paterno, 2000) aims to design a virtual assistant for museums. Users are supported, during their visit, by a virtual guide using techniques such as user stereotypes (tourist, student, expert) or models derived from user preferences. At the

62

beginning, user needs can be explicitly indicated among a set of predefined options, and they can be updated during a session taking into account the user accesses. The system suggest various kinds of information, such as summaries, comparison and difference information related to the current page. Nevertheless, it does not provide any adaptivity about the organization and sequencing of the available informative units. Kadobayashi et al. (Kadobayashi, Nishimoto, Sumi & Mase, 1998) allows users to explicitily express interest on a set of topics. Then, using a predefined network that associates the topic according to their semantic closeness, a mediating agent identifies further new information that can be interesting for users. Finally, the AHA! system (de Bra, Smits & Stash, 2006) uses Link Hiding and Annotation techniques in order to help students to learn the proposed knowledge domain. This system, designed as a generic adaptive hypermedia system. The AHA! system allows authors to define new concept relationships types in order to be a multi-domain Adaptive Hypermedia authoring system as well. The system records, for each user, the visited nodes and, by means of pre-set rules, suggests some nodes to visit. Differently, our system was designed to run on closed and complex domains in order to be more effective in helping users to not loose themselves in hyperspace.

CONCLUSION AND FUTURE WORK Our contribution is focused on an approach based on cases for guided navigation in hypermedia environment and its application within the HyperCase system, particularly tailored for educational purposes. The main idea of the proposed approach lies in the attempt to automatically deduce users’ learning goals and subsequently supply the relevant guidance for their hypermedia navigation. The interaction process with the system is based on our constructivist and self-directed learning vision. The idea has taken the practical form of

A Case-Based Approach to Adaptive Hypermedia Navigation

a completely unobtrusive help system, where the system “steps in” only at the user’s specific request. An experimental evaluation with nonparametric statistics techniques shows evidence in the effectiveness of the proposed system. The adaptive hypermedia system is well designed for closed-corpus that can be manually tagged by an expert but it is not easily scalable to wider domains such as the Web. To reach this target, new techniques able to recognize abstract goals on the basis of user actions and automatically retrieve and organize learning paths must be developed. Thanks to these techniques, the domain expert is not longer required and the CBR approach may be successfully applied in the every-day user task.

REFERENCES Akscyn, R. M., McCracken, D. L., & Yoder, E. A. (1988). Kms: a distributed hypermedia system for managing knowledge in organizations. Communications of the ACM, 31(7), 820–835. doi:10.1145/48511.48513 Bollen, J. (2000, August 28-30). Group user models for personalized hyperlink recommendations. In Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Trento, Italy, (pp. 38-50). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Botafogo, R. A., Rivlin, E., & Shneiderman, B. (1992). Structural analysis of hypertexts: identifying hierarchies and useful metrics. ACM Transactions on Information Systems, 10(2), 142–180. doi:10.1145/146802.146826 Brunetta, G. P. (1993). Storia Del Cinema Italiano - dal Neorealismo al Miracolo Economico: 1945-1959 (Vol. III). Rome, Italy: Editori Riuniti.

Brusilovsky, P. (2007). Adaptive navigation support. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The Adaptive Web, Methods and Strategies of Web Personalization, vol. 4321 of Lecture Notes in Computer Science (pp. 263–290). Berlin, Heidelberg, Germany/New York, NY: SpringerVerlag. Brusilovsky, P., & Maybury, M. T. (2002). From adaptive hypermedia to the adaptive web. Communications of the ACM, 45(5), 30–33. doi:10.1145/506218.506239 Brusilovsky, P., & Millan, E. (2007). User models for adaptive hypermedia and adaptive educational systems. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The Adaptive Web, Methods and Strategies of Web Personalization, vol. 4321 of Lecture Notes in Computer Science (pp. 3-53). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Charney, D. (1987, November 13-15). Comprehending non-linear text: the role of discourse cues and reading strategies. In HYPERTEXT ’87: Proceedings of the ACM conference on Hypertext, Chapel Hill, NC, USA, (pp. 109–120). New York, NY, USA: ACM. Cheverst, K., Davies, N., Mitchell, K., & Smith, P. (2000, August 28-30). Providing tailored (context-aware) information to city visitors. In Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Trento, Italy, (pp. 73-85). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag de Bra, P., Smits, D., & Stash, N. (2006, August 22-25). The design of AHA! In U. K. Wiil, P. J. Nurnberg, and J. Rubart (Eds.), In HYPERTEXT 2006, Proceedings of the 17th ACM Conference on Hypertext and Hypermedia, Odense, Denmark, (pp. 171–195). New York, NY, USA: ACM. Duffy, T. M., & Knuth, R. A. (1990). Hypermedia and instruction: where is the match? Designing hypermedia for learning, 199–226.

63

A Case-Based Approach to Adaptive Hypermedia Navigation

Ebel, R. L., & Frisbie, D. A. (1991). Essential of Educational Measurement. Englewood Cliffs, NJ: Prentice-Hall. Fink, J., A. K., & Nill, A. (1998). Adaptable and adaptive information provision for all users, including disabled and elderly people. New Review of Hypermedia and Multimedia, 4, 163–188. doi:10.1080/13614569808914700 Fink, J., Kobsa, A., & Nill, A. (1998). Adaptable and adaptive information provision for all users, including disabled and elderly people. New Review of Hypermedia and Multimedia, 4, 163–188. doi:10.1080/13614569808914700 Funk, P., & Conlan, O. (2002, September 4). Using case-based reasoning to support authors of adaptive hypermedia systems. In Proceedings of Workshop on Case-Based Reasoning for Education and Training, CBRET’2002, Aberdeen, Scotland, (pp. 15–23). Aberdeen, UK: Robert Gordon University. Furnas, G. W. (1986). Generalized fisheye views. SIGCHI Bulletin, 17(4), 16–23. doi:10.1145/22339.22342 Garzotto, F., Paolini, P., & Schwabe, D. (1993). Hdm—a model-based approach to hypertext application design. ACM Transactions on Information Systems, 11(1), 1–26. doi:10.1145/151480.151483 Gori, M., Maggini, M., Martinelli, E., & Scarselli, F. (2000). Learning user profiles in nautilus. In AH ’00: Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, London, UK, (pp. 323–326). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag Haykin, S. (1999). Neural Networks: A Comprehensive Introduction. Prentice Hall.

64

Hodges, J., & Lehmann, E. (1956). The efficiency of some non parametric competitors of the t-test. Annals of Mathematical Statistics, 35, 324–335. doi:10.1214/aoms/1177728261 Hodges, J., & Lehmann, E. (1963). Estimates of location based on rank tests. Annals of Mathematical Statistics, 34, 598–611. doi:10.1214/ aoms/1177704172 Jonansen, D., Mayers, T., & McAleese, R. (1993). A manifesto for a constructivist approach to technology in higher education . In Duy, T., Jonassen, D., & Lowyck, J. (Eds.), Designing Constructivist Learning Environments (pp. 231–247). Berlin, Heidelberg, Germany/New York, NY: SpringerVerlag. Kadobayashi, R., Nishimoto, K., Sumi, Y., & Mase, K. (1998). Personalizing museum exhibition by mediating agents. In IEA/AIE ’98: Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, London, UK, (pp. 648–657), Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Kobsa, A., Koenemann, J., & Pohl, W. (2001). Personalised hypermedia presentation techniques for improving online customer relationships. The Knowledge Engineering Review, 16(2), 111–155. doi:10.1017/S0269888901000108 Lindquist, E. F. (Ed.). (1996). Educational Measurement. Washington, DC: American Council on Education. Marucci, L., & Paterno, F. (2000). Designing an adaptive virtual guide for web applications. In Proc. of 6th ERCIM Workshop User Interfaces for Al l, Firenze, Italy, (pp. 57-67). Nielsen, J., & Loranger, H. (2006). Prioritizing Web Usability. Thousand Oaks, CA, USA: New Riders Publishing.

A Case-Based Approach to Adaptive Hypermedia Navigation

Pal, S. K., Aha, D. W., & Gupta, K. M. (2006). Case-Based Reasoning in Knowledge Discovery and Data Mining. New York, NY, USA: John Wiley & Sons.

Weber, G., & Brusilovsky, P. (2001). Elm-art: An adaptive versatile system for web-based instruction. International Journal of AI in Education, 12(4), 351–384.

Rivlin, E., Botafogo, R., & Shneiderman, B. (1994). Navigating in hyperspace: designing a structure-based toolbox. Communications of the ACM, 37(2), 87–96. doi:10.1145/175235.175242

Wilcoxon, F. (1947). Probability tables for individual comparisons by ranking methods. Biometrics, 3, 119–122. doi:10.2307/3001946

Seeberg, C., Reichenberger, K., Fischer, S., Steinmetz, R., & Steinacker, A. (1999, June 1924). Dynamically generated tables of contents as guided tours in adaptive hypermedia systems. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications, Seattle, WA, USA, (pp. 640-645), Charlottesville, VA, USA:AACE. Snaprud, M., & Kaindl, H. (1994). Types and inheritance in hypertext. International Journal of Human-Computer Studies, 41(1-2), 223–241. doi:10.1006/ijhc.1994.1057 Stanton, N., & Baber, C. (1992). An investigation of styles and strategies in self directed learning. Journal of Educational Multimedia and Hypermedia, 1(2), 147–167. Sun, C., Ching, Y., & Lin, F. (1995). Modeling hypermedia navigation: An AI approach. In Proceedings of the 4th International Conference on Artificial Intelligence in Education (AI-ED), Washington, DC, (pp. 365-372), Charlottesville, VA, USA:AACE. Vinga, S. (2006). Analysis and prediction of user behaviour in a museum environment. PhD thesis, University of Melbourne.

Wilkinson, R., Lu, S., Paradis, F., Paris, C., Wan, S., & Wu, M. (2000). Generating personal travel guides from discourse plans. In AH’00: Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, London, UK, (pp. 392-395), Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Willis, J. (2000). The maturing of constructivist instructional design: Some basic principles that can guide practice. Educational Technology, 40(1), 5–16. Zancanaro, M., Kuflik, T., Boger, Z., Goren-Bar, D., & Goldwasser, D. (2007, June 25-29). Analyzing museum visitors’ behavior patterns. In User Modeling 2007, 11th International Conference, UM 2007, Corfu, Greece, (pp. 238-246), Berlin, Heidelberg, Germany/New York, NY: SpringerVerlag.

ENDNOTE 1



The modalities developed to answer the first question Where am I?, are treated in the next section.

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 35-53, copyright 2009 by Information Science Reference (an imprint of IGI Global)

65

66

Chapter 4

Animated Pedagogical Agents: The Effect of Visual Information on a Historical Figure Application R. Heller Athabasca University, Canada M. Procter Athabasca University, Canada

ABSTRACT The role of Animated Pedagogical Agents (APAs) depends on an understanding of the persona effect as a mechanism for increasing student engagement and motivation. We argue that historical figure applications of APAs may be helpful to identify the parameters that give rise to a persona effect. Given the importance of visual information, an experimental approach was used to examine how different image conditions would affect perception of a historical figure APA interaction. Eighty-eight participants were randomly assigned to one of three conditions; no image, static image, or animated image. Contrary to expectations, the no image condition was associated with significantly higher ratings for 6 of the 12 measures, including 3 measures of social presence. These findings stand in contrast to previous research and suggest that historical figure applications may be unique in their evocation of a persona effect and valuable for understanding the nature of the persona effect.

INTRODUCTION Animated Pedagogical Agents (APAs) can be defined as computer-based characters with 2D or 3D animated representation and interactive capabilities through one or more modalities (e.g. text, speech, emotion, gesture, eyes movements) (Clarebout, Elan, & Johnson., 2002; Clark & Choi,, 2005, Craig, Driscoll, & Gholson, 2004; Craig, DOI: 10.4018/978-1-60960-153-9.ch004

Gholson, & Driscoll, 2002; Gulz & Haake, 2006). Importantly, APAs have some type of artificial intelligence or intelligent tutor system backend that allows the designer to simulate communicative agent behaviour while guiding human-agent interactions towards pedagogical goals and objectives. Johnson, Rickel, and Lester (2000) argue that APAs were created when animated interface agents were combined with intelligent tutor systems. According to Johnson et al., “APAs present two key advantages over earlier work; they increase the

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Animated Pedagogical Agents

bandwidth of communication between students and computers and they increase the computer’s ability to engage and motivate students” (p2). It is further assumed that these two features, traditionally problematic in distance education, ultimately improve learning outcomes and experiences. Lester, Converse, Kahler, Barlow, Stone, and Bhogal (1997) refer to these predictions as the ‘persona effect’ based on their findings that the mere presence of an animated agent had a strong positive effect on learner perceptions of the learning experience. More recently, Hadwin, Winne, & Nesbit (2005) identified APAs as an important research field at the “juncture of HCI and educational psychology” with the potential to improve learner interest, retention, and knowledge transfer. Clearly, understanding the persona effect and the variables that interact with the persona effect are important pre-requisites in the design of effective APAs. In this article, we provide a brief review of the persona effect, a rationale for using historical figure applications to investigate the scope of the persona effect and the results of an experimental investigation into the role of visual information and its modulation of the persona effect.

THE PERSONA EFFECT Although there have been numerous investigations of the persona effect in APAs (e.g. André, Rist, & Müller, 1999; Atkinson, 2002; Dirkin, Mishra, & Altermatt, 2005; Heller, Procter, Mah, Jewell, & Cheung, 2005; Johnson et al., 2000; Koda & Maes, 1996; Mayer, Sobko, & Mautone, 2003; Sproull, Subramani, Keisler, Walker, & Waters, 1996), a close examination of the literature concludes that the evidence for a persona effect is mixed (Clark & Choi, 2005; Dehn & van Mulken, 2000). Dehn & van Mulken (2000) identify 3 possible effects on the user as a result of an APA interaction. Evidence for a persona effect could be found in the user’s (1) subjective experience and perceptions of the system (2) behavioural record produced during the interaction, and (3) learning outcome as revealed

by performance measures taken subsequent to the interaction. In terms of subjective experience, as assessed through self report, there are numerous reports that interactions with animated agents are perceived by users to be engaging and entertaining (Takeuchi & Naito, 1995; Koda & Maes, 1996; Van Mulken, André, & Müller, 1998), believable (Lester et al., 1997), comfortable (Koda & Maes, 1996), and useable (Cassell & Thórisson, 1999; Lester et al., 1997; Takeuchi & Naito, 1995). Although the use of self-report data is important, the construct validity of many of the self-report measures has not been established (Dehn & van Mulken, 2000). Moreover, many of the studies lack suitable control conditions to establish the degree of attitudinal preference (Clark & Choi, 2005). Importantly, Gulz and Haake (2006) have pointed out that issues of visual rendering have been virtually ignored despite the close relation between visual information and attitude formation. Finally, an evaluation of the agent will be closely related to the overall performance of the system with respect to task goals and objectives (Dehn & van Mulken, 2000). Compared to subjective experience, there have been fewer studies that have examined the behavioural record for evidence of a Persona effect. One important source of behavioural data is the conversational record between the user and the APA. Cassell and Thórisson (1999) examined the efficiency of communication by documenting linguistic indices of errors (hesitations, repetitions, & communicative overlap). However, their findings were mixed, revealing that more natural acting animated agents were associated with users providing less repetitions but more hesitations and overlaps in comparison to less natural acting agents. Similarly, Takeuchi & Nagao (1993) calculated an index of communicative efficiency by recording the topic shifts and correct answers per unit time. They found that animated agents initially led to a better efficiency index but, as the communicative sessions increased, the improvement wore off. 67

Animated Pedagogical Agents

Surprisingly, there have been few investigations of social presence in the communicative exchange between learners and APAs as most studies have focused on self-report measures of perceived social presence (Dirkin et al., 2005; Moreno & Mayer, 2004; Phillips & Lee, 2005). Social presence is generally defined as the ability of learners to feel emotionally and socially connected to other social agents (Moreno & Mayer, 2004) and is an important outcome measure in the analyses of online courses and asynchronous discussion forums (Rourke, Anderson, Garrison, & Archer, 2001; Swan & Shih, 2005). If learners actually accept APAs as social agents, there should be evidence of social presence in the conversational logs. Moreover, the degree of social presence may in turn be positively related to other measures of agent perception. Finally, the evidence for a persona effect on performance measures is also very weak, especially if methodological limitations are taken into account. Lester, Converse, Stone, Kahler, & Barlow, (1997) were the first to report an increase in problem solving ability following students’ interactions with a fully animated APA compared to less animated agents and other researchers have reported similar findings (Mayer et al., 2003; Moreno, Mayer, Spires, & Lester, 2001; Moundridou & Virvou, 2002). In contrast, other researchers have found no differences between groups on measures of learner outcomes (André et al., 1999; Atkinson, 2002; Craig et al., 2004; Van Mulken et al., 1998). In our own work with conversational agents, we found that learning outcomes were actually better for a standard web interface in comparison to a carefully-matched conversational-based interface (Heller & Procter, 2007). Much of this literature is difficult to interpret because of the confounded variables in many of the experimental designs and the lack of appropriate control conditions (Clark & Choi, 2005; Dehn & van Mulken, 2000). In summary, the evidence for a persona effect is somewhat equivocal and may only occur for the affective component of the learning experience.

68

Clark & Choi (2005) make a number of recommendations to address the weak internal validity of previous research. In addition, the evidence is difficult to interpret because of the limited range of APA operationalization. According to Clarebout et al.’s (2002) review, most APAs are designed to act in the role of a teacher or coach embedded within a complex learning environment. Much of this research was focused on the acquisition of domain specific knowledge using well structured problems with procedural-like solutions. Although important as APAs, coaches do restrict the kinds of social relationships and roles that can be effectively utilized in learning situations. Not only may coaches be intrinsically less engaging than other personas, the role of a coach is mostly limited to explaining and showing (Clarebout et al., 2002). In the next section, we argue that the scope of APA deployment should be expanded by investigating historical figures as APA applications

HISTORICAL FIGURE APPLICATION As noted earlier, the APA’s ability to engage and motivate the student is a critical prerequisite for the persona effect to occur (Gulz & Haake, 2006). We hypothesize that APAs based on well-known historical figures may generate significant intrinsic interest in the users and, in turn, maximize the APA’s potential to engage and motivate. Moreover, users with an intrinsic interest in the APA may adopt a lower psychological threshold for agent believability and realism. Johnson et al. (2000) note that, like agents designed for entertainment, APAs must be lifelike and believable in order to maximize engagement. These are critical aspects of APA design that tend to require costly technology. Unlike the role a student adopts when interacting with a teacher-oriented APA with structured problem solving & procedural-like solutions, the role of a learner interacting with a historical figure APA is more of a journalist or interviewer. Their

Animated Pedagogical Agents

primary task is to formulate questions and comments around the life and times of the historical figure and contribute appropriately to the ongoing conversation. In response, a historical figure APA should be prepared, at the very least, to answer domain relevant questions as well as questions that are more autobiographical in nature. Thus, the conversational ability of a historical will be a critical feature that determines success. Especially important are the use of paralinguistic cues (voice, expression, gestures, etc.) that serve to increase the bandwidth of communication. As reported above, Cassels & Thórisson (1999) found that the provision of paralinguistic cues (or envelope feedback) is a crucial factor for supporting effective dialog. Another important feature in this type of application is the evocation of stories or narratives (Heo, 2004). Many of our day-to-day conversations involve the communication of the episodic events that occur in our lives. Some of these events are celebrated narratives from our past whereas others may revolve around the more mundane events of daily living. For historical figure applications, much of the content can be expressed in the form of a narrative which is expressed using the turn-taking rules & expressions associated with effective conversation. Surprisingly, the use of narratives by APAs is very infrequent despite the arguments supporting narratives as effective pedagogical tools for social exchange and learning (Shank, 1995; Shank & Neaman, 2001). Not only do Historical Figure applications increase the range of social roles and provide opportunity for use of narratives, they also provide a tighter synthesis between content and persona. As Johnson et al. (2000) noted, many APAs are the combination of a animated interface agent attached at the front end of an intelligent tutor system and that evaluations of the agent can also include evaluations of the system (or be driven by system performance). In a historical figure application, the content or system is more tightly woven into the agent.

In summary, we argue that historical figure applications are a strong test of the engagement function of an APA which should maximize the hypothesized persona effect associated with APAs. In addition, the historical figure application stresses the importance of conversation and narrative as the basis of information exchange and extends the set of social roles for students in learning and content interaction. Perhaps most importantly, the use of a historical figure application allows us to build on our previous work with conversational agents which is described below.

PREVIOUS CONVERSATIONAL AGENT RESEARCH The current research evolved out of earlier research on historical figure applications of conversational agents. Our first conversational agent (or chatbot) was based on Sigmund Freud, the father of psychodynamic theory and arguably the most well-known figure in psychology by university undergraduates. Freudbot was a conversational agent programmed to chat in the first person about Freudian theory, concepts and biographical events (Heller et al. 2005). In addition to the text windows used to display user input and agent output, a photo image of Sigmund Freud was displayed on the side and partially animated to appear as though the lips were moving as new text output was presented and with smoke occasionally wafting from a depicted cigar. Freudbot was developed using Artificial Intelligence Markup Language (AIML), an XML-based open-source programming language, developed by Richard Wallace. AIML is the language used to support ALICE (http://www.alicebot.org), an award winning chatbot and progenitor of thousands of other chatbots as hosted on Pandorabots (www.pandorabots.com). At its core, AIML relies on pattern matching and consists of “category” tags, that in turn contain a “pattern” and “template” tag. If the input matches the pattern, the template

69

Animated Pedagogical Agents

defines the action to be taken. Simple categories can be combined using a built in recursion function. Adding content to AIML agents is an iterative and incremental manual process where user input is targeted for failed matches and new content is added. In addition to programming content, AIML can also be used to manage the dialogue in order to present content as narrative. Freudbot was designed to represent topical content using a narrative structure similar in function to the story grammar approach of Thorndyke (1977). In addition to Freudbot’s general chat ability, close to 91 autobiographical and conceptual narratives were created that could be evoked by a user typing specified keywords and phrases. For example, when user asked about a particular concept or life event, Freudbot would provide an answer with implicatives that would invite the user to request more information using conversational directives (e.g. go on, tell me more, is that all, why is that, etc.), a feature consistent with the conversational rules related to turn-taking. The learner effectively controls the way in which a story can be told by switching to other stories or entering into specific parts of a story. Freudbot also has the capacity to return to a story after branching to a new location and also retains the parts of a story that have been told to prevent repetition. We also developed agent strategies loosely consistent with Speech Act theory that direct the user to ask about content within each agent’s repertoire. In cases in which no input was recognized, the agent would default to one of several conditional strategies: ask for clarification, suggest a new topic for discussion, indicate that he had no response, or ask the user for a suggested topic. Another type of conversational pickup strategy was to ask a question and then redirect to a known topic. For example, Freudbot could ask a question like “Are you happy?” and regardless of how the user responded, Freudbot would respond with a leading statement like “That reminds me of the pleasure principle.” This feature was designed

70

to lead the user back to a discussion of relevant agent topics. Freudbot was evaluated initially as a proof of concept and focused primarily on user’s subjective experience and conversational behaviour as dependent measures. There was also an interest in the effect of instructional set because pilot work indicated some confusion around the instructions on chatting with agents. An experimental approach was used to test two instructional sets; one that was elaborate and explained the kinds of things one can ask of Freudbot and the other that was sparse and simply introduced Freudbot as a conversational partner. The findings are summarized briefly below but a fuller description of the results can be found in Heller et al. (2005). Freudbot was evaluated in an online study involving 53 psychology students (81% women) who participated as an extracurricular activity mostly in response to an email request (Heller et al., 2005). After providing informed consent, participants were randomly assigned to one of the two instructional sets and then began their chat with Freudbot. After 10 minutes of chat, students were automatically directed to a questionnaire web page where they provided evaluations of their Freudbot experience as well as demographic and background information. Across the entire sample, participants were generally neutral towards Freudbot as the average rating for the 6 user experience questions ranged from 2.83 to 3.08 on a 5-point scale where higher values were associated with positive experiences. One exception to this neutral evaluation involved a question about expanding conversational agent technology to other areas. Participants were much more positive about the role of agents as the rating on this question was significantly higher than all other ratings. In addition, a clear majority of the participants were willing to chat again with Freudbot (68%) compared to 32% who said no. Not surprisingly, the group of participants who said yes to another chat rated their chat experience

Animated Pedagogical Agents

significantly higher across all questions than did the group who said no. In terms of the conversational record, participants were quite cooperative in the task as close to 90% of their input was judged to be on-task in the form of a question (46.7%), a statement (36.5%), a one word response (4.7%) or some other combination (1.8%). There was also a significant positive correlation between the proportion of on-task user responses and a global measure of chat evaluation (r = .27). Less cooperative was Freudbot as only 61% of Freudbot’s responses were judged to be appropriate. Importantly, there was no effect of instructional set on chat behaviour or questionnaire ratings which speaks to the intuitiveness of the conversational interface. Also notable were the findings that historical figure and quizbot applications were the most strongly endorsed directions for future development, especially by those who would chat again with Freudbot. The findings provided modest support for the potential of historical figure chatbots, especially for students who indicated they would chat again if given an opportunity. Historical figures applications were one of the highest rated applications which supports our assertion on their intrinsic appeal. There was, however, an obvious need for improvement in conversational performance. Although designed to speak in narratives, many students were unable to advance Freudbot completely within a story because of unanticipated questions and insufficient strategies/mechanisms for avoiding repetition and recovering from conversations that went off-topic. Subsequent work on Freudbot has focused on using the conversational record to improving performance by adding content and additional conversational strategies. It was interesting to note that despite the number of these ‘dead-end’ exchanges, virtually all participants were willing to keep trying and stay within their assumed role which we believe is related to the intrinsic appeal of this application. In the words of one participant; “It was pretty cool the way it felt

like I was actually interacting with Freud... he’s deceased though, yeah, but the picture, the fast answers... made me pay attention to the answers alot more than if I had been simply reading a text written by someone else. Plus it was cool to feel like I could voice my own opinion with the most well-known psychoanalyst of all time.” In summary, research on historical figure applications of conversational agents led us to believe that animated historical figures would be useful for investigating the scope of the persona effect in APAs. In addition, the open source nature of AIML afforded several options with respect to animation software for the chat agent interface. In the next section, we describe the creation of the historical figure APA application and an experimental test of the role of visual information in relation to the persona effect.

HISTORICAL FIGURE APA: VISUAL INFORMATION AND THE PERSONNA EFFECT A prototype historical figure APA was created by integrating the AIML-based Freudbot conversational agent with character agent software by Haptek (www.haptek.com). The Haptek software enabled us to create an animated image of Freudbot capable of head and eye movements and facial expressions. The same image of Freud used in Heller et al. (2005) was used to create the Haptek image. When the Haptek Player software is installed on the user’s computer, output from the AIML server is fed through the Haptek client’s text-to-speech engine to produce speech output with synchronized lip movement. Based on the user data collected in the previous study, the AIML content supporting Freudbot was improved through the targeting process; using the conversational record to add new categories that match user questions and comments for which there were no existing matches. Moreover logical mechanisms were added to detect conversations

71

Animated Pedagogical Agents

that were going off topic for too long, or indications that Freudbot was unable to deal with a user’s question. In such cases, a suggestion or request by Freud for a new topic was used to address the issue. The impact of visual information on the scope of the persona effect for a historical figure was examined using an experimental design patterned after previous studies that used a no agent image condition to contrast with one or more agent image conditions differing on a dimension of naturalness (Baylor & Ryu, 2003; Craig et al., 2002; Dirkin et al., 2005; Graesser et al., 2003; Moundridou & Virvou, 2002; Phillips & Lee, 2005; Sproull et al. 1996). It is important to note that some of these studies found that the presence of an agent image was associated with positive learning experiences (Baylor & Ryu, 2003; Moundridou & Virvou, 2002; Phillips & Lee, 2005) whereas others did not (Craig et al., 2002; Graesser et al., 2003). Interestingly, Dirkin et al. (2005) reported an all-or- nothing effect in which a no agent image condion and a fully expressive agent image were associated with better learning outcomes than less expressive agents. All of the aforementioned studies used agents that could be classified as coaches. The goal of the present study was to examine how visual information would affect a historical figure application. We assumed that the persona of historical figures had been already established and hypothesized that visual information would enhance the overall experience based on Lester et al. (1997) and Phillips & Lee (2005) who suggest the mere presence of a visual image can enhance the interaction between user and agent. Thus, the experimental design was identical to that of Baylor & Ryu (2003) and included a no image condition, a static image condition that was identical to the conditions used in Heller et al. (2005) and an animated image condition. In all conditions, the same conversational agent was used to manage the conversation. In addition, the same online research methodology developed in

72

previous research was used to recruit and direct participants through the study. One set of dependent measures were based on the earlier Freudbot study and focused on ratings of the activity along various dimensions. In addition, we developed 6 questions that addressed perceptions of social presence following Mayer and Moreno (2004). We expected that the animated image would be associated with the highest user ratings which would be consistent with the personna effect and that the no image condition would be associated with the lowest user ratings. We also expected the improvements in Freudbot’s conversational performance to be reflected in user ratings.

Method Eight-eight students in psychology (81% women) were recruited to participate in the study primarily through an email request from the first author. A small monetary incentive (1/30 chance in a draw for $300) was also provided to enhance participation rates. After providing informed consent, participants were randomly assigned to one of three interface pages. In the No Image condition, only the text boxes were presented. The right side of the computer screen as shown in Figure 1 was blank. The static image condition was identical to the display shown in Figure 1. In the animated condition, the static picture was replaced with the animated version shown in Figure 2. Participants assigned to the Animated condition underwent a separate installation process complete with a diagnostic test of Haptek functionality. Only those that passed the test were admitted to the animated condition. In all conditions, brief instructions on how to chat with Freudbot were presented and after reading the instructions, participants were advanced to one of the interface pages as described above. Once connected to the page, Freudbot would respond with “Hello, my name is Sigmund Freud. What would you like to talk about?”. After 10

Animated Pedagogical Agents

Figure 1. Screen capture of Freudbot from Heller et al. (2005)

minutes of unstructured chat behaviour, participants were automatically directed to a web questionnaire survey where they completed questions on their chat experience and relevant demographic variables.

Results Table 1 displays the average ratings for the two sets of questions used to measure chat experience on a 5-point scale where higher values were associated with positive experiences. As can be seen, the highest ratings were consistently given in the no image condition. For the first set of questions which focus on the user experience of the activity, there were significant differences between conditions on three of the 6 questions. Post hoc comparisons indicated the No Image condition Figure 2. Animated Freudbot with Haptek software

was significantly different from at least one of the two other conditions and that there were no statistically significant differences between the Static Image condition and the Animated Image condition for the 3 questions. The second part of Table 1 displays the six additional questions that focus on user perception of social presence. There were significant differences between groups on three of the 6 questions. Post hoc comparisons indicated the No Image condition was significantly different from at least one of the two other conditions and that there were no statistically significant differences between the Static Image condition and the Animated Image condition for the 3 questions. Of the participants who were asked whether they would be willing to chat again with Freudbot, 64% (n=56/88) of the participants indicated that they would chat again, a number not unlike the ratio obtained in Heller et al. (2005). However, when we look at the ratio across conditions, we can see that the no image condition is associated with highest proportion of return chatters (78%) compared to the static image (68%) and animated image conditions (48%), a difference that approached significance, χ2 = 5.68, df=2, p=.058. In terms of the conversational record, there were no differences between conditions in either the number of exchanges or in the number of content units expressed by Freudbot.

73

Animated Pedagogical Agents

Table 1. Subjective ratings of the activity across the three experimental conditions No Image

Static

Animated

F

P

How enjoyable was this activity?

3.44

3.13

2.86

1.28

.284

How engaging was this activity?

3.57

3.00

2.97

1.49

.232

*How easy was this activity?

4.43

3.83

3.60

4.30

.017

How useful is this activity for learning information about SF?

3.50

3.30

3.13

.66

.517

*How useful is this activity for remembering information about SF?

3.93

3.47

3.23

3.74

.028

Would you recommend this activity to others?

3.46

2.90

2.83

1.78

.174

*Overall, how would you rate this activity?

3.50

2.83

2.90

3.20

.046

How lifelike was Freudbot?

2.68

2.13

2.37

1.61

.206

How good was Freudbot’s use of language?

3.96

3.43

3.33

3.05

.052

*How natural was your interaction with Freudbot?

3.00

1.97

1.97

8.42

.000

*How easy was it to pretend you were talking to Freud?

3.35

2.50

2.27

5.57

.005

How compelling were the visual aspects of the interface?

2.61

2.13

2.48

.91

.407

*How friendly was Freudbot?

3.86

3.17

3.34

3.15

.048

Discussion Contrary to our expectations, the no image condition led to significantly higher user ratings than both the static and animated version of the identical conversational agents, a finding that undermines the putative role of visual information in the creation of a persona effect. These findings, although surprising, are partially consistent with the work of Dirkin et al. (2005) who reported an all-or-none effect in a similar study of APAs. In Dirkin’s study, user ratings of an intelligent tutor system were greatest in the absence of any interface agent or when a fully functional agent was present compared to other conditions involving a visual only or audio only agent was present. Dirkin et al. suggest that their ‘none’ effect was related to Reeves and Nass’s (1996) Media Equation hypothesis which states that people are predisposed to ‘see’ personality in agent-less software and other forms of media. Perhaps when the historical figure agent is presented in the absence of visual information, users fill in the gap with their own

74

knowledge and information about Freud. Ironically, when participants in the no image condition were asked whether an image of Freud would be useful, over two thirds of the sample indicated yes. However, unlike Dirkin et al., we did not obtain an ‘all’ effect. Although nonsignificant, the vast majority of ratings were lowest for the Animated condition. We suspect that the animated version of Freudbot requires improvement by creating a tighter synthesis between paralinguistic cues and conversational content. In the current implementation, the use of eye and head movements and facial expressions were minimized and occurred somewhat randomly to convey the illusion of animacy. It is possible that these cues were discordant with the conversational output thus creating a distraction. We also are concerned about the audio properties of voice synthesis and its discrepancy with beliefs about Freud’s voice as well as the co-presentation of audio with text. Craig et al. (2002) report that a spoken-narration-only condition was associated with significantly better learning outcomes than a narration-with-text condition. Although intrigu-

Animated Pedagogical Agents

ing, the present findings do require replication to rule out competing explanations. We also found no statistical differences between the previous Freudbot used in the previous study and the enhanced Freudbot used in the present study. Although we expected some improvement to be reflected in user ratings, a better test will be found in a detailed review of the conversational record which is currently underway. In addition, the conversational logs are also being measured in terms of (1) conversational flow based on the linguistic concept of adjacency pair, or the unit of exchange between two interlocutors and (2) the degree of social presence as reflected by the discourse style of the user.

CONCLUDING COMMENTS As Gulz and Haake noted in their 2006 review, the question regarding APAs has moved away from “Do they work?” to “When do they work and in what context?”. According to Clarebout et al. (2002), APAs are an opportunity to be grasped with potential to improve learner interest, retention, and knowledge transfer. In this article, we provided a rationale for exploring historical figure APAs that builds on our previous research incorporating a rigorous experimental approach and measures sensitive to the different dimensions of the persona effect. The findings from our first study of historical figures APAs are contrary to the expectations associated with visual information and its role in modulating the persona effect. Paradoxically, these findings suggest that historical figure applications may be ill-suited for animation. Subsequent studies are underway to replicate the ‘none’ effect obtained in the present study and untangle the variables that were necessarily confounded in the present study.

ACKNOWLEDGMENT We would like to acknowledge the contributions of Dean Mah, Lisa Jewell, Billy Cheung, Daniel Ha, & Jude Onuh for their work on portions of this research. We would also like to acknowledge financial support through the Mission Critical Research Fund from Athabasca University.

REFERENCES André, E., Rist, T., & Müller, J. (1999). Employing AI methods to control the behaviour of animated interface agents. Applied Artificial Intelligence, 13, 415–448. doi:10.1080/088395199117333 Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94(2), 416–427. doi:10.1037/0022-0663.94.2.416 Baylor, A. L., & Ryu, J. (2003). The effects of image and animation in enhancing pedagogical agent persona. Journal of Educational Computing Research, 28(4), 373–394. doi:10.2190/V0WQNWGN-JB54-FAT4 Cassell, J., & Thórisson, K. R. (1999). The power of a nod and a glance: Envelope vs. emotional feedback in animated conversational agents. Applied Artificial Intelligence, 13, 519–538. doi:10.1080/088395199117360 Choi, Y. K., Miracle, G., & Biocca, F. (2001). The effects of anthropomorphic agents on advertising effectiveness and the mediating role of presence. Journal of Interactive Advertising, 2(Fall), available online: http://wwwjiad.org Clarebout, C., Elan, J., & Johnson, W. L. (2002). Animated Pedagogical Agents: An opportunity to be grasped? Journal of Educational Multimedia and Hypermedia, 11(3), 267–286.

75

Animated Pedagogical Agents

Clark, R. E., & Choi, S. (2005). Five design principles for experiments on the effects of animated pedagogical agents. Journal of Educational Computing Research, 32(3), 209–225. doi:10.2190/7LRM-3BR2-44GW-9QQY

Hadwin, F. H., Winne, P. H., & Nesbit, J. C. (2005). Roles for software technologies in advancing research and theory in educational psychology. The British Journal of Educational Psychology, 75, 1–24. doi:10.1348/000709904x19263

Craig, S. D., Driscoll, D. M., & Gholson, B. (2004). Constructing knowledge from dialog in an intelligent tutoring system: Interactive learning, vicarious learning, and pedagogical agents. Journal of Educational Multimedia and Hypermedia, 13(2), 163–183.

Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behaviour. Trends in Cognitive Sciences, 9(4), 188–194. doi:10.1016/j.tics.2005.02.009

Craig, S. D., Gholson, B., & Driscoll, D. M. (2002). Animated pedagogical agents in multimedia educational environments: Effects of agent properties, picture features, and redundancy. Journal of Educational Psychology, 94(2), 428–434. doi:10.1037/0022-0663.94.2.428 Dehn, D. M., & van Mulken, S. (2000). The impact of animated interface agents: A review of the empirical literature. International Journal of Human-Computer Studies, 52, 1–22. doi:10.1006/ ijhc.1999.0325 Dirkin, K. H., Mishra, P., & Altermatt, E. (2005). All or nothing: Levels of sociability of a pedagogical software agent and its impact on student perceptions and learning. Journal of Educational Multimedia and Hypermedia, 14(2), 113–128. Graesser Graesser, A.C., Moreno, K., Marineau, J., Adcock, A., Olney, A., & Person, N. (2003). AutoTutor improves deep learning of computer literacy: Is it the dialog or the talking head? Proceedings of Artificial Intelligence in Education Gulz, A., & Haake, M. (2006). Design of Animated pedagogical agents: A look at their look. International Journal of Human-Computer Studies, 64(4), 322–339. doi:10.1016/j.ijhcs.2005.08.006

76

Heller, R. B., & Procter, M. (2007). Conversational Agents and Learning Outcomes: An Experimental Investigation. Proceedings of the World Conference on Multimedia, Hypermedia, and Telecommunications. Heller, R. B., Procter, M., Mah, D., Jewell, L., & Cheung, B. (2005). Freudbot: An Investigation of Chatbot Technology in Distance Education. Proceedings of the World Conference on Multimedia, Hypermedia, and Telecommunications. Henderson, J. M., & Hollingworth, A. (1999). High-level scene perception. Annual Review of Psychology, 50, 243–271. doi:10.1146/annurev. psych.50.1.243 Heo, H. (2004). Story telling and retelling as narrative inquiry in cyber learning environments. In R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds), Beyond the comfort zone: Proceedings of the 21st ASCILITE Conference Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000). Animated pedagogical agents: Face-to-face interaction in interactive learning environments. International Journal of Artificial Intelligence in Education, 11, 47–78. Koda, T., & Maes, P. (1996). Agents with faces: The effect of personification. Proceedings of the 5th IEEE International Workshop on Robot and Human Communication.

Animated Pedagogical Agents

Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A., & Bhogal, R. S. (1997). The persona effect: Affective impact of animated pedagogical agents. In S. Pemberton (Ed.), Human Factors in Computing Systems: CHI’97Conference Proceedings. New York: ACM Press. Lester, J. C., Converse, S. A., Stone, B. A., Kahler, S. E., & Barlow, S. T. (1997). Animated pedagogical agents and problem solving effectiveness: A large-scale empirical evaluation. In Proceedings of the Eighth World Conference on Artificial Intelligence in Education. Louwerse, M. M., Graesser, A. C., Lu, S., & Mitchell, H. H. (2005). Social cues in animated conversational agents. Applied Cognitive Psychology, 19, 693–704. doi:10.1002/acp.1117 Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds. Journal of Educational Psychology, 95(4), 806–813. doi:10.1037/00220663.95.4.806 Mayer, R. E., Sobko, K., & Mautone, P. D. (2003).. . Journal of Educational Psychology, 95(2), 419–425. doi:10.1037/0022-0663.95.2.419 Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: the case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733. doi:10.1037/00220663.92.4.724 Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610. doi:10.1037/0022-0663.94.3.598 Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning in virtual environments. Journal of Educational Psychology, 96(1), 165–173. doi:10.1037/00220663.96.1.165

Moreno, R., & Mayer, R. E. (2005). Role of guidance, reflection, and interactivity in an agentbased multimedia game. Journal of Educational Psychology, 97(1), 117–128. doi:10.1037/00220663.97.1.117 Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177–213. doi:10.1207/S1532690XCI1902_02 Moundridou, M., & Virvou, M. (2002). Evaluating the persona effect of an interface agent in a tutoring system. Journal of Computer Assisted Learning, 18, 253–261. doi:10.1046/j.02664909.2001.00237.x Phillips, B., & Lee, W. (2005). Interactive Animation: Exploring spokes-characters on the Internet. Journal of Current Issues and Research in Advertising, 27. Reeves, B., & Nass, C. I. (1996). The media equation: How people treat computers, television, and new medialike real people and places. Cambridge, UK: Cambridge University Press. Rourke, L. T., Anderson, T., Garrison, D. R., & Archer, W. (2001). Assessing social presence in asynchronous text-based computer conferencing. Journal of Distance Education, 14(2), 50–71. Shank, R., & Neaman, A. (2001). Motivation and Failure in Educational Systems Design, Smart Machines in Education (Forbus, K., & Feltovich, P., Eds.). Cambridge, MA: AAAI Press/ The MIT Press. Shank, R. C. (1995). Tell me a story: Narrative and Intelligence. Northwestern University Press. Sproull, L., Subramani, M., Keisler, S., Walker, J. H., & Waters, K. (1996). When the interface is a face. Human-Computer Interaction, 11, 97–124. doi:10.1207/s15327051hci1102_1

77

Animated Pedagogical Agents

Swan, K., & Shih, L. F. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115–136.

Thorndyke, P. (1977). Cognitive structures in comprehension and memory of narrative discourse. Cognitive Psychology, 9, 77–110. doi:10.1016/0010-0285(77)90005-6

Takeuchi, A., & Nagao, K. (1993). Communicative facial displays as a new conversational modality. Proceedings of the Conference on Human Factors in Computing Systems.

Van Mulken, S., André, E., & Müller, J. (1998). The persona effect: How substantial is it? In H. Johnson, L. Nigay, & C. Roast Eds. People and Computers XIII [Berlin: Springer.]. Proceedings of, HCI98, 53–66.

Takeuchi, A., & Naito, T. (1995). Situated facial displays: Towards social interaction . In Katz, I., Mack, R., Mack, L., Rosson, M. B., & Nielsen, J. (Eds.), Human Factors in Computing Systems (pp. 450–455). New York: ACM Press. doi:10.1145/223904.223965

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 54-65, copyright 2009 by Information Science Reference (an imprint of IGI Global)

78

79

Chapter 5

A Case Study of OntologyDriven Development of Intelligent Educational Systems Gordon Deline CBC/Radio-Canada, Canada Fuhua Lin Athabasca University, Canada Dunwei Wen Athabasca University, Canada Dragan Gašević Athabasca University, Canada Kinshuk Athabasca University, Canada

ABSTRACT This article presents a case study of ontology-driven development of intelligent educational systems. Following a review of literature related to ontology development, ontology-driven software development, and traditional software engineering, we developed an ontology-driven software development methodology appropriate for intelligent ontology-driven systems which have ontologies as key execution components, such as e-Advisor, and which is biased toward an integration of incremental and iterative ontology development and downstream Model Driven Architecture for development of software components.

INTRODUCTION Recent research indicates that ontologies will play a greater role in the development and╯maintenance╯of intelligent and adaptive educational systems. DOI: 10.4018/978-1-60960-153-9.ch005

The benefits of ontologies for intelligent educational systems are that (1) intelligent agents can use the developed ontologies as the basis for their knowledge base construction, reasoning and interface design; (2) in a distributed education environment, the ontologies developed for different entities can serve as standardized and open interfaces for interoperability and communication.

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Following review of the e-Advisor system and its development, we looked at how to formalize ontology-driven software construction. Areas of focus included ontology discovery, evaluation, reuse, integration, tie-ins with traditional software engineering methodologies and tools, and integration with governance frameworks. Using e-Advisor development as a case study, specifically how ontologies are developed and maintained, we have developed an ontologydriven software development methodology that would be appropriate for intelligent ontologydriven systems such as e-Advisor. This article presents a case study of ontologydriven software development methodology of intelligent educational systems. The organization of the rest of this article is as follows: Section II is a literature review; Section III describes e-Advisor and its ontologies that are key components of the e-Advisor architecture and their development and maintenance; Section IV and Section V review our ontology-driven development methodology as related to e-Advisor; and Section VI relates our conclusions and future work.

LITERATURE REVIEW As related by Chandrasekaran et. al (1999), ontologies are a key component that can enable effective communication between agents in a multiple agent system, and the building of agents’ knowledge. The advantages of ontologies in learner/user models are put forth by Kay (1999) and Chen & Mizoguchi (1999). Razmerita, et al. (2003) put forward an architecture for ontology-based user modeling. Mizoguchi and Bourdeau (2000) discussed the use of ontologies to overcome problems with the use of AI in education. The W3C’s Web Ontology Language (OWL) (Bechhofer et al., 2004) supports the definition of ontologies by building on and adding to the basic support provided by Resource Definition Framework (RDF) and RDF Schema for objects,

80

classes, properties, and hierarchies. OWL supports publishing and sharing of ontologies, knowledge management, and software agents. Protégé OWL is a tool that is used by domain experts to create and maintain reusable ontologies for knowledge-based systems and is the tool that the e-Advisor ontologies were developed using. As an open platform with a strong user base, a number of useful plug-ins can be found for Protégé to support such functionality as visualization and code generation, as well as the capability to build custom plug-ins. The architecture and features of Protégé-OWL are described by Knublauch (2003); Knublauch, Feargerson, Noy & Musen (2004); and Knublauch, Musen, & Rector (2004). Rector (2003) describes a method for normalization of Description Logics (DL)-based ontologies, specifically those constructed with OWL-DL. Seidenberg & Rector (2006) discuss ontology segmentation techniques and benefits. Pinto & Martins (2003) give guidelines for qualifying ontologies and enumerate both strict and desirable requirements to aid in this process. Barresi, Rezgui, Lima, & Meziane (2005) outline a methodology for integrating ontologies and Abels, Haak, & Hahn (2005) provide an overview of ontology integration methods categorized as mapping, aligning and merging and Euzenat & Shvaiko (2007) provide more recent coverage of ontology mapping. Knublauch (2006) makes recommendations applicable for building ontologies with ProtégéOWL and Rector et al. (2004) describe commonlyseen errors and issues with people learning OWLDL using Protégé OWL and relate best practices and guidelines. A natural integration point between ontologies and traditional Software Engineering methodologies is the OMG’s Model Driven Architecture (MDA) (OMG MDA, 2008), with benefits that can be seen as analogous to the benefits of using ontologies to model domains. Knublauch (2002) suggested the use of Agile development methodology for the development

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

of ontologies and proposed an ontology-driven software development (ODD) methodology built on the use of tools such as Protégé OWL (2006), with discussion of synergies with OMG MDA and efforts to bridge OWL and MOF/UML. Terrasse, Savonnet, Leclercq, Grison, & Becker (2006) proposed the use of ontologies as the first phase of an approach that is driven by meta-models which further refine the domain modeled by the ontologies, linking ontology concepts with UML concepts. The W3C Semantic Web Best Practices & Deployment Working Group’s working draft on Ontology Driven Architectures (W3C ODA, 2006) further supports MDA as a vehicle to support Ontology Driven Architecture (ODA).

E-ADVISOR AND ITS ONTOLOGIES This section introduces e-Advisor and reviews the key ontologies in e-Advisor and how knowledge is acquired and maintained. Students in degree programs have to balance personal and career objectives, preferences, and financial and time constraints against degree requirements, course availability and course interrelationships. If students go about planning their programs entirely on their own they can make non-optimal program choices that may not be discovered until a potentially non-recoverable problem arises. In traditional learning settings where the student is collocated with the academic and administrative staff, face-to-face meetings can facilitate the program planning process but this requires a non-trivial amount of time on the part of the advising staff members. The constraints and demands faced by faculty of post-secondary educational institutions are such that little time is left for faculty to personally advise students. The trends toward cost-effective lifelong learning have increased the demand for distance education and, especially in distance-education scenarios, both students and advisors face more

problems: face-to-face interviews are infeasible; students tend to have more severe work and family commitments that studies must be balanced against; completion of a degree or program tends to take much longer; and courses may be taken out of sequence due to students’ prior learning and experience or to facilitate immediate career objectives. Complicating matters further, course delivery schedules and prerequisite relationships are dynamic and change over time as a given program curriculum is developed and maintained via course revisions, additions, and closures. The longer period of time it takes to complete a course of study in a lifelong learning and distance education environment exacerbates the impact of these constant changes on academic advising. To assist students and advisors and address these issues in a more comprehensive manner than possible using more basic tools, many Expert Systems and Decision Support Systems (DSS) have been proposed and developed since the 1980s. These tools are able to provide more comprehensive support for academic planning, advising, and evaluation by leveraging advances in computer technology such as artificial intelligence (AI) techniques. Caroll & Chappel (1996); Murray & Le Blanc (1995); and Turban, Fisher, and Altman (1988) reviewed various approaches to the use of DSS in academic administration. Since 2003, a number of the authors of this article have been developing e-Advisor, an intelligent system that facilitates academic advising for students and administrators in the program of Master of Science in Information Systems (MSc IS) of Athabasca University1. Since academic advising involves intensive multi-participant cooperation, multiple intelligent agents were used in the architecture of e-Advisor. The system consists of four types of user agents: Student Agent, Administrator Agent, Instructor Agent, and Advisor Agent; and two types of resource agents, Ontology Agent and Database & Knowledge Base (DB&KB) Agent. Figure 1 depicts the architecture of e-Advisor.

81

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

In the e-Advisor architecture, the ontologies formally define domain entities and the relations among them. Based on the ontologies, the structural part of the knowledge base is modeled. The Student Agent acts on behalf of the individual student and as such must identify and understand learners’ preferences and requirements to generate and maintain a learner model for the student incorporating things such as job objectives, career track, learning style, and target date of completion. Using this knowledge and co-operating with Advisor Agents in the system, the User Agent develops and recommends personalized and correct schedules for the student. The Advisor Agent acts on behalf of an academic advisor to generate schedules for students being advised by the advisor, negotiating with Student Agents to assist in development of personalized and correct schedules for these individual students and evaluates the status of these students. The Instructor Agent assists the course instructor when defining and maintaining pre-requisites for courses the instructor is in charge of. The Administrator Agent Figure 1. E-Advisor high level architecture

82

maintains the curriculum model and conducts course curriculum projection. DB & KB Agents handle data/knowledge requests from other Agents in the system and notify interested Agents of changes in the system’s databases and knowledge bases so they can act on them. Ontology Agents support querying and knowledge inference and maintenance across the system’s ontologies on behalf of other agents in the system. The ontologies discussed here relate to the program and courses and the student being advised. The program and courses are modeled via the Topic Ontology, Course Ontology, and Program Ontology. The student is modeled using the Student Ontology and Preference Ontology. e-Advisor selects the ‘best’ possible Plan from a set of feasible Plans by relating the student’s preferences to each plan. This is done using associations between Program Topic (see Topic Ontology, below) and Program Preference (see Preference Ontology, below). A Program Preference, such as a Specialization, may be associated

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

with a set of Program Topics with a varying degree (real number in [0,1]) for each association. 1. Topic Ontology Program Topics are the lowest level concepts related to programs and courses, and describe topics that can be found in a given domain at the program level (may be taught in a course in a given program). In the Information System domain Program Topics include concepts such as Data and Object Structures, Data Management, and Data Mining. The Topic Ontology also models relationships between Program Topics. Prerequisite dependencies are modeled using the ‘is prerequisite of’ relation. This prerequisite relation is used by Instructor Agent to determine course prerequisites using a matching algorithm. The initial set of Topics in the Topic Ontology and their pre-requisite relations were derived from analysis of the MSc IS program structure and curriculum course descriptions. 2. Course Ontology The Course Ontology is made up of classes, subclasses, and properties related to courses in general, as well as courses in MSc IS program. As discussed above (see Topic Ontology), a Course is made up of a set of Topics. The Course class has basic properties such as the course title, description, language, and Topics covered (see Topic Ontology, above). Course is subclassed by CoursesInMScIS, which adds properties to model elements such as prerequisites and syllabus. Two more Course subclasses, CourseInPlans and CourseInTranscript, are further specializations. 3. Program Ontology The Program Ontology is used to build the logical structure of an academic program, including rules and regulations. The Program class has

properties that relate to the maximum duration, minimum number of credits, number of semesters per year, minimum number of courses to be taken in an academic year, etc. The MScIS class is a subclass of Program and contains properties specific to the MSc IS program. For example, since the MSc IS program has course requirements specific to its four building blocks of Foundation, Core, Elective, and Integration, the MScIS class has properties specific to these building blocks. 4. Student Ontology The Student Ontology includes: basic identifying information (e.g., address, phone number, email, occupation, and job title), course history (e.g., courses taken and courses passed), student preferences, planning parameters, and the currently selected plan. Students in the MScIS program can maintain their profiles by interacting with the Student Agent using a Web-based interface. Student is a specialization of User and MScIS Student is a specialization of Student with additional properties relevant to MSc IS students. 5. Preference Ontology In order to enable the selection of an optimal plan from a given set of feasible plans it is necessary to be able to understand and relate a given student’s preferences to course selection and program planning. The Preference Ontology was modeled to assist in this by capturing the student preferences, which can then be related to program topics. There are five program planning preferences, each with a set of subclasses. The program planning preferences are: Job Objective, Career Track, Assessment Style, Specialization, and Thesis Type.

83

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

ONTOLOGY-DRIVEN DEVELOPMENT IN CONTEXT OF E-ADVISOR As a result of review of the experience developing e-Advisor, a review of documented best practices, and qualitative analysis with subject-matter experts, we have also developed a methodology that supports Ontology-driven Development (ODD) suitable for development of intelligent systems such as e-Advisor. Areas reviewed and covered include documented methodologies, tools, and best practices for ontology building, ontology refactoring (normalization, segmentation), ontology discovery and integration, Model-Driven Architecture, iterative and incremental software development, and integration with project governance frameworks. Some findings from the development activity and especially the qualitative analysis are related in Deline, Lin, Wen, Gasevic, & Kinshuk (2007). In this section, we discuss why ODD was chosen as being well-suited to intelligent systems such as e-Advisor, stakeholder roles, objectives and review areas, and an overview of the methodology.

A. Why Ontology-Driven Development? We looked at ontology-driven development for our methodology from early on given the benefits of ODD and how well ODD integrated with e-Advisor development practices. We can see that agents use the ontologies as the basis for their reasoning in plan generation, pre-requisite determination, and course schedule negotiation. The use of ontologies can be seen as an evolution of the accepted best practice of separating business knowledge from technical implementation (the ‘what’ from the ‘how’). The use of ontologies to model the domain makes business knowledge explicit, and facilitates communications between the main stakeholders of the software development cycle.

84

Driving the software construction from the ontology itself ensures that the ontology model remains up to date and that business rules and knowledge are added to the ontology model as opposed to becoming encoded in the implementation. This benefit echoes and has synergies with MDA, where the model becomes the repository of the system design. Software construction of the e-Advisor itself has been effectively driven by the ontology development and this approach lends itself to other intelligent educational systems as well as systems that incorporate ontologies into their execution in general. We are developing an Internet-based collaborative advisory system in which the ontologies serve as standardized and open interfaces for the interoperability of distributed advisory systems.

B. Main Stakeholders There are two main stakeholder roles in the methodology we developed: Sponsor and Development Team. The Sponsor funds, authorizes, guides, and, when necessary, stops a project. The Development Team refers to both those with Analysis and Development skill sets, including knowledge workers and software developers. The Development Team is most immediately impacted by any new technology, tool, or methodology. A software Development Team has many people involved, and typical roles/titles include Business Analyst, Systems Analyst, Technical Architect, Solutions Architect, Systems Architect, Developer (many types), Tester, Project Lead, and Project Manager. This article focuses on the Analyst and Software Developer roles, and considers them to subsume all other Development Team roles key for the software construction phases with the exception of Project Lead/Project Manager. The Project Lead/Project Manager role is important and can be considered implicit in the communications between the Development Team and Sponsor and in administration of the processes followed

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

by the Development team but it is not addressed explicitly in this article. Projects require resources – people to work on them, materials that are used or consumed in the process of execution. These resources are provided or funded by a Sponsor. From the Sponsor’s point of view, a project is successful if it meets the need that started it within required timelines and does not exceed the budgeted resources. A Sponsor may cancel a project if it appears probable it will overrun budgeted resources or in response to a change in strategic goals. This article presents the Sponsor as the primary stakeholder role outside of the Development Team.

C. Objectives and Review Areas The process of developing a methodology suitable for development of ontology-driven applications was framed by the example of e-Advisor and focused by a number of objectives and review areas. Guiding principles for our methodology were that it fit within the Software Construction phases of a typical project life cycle, and fill the needs of both Sponsor and Development Team stakeholders (proactively deal with potential resistance or concerns from the former, support adoption by the latter). Objectives specifically for the Development Team stakeholders included that the methodology be easy to use (for the Development Team), and build on existing skill sets (be evolutionary, not revolutionary). Objectives specifically for the Sponsor stakeholder included that the methodology not introduce significant changes to the way the Sponsor normally interacts with delivery projects. Focus areas were also identified including ontology reuse and roles on the development team. In terms of ontology reuse, one of the benefits of starting the software construction process with ontologies is the potential to reuse existing ontologies as opposed to developing new ontologies for each application. There are a number of issues related to enabling ontology reuse, including: how

to encourage ontology reuse; how to catalogue/ publish, discover, and evaluate available ontologies for use; ontology integration; and ontology interaction. Roles and responsibilities were also focal points. In an environment that uses ODD, the development of the ontologies themselves needs more attention. As an artifact that documents the domain, drives the development of and serves as an important runtime element of the system, both domain and technical expertise are required to develop an ontology.

D. Methodology Overview Excluding project initiation and deployment of the finished product, our methodology can be viewed as being comprised of three major activities: plan what needs to be done, prepare to do what was planned, and execute against the plan to build what is needed. These high level processes are shown in Figure 2, as ‘Plan’, ‘Finalize Resourcing’, and ‘Build’ Following is an overview of these processes with a focus on the ontology-related artifacts that link these processes together. 1. Plan the work (‘Plan’ process) ‘Plan’ encompasses both what is going to be done (top-down from architecture) and how it will be done (bottom-up work plan). First, what is going to be done is planned in a top-down manner starting with key scenarios that illustrate system requirements. The main ontology-related artifacts of interest that are produced are the Ontology Architecture and Ontology Skeletons. The Ontology Architecture shows all needed ontologies and how they are interrelated. For each ontology an Ontology Skeleton is produced, which is essentially a lightweight ontology definition showing the important classes that directly support the scenarios as well as those that are required for integration.

85

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Figure 2. Overall flow1 need identified event

The Ontology Skeletons are used to perform bottom-up planning and assist in development of the Work Plan. For each ontology, build/buy decisions are made, a build/integration approach is determined and cost/effort estimates are developed. The aggregate Work Plan takes into account the output of this planning to determine task dependencies and sequencing and resource requirements. 2. Prepare to do the work (‘Finalize Resources’ process) Once the planning is done, and before construction can commence, resourcing needs to be confirmed or adjusted and the Work Plan may require adjustments due to resource availability. 3. Build (‘Build’ process) Iterative and incremental development of the ontologies and ODD of related software takes place according to the Work Plan and following best practices and guidelines validated with knowledge and software development specialists. In the case of ontology build/refactor, for each increment, the ontology is iteratively and progressively modeled, using prototypes where applicable. Once the ontology model is considered

86

stable enough, the ontology itself is used to drive associated software development. For each increment’s application development work, driven by the same increment’s ontology development, the main steps are: develop application models based on ontology/ontologies; develop the application increment and unit test; and integration test. Section V relates these main processes in our methodology, with a focus on ontology-related activities and artifacts. One of the assumptions of this methodology is that it is used for systems where ontologies not only drive the development but are also key run-time elements, as is the case with e-Advisor.

PROCESS FLOWS The following process flows give an overview of our methodology for ontology-driven development of intelligent systems, focusing on activities performed by the Development Team that are directly related to software construction. This article discusses at a high level how these processes fit in a framework that fills the Sponsor’s needs. While the processes described in this article work with processes such as project management, requirements management, and quality control, this is not discussed in detail in this article.

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

A. Top Level Flow The overall process flow is illustrated by Figure 2 and the processes are listed below, along with their outputs. 1. Need Identified Event A need is identified and it is decided to investigate starting a project to address the need. Generally sufficient funding is allocated for estimates to be arrived at or funding limits will be set. 2. Initiate Project This methodology holds the Sponsor accountable for initiating the project. Project initiation has ties into strategic investment decisions and, although capital planning and related topics may seem unrelated to the subject of systems development, we felt it important that our methodology not ignore the importance of this type of activity considering it is a prerequisite for development to occur. This initiation may include gathering very high level cost/effort/time estimates from the groups involved in the project, or detailed cost/effort/ time estimates for arriving at higher-confidence estimates. 3. Govern Project Project Governance is how projects are brought into alignment with strategic goals. For example, based on the progress of the project or alignment with strategic objectives of the organization, a project can be stopped or put on hold at any time. Specification of this and other governance activities is outside the scope of this article - each organization will have a different model for governance, with different funding and go/no-go gates. The intent is to provide a structure that supports the overlay of governance, allowing for the ontology modeling and ODD processes to fit within existing models of project governance. For an overview of

project governance and how business strategy is supported by projects via governance see Morris & Jamieson (2004). 4. Plan Following project initiation the Development Team is accountable for developing a high-level architecture and strategy for the ontology modeling and ontology-driven software construction work to be done. The Plan process is described in more detail below in ‘B. Plan process flow’, ‘C. Plan – Architecture’, and ‘D. Plan – OntologySpecific Strategy’. Output: Ontology Architecture, Ontology Strategies, Ontology Skeletons, Work Plan. 5. Finalize Resourcing In some situations, resourcing may need to be finalized. This is especially true where people are working on multiple projects. Based on this activity, the timelines, activity sequencing, and resources assigned to the Work Plan may change. Output: Work Plan (updated) 6. Build Based on the output from Plan, and working against the Work Plan, ontology modeling and ontologydriven software construction occurs. This activity is discussed further in ‘E. Build’, below. Output: Ontologies, Design Models, Software 7. Support Deployment Once the construction is complete, the system is deployed. The deployment of an application into an existing production environment can be considered a parallel, related project to the development activities this article focuses on and incorporates necessary processes related to maintaining the integrity of the production system

87

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

(e.g. configuration management) and ensuring appropriate adoption of the changes in production (e.g. people/organizational change management). Although these activities are outside the scope of this article, the Development Team will need to support such activities via knowledge transfer and assistance in resolving unforeseen issues during the actual deployment.

B. Plan Process Flow The Plan process sets the stage for all further development and allows for the Sponsor to have visibility into schedule and cost baselines. At the end of this process flow, there will be more certainty around timelines and effort. This is important for both the Delivery Team and the Sponsor. The Delivery Team needs a consistent vision of where they are going in order to work together and execute effectively and the Sponsor needs to know what is going to be delivered when and confirm that the criteria used to approve the project are not compromised (for the purposes of

Figure 3. Plan process flow

88

this article we can read this in terms of forecasted spend against delivery timelines and scope). Important ontology-related deliverables from the Architecture subprocess include an Ontology Architecture, Ontology Skeleton for each ontology, and an integration strategy as applicable. Following this, during the Ontology-specific Strategy subprocess, plans for the development / acquisition of each ontology identified in the Architecture are developed. Finally, using the ontology-specific strategy work and the architecture, the Work Plan is developed. This Work Plan is used to drive the ontology modeling and ontology-driven software construction and serves as a very important hook into the governance framework. Figure 3 shows the Plan process flow and the subprocesses and their outputs are described below and in ‘C. Plan – Architecture’ and ‘D. Plan – Ontology-Specific Strategy’. 1. Architecture The first activity involves development of an architecture. Of interest to this article are the

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

ontology-related artifacts within this architecture, specifically the Ontology Skeletons and Ontology Architecture. The Ontology Architecture illustrates the main ontologies that are involved in the system and how they are related. An Ontology Skeleton illustrates, for a given ontology in the Ontology Architecture, the key classes including any classes that are involved in relationships to other ontologies. The skeletons can be seen as templates that can assist in identification of candidate ontologies for reuse/integration or be used as integration stubs. During the Architecture task, key scenarios for the product/functionality to be developed are documented and required ontologies are identified. For each ontology that is identified the concepts to support the scenarios and integration are identified to form a Skeleton Ontology. This assists in sourcing ontologies for integration/reuse and assists in the decoupling of related construction by providing an integration stub. The Ontology Architecture relates all the ontologies with their key concepts and, at a high level, how they are integrated. Note that strategic direction or policy may influence the output of this activity by mandating that certain integration methods are followed or certain ontologies are used. This activity is described below in more detail below in ‘C. Plan – Architecture’. Output: Ontology Architecture, Ontology Skeleton (or identification of known or mandated ontology to be integrated with).

This activity is described in more detail in ‘D. Plan – Ontology-Specific Strategy’, below. Output: Ontology Strategy, including potential ontology sources, selected ontology source, Integration/Build approach, and cost/effort estimates.

2. Ontology-Specific Strategy

The first activity is to identify the key scenarios to be supported by the new system/functionality. This is analogous to documenting system requirements via use cases or scenarios. Our intent is to both document required system functionality and assist in the identification of required ontologies. Output: Key Scenarios to be handled by the system

During the Ontology-Specific Strategy activity, the construction activities related to a specific ontology are examined and decisions that impact or involve the construction and cost are made. These decisions, which include things such as build/buy/ integrate/reuse and mandated or preferred ontologies for reuse or integration, are documented in an Ontology Strategy. Note that organizational direction or policy may influence this strategy.

3. Develop Work Plan During the Develop Work Plan activity a work plan is developed to drive the actual construction. The Work Plan at this point in time is based on effort estimates, assumed resourcing, and decisions that have been made during Architecture and Ontology-Specific Strategy. This Work Plan will not be baselined until after resourcing is finalized. Output: Work Plan

C. Plan: Architecture The architecture includes the main ontologies to support the key scenarios to be supported by the system/functionality to be developed. In addition, for each case where the ontology has not been decided, an ontology skeleton is developed to assist in sourcing the ontology and aid construction activities. This process flow is illustrated in Figure 4, and the activities and their outputs are listed. 1. Identify Scenarios

89

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Figure 4. Plan: architecture flow

2. Identify Ontologies This task follows on the Develop Scenarios activity and involves identifying ontologies that are required to support the Key Scenarios identified earlier. Output: descriptions of ontologies required to support the Key Scenarios identified by the Develop Scenarios activity. 3. Develop Ontology Skeleton In the event that the source of a given ontology is not mandated, a skeleton ontology is developed, including the Concepts required to support related Key Scenarios. This skeleton serves as a template for sourcing the ontology, and as an input to the construction activities. Output: Ontology Skeleton 4. Ontology Integration Strategy The Ontology Integration Strategy determines how the ontologies are interrelated and relates the strategy for integrating the ontologies. It is

90

finalized after all ontologies are identified and their skeletons defined. Output: Integration Strategy 5. Document Architecture This task involves packaging the output from all previous tasks into an overall architecture document. Output: Ontology Architecture

D. Plan: Ontology Specific Strategy The Ontology-Specific Strategy process is executed for each ontology in the Ontology Architecture. The ontology’s source is identified (re-use or refactor an existing ontology, build from scratch), the approach for integrating with or refactoring an existing ontology or building a new ontology is decided upon and, based on that, cost/effort estimates are developed. The flow is illustrated in Figure 5. A list of activities and their outputs follows.

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Figure 5. Plan: ontology-specific strategy flow

1. Identify Ontology Source The Ontology Skeleton can be used as a template for identifying potential ontology sources. This is analogous to “Candidate SRs Identification” in (Barresi, Rezgui, Lima & Meziane, 2005). Sources of candidate ontologies include sources internal to the organization and external to the organization. Output: potential ontology sources for the ontology, selected Ontology Source

addition of concepts to this structure, classifying and normalizing as this is done. Output: Build Approach, Cost/Effort Estimates 4. Document Strategy Based on the results of preceding tasks, the strategy is documented. Output: Ontology Strategy

2. Determine Integration Approach

E. Build

If an existing ontology has been identified, how that ontology is going to be re-used is determined, along with associated costs. Output: Integration Approach, Cost/Effort Estimates

The Build process is where the ontologies and software are implemented and is driven by the project-specific Work Plan. Depending on the Work Plan, there may be a number of parallel and interrelated instances of this process involved in one project. This is primarily a function of the number of ontologies and their interdependencies as well as resource availability and capacity. Our methodology is biased toward an integration of incremental ontology development and downstream Model Driven Architecture for development of software components.

3. Determine Build Approach If the decision is made to build a new ontology, how that ontology is going to be built is decided, and thus the activities and cost/effort estimates determined. One approach is top-down modeling to obtain a clear structure and then incremental

91

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

This use of incremental development and application of Agile techniques to ontology development is in line with suggestions made by Knublauch (2006) and was validated and confirmed in focused interviews with software development and knowledge experts. Each increment focuses on ontology development to a point where the model can drive the application design and/or the knowledge base can support application execution, followed by ontology-driven development of related software. While modeling is both a science and an art, certain guidelines, suggested by the literature and confirmed by our review of e-Advisor development and qualitative analysis, are documented in our methodology. For ontology development, the main steps are: develop the ontology in increments, validating each increment with Protégé’s built-in reasoners, and creating individuals to validate semantic restrictions (cf. Knublauch (2006)); prototype as appropriate; maintain tree structure based on increasing specialization (untangle as required), clearly differentiate partitioning Concepts (used to untangle) from self-standing Concepts (cf. Rector (2003)). For each increment’s application development work, which is driven by the same increment’s ontology development, the main steps are: develop application models based on ontology/ontologies; develop the application increment and unit test; integration test.

CONCLUSION AND FUTURE WORK This article has reviewed e-Advisor as an intelligent web-based intelligent advising application and a methodology for Ontology-Driven Development that is suitable for intelligent systems such as e-Advisor, whose execution is driven by ontologies. Our methodology, developed using the e-Advisor system and development as a case study, and reviewed with knowledge and software development experts, meets the needs of

92

the project Sponsor as well as the Development Team, leverages traditional software engineering techniques to support incremental, iterative ontology modeling and ontology-driven development of intelligent systems. Future work and areas to review include incorporation of ontology change management, reverse-engineering of ontologies, and ontology development estimation.

REFERENCES W3C ODA (2006). Ontology Driven Architectures and Potential Uses of the Semantic Web in Systems and Software Engineering, http://www. w3.org/2001/sw/ BestPractices/SE/ODA/ Abels, S., Haak, L., & Hahn, A. (2005). Identification of common methods used for ontology integration tasks. In the Proceedings of the first international workshop on Interoperability of heterogeneous information systems IHIS ’05 Publisher: ACM Press Barresi, S., Rezgui, Y., Lima, C., & Meziane, F. (2005). Architecture to support semantic resources interoperability. In the Proceedings of the first international workshop on Interoperability of heterogeneous information systems, pp 79 - 82, ACM 2005 Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D. L., Patel-Schneider, P. F., & Stein, L. A. (2004), OWL Web Ontology Language Reference [Online]. Available: http:// www.w3.org/TR/owl-ref/ Carrol, J., & Chappell, G. (1996). An Intelligent Universal Advisor. in The 1996 ACM symposium on Applied Computing, Philadelphia, Pennsylvania, United States, 1996, pp. 105-109.

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies, and why do we need them? IEEE Intelligent Systems and Their Applications, 14, 20–26. doi:10.1109/5254.747902

Knublauch, H., Musen, M. A., & Rector, A. L. (2004). Editing Description Logic Ontologies with the Protégé OWL Plugin. Presented at the International Workshop on Description Logics, Whistler, BC, Canada (2004)

Chen, J., & Mizoguchi, R. (1999). Communication Content Ontology for Learner Model Agent in Multi-Agent Architecture. in AIED99 Workshop on Ontologies for Intelligent Educational Systems, 1999.

Lin, F., Holt, P., Leung, S., & Li, Q. (2006). A Multiagent and Service-Oriented Architecture for Developing Adaptive e-learning Systems. International Journal of Continuing Engineering Education and Lifelong Learning, 16, 70–91. doi:10.1504/IJCEELL.2006.008919

Deline, G., Lin, F., Wen, D., & Gasevic, D. Kinshuk. (2007). Ontology-Driven Development of Intelligent Educational Systems. Presented at the 2007 IEEE Pacific-Rim Conference on Communications, Computers and Signal Processing (PACRIM07), Victoria, BC, Canada, 2007. Euzenat, J., & Shvaiko, P. (2007). Ontology Matching. Berlin Heidelberg, Germany: Springer-Verlag. Kay, J. (1999) Ontologies for reusable and scrutable student model. in Proceedings of AIED99 Workshop on Ontologies for Intelligent Educational Systems, 1999. Knublauch, H. (2003). An AI tool for the real world - Knowledge modeling with Protégé. In Java World, June 20, 2003 Knublauch, H. (2006). Ontology-Driven Software Development in the Context of the Semantic Web: An Example Scenario with Protégé/OWL. Presented at the International Workshop on the Model-Driven Semantic Web, Monterey, CA (2004) Knublauch, H., Fergerson, R. W., Noy, N. F., & Musen, M. A. (2004)The Protégé OWL Plugin: An Open Development Environment for Semantic Web Applications. Presented at the Third International Semantic Web Conference, Hiroshima, Japan (2004)

Mizoguchi, R., & Bourdeau, J. (2000). Using ontological engineering to overcome AI-ED problems. International Jounal of Engineering Education, 11, 107–121. Morris, P., & Jamieson, A. (2004). Translating Corporate Strategy into Project Strategy: Realizing Corporate Strategy Through Project Management. Project Management Institute. Murray, W. S., & Le Blanc, L. (1995). A Decision Support System for Academic Advising, in 1995 ACM Symposium on Applied Computing, Nashville, TN, USA, 1995. OMG MDA. (2008). Object Management Group: Model Driven Architecture, http://www.omg. org/mda Pinto, H., & Martins, J. (2003). A methodology for ontology integration. In the Proceedings of the 1st international conference on Knowledge capture, pp 131 – 138, ACM 2001 Razmerita, L., Angehrn, A., & Maedche, A. Ontology based user modeling for Knowledge Management Systems. In the User Modeling Conference, Pittsburgh, USA, 2003, pp. 213-217. Rector, A. (2003) Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In the Proceedings of the 2nd international conference on Knowledge capture, pp 121 – 128, ACM (2003)

93

A Case Study of Ontology-Driven Development of Intelligent Educational Systems

Rector, A., Drummond, D., Horridge, M., Rogers, J., Knublauch, H., Stevens, R., et al. (2004). OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns. Presented at the 14th International Conference on Knowledge Engineering and Knowledge Management (EKAW), Whittlebury Hall, Northamptonshire, UK (2004) Seidenberg, J., & Rector, A. (2006). Web ontology segmentation: analysis, classification and use. In the Proceedings of the 15th international conference on World Wide Web, pp 13 - 22, ACM 2006

Terrasse, M., Savonnet, M., Leclercq, E., Grison, T., & Becker, T. (2006). Do we need metamodels AND ontologies for engineering platforms? In the Proceedings of the 2006 international workshop on Global integrated model management, pp 21 – 28, ACM 2006 Turban, E., Fisher, J. C., & Altman, S. (1988, March). Decision Support Systems in Academic Administration. Journal of Educational Administration, 26, 97–113. doi:10.1108/eb009943

ENDNOTE 1



http://www.athabascau.ca

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 66-81, copyright 2009 by Information Science Reference (an imprint of IGI Global)

94

Section 2

96

Chapter 6

Learning with Online Activities: What Do Students Think About Their Experience? Salam Abdallah Abu Dhabi University, UAE

ABSTRACT Learning through social interactions and critical thinking is becoming a fundamental teaching approach, especially for adult students. This approach promotes holistic and deeper understanding for the subject being learned. Online technologies are offering us new opportunities to create communities of inquiry that allow for more active learning that enhances students’ critical thinking. This article introduces an exploratory case in a Middle Eastern context that uses multiple online activities to supplement and strengthen the students’ face-to-face learning environment. This interpretive case discusses the students’ perceptions of their experience when using online activities. The case indicates that students improved their learning, are very positive about their first interaction with online activities and would like to see it as a standard practice to supplement their face-to-face learning.

INTRODUCTION Didactic or teacher-centered teaching is still seen as the dominate approach for teaching in the Arab Countries (UNDP, 2005). This approach fails to provide higher-order thinking. Higher order thinking is a term used as an umbrella to include skills that go beyond knowledge acquisition, like critical thinking and becoming self-directed. Critical thinking includes, cognitive activities such

as interpretation, analysis, evaluation, inference, explanation, and self-regulation (self examination & correction) (Facione, 2007). Dewey (1982) defines critical thinking as “reflective thought”, i.e. to suspend judgment, to be both skeptical and open minded; and to achieve this requires both intellectual and emotional ability. Self-direction is also an essential skill to be instilled in our students, which is an important ingredient for effective learning (Garrison et al, 2003). We want

DOI: 10.4018/978-1-60960-153-9.ch006 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Learning with Online Activities

learners to become responsible in controlling and managing their learning and to go beyond rote memorization. The recent World Bank Report (2008) states the Middle East is still in need of education reform and fails to meet the needs of the invading globalized economy despite the high investment in education. The report also emphasizes that education in the region focuses too much on rote memorization, neglecting higher-order skills and complex communications that are critical to further advancement. Benard (2006) has made a similar argument about the need for reform in education for it become a tool for change. Benard quotes Tibi (1981), in which he argues that the problem in education in the Arab world is due to the teaching approaches. Problem-oriented thinking cannot be learned through raw memorization. Traditional education, which expands its energies in no creative thinking but in memorization and reproduction, cannot produce a functioning intellectual group able to pose problems, define them, analyze them and finally solve them. The World Bank report (2008) also makes a recommendation for the need for teacher training in higher-order learning with emphasis on soft skills. The teacher-centered approach relies solely on pedagogies that emphasize rote memorization, and very little on higher order thinking. In this transmission paradigm, students are passive and may lack the motives to continue learning or retain knowledge (Felder et al. 1995). This style of teaching can be stressing, exhausting and not suitable for adult learners in particular, who have difficulties in memorizing facts. In-addition, it does not enhance the student’s working skills that require engaging and communicative abilities or even train them for lifelong learning and for becoming self-directed. The teacher-centered approach can also make teachers bored due to their static and mechanistic role in teaching. This staleness

can also be mirrored in the students (Fink, 2003). There is some evidence that the teacher-centered approach may be more effective with students with lower intellectual abilities (Saulnier et al., 2008; Talbert el al., 1993). However, the current literature on education theories are in favor of the student-centered approach, In a teacher-centered paradigm, lectures usually follow a linear fashion moving from one topic to the other, with several stops for memory testing. Deep understanding and building relationships between the various topics is uncommon. In this approach students learn in fragments and usually end with vague ideas of the overall course content and do not see knowledge relevancy. Students failing to see connected knowledge make it difficult to accumulate and apply knowledge in other subjects or in their working lives (Entwistle, 2003; Gow et al., 1993). To make learning more significant requires us to experiment with more active pedagogies to supplement the passive and disintegrated style of instruction. Active pedagogies are based on activities that encourage dialogue, critical thinking, and collaborating (Long et al., 2005). These activities may be exercised in face-to-face and or in online environments. Online technologies are offering us new opportunities to create communities of inquiry that allow for higher-order learning that enhances students’ critical thinking (Garrison et al., 2000; Imel, 2001; Bates, 1997; Duffy et al., 1996). This article examines a case study on the use of online environment as one way to improve students’ learning at one of the universities in Jordan. Jordan is one Middle Eastern countries where education is being put in the forefront as the means for social and economic development. The effective use of technologies is at the core of this initiative to improve teaching practices for active learning. The study discusses implementing open-source software learning management system to deliver online activities to supplement face-to-face teach-

97

Learning with Online Activities

ing of information systems-related subjects at the postgraduate level. The online environment includes a combination of online activities that are grounded in social constructivism educational theory. The article provides an interpretation of the experience gained, which had a positive outcome on students’ learning. The results should encourage other faculties to seriously consider using online technologies to create an engaging learning environment that can promote a significant learning experience (Fink, 2003). This study adds to the emergent body of research on ways to integrate technology in the Middle Eastern educational context. In addition, the document states the motive of this research and discusses relevant learning theories. This will be followed by discussions on online learning and the use of open-source learning management systems as a cost-effective solution to integrating technology in learning. The article will then discuss the methodological approach used in this study and its findings, followed by a discussion of the findings highlighting the significance of this study.

Research Motive The motive behind this study was to overcome some of the challenges being faced by students in the Middle East. The author has identified these challenges through class discussions with students and personal observations of the students’ aptitude. The students had described their prior learning environment as being a) restrictive and b) burdensome: Restrictive because it is teacher-centered. Students were not being put in an environment to exercise self expression, collaboration, communication and critical thinking. Students were also not given enough practical work using technologies. The environment was considered burdensome because students were overwhelmed and burdened with facts to remember. Consequently students’ eventual goal is not to learn but to pass exams. Students further faced difficulties in understanding

98

the subject matter because the texts books were in the English language. These challenges were considered important in rethinking the instructor’s pedagogy. The challenges were addressed by developing face-to-face and online activities. The online activities are the focus of this study.

Learning Theories The teaching strategies used in this case relate to Knowles’ Andragogy Theory of Adult Education (Smith, 2002; Thompson, 2001; Conner, 1997) and Vygotsky’s Social Constructivism Theory (Thompson, 2001; Dabbagh, 2004). These two theories are interrelated and can provide better directions on how to design sound teaching pedagogies. Knowles (1970, 1984) argued that adults learn differently from children because the learning process of adults is different (Smith, 2002; Wurm, 2005). According to Knowles’s theory of andragogy, adult learners are more self-directed and autonomous. Adult learners are more responsible for their learning and in making decisions than children. Adults have accumulated experiences over the years and they become aware of what is relevant and useful to them. In this theory, teachers take on a facilitating role. According to the concept behind andragogy, adults need opportunities to construct relevant knowledge and to collaborate with others to simulate life experiences. To motivate adult learners, they need activities to make them think, reflect and express their experiences and views. Knowles theory enforces the idea that adult students need to experience learning in an experimental environment. Andragogy is also in line with social constructivism theory. Social constructivism is about knowledge construction not independently constructed by individual learners but co-constructed through social interaction (Simpson, 2002; Brown, 2005). Social constructivism is driven by the value of knowledge that is built socially in a learning community. The basis of its phi-

Learning with Online Activities

losophy is that students’ learning is strengthened by applying prior knowledge and principles to a new environment resulting in construction of new knowledge (Beaumie, 2001). It is also said that if students construct knowledge for others to read, it will result in a more effective way of learning and remembering knowledge. Students become learners and teachers at the same time. Brown (2005) argues that constructivism is best performed when it is: • •

•

Contextual: Taking into account the student’s understanding. Active: Engaging students in learning activities that use analysis, debate, and criticism (as opposed to simply memorization) to receive and test information. Social: Using discussions, direct interaction with experts and peers, and teambased projects.

Therefore, students need to connect with other students and become part of a community of learners. Through this community, students will be motivated to learn and collaborate on knowledgebuilding and exchanging experiences. To reiterate, adult learners need environments that nourish deep learning and active learning in a social setting to allow engagement through critical thinking and collaborating on content creation to form a more significant learning experience (Imel, 1990).

ONLINE COLLABORATIVE TOOLS The use of online technologies can be a facilitator to move away from a transmission paradigm to a constructivism paradigm. Online technologies provide a range of new Web tools that promote different ways to teach and learn in a social networking environment (Dede, 2005). These tools include asynchronous and synchronous types such as wikis, blogs, RSS, discussion boards, chatting tools, etc (Fichter, 2005; Wagner, 2004; Godwin-

Jones, 2003). The combination of this type of tools has been recently referred to as Web 2.0 (O’Reilly, 2005) and the application of these tools for online learning through communities has been called as e-learning 2.0 (Downes, n.d.). These tools create a medium for online communities to learn together and build knowledge repositories by interacting through published content either individually or collaboratively (Jennings, 2005). The use of asynchronous tools is effective for learning, since it allows for integration of reflection and collaboration. Online activities allow more time for the student to understand and reflect before collaborating with others (Harvard et al. 2005; Popolov et al. 2002). Garrison (2003) describes effective learning as way of engendering higher-order thinking through critical thinking and self-direction. Asynchronous online tools have the ability to create an environment for higherorder learning, which is in line with the modern pedagogy of constructivism. The use of learning management systems (LMSs) has also recently become popular because they encompass Web 2.0 tools in an enclosed learning environment to give teachers control in conducting online activities, grading and giving students privacy. LMSs can link face-to-face teaching and home education through computer technology in meaningful ways (Martin et al., 2005). Students can have access to online activities and resources on their own time and from anywhere (Bonk, 2004). LMSs deliver online learning based on a certain educational pedagogy. Coates et al. (2005) argue the causes for popularity of LMSs are because they increase teaching efficiency by delivering flexible courses and facilitating teacher-student, student-teacher and student-student dialogue. LMSs provide a creative environment for teachers in which to experiment with and design new activities through new ways of communication and assessment. Coats et al. (2005) adds that these activities enrich learning because they are based

99

Learning with Online Activities

on sound educational theories such as constructivism theory. There are significant LMS implementations especially in North America, Australia, the United Kingdom and Canada, which are affecting core activities and transforming the culture of teaching and learning (Coates et al., 2005). Meanwhile the use of LMSs in the Middle East and in particular Jordan still has low visibility. The need to integrate technology into curriculum to affect students’ learning is at the heart of most Jordanian teaching philosophy statements. The intake of this integration is low, probably due to lack of awareness on its potential impact on the learning of students and also the lack of funding available for such projects.

Design and Procedure Moodle, as an open-source software, was selected as the learning management system for this study. The basis of the learning philosophy of Moodle is “social constructionist pedagogy,” which includes collaboration, sharing, and building community (Dougiamas et al., 2003). Courses in Moodle can contain activities such as discussion forums, journals, quizzes, surveys, assignments, chats, glossaries, workshops, internal e-mail, blogs, and wikis. Moodle integrates well with many information sources such as text, HTML, graphics, video, audio, PowerPoint, and flash applications. The use of online activities to supplement face-to-face learning was a new approach to the instructor and students. The instructor also had no prior knowledge on the willingness and the readiness of the students to change their accustomed learning style. From this premises, the study was positioned to answer the question “What do students think about their own learning when using online activities?” The most common research approach to understand the depth of learning that had occurred using online activities is to conduct content analysis on students’ posted text (Anderson et. al, 2001) or

100

capture students’ perceptions through interviews and surveys. The study adopted the former approach due to the nature of the research question and since the participants are adult students who are sophisticated enough to communicate their experiences and thoughts through writing.

Method The research question mentioned earlier seeks a deeper understanding of students’ perception of using online activities. The aim is to gain insights rather than gather statistically significant evidence. The study may be considered explorative in nature and therefore requires a qualitative research approach (Yin, 1994). Qualitative research method refers to the strategy for data collection and analysis (Creswell, 1998). Theories developed using qualitative approaches are more representative of the real world because they generate ‘rich’ data collected from the words, actions, and symbols (explicit and tacit knowledge) of people. Rich or qualitative data are the results of meaning allocated by people to events and objects (Manen, 1990). In this paradigm, data analysis can be either based on a positivist or interpretivist approach (Yin, 1994). Burrell et al. (1979, p.253) argue that the interpretivist approach aims for understanding the “subjective experience of individuals”. This study has adopted an interpretivist approach. Qualitative data are basically made up of text and meaning and the endeavor for the researcher is to reach an accurate understanding by interpretation of the collected data. Coffey et al. (1996, p.10) summarize the process of analysis as not “adhering to any one correct approach or set of right techniques; it is imaginative, artful, flexible, and reflexive. It should also be methodical, scholarly, and intellectually rigorous.” Interpretation of qualitative data remains subjective because researchers’ presuppositions or pre-understandings are usually embedded in interpretations to make it more comprehensible (Lopez et al., 2004).

Learning with Online Activities

The richness of qualitative data allows certain dynamics to be continually projected based on the perspective held by the researcher, which makes analysis of qualitative data open to many interpretations, and their validation may be argued for or against. Research that seeks to understand qualitative knowledge is not subjected to the “rigors of a hypothesis test” but rather “rests on the strength of the analytical arguments used to defend the interpretation” (Lacity et al., 1994, p.146). The plausibility of the finding also relies on the logical analysis and the construction process. The findings of this research are a blend of the students’ perceptions and the researcher’s background that he brings with him to collect and interpret the data; therefore, the findings are the researcher’s interpretation of the students’ experiences (Lopez and Willis, 2004). Researchers tend to adapt methods of analysis according to their situation; there are no standardized processes (Patton, 1990). Data are transformed into meanings in the form of categories or patterns that inductively emerge from data. The interpretation of the data collected will be discussed by using a group of categories to provide the framework for analysis to interpret students’ perceptions of their first online learning interaction.

Research Context and Data Collection The study participants were enrolled in Master’s degree courses at one Jordanian universities. One hundred and forty adult students were attending either Management Information Systems or Electronic Commerce courses (50 female & 90 male). The students were mostly working adults and accustomed to teaching methods where the teacher is in the center and totally controls the learning environment. The participants were native speakers of Arabic. The instruction mode was in English, but students were allowed to express

themselves in either Arabic or English language. All students for the first time were subjected to a blended learning environment (Vaughan, 2007). Students had to attend on a weekly basis three hours of traditional lecturing and interaction and to carry out online activities through a specifically designed website, which hosted the LMS application. The online activities were implemented outside the classroom at students’ own time and place. Approximately 300 qualitative statements were collected over a period of five semesters. The statements captured the students’ perceptions on what they think about using online activities. Multiple data collection method was used. The primary data was collected by asking online open-ended questions, which was posted online. Students were asked to provide their impression on using online activities (liked and disliked) and to describe their perceived experience in general. Students’ responses were also submitted online in MS Word format and later converted to MS Access for analysis. The author also noted and catalogued other comments, which was collected through periodical informal class discussions to get further understandings on the value of using online activities. These discussions were short and would normally last for 15 minutes. The teacher had also observed and noted the students’ behavior online, such as the extra time spent doing online activities and the continuing access to the Web site after the course completion. The source of this data was the date/time stamp on the online activities and from the detailed logs maintained by the LMS. These notes were mainly used to assist in the analysis and understanding of the primary data collected. To analyze the students’ statements, a framework of analysis was adopted to answer the previously stated research questions “What do students think about their own learning when using online activities?”

101

Learning with Online Activities

Online Constructivism Activities Online activities were designed by considering Knowles’ (1970) theory of andragogy. The activities gave students opportunities to be more self-directed, autonomous and involved in constructing their own knowledge through the use of asynchronous tools such as discussion forums, blogs, wikis and building glossaries. Through these activities students were in engaged in discussing, abstracting, translating and collaborating. The four activities were also designed to enforce understanding and deep thinking on topics that were discussed in the face-to-face environment. These four activities are discussed below along with their values: •

102

Critical thinking discussion forums (Discussing): This activity is based on using discussion forums. Krentler et al. (2005) found that online discussion forums clearly influenced students’ learning. This activity provided threaded discussion forums for asynchronous communication to discuss a certain issue in details and from multiple perspectives. Students can post questions and opinions and allow students to respond to them. Participation in forums can improve students’ learning experience, by helping them to define, clarify and understand the content of the subject matter. In this study, the discussion forums were used by students on weekly basis to raise and answer critical thinking questions pertaining to topics discussed in the face-toface lectures. In this activity students engage in a dialogue triggered by one student asking a critical thinking question and the other students respond with their own fact findings, opinions or seek further clarifications at their own time. This activity encouraged students to examine concepts from different perspectives and to allow students to go beyond the information giv-

•

•

en in the prescribed textbooks. This gave students opportunities to question concepts viability in a local context or to explore new ideas. This activity also allows students to encounter and handle arguments by engaging them in thinking critically, reflecting, and also to search for supporting material before posting their answers or questions (Gordon, 2006). Concept impact blog (Abstracting): This activity is based on using the blogging tool. The use of blogs on the Internet is growing at a high rate, in which every second a new blog goes online somewhere (Gordon, 2006). Individuals, research institutions and corporations use blogs. In education, students use blogs as on-line personal journals to write their reflections. Blogs provide an individual writing and reading environment and the ability for other students to comment on the content of the written text. No special skills are needed for creating the content; new pages are easily created and updated. Students were asked to select a concept/topic on weekly basis and to abstract the significance or the implications of the concept on individuals, or organizations or societies in a local or global context. This activity supplements students’ understanding by reflecting on the importance and the implication of what is being studied in class. The blogging tool allows students to categorize (tag) their contributions and this facilitates concept relationship build up. By the end of the semester students can select a concept and examine it from different perspectives and see its relationship to other concepts. Arabic concepts glossary (Translating): This activity is based on using the glossary tool, which was used by students to collaboratively build glossary of the most important concepts or key terms. Students were asked on weekly basis to select one

Learning with Online Activities

•

concept and define it in Arabic. This activity will benefit students by understanding concepts in their own language and build up their language (lingo) of the subject. This collaborative activity distributes the workload among students, giving them more time to read and learn from each other’s contributions. Group wiki project (Collaborating): This activity is based on using the wiki tool, which enables students to collaborate on a dynamic information publishing project that can be later used as a source of self-contained hyperlinked documents. In business, they have been used for knowledge management and intranet applications (Leuf et al. 2001; Wagner, 2004; Lamb 2004; Clyde, 2005). Groups of three to four students were asked to work on a certain project using the wiki as the development tool. This was an opportunity for students who rarely work in groups to collaborate online on a certain project, such as enriching concepts in Arabic, preparing electronic commerce business plan, and so on. The instructor also used the wiki as knowledge-base to host students’ class presentations, which made it accessible to everyone to learn from. Students engaging in a wiki environment gain technical literacy, digital content creation, learn to deal with others, consensus building, communicate ideas, and learn from each other’s styles of writing and way of thinking.

It was mentioned earlier that (Brown, 2005) argues that constructivism is based on three factors: contextual, active and social. Students were encouraged to use their existing understanding and experience to make their learning ‘contextual.’ They were asked to reflect on the concepts gained from Western textbooks and to examine their viability in their local or regional ‘context.’ The application of the blogs, wikis, discussion forums,

and glossaries tools gave students opportunities to be ‘active;’ to critically observe the contribution of other students and to freely express their opinions in a supportive environment, and to gain deep understanding of concepts from different activities and from different perspectives. Students were being self-directed and in control of their learning; they were free to choose what and when to write. It is expected that the use of these four types of online tools encourage ‘social’ interaction, where meaningful understanding of concepts can only be achieved when all students contribute content and be supportive of each other. Most tasks were based on students working individually and collaboratively to exchange opinions, elaborate on concepts and produce resources. The instructor’s role in these activities was to give online feedback and pointing students to other students’ quality work. Feedback during lecture time was also given to student addressing quality criteria of input and resolving technological problems faced by them. The LMS was also used for posting lecture notes and to inform students about planned events and remind them of their weekly assignments. Students were required to submit all their assignments online, which allowed them to see and compare their work with others. A minimum number of contributions was required by each student and all activities were given marks. The timing of their contributions had to be flexible and was also negotiated with them, since most students were working adults.

DATA ANALYSIS To provide a thematic explanation to understand the students’ perceptions and the impact of online learning, a group of categories was used that were inspired from the Dimensional Analysis framework (Schatzman, 1991). Dimensional analysis is a structured way of categorizing data used by researchers to analyze qualitative data. It was

103

Learning with Online Activities

proposed in the late 1970s by Schatzman as an alternative approach to the ‘Grounded Theory’ method (Glaser and Strauss, 1967). The method relies on providing serial explanation of what is going on by inductively determining contexts, conditions, processes and consequences. The purpose of these four categories is to facilitate coding and to provide the researcher with a means to explain and tell a story about the phenomenon in terms of the relationship between actions and consequences under selected conditions in a specific context for a given perspective (Kools et al., 1996). To clarify further, quoting from Schatzman (1991, p.308): An explanation, after all, tells a story about the relations among things or people and events. To tell a complex story, one must designate objects and events, state or imply some of their dimensions and properties – that is, their attributes – provide some context for these, indicate a condition or two for whatever action or interaction is selected to the be central to the story, and point to, or imply, one or more consequences. To do all this, one needs at least one perspective to select items for the story, create their relative salience, and sequence them. The outcome of the analysis is to portray to the reader a sense of authenticity and conviction for the overall findings in terms of its main constructs and properties. The analysis is derived by induction, taking into account a single statement at a time. The analysis of the statement was based on a certain perspective, which is the aim of this research; that is, to understand what happens when students engage in online learning and particularly in the context of carrying out the four online activities. After establishing the perspective and the context, each statement was taken separately and grouped according to the other three categories (conditions, processes and consequences). Students’ statements were sometimes refereeing to either a single or multiple categories. For example

104

a typical statement shown below, relates to more than one category: …a very rich learning experience, the online activities gives a real depth for the theoretical information we gain at class, makes the learning process an interactive interesting process. The interpretation of the above statement relates to several conditions related to the environment, which resulted in a positive consequence. The statement illustrates that the student had gained in-depth understanding (consequence) because the activities were perceived interactive (condition), rich (condition) and interesting (condition). See Table 1 for more sample data and their interpretation. The analysis goes through an iterative and refinement process until all statements were resolved into categories and sub-categories. Eventually saturation is reached and a feeling that a consistent, plausible pattern or story was emerging. The labels for the categories and sub-categories were chosen by the researcher to best describe the meaning of the abstracted data. Three conditions were identified, four processes and nine consequences, see Figure 1. The figure can provide us with a model to describe and understand the learning experience of the described case, which are discussed in the next section.

FINDINGS The categories and the most prevalent findings will now be discussed. The discussions do not highlight the merits of each activity or the use of specific online tools, but rather will examine the reaping value gained from the total environment and how it addresses the challenges mentioned earlier.

Learning with Online Activities

Table 1. Sample analysis using the categories from dimensional analysis (Schatzman, 1991) Students Statement

Conditions

Critical thinking forum extends the boundary of thinking, by trying to predict the possible outcomes or problems.

Processes

Consequences

Deliberation

The feeling that the student is attached to the subject throughout the week and not only during the lecture time that is fixed to a time and place.

Systems Quality (Accessibility)

The most three things I liked about learning online was sharing knowledge gained from the class and discuss it on online using wikiblogs and weblogs and glossaries which made it easy for me to refer to any of them when studying.

Systems Quality (Multiple activities) Activities Quality (Interactivity)

Learning From Others

Building Knowledge Repository

The critical question forum helped me to think more deeply about things, expand my knowledge and somehow changed the way I think.

Activities Quality (Useful)

Gaining Insights

Knowledge Transformation (Open-Minded)

reading posts, you get to know the way that my colleagues are thinking and their opinion, which can improve my thinking way

Activities Quality (Useful)

Observing, Learning From Others

Learning Strategies

Gaining Insights

Comprehension

It made me reflect and search different sources to enrich my contribution, which resulted in increasing my understanding of the topic.

Attachment

Figure 1. A model for understanding students online learning experience

105

Learning with Online Activities

Conditions Students’ statements have highlighted many issues related to the quality characteristics of the learning environment. Many student where gratified with the learning environment. Comments such as unusual, interesting, memorable, rich, enjoyable, inventive, nice way of learning, etc., were frequent comments by the students. This indicates that the learning environment was implemented under certain conditions or quality characteristics that impelled student to give such remarks. These quality characteristics can be considered as conditions that were responsible for the attained consequences of the learning environment. Student comments were categorized under three qualities: a. Systems Quality: This is related to the basic characteristics of the learning management system. The students liked the idea of doing a variety of activities and having access to them from anywhere and at any time. Other characteristics that seemed to be essential for the success of the learning environment, such as ease of use, the ability to handle multiple languages (Arabic and English), and use of a database to store all students contributions, including the ability to submit assignments. b. Activities Quality: The nature and the design of the activities is a critical component in achieving positive learning outcomes. Students had commented on the merits of the activities, which can also be considered as desired quality characteristics of the activities, and they include: Usefulness: Students have commented that the activities were interesting, innovative, influential, and complementary; add value to their learning needs and also build skills, experiences and can influence their knowledge. Students appreciate the idea of using only the issues seen as relevant to them in what is being developed and discussed online, and communicated in their own plain words

106

(Arabic/English). The learning environment was enriched because of the diversity of the group, where each student brings in his/her experience and way of thinking. Flexibility: Flexibility is another characteristic that was valued by students. Flexibility is related to the time of submission of activities and having an environment that encourages students’ autonomy, such as the ability to express themselves freely, comfortably and make choices to introduce any new relevant topics at the their convenience. Most of the students were working adults and had limited time to do their activities. Some students would be active for one week and passive in the following week. Visibility: The open learning environment enriches the students’ knowledge and creates competitiveness between them, because all students’ contributions and assignments are visible to each other. This gave students a sense of being under scrutiny from their peers. Interactivity: Students valued the interactivity of the learning environment and the dynamics of content build up from diversified group of students. Students also liked to enter into an open dialogue with each other to express themselves and to also collaborate on building artifacts, such as the wiki project or building glossaries. Therefore, the success of the learning environment relies on how large and diversified are the group of students, and the nature of tools that can encourage group interactivity or collaboration. c. Teacher Quality: The instructor or the moderator plays a critical role to encourage and motivate students to participate on line. Students have commented on how they have perceived the instructors as being knowledgeable and working within a learning strategy. This perception was important for the students to trust him/her and consequently encouraged their participation. Students had also appreciated the flexibility of the instructor. The instructor needs to be

Learning with Online Activities

flexible and structure the activities according to the students’ needs, abilities, work within their time constraints, and to encourage intellectual openness. The instructor’s ultimate aim was to empower students to encourage life long learning skills development and emphasize process rather than content.

Processes Examining the students’ comments in the context of the four activities, a pattern of different processes was manifested and categorized into four different cognitive processes that are related to critical thinking: a. Observing: Students were extensively engaged in observation, due to searching for information or trying to understand or read students’ postings that reflect ways of thinking and opinions. This gave students the opportunity to progressively learn by observation. b. Gaining Insights: Gaining insights on issues is a higher level of thinking than a mere observation. In observation, students are engaged in noticing or becoming aware of information without gaining a deep, clear picture or gaining insights. Some of the students’ comments show that they were actively seeking deep perception, such as seeking elaboration or gaining clarification through reading and searching to get insights on specific issue in order to understand and enrich their contributions. c. Learning from others: Learning from others is also a cognitive process that was frequently mentioned by students; learning from their peers can be an important learning process. Students who fail to learn from others may miss opportunities to learn from peers’ experiences (mistakes and successes). This process is different from the previous two processes. Here, students engage in

active thinking in order to extract a lesson that can be acquired and utilized elsewhere or to avoid repeating a similar mistake, such as commended or disapproved thinking approaches as indicated by other students’ comments. d. Deliberations: This is probably the highest level of cognitive process used by students. The act of deliberation is different from gaining insights. The act of deliberation requires more analytical skills and students attempt to bring together fragments of knowledge together in order to develop a holistic understanding and try to understand the purpose or deep meaning of things. Students’ comments relate to processes such as thinking deeply, reflecting, analyzing, comparing, abstracting, constructing, organizing ideas and thinking, innovative thinking, predicting outcomes, solving problems, making choice, and taking group decisions. Also, because content is always accessible, students were prompted to reassess and edit or clarify their contributions. In addition, students were involved in applying certain knowledge to different contexts, including their own working lives.

CONSEQUENCES The consequences of the online learning environment had reshaped students’ learning in significant ways. From the analysis, nine consequences were determined: a. Knowledge: Although students were attending face-to-face lectures and obtained fundamental knowledge, they also perceived that learning through the set of online activities had enforced and provided them with richer environment to gain further knowledge. The activities created a medium for knowledge accumulation. Students expressed themselves quite frequently that the environment

107

Learning with Online Activities

provided them with new, broadened, and diversified knowledge, which also resulted in strengthening their subject and specific terminology. Knowledge acquisition was also facilitated because communication was carried out in their own plain language. b. Comprehension: The nature of engagement had positioned students to comprehend topics in greater depth and more accuracy because the topics were being elaborated from diversified students’perspectives, which also gave a more holistic understanding of the various topics. Again, comprehension was easier for students because communication was elaborated in their own plain language (Arabic or English). c. Retention: All activities required student to actively engage in searching and writing intensively in their own language, which had assisted in retention. The term in “their own language” means that it is written in simple language away from the jargon of text books or written in their own Arabic language. The retention assisted students to recall information easily and weave it into their contributions. Some students needed less effort to prepare for exams because they were more confident of their retained and related knowledge. d. Experience: The students were engaged in a number of processes, which gave students the opportunity to practice and gain experience in a number of skills. Communication skills: Students were compelled to practice writing in order to express their ideas and opinions clearly in order to encourage other students to respond to their contributions. Students were conscious of the fact that other students will be reading and responding to their writing, thus giving them a sense of authorship. The nature of activities encouraged students to exert more effort in reading and try to understand (listen to) what others are trying to communicate

108

in order to respond with an intelligent response. Student had also mentioned that the process of translation benefited them; it improved their English language and gave them experience in Arabization. Engagement: A skill that was stressed in the students’ feedback. Student mentioned that the environment encouraged collaborative learning and working to build artifacts, which assisted them in gaining skills on how to engage with others remotely, how to weave ideas into discussions or how to exchange ideas and to reach consensus. Technology use: Students had commented that they gained experience in using technologies. Students were encouraged to use computers and to search the Internet more frequently than before in order to complete the activities online. Also, the use of the learning management systems gave students an opportunity to deal with a practical online application and to become familiar with its features, tools and functions. Autonomous: Being autonomous was a skill that was also frequently mentioned by students. Students, probably for the first time, had sensed that they were responsible for their own learning. Students were given the opportunity to express themselves. They were expressing ideas, opinions, and knowledge in their own words freely and honestly without being threatened with ridicule from other students or the instructor. Knowledge Construction: Students were not only gaining new knowledge, they were also involved in constructing new knowledge either collaboratively or individually. Students were involved in building wiki projects, glossaries and summaries. Students gained experience on how to formulate good critical thinking questions in order to attract greater comments from other students, and also how to construct effective answers to convince others of their arguments. Knowledge Integration: One of the ultimate objectives of learning is to turn knowledge into action. Students had expressed in details how the environment had inspired them to integrate

Learning with Online Activities

knowledge into other realms of knowledge to build a holistic understanding of a certain topic, or to apply knowledge gained into different situations, or to connect different ideas together. Others went as far as integrating knowledge into their working environment, such as building a web site for their organization or participating in a public electronic auction. e. Learning Strategies: Students had recognized the value of learning online and have expressed themselves on how the learning environment assisted them in developing strategies for learning, thinking and remembering. These strategies were developed because students were engaged in the processes mentioned earlier (observing, gain insights, learn from others, and deliberations). Some of the student had mentioned how they improved their ways of learning through interacting with others by exchanging ideas and opinions, which provided opportunities to learn from each other’s diversified experience and different ways of thinking. This also gave students the ability to compare their competencies with others. This type of interactivity was recognized by students as a new way of learning the subject without going back to the textbook. Some students had also recognized that learning is in the conversation and collaboration, which had changed their ways of studying. As mentioned earlier, students had commented that the nature of activities had made it easy to remember facts and information because of engagement in deep learning about relevant topics and in their own wordings. They had also commented that the online activities made them reflect on what is being learned and to think in more rational and scientific ways. Exposure to diversified opinions had also improved their ways of organizing their thinking and ways of analysis.

f.

Transformation: Good learning environment should have a long lasting change on the learner (Fink, 2003). The experience expressed by students may be described as being enlightening since the synchronicity of the environment gave student ample time to be reflective, predictive, analytical and rational. The environment was transformative for some students. It changed their way of thinking and expanding its boundary. Students’ comments indicate that they may have become conscious of certain feelings and thoughts about themselves or others, which may have a long-lasting effect on their lives.

Emotion: Good feelings were sensed by students while doing online activities. This was exemplified by statements related of having good feelings for helping others students, nurturing a spirit of sharing, respecting each others’ opinion, a satisfied feeling when receiving a requested information or when adding value to knowledge, and also discovering how shy students in class think. Open-mindedness: The nature of the environment and activities gave students the opportunity to be open-minded and exercise making judgments. Students have admitted that they had changed their minds and opinions on certain issues, and consequently a change in the way of thinking and beliefs. Self-Knowledge: The environment had given some students a sense of growth. Students had commented that the nature of the activities have built their self-confidence and have become more self-dependent, which allowed them to freely express their thoughts and opinions. Students also had the opportunity to self-reflect and evaluate themselves in comparison to other students’ contributions and ways of thinking. Such skills allow students to interact more effectively with themselves and with others more confidently and purposefully.

109

Learning with Online Activities

g. Motivation: The openness and the interactivity created by the environment had aspired students to exert more time and effort to complete activities. Exertion: Students have mentioned that they have spent much more time and effort than on any other subject that was being taught in a traditional method; the online interactivity gave them incentive to learn. Students were exerting more effort to read, search, write and use technologies. The openness and the high visibility of the environment made students write for each other and to be more conscious of the quality of their contributions. Students have commented that they have put more effort and time to ensure that their answers or contributions are prepared with care and accuracy. Aspiration: Students were impelled to exert more effort in completing their activities not through coercion but rather out of aspiration. Students were aspired to think deeply, be more creative, and encouraged to engage with others. One student was aspired and purchased a laptop to be in continual contact with the course website. Students have commented that the nature of the activities made them discover and seek new knowledge. One student also mentioned that he would now consider taking a course completely online. h. Attachment: Over the course of the semester, students tend to become attached to the website. Students have mentioned that the course website had become part of their daily activity similar to checking their email. The website had a stickiness effect on students; they liked the idea of being in contact with course 24/7 and being accessible from anywhere. The course Web site tends to build stronger connection between students themselves and what they are learning. It has also been observed that students continued to visit the website weeks after the course’s

110

i.

completion, which signifies that doing online activities can create a strong bond between students, instructors and the course content. Building Knowledge Repository: The environment had encouraged students to write more over the whole semester, which resulted in an accumulation of shared repository of knowledge, discussions, opinions, experiences, ways of thinking, terminologies and related information -- all expressed in their own simplified Arabic and English language The students had valued the accumulated knowledge because it gave them in-depth understanding of various topics. The repository was also perceived as a memory aid and assisted them to prepare for exams without referring to the prescribed textbook. At the end of each course, the learning management systems (knowledge repository) would contain 250 to 400 defined concepts using the glossary tool; 200 to 300 concept impact using the blogging tool; 100 to 200 posts on the discussion forum; and 50 to 80 pages using the wiki tool, including students’ written assignments and presentations, which were also accessible for students to read.

Discussion The emerged set of categories illustrated in Figure 1 can provide perspective on answering the research question, “What do students think about their own learning when using online activities?” which helps to understand their experience. For some it was a positive experience as stated by this student’s statement “many years later I will remember all about this subject” – this sensation was partly driven by online collaboration. The online activities were the context for the analysis and were comprised of various tasks that engaged students in “discussing”, “abstracting”, “translating” and “collaborating” using various online tools (discussion forums, blogs, glossaries, and wikis). The resultant categories

Learning with Online Activities

can inform us better about the intricacy of the online learning environment as experienced by those students. The inherent consequences of the environment on the students were evident in a range of desired educational goals (retainsion, comprehension, knowledge, experience, learning strategies, transformation, and attachment, motivation, and knowledge repository). These desirable outcomes were assumedly the byproduct of students engagement in higher-level cognitive processes (observing, gaining insights, learning from others and deliberations). Students were able to engage in this positive environment because of three quality conditions (system, activity, and teacher). In other words, students expressed their thinking about their own learning, in terms of the perceived conditions of their learning environment, their engagement in cognitive processes and the benefits they have attained or sensed.

Consequences Most of the literature discusses the merits of critical thinking when using online learning, specifically discussion boards, and focuses little on the byproducts of this conducive environment. There was clear evidence from the students’ statements that the learning environment was beneficial and nourishing due to their engagement in cognitive processes, as expressed by one student: “The online one provides me with real experience far away from the course text book and material”. The intensive engagement in online learning allowed students to gain a number of skills including autonomy, which enabled their confidence to engage with others in knowledge construction and integration. The emergent consequences are indicative of how intense the online critical thinking engagement was for students. If the environment did not engage students intellectually, it would be difficult for students to develop learning strategies, build useful knowledge repository, feel humanized about the whole learning experience and to become attached to the community. The following statements from

students illustrate the perceived value of the online learning environment: Learning online, had increased my knowledge on how to use the internet and how to deal with other and exchange ideas…The critical question forum helped me to think more deeply about things, expand my knowledge and somehow changed the way I think.. …After this experience I was able to conclude how to harness much of this information and concepts in a practical way, which encouraged me to shoulder the responsibility for designing and building a website for the company that I work for…encouraged me to discuss subjects that I feel is important, which encouraged to learn more about it and stored in my mind. Students made frequent verbal requests to continue to access the course’s online activity after completion of the course. Such a request can only be made when a sense of added-value and benefit is perceived by them. It is interesting to note that the consequences can be almost exactly mapped to Fink’s (2003) “Taxonomy of Significant Learning” (see Table 2). Fink’s taxonomy is based on 6 interactive desired learning outcomes, which are achievable depending on the course design. These elements are: Foundational Knowledge (understanding and remembering information & ideas), Application (skills, thinking, managing projects), Integration (connecting ideas/people/realms of life), Human dimension (learning about oneself and others), Caring (Developing new feelings, interests, value) and Learning How to learn (Becoming a better student, inquiring about a subject and selfdirecting learners). This may indicate that students in this study experienced significant learning (Fink, 2003). One consequence which does not map into Fink’s taxonomy is the students’ created artifact the “Knowledge repository”, which was captured through LMS’s database. This student highlighted the value of the repository: “We have

111

Learning with Online Activities

Table 2. Cognitive processes Fink’s Taxonomy

This study

Foundational Knowledge

Knowledge, Retention, Comprehension

Application Integration Human Dimension

Transformation

Caring

Motivation, Attachment

Learning how to learn

Learning Strategies

ended up with large number of questions and answers which helps me to study and understand the subject” The value or usefulness of the repository could be an indication and a measure of the learning experience, whether it was surface or deep learning. This is an issue that can be examined in future studies.

Processes In the context of these four online activities, students were reading, thinking, and writing, which seemed to have a positive impact on their critical thinking, as indicated by one student: “discussions helped to enlighten my thinking in a more rational way”. The study by Quitadamo et al. (2007) demonstrates that writing positively influences critical thinking performance for general education. The term critical thinking is difficult to define and has many interpretations (Facione, 2007), but it is greed that it is a desired aim of higher education and usually involves various levels of cognitive processes and skills (Dewey, 1982). Dewy argued that critical thinking is a process of judgment that one makes while solving problems. Pascarella et al. (1991, p. 118) argue that critical thinking is “defined and measured in a number of ways but typically involves the individual ability to do some or all of the following: identify central issues and assumptions of arguments, recognize important relationships, make correct inferences from data, deduce conclusions from information or data provided, interpret whether conclusions

112

Experience

are warranted on the basis of the data given, and evaluate evidence or authority.” The following students’ statements demonstrate that students were engaged in higher-level cognitive processes: It is very useful and effective for me, I have gained great benefits because it helps to analyze the topics in a different way and makes the student think in a different way and to imagine the subject in his/ her mind in order to create questions...It pushes me to think deeper, in a more scientific way in order to link between what I’m learning and our daily life details and practices to reach to some critical situations …gave me richness in ideas and sometimes it directed me to many thoughts I have ignored. Guiller et al. (2007) have argued that on-line discussions can increase the quality of critical thinking in comparison with face-to-face environment; however, the authors recommend using a combination of the two environments to provide more value for students. One of the student’s statements is in agreement about learning in a blended environment “I prefer both, because the first provide the direct communication, and the second give the chance to be in contact 24 hr 7 days a week.” Sanders et al. (2002) examined student attitudes with regard to Web-enabled learning, the results show a positive effect on student learning, problem-solving skills, and critical thinking skills. Online learning is different from face-to-face learning in two ways: the nature of the interac-

Learning with Online Activities

tion and independence. These two ways were powerful enough to trigger in this study several complementary levels of critical thinking processes (observing, gaining insights, learning from others, and deliberating. These critical thinking skills must not be viewed as separate levels; these processes may be utilized in concert as needed. Learning from others is probably seen as odd as a critical thinking process, but it was considered in this case as an important cognitive process, as illustrated by this student’s statement, “The exchange of questions and opinions helps a lot in understanding the subject, because knowing what others think helps to think about a specific topic from different perspectives which maybe they be all right… it gives us a chance to know different points of views.” Students were engaged in analyzing other students’ contributions to extract a learning lesson. There are numerous studies that have attempted to categorize critical thinking processes. Garrison et al. (2000) has proposed a four-stage cognitive processing model that has been widely used to evaluate critical thinking in online discussion forums. These categories are Triggering (recognizing the problem), Exploration (divergence, information exchange, brainstorming, leaps to conclusion), Integration (connecting ideas, synthesis, creating solutions), and Solution (testing and defending solutions). See Perkins et al. (2006) and Murphy (2004) have summarized a number of critical thinking models. Similarly, the emerged processes from this study may also be used to contribute to the growing body of knowledge on critical thinking processes when students engage in asynchronous online activities.

Conditions A critical success factor of the mentioned learning environment is fundamentally based on the characteristics of the online learning activities. Students do not only acquire knowledge, they also construct their own knowledge through interaction

with other learners and other resources (Simpson, 2002; Brown, 2005). Therefore, online activities must be designed to encourage discussions or dialogues in order to challenge students’ intellectual traits and to further develop these abilities (Richard, 2005). Hudson (2002, p. 53) argues that “the very basis of thinking is rooted in dialogue, drawing on a socially constructed context to endow idea with meaning”. Online activities can be used to foster a student-centered approach to open grounds for students to engage in activities that resemble real-world tasks and to encourage a deeper approach to learning (Gow et al., 1993). A statement from one of the students illustrates the need for interaction and dialogue: “by learning from each other and exchanging information and ideas, this will produce new concepts.” The activities used in this case encouraged discussions and collaboration and were designed to supplement the class lectures. In online learning, the teachers’ role is redefined, since learning moves into a more constructivist model where learning can be more active and self directed (Anastasiades et al., 2001; Koohang et al. 2005, Kandies et al., 1999). The teacher acts as a channel to ensure activities are carried according to the general guidelines and to encourage the building of community among learners. The teacher quality element was emphasized in the community of inquiry theory by Garrison et al. (2000) and it is referred to as ‘teacher presence’. Anderson et. al (2001) stress that teacher and learner interaction is not enough on its own; “structure and leadership are crucial for online learners to take a deep and meaningful approach to learning.” The teacher’s role is akin to that of a facilitator who encourages and motivates students to participate online and to empower them to trust their ability to engage in purposive interaction. Perry et al. (2005) in their interpretive study have highlighted how teachers (facilitators) have exemplary roles in challenging the students’ abilities to go beyond their expectations, to be good affirmers, recognizing their potential, treating learners with

113

Learning with Online Activities

respect and to help resolve problems. In this study the teacher was not only intervening and directing students online but also in class, which had a more positive impact on students’ participation. The teacher in this study commented that extra care and sensitivity is needed at the beginning of the online engagement as “we do not want to lose and discourage anyone.” How and when we direct students can be either an enabler or inhibitor for their online engagement, as indicted by this statement from one of the students: “the quick response from the site administrator (instructor) and his wide interest and respect to his student which encouraged everybody to speak and write without fear.” Another student commented on the environment: “I really like the comfort atmosphere that we live in learning on line, getting us away from the high tension we used to face in traditional methods of learning, specially at the exams time.” System quality also plays a central role in the success of the online learning environment. The adopted learning systems must be accessible to students outside the university campus to allow students to experience anywhere anytime learning, as stated by one student: “online learning very beneficial because of the 24 hour connectivity, which gave me more time to read the question and reflect on it and answer it with care”. From the experience gained from this study, the choice of LMS depends on the tools and their features to allow for designing innovative activities. Features such as ease of use and the ability to allow students to create bilingual content is also important to allow students to express themselves in a language they are comfortable with.

Students Satisfaction Although students were attending face-to-face lectures and obtained fundamental knowledge, they perceived that the learning through the set of online activities reinforced and provided a richer environment to gain further knowledge and develop different skills (Kanuka et al., 2004).

114

Because all activities were student-driven rather than teacher-driven, students experienced for the first time what it means to be an active learner or self-directed, as illustrated by some of the students’ statements: “Stirring students up to continue learning all through their life, and helping others to do so… Taught me how to learn, and how can I effectively introduce a technology and MIS in my work to succeed and meet work environment challenges”. Student’s level of satisfaction and perceived success is enhanced as students move more towards self-directed learning (Garrison et al., 2004). The four mentioned online tools were asynchronous communication tools that can support knowledge construction, which is the foundation for social constructivism learning theory, or collaborative learning. According to this theory knowledge is constructed collaboratively from the previous knowledge of the participants. In general collaborative learning can provide many benefits such as building self-esteem in students, enhances student satisfaction with the learning experience, promotes a positive attitude toward the subject matter with deeper understanding. (Zaho et al., 2001, p. 2). Some of the students’ statements shown below illustrate why they may have been satisfied with the online learning: Increased the self dependency, and give the person a great feeling when he get the information he want and add values for his knowledge…It was a great unique experience that I wish if it was implemented in other courses... Online activities made it easy for us to understand the material easily without the need to memorize as in the traditional way… encourages students to read more and think deeply about the subject so the y can contribute. The model shown in Figure 1 represents conceptualization of student statements, which is suggestive of a successful learning model. Students who have been actively involved in the mentioned processes were generally satisfied about their

Learning with Online Activities

experiences as indicated by their statements and were able to acquire useful and significant learning experience (Fink, 2003). Chao-Min et al. (2005) in their study show that the perceived quality of information, perceived value and usability have significant impact on user satisfaction and continued usage. Benke et al (2004) argue that student satisfaction is also related to access, quality of program, student’s support and opportunities for personal interaction. Teacher presence was also an important satisfaction factor, to orchestrate the learning environment (Carrision et al., 2004; Carswell et al. 2003; Abdul-Hamid et al., 2005). Probably the highest contributor to the students’ satisfaction in this study, is the cognitive process that was evoked by the asynchronous learning tool, which had challenged their intellectual traits leading them to better learning (Richard, 2005). The instructor observed that students were able to deal with the subject’s concepts and terminology much more easily and were able to retain much of the information because learning was relevant, cumulative and occurring from different activities and in collaboration, as explicated by this student’s statement: “I was not sure that studying the MIS course will be enjoyable because the subject is not flexibility and hard to study through this way, but the study in this way give the course the flexibility and easy way to remember the main concept of the MIS than read it directly from the book, the main concepts was repeated in the bogs, critical thinking question and the glossary.” The interactive environment made students conscious of their learning, which stimulated higher order thinking skills, and students learned to relate fragments of knowledge and apply their knowledge and skills to their working lives. Students perceived that online learning is useful because it gave an opportunity for collaborative learning, which is a necessary component to teaching and learning (Schellens, 2004). The social aspect of this environment was critical to facilitate dialogue for exchanging information, ideas and opinions (Vygotsky, 1978) and to create

a medium for knowledge accumulation (de Laat, 2006; Koschmann, 1994).

Challenges and Recommendations Students perceived the use of online activities as a positive supplement to their learning but not as a substitute for the face-to-face environment. The experience of the students may have been different if learning was totally online. The students were attending face-to-face lectures, which gave them access to knowledge and a chance to get acquainted with the instructor and to each other, which may have encouraged the students to participate online in a relaxed environment as expressed by one of the students: …I really like the comfort atmosphere that we live in learning on line, getting us away from the high tension we used to face in traditional methods of learning. However, use of online technology is not a panacea. Some students were active and some were not, and we should not assume that all students would like this approach. Some students were critical of the online learning, as expressed by one student who “…did not like to sit for a long time in front of the computer screen.” Some did not like online learning because they did not have necessary computer skills to carry out the activities and to recover from unforeseen technical problems as expressed by one student, who said: “....it needs computer skills, which is not available to all students”. Teachers need to explain the activities and the tools very clearly to avoid confusion and suggest ways to recover from technical glitches. Lack of skill has put some students under pressure as they found themselves spending much time to carry out a single activity. Another recurring issue is the Internet in terms of access, speed and cost. Some comments from students illustrate this challenge:

115

Learning with Online Activities

...because of the slow connection, we are spending long time to interact with the website… sometime you can’t find a PC to start learning or the internet is out of service…the net connection is slow, which gave me a hard time…it needs infrastructure in my home like ADSL and I don’t have it…It is more expensive to subscribe to the internet…need extra cost to be in touch with the site. Internet access would remain a limitation, unless the local government takes steps towards reducing the cost of connectivity to increase its accessibility. The internet was considered an additional cost to their education; this may be slightly offset by switching to accepting only online assignment submission. Use of online environment took much from the students’ time, Students can easily end up with a course and half with this approach as clearly expressed by one student: “I Think that our work for this semester worth more than 50%”. Most of the students were working adults who seemed to have little time to carry out the activities online, some of the students’ comments were: One small comment, if you could reduce the quantity of the assignments… Sometimes, I don’t have time to connect and access the site especially when I have deadlines at work or exams at the university…shortage of time, as I am a worker, and some times we have a lot of assignments with a short dead line of sending it…Although the continuous follow-up is good where student stays updated with all activities, it’s also hard for some since they are working and not fully dedicated to the study only. The number of activities or contributions needs to be considered carefully in light of this limitation. However, most students were satisfied with this overload because a sense of learning was highly observed and achieved.

116

RESEARCH SIGNIFICANCE Most research on using online activities has focused primarily on the use of one type of tool such as blogs or wikis. This research had used multiple tools that had a positive synergetic affect on the cognitive and emotional processes of students. Students were confident to enter the final exam with a thinking mind rather than memory-crammed mind and with little preparations as stated by this student: “When I write about this topic in my own words, I feel I don’t have to spend that time on that topic when I study for the exam, because I already had studied it in a different way”. The notion of the synergetic impact when using multiple activities requires further research to validate. The study has also illustrated that students were engaged in various levels of critical thinking. Critical thinking processes such as insights and deliberation have been discussed extensively in literature (Riddell, 2007; Facione,2007; Brabeck, 1983), but with little mention of the inclusion of learning from others as a critical thinking process, which was highly stressed in the students’ comments. The challenge here is how to design an effective learning environment that encourages students to learn from each other and extract valuable lessons from each other. Another interesting finding that was highlighted by the students’ comments is the build-up of a knowledge repository as the result of their cumulative contributions. The knowledge-base was a simplified reference composed of students’ understandings expressed in the Arabic and English languages. As mentioned earlier, the extent of use of the knowledge repository by students to prepare for exams may be utilized as a good indicator for validating the value and quality of the students’ online learning. From a researcher perspective, the use of Schatzman’s Dimensional Analysis has proved to be useful as a framework for understanding students’ online learning experiences. The framework allows the researcher to capture somewhat holisti-

Learning with Online Activities

cally the rich experiences of students by examining the conditions, processes and consequences. These three categories can provide researchers or academics with a practicing lens through which to research or design more effective pedagogies. The ultimate contribution of this study is the local context of this case and its results, which should encourage other universities in the Arab world to establish strategic and operational plans to support such initiatives. Plans must include policies on how to integrate online technologies with the face-to-face approach and to provide the necessary resources and support both for students and faculty. Blended learning does present certain challenges such as how to bring students, faculty, technologists and management to collaborate in such an initiative. Resistance to organizational change is also expected (Vaughan, 2007).

CONCLUSION The aim of the study was not to generalize the findings, but to share an authentic experience in a Middle Eastern context. Online activities can create a platform for establishing learning communities and a gateway for building lifelong learning skills. It was evident from this study that social constructivism educational theory supported by open-source learning management systems provided an adequate environment in which to encourage students’ deep learning and build a variety of skills and experiences and to learn from each other’s styles and ways of thinking. One can conclude that the discussed learning environment was considered by students less burdensome and restrictive. Students experienced for the first time what it means to be an active learner to improve their learning cognitively and emotionally. The study may also be viewed as an attempt to capture the determinants of a successful online environment. However, to successfully engage everyone in online activities, we need to be aware of the challenges related to technology, time, and effort.

Finally, the use of Schatzman’s ‘Dimensional Analysis’ framework proved to be a useful tool to gain insight on what do students think about their own learning when using online activities.

REFERENCES Abdul-Hamid, H., & Lewis, C. (2005). Identifying effective online instructional practices in undergraduate and graduate level courses. In G. Richards (Ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2005 (pp. 1864-1868). Chesapeake, VA: AACE. Anastasiades, P., & Retalis, S. (2001, June 2530). The educational process in the emerging information society: Conditions for the reversal of the linear model of education and the development of an open type hybrid leaning environment. [Tampere, Finland.]. Proceedings of ED-MEDIA, 2001, 43–50. Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1–17. Bates, A. W. (1997). The impact of technological change on open and distance learning. Distance Education, 18(1), 93–109. doi:10.1080/0158791970180108 Beaumie, K. (2001). Social constructivism. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Retrieved: 1/2008, from http://www.coe.uga.edu/e pltt /SocialConstructivism.htm Benard, C. (2006). Fixing What’s Wrong - and Building on What’s Right - With Middle East Education (pp. 29–46). SAIS Review.

117

Learning with Online Activities

Benke, M., Bishop, T., Scarafiottiet, C., SchWeber, C., & Thompons, M. (2004). Promoting student support and satisfaction in online learning, SloanC series, 5. Bonk, C. J. (2004). The Perfect E-Storm emerging technology, enormous learner demand, enhanced pedagogy, and erased budgets. Retrieved 8/2006, from http://www.publicationshar e.com/part1.pdf Brabeck, M. M. (1983). Critical thinking skills and reflective judgment development: Redefining the aims of higher education. Journal of Applied Developmental, 4, 23–34. doi:10.1016/01933973(83)90056-4 Brown, M. (2005). Learning Theory. Retrieved: 1/2008, from http://www.dartmouth.ed u/comp/ about/pubs/2005-spaces/theory.html. Burrell, G., & Morgan, G. (1979). Sociological Paradigms and Organizational Analysis. Brookfield: Ashgate Publishing Company. Carswell, A., & Fleming, E. (2003, January/February). Graduate school faculty evaluation study. DE Oracle@ UMUC. Retrieved 10, 2008, from http:// info.umuc.edu /de/ezine/f eatures /jan_feb_2003/ fac_eval_study.htm Chao-Min, C., Meng-Hsiang, H., Szu-Yuan, S., Tung-Ching, L., & Pei-Chen, S. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45, 399–416. doi:10.1016/j.compedu.2004.06.001 Clyde, L. A. (2005). Wikis. Teacher Librarian, 32(4), 54–57. Coats, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11, 19–36. doi:10.1080/13583883.2005.9967137 Coffey, A., & Atkinson, P. (1996). Making Sense of Qualitative Data. USA: Sage.

118

Conner, M. L. (1997-2004). Andragogy and Pedagogy. Ageless Learner. Retrieved: 1/2008, from http://agelesslearner.com/intros/ andragogy.html. Creswell, J. W. (1998). Qualitative Inquiry and Research Design - Choosing Among Five Traditions. Sage Publications Inc. Dabbagh, N. (2004). Distance learning: Emerging pedagogical issues and learning designs. Quarterly Review of Distance Education, 5(5), 37–40. De Laat, M. (2006). Networked Learning. Utrecht: Unpublished PhD, University of Utrecht. Dede, C. (2005). Planning for Neomillennial Learning Styles. EDUCAUSE Quarterly, 28(1). Dee Fink, L. (2003). Creating Significant Learning Experiences. Jossey-Bass, Dewey, J. (1982). How we think (rev. ed.). Lexington, Mass: Heath. Dougiamas, M., & Taylor, P. (2003). MOODLE: Using learning communities to create an open source course management system. In Proceedings of the EDMEDIA Conference, Honolulu, Hawaii. Downes, S. (n.d.). E-learning 2.0. Retrieved: 1/2008, from http://www.elearnmag.org/s ubpage. cfm?section=articles&article=29-1 Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction . In Jonassen, D. H. (Ed.), Handbook of research for educational communications and technology. New York: Simon & Schuster Macmillan. Entwistle, N. (2003). Enhancing teaching learning environments to encourage deep learning. In E. De Corte (Ed.), Excellence in higher education. Wenner-Gren international series, 82, 83-96. London: Portland Press. Facione, P. A. (2007). Critical thinking: What it is and why it counts. Retrieved: 12/2008, from http://www.insightassessm ent.com /pdf_files/ what&why2006.pdf

Learning with Online Activities

Felder, R. M., Felder, G. M., & Dietz, E. J. (1995). A longitudinal study of Engineering student performance and retention vs comparisons with traditional taught students. Journal of Engineering Education, 87(4), 469–480. Fichter, D. (2005). The Many Forms of E-Collaboration: Blogs, Wikis, Portals, Groupware, Discussion Boards, and Instant Messaging. Online, 29(4), 48–50. Garrison, D. R. (2003). Cognitive presence for effective asynchronous online learning: The role of reflective inquiry, self-direction and metacognition. In J. Bourne & J. C. Moore (Eds.), Elements of quality online education: Practice and direction. Volume 4 in the Sloan C Series, Needham, MA: The Sloan Consortium. Garrison, D. R., Anderson, T., & Archer, W. (2000, Spring). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2), 87–105. doi:10.1016/S1096-7516(00)00016-6 Garrison, D.R., & Clevelan-Innes, M. (2004). Critical factor in student satisfactions and success: Facilitating student role adjustment in online communities of Inquiry, Slocan-C series, CD-ROM 5. Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago: Aldine. Godwin-Jones, R. (2003). Emerging technologies: blogs and wikis: environments for on-line collaboration. Language Learning & Technology, 7(2), 12–16. Gordon, S. (2006). Rise of the blog. IEE Review, 52(3), 32–35. doi:10.1049/ir:20060301 Gow, L., & Kember, D. (1993). Conceptions of teaching and their relationship to student learning. The British Journal of Educational Psychology, 63, 20–33. Guller, J., Durndell, A., & Ross, A. (2007). Peer Interaction and crtictical thinking: Face-to-face or online discussion, 18(2), 187-200.

Harvard, B., Du, J., & Olinzock, A. (2005). Deep Learning: The knowledge, methods, and cognition process in instructor-led online discussion. Quarterly Review of Distance Education, 6(2), 125–135. Hudson, B. (2002). Critical dialogue online: Personas, covenants, and candlepower. In K.E. Rudestam, & J. Schoenholt – Read (Eds.), Handbook of online learning: innovations in higher education and corporate training (pp. 53-90), London, Sage. Imel, S. (1990). Collaborative Learning in Adult Education. ERIC Digest, 113. Imel, S. (2001). Learning technologies in adult education. Myths and realities. ERIC Clearinghouse on Adult, Career, and Vocational Education, No. 17. Retrieved: 12/2008, from http://eric.ed.gov/ER ICDocs/data/ericdocs2sql/ content_storage_01/ 0000019b/80/19/83/bf.pdf Jennings, D. (2005). E-learning 2.0, whatever that is. Retrieved: 12/2008, from http://alchemi.co.uk/ archives/ele/elearning_20_wh.html Kandies, J., & Stern, M. B. (1999). Weaving the Web into the classroom: An evolution of Web enhanced instruction. Paper presented at the Teacher Education International Conference, San Antonio, TX. (ERIC Document Reproduction Service No. ED 432270). Kanuka, H., & Garrison, D. R. (2004). Cognitive Presence in Online Learning. Journal of Computing in Higher Education, 15(2), 30–49. doi:10.1007/ BF02940928 Knowles, M. (1984). The Adult Learner: A Neglected Species. 3rd Ed edn, Gulf Publishing, Houston. Knowles, M. S. (1970). The modern practice of adult education: Andragogy vs. pedagogy. New York: Association Press. Koohang, A., & Harmon, K. (2005). Open source: A metaphor for e-learning. Informing Science Journal, 8, 76–86.

119

Learning with Online Activities

Kools, S., McCarthy, M., Durham, R., & Robrecht, L. (1996). Dimensional Analysis: Broadening the conception of grounded theory. Qualitative Health Research, 6(3), 312–330. doi:10.1177/104973239600600302 Koschmann, T. D. (1994). Towards a theory of computer support for collaborative learning. Journal of the Learning Sciences, 3, 219–226. doi:10.1207/ s15327809jls0303_1 Krentler, K. A., Willis-Flurry, L. A., & Washington, J. (2005). Does Technology Enhance Actual Student Learning? The Case of Online Discussion Boards. Journal of Education for Business, 80(6), 316–322. doi:10.3200/JOEB.80.6.316-321 Lacity, C. M., & Janson, A. M. (1994). Understanding qualitative data: A framework of text analysis methods. Journal of Management Information Systems, 11(2), 137–155. Lamb, B. (2004). The Standard Wiki Overview. EDUCASEUSE Review, 39(5), 36–48. Leuf, B., & Cunningham, W. (2001). The WIKI WAY. Quick Collaboration of the Web. Addison-Wesley. Long, P. D., & Ehrmann, S. C. (2005). Future of the Learning Space: Breaking Out of the Box. EDUCAUSE Review, 40(4), 42–58. Lopez,A. K., & Willis, G. D. (2004). Descriptive versus Interpretive phenomenology: Their contribution to nursing knowledge. Qualitative Health Research, 14(5), 726–735. doi:10.1177/1049732304263638 Manen, M. (1990). Researching Lived Experience. USA: The State University of New York. Martin, K., Quigley, M. A., & Rogers, S. (2005). Implementing a learning management system globally: An innovative change management approach. IBM Systems Journal, 44(1), 125–143. doi:10.1147/ sj.441.0125

120

Murphy, E. (2004). An instrument to support thinking critically about critical thinking in online asynchronous discussions. Australasian Journal of Educational Technology, 20(3), 295–315. O’Reilly, T. (2005). What Is Web 2.0. Retrieved: 1/2008, from http://www.oreillynet.co m/pub/a/ oreilly/tim/ news/2005/09/30/wha t-is-web-20.html Pascarella, E., & Terenzini, P. (1991). How college affects students: Findings and insights from twenty years of research. San Francisco, CA: Jossey Bas. Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Newbury Park, CA: Sage Publications, Inc. Perkins, C., & Murphy, E. (2006). Indentifying and measuring individual engagement in critical think in online discussions: an exploratory case study. Journal of Educational Technology & Society, 9(1), 298–307. Perry, B., & Edwards, M. (2005). Exemplary online educators: Creating a community of Inquiry. Turkish online . Journal of Distance Education, 6(2), 1–8. Popolov, D., Casllaghan, M., & Luker, P. (2002). Tying models of learning to desing of collaborativelearning software tools. Journal of Computer Assisted Learning, 18(1), 46–47. doi:10.1046/j.02664909.2001.00207.x Quitadamo, J., & Kurtz, M. J. (2007). Learning to Improve: Using Writing to Increase Critical Thinking Performance in General Education Biology. CBE Life Sciences Education, 6(2), 140–154. doi:10.1187/cbe.06-11-0203 Richard, P. (2005). The state of critical thinking today. New Directions for Community Colleges, 130, 27–38. Riddell, T. (2007). Critical Assumptions: Thinking Critically About Critical Thinking. The Journal of Nursing Education, 46(3).

Learning with Online Activities

Sanders, D. W., & Morrison-Shetlar, A. I. (2002). Student attitudes toward web-enhanced instruction in an introductory biology course. Journal of Research on Computing in Education, 33(3), 251–262. Saulnier, B. M., Landry, J. P., Longenecker, H. E. Jr, & Wagner, T. A.From Teaching to Learning: Learner-Centered Teaching and Assessment in Information Systems Education. Journal of Information Systems Education, 19(2), 169–175. Schatzman, L. (1991). Dimensional Analysis: Notes on alternative approach to the grounding of theory in qualitative research . In Maines, D. R. (Ed.), Social Organization and Social Work Essays in Honor of Anselm Strauss (pp. 303–314). New York: Walter de Gruyter. Schellens, T. (2004). Collaborative learning in asynchronous discussion groups: What about the impact on cognitive processing? Computers in Human Behavior, 21(6), 957–975. doi:10.1016/j. chb.2004.02.025 Simpson, T. L. (2002). Dare I oppose constructivist theory. The Educational Forum, 347–354. doi:10.1080/00131720208984854 Smith, M. K. (2002). Malcolm Knowles, informal adult education, self-direction and anadragogy the encyclopedia of informal education. Retrived from www.infed.org/thinkers/et-knowl.htm. Talbert, J. E., & McLaughlin, M. W. (1993). Understanding teaching in context . In Cohen, D. K., McLaughlin, M. W., & Talbert, J. E. (Eds.), Teaching for understanding: Challenges for policy and practice. San Francisco: Jossey-Bass Publishers.

Thompson, K. (2001). Constructivist curriculum design for professional development: A review of the literature. Australian Journal of Adult Learning, 41(1), 94–109. Tibi, B. (1981). The Crisis of Modern Islam. Munich: Beck. UNDP (United Nationas Developmnet Projgramme). (2005). Regional Bureau for Arab States, Quality assessment of computer science and business administration education in arab universities. Retrieved: 1/2008, from: http://www. undp.org/ar abstates/site_ docs/HE%20Overvie w%20Report.pdf Vaughan, N. (2007). Perspective on Blended Learning in Higher Education. International Journal on E-Learning, 6(1), 81–94. Vygotsky, L. S. (1978). Mind in Society. Cambridge, MA: Harvard University Press. Wagner, C. (2004). WIKI: A Technology for Conversational Knowledge Management and Group Collaboration. Communications of the Association for Information Systems, 13, 265–289. Wurm, K. B. (2005). Andragogy in Survey Education. Surveying and Land Information Science, 65(3), 159–163. Yin, R. (1984). Case Study Research: design and methods. Beverly Hills, CA: Sage Publications. Zhao, J., & Kanji, A. (2001, July 4-6). Web based Collaborative learning methods and strategies in higher education. International Conference on Information Based Higher Education and Training, Kumamoto, Japan

The World Bank. (2008). The Road Not Traveled: Education Reform in the Middle East and North Africa. Retrieved: 10/2008 http://go.worldbank. org/JLMVU0I6R0 This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 1-25, copyright 2009 by Information Science Reference (an imprint of IGI Global)

121

122

Chapter 7

Analyzing functionalities of Course Management Systems: A Faculty Perspective V. Adlakha University of Baltimore, USA A. Aggarwal University of Baltimore, USA

ABSTRACT In this chapter the authors offer a faculty perspective on desirable features of a Course Management System (CMS) to teach a course efficiently and effectively. This paper is the result of our Web teaching experiences over a period of ten years using three different CMS platforms. We develop a list of necessary functionalities that a CMS must provide web-based or web-enhanced learning. The authors anticipate that this paper could help guide software developers in developing appropriate CMS tools and would help institutions to gain greater insight into the selection of an appropriate CMS for effective Web-based or web-enhanced education (WBE), also called hybrid education. The discussion could also assist current and future Web course instructors by increasing their awareness to take advantage of many features that might exist in their CMS.

INTRODUCTION A Course Management System (CMS) is an Internet-based software program that provides a set of integrated tools for assessment and evaluation, content development, content management and delivery, communication, and course administration. A CMS manages student enrollment, tracks student performance, and creates and distributes course content. In this way, a CMS enables instructors DOI: 10.4018/978-1-60960-153-9.ch007

to break the time and space constraints of traditional face-to-face teaching, allowing them to post information on the web without any knowledge or understanding of Hypertext Markup Language (HTML). Students only need access to a browser with plug-in capabilities to view the course from any place at any time. Typically, a CMS contains aspects of administration (class rosters, recording of grades, enrollment information) and also deals directly with the core aspects of teaching. It may contain tools for real-time chats or asynchronous bulletin board style communications. CMSs have

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Analyzing functionalities of Course Management Systems

been recognized as the key technology for delivering courses and programs (Gallagher, 2003; Kemery, 2000). How a CMS is implemented is usually left to the individual university – or more often to the individual instructor. The different CMSs are relatively similar in their features; it is the ability fully to take advantage of these features that generally determines true value of a particular CMS to a particular institution. CMSs are an essential part of e-learning.. They are continually evolving and pose challenges to administrators who need to make decisions about their use and deployment at a time when the number of faculty using these systems is increasing (Aggarwal and Bento, 2000). They are being used by web-based, hybrid, and blended courses, and have reached a level of capability making it feasible to offer instructions from a distance. Many institutions are adopting and/or changing CMSs as part of the development and improvement of their web-based education (WBE) programs. Experiments with these tools are having positive results at institutions, and several schools are already offering fully online programs. In addition partnerships between corporations and universities are emerging (Demirkan, Goul, Gros, M., 2010) to facilitate online learning. Indeed, studies are beginning to suggest that there might be no significant difference (Aggarwal, 2003; Aggarwal and Bento, 2000) in learning between the face-to-face classroom and the virtual classroom in which these new tools are used. The time is appropriate for institutions to seriously consider WBE as a viable option for enhancing the availability of education without sacrificing quality (Schiffman et. al., 2007). A CMS represents an opportunity and a challenge. A large number of educators are placing a variety of course elements such as lecture notes, presentations, publications, online textbooks, and assignments on the web. CMS could be used for both completely web based and web enhanced learning through blended courses. While the use of CMSs by faculty is increasing rapidly, much

of it is concentrated on the content presentation tools within the CMS. Faculty members are much slower to adopt the more complex or interactive tools of the CMS, such as discussion forums, quizzes, and grade books. Once these tools are used, however, they are used extensively (Morgan, 2003). Although CMSs are becoming omnipresent, widespread adaptation of these CMS tools by faculty members has been hampered for various reasons (Katz, 2003). The resistance to adaptation can be overcome as systems become more robust and flexible and as faculty members become more experienced with their use (Katz, 2003). CMSs became widely available in the mid 1990s and their popularity has dramatically increased ever since (Ullman and Rabinowitz, 2004). Numerous CMSs are marketed to, and adopted by, colleges and universities. Resources are available to compare various available CMSs by their functionality, product name, and/or by features [http://www.edutools.info/course/help/ howto.jsp] (Haag et al., 2007; Van de Pol, 2001). It is important to keep in mind that the features of CMSs and their compliance/conformance with technical standards are rapidly changing, so any comparison of products needs to be updated regularly. Given the increased adoption of a CMS as an instructional tool, it is important to address how instructors are to make use of this technology. Typical steps in a complete WBE include inquiry, admission, enrollment, course work, and graduation. Though all steps are essential, none is more important than the course work itself, where the actual delivery, learning, and assessment take place. However, how to incorporate the functionality of a CMS into an existing course has rarely been addressed (Ullman and Rabinowitz, 2004). Though some authors have discussed general CMS functionalities (Hall, 2003; Valenti et al., 2003), this is the first attempt to study functionalities from faculty perspectives. In an earlier paper, Aggarwal and Adlakha (2006) present a quality model for a Web-based

123

Analyzing functionalities of Course Management Systems

course using the concepts suggested by quality leaders such as W. Edwards Deming and Joseph M. Juran. They develop a framework for implementing total quality management in a Web-based course and provide guidance on development, management, delivery, and continual improvement of such a Web course. In this paper, we extend their work and present CMS aspects with respect to a Web-based course. We discuss major components of a CMS with respect to the development, management, delivery, and assessment of a Web course and desirable supporting features in a CMS. Wherever possible, the discussion is supplemented with examples based on the authors’ own teaching experiences. These experiences are based on teaching several hundred sections of over thirty different courses at the graduate and undergraduate level by the authors and their colleagues using three different platforms over an eight-year period:

used. A few of the functionalities discussed in the paper may already be available in some of current CMSs. We, however, refrain from referring to any particular platform during our discussions and make an effort to set forth the ‘ground rules’, for proceeding with this highly viable and critical knowledge dissemination medium.

1. Eduprise, which is now a part of Collegis, an IT support company offering a broad array of services (from Spring 1999 to Spring 2001); 2. Prometheus, a platform developed at George Washington University and subsequently marketed commercially (from Summer 2001 to Spring 2005); 3. WebTycho, developed by University of Maryland University College (from Summer 2005 to date).

•

We had selected around 10 colleagues teaching online courses from various disciplines. In addition, input was obtained from over 40 participants in workshops/panels related to WBE at many conferences. Our discussion in this paper, however, is generic and from a faculty perspective only. It is not our intention to describe, compare, or contrast the functions of the three platforms we used or any other CMS platforms like WebCT or Blackboard. The purpose of this paper is to discuss desired functionalities irrespective of the platform

124

ESSENTIAL CMS FEATURES In this section we present essential features of a CMS for offering a Web course through the stages of development to delivery. CMS functionalities can be divided into four general categories: security, user-friendliness, Web-authoring tools, and assessment and feedback (Turoff et. al., 2005, Lane, 2009). A typical CMS should, at a minimum, have the following functionalities and related capabilities:

•

•

•

Security ◦⊦ Authentication ◦⊦ Authorization ◦⊦ Data Privacy and Protection User-Friendliness ◦⊦ User Interface ◦⊦ Personal Portals ◦⊦ Course Portal Web-Authoring Tools (Content Related) ◦⊦ Development, Management and Delivery Assessment and Feedback ◦⊦ Grading ◦⊦ Tracking Activities ◦⊦ Generate Statistics

The following sections describe these desired functionalities and capabilities in more details.

Analyzing functionalities of Course Management Systems

SECURITY Security is an important issue in the Internet environment. Hackers and other unauthorized people access and destroy critical information everyday, for personal gain or just for fun. It is necessary to secure the system from such unauthorized access and malicious or unintentional data destruction. A CMS, at a minimum, should provide the following basic security functions.

Authentication Though the first-stage security is provided by the operating system, it is necessary to provide second-stage, software-level security. Authentication involves verification and validation of the person (Haag et al., 2007). This requires a userID, a password, and procedures for and reminders about resetting the userID and password. In case of weak security it may be necessary to change passwords every few weeks to avoid security breaches. One of the biggest criticisms of WBE is authentication of students. Though many procedures are available, streaming live video might be the best way to authenticate all users. A pre stored picture could be compared to the live picture to authenticate a user. Streaming-based authentication is also very useful during a timed exam process where student authentication can provide more validity to assessment.

Authorization Once users are authenticated, the next step is to determine the level of access to information that is to be granted to individual users (Laudon & Laudon, 2010). There are many different stakeholders in WBE - students, professors, IT personnel, graduate assistants (GA), observers, non-credit students, etc. Each group would require different level and detail to course access. For example, a GA may only be given access to particular assignment that needs grading or a non-credit student

may have access to course content only. A CMS should allow the professor to create, modify or delete access levels. In addition, when a student drops the course, a CMS should automatically remove all authorization from the stakeholder. This would maintain currency of appropriate authorization. Several researchers (Madhuri, et al., 2010; Goriparthi, et al., 2009) have examined the issues of authentication and authorization issues and new techniques are emerging that should be incorporated in a CMS. Table 1 shows a sample access matrix. The access matrix, of course, can be modified as needed.

Data Privacy and Protection It is important to protect both intellectual and private data from internal as well as external stakeholders. If student pictures are stored for authentication purposes, they should be protected from misuse. A CMS must protect any data generated during the WBE process. This includes e-mails, exams, solutions, grades, personal information, forum discussions and any other data generated during the learning process. This could require a very large database - possibly an enterprise database - that can store data both locally and at remote sites. Though the database itself may not be a part of the CMS, it must be able to communicate with enterprise data and be able to transfer a large amount of data in real time. The database must provide seamless integration with the CMS and stakeholders’ desktops. Data protection systems must also protect data from intentional and unintentional destruction. If the data are lost, it may not be feasible for instructor to recreate grades or assignments. As soon as data are generated, backups must be created and stored at different sites so that the data may be re-created and recovered in the case of system failures. An intelligent filter could also be used to categorize data by date, type and currency.

125

Analyzing functionalities of Course Management Systems

Table 1. Access Authorization Matrix

Role IT Personnel

Class Accounts Yes

Lectures No

Conference area No

Exams No

Grades

File Management

Content management

No

Yes

Yes

e-mails Yes

Instructor

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Students

Limited (own accounts)

Yes

Yes

Yes

Limited (own grades)

No

No

Limited (their group accounts)

Student Assistants(GA)

No

No

No

Limited

No

No

No

No

Observers

Yes

Yes

Yes

No

No

No

No

No

Non-credit students

Yes

Yes

Yes

Yes

No

No

No

No

USER-FRIENDLINESS A CMS is used to facilitate interaction and provide information in a user-friendly environment. This entails making navigation and information access as simple as possible.

User Interface The basic principle of user interface is What You See Is What You Get (WYSIWYG). Quality of interface design is important here. It would be desirable if text created in Word retains much of its formatting when pasted in the course. Special characters (such as number (#), dollar ($), or quotes) should not cause problems. It should be feasible to invoke a spell-checker within the course. What students see should be attractive and clear of errors. It should be easy to navigate from link to link, lecture to lecture, forum to forum. Many authors have suggested that stakeholders should be able to reach the “final” product within three clicks (McGovern, 2000). Students may feel lost if they have to click much more. Of course, it is not only a function of a CMS but also of how well a course is designed. However, CMSs do assist in the process. If the CMS allows a faculty member to design a quality course easily, it would be much more useful for students and the faculty

126

member. A well designed course also reduces the number of queries from students.

Personal Portals It is important that students be able to see all pertinent information on their personal portal page. The portal should be complete and provide student-oriented information (Bender, 2003). This includes course related material and other administrative information. A calendar function is desirable that could provide an overall picture, for example, dates lectures are posted, assignments due dates, exams to be written, etc. A CMS should provide templates to allow for customized personal portfolios. The following information should be available on student as well as faculty portals: • • • • • • • •

All courses for the current semester CMS and Portal related tutorials Help links Password change/reminder help Specific hardware/software requirements Automatic plug-ins Personal triggers Calendar function

Analyzing functionalities of Course Management Systems

Course Portal (Home) Because the first impression of a Web-course is of utmost importance for a student, the layout, appearance, and design of the course portal are crucial. The portal contents should be clear to students, be easily accessible and provide information for all their courses. The portal should indicate where and how to access any specialized software/hardware needed for the course. It is on this page a CMS should facilitate links to tutorials and details on the workings of the CMS platform. Different plug-ins should be supported to allow availability on different platforms. A CMS should provide suitable portal views for each of the following stakeholders: • • •

Students Faculty Technical personnel

Each stakeholder should have different view and access capabilities. Student portals should provide course- and student-specific information and should include instructions on course navigation. This page should also include a link to frequently asked questions (FAQs). The faculty portal should provide student information in addition to content and student management capabilities. This includes developing syllabi, developing lectures, developing discussion topics, monitoring discussion forums, grading, and providing instant feedback. Technical personnel should have access to both student and faculty portals to allow changes if needed. Depending on the authority of technical personnel, they may have administrative capabilities which include management of course, student, and faculty portals.

WEB-AUTHORING TOOLS The ultimate goals of education are critical thinking and life-long learning. These goals are

achieved through courses and programs offered by the university. The Web creates a cooperative and collaborative learning environment (Kemery, 2000) that encourages interaction among three major stakeholders -- students, faculty, and technical support personnel (see Figure 1). It should be noted that most interaction is between faculty and student, which lasts throughout the course. In the beginning, during the course preparation stage, technical personnel may also be involved in assisting both the student and the faculty to get started. A CMS should be designed to provide maximum support for faculty-student interaction. An instructor needs to carefully consider these elements in the development of a course layout; a CMS, therefore, should be both a software as well as a communication- and content-manipulation tool. The purpose is to develop contents for smooth delivery and management in the later stages.

Development, Management and Delivery A CMS should allow web-authoring tools that allow flexibility in designing the course. It should allow easy navigation among links, open new windows as needed, and self-correct typing errors. When a student accesses a course, there should be visible links to the following features, with the option to hide any feature that is not being used by an instructor: • • • • • • • •

Syllabus Announcements Weekly lectures Discussion forum for asynchronous and synchronous communication Team formation/areas/discussions E-mail management Projects (individual/group) Exams ◦⊦ On-line ◦⊦ Take home

127

Analyzing functionalities of Course Management Systems

Figure 1. Typical interaction among stakeholders

A CMS should allow for flexibility in terms of selection of features. We discuss each of these features in more details below-

Syllabus The syllabus is the most important component of a Web-course. A CMS should have several generic syllabus templates. The link to the syllabus should be prominent. It should be feasible for the syllabus to open in a new window and for a student to be able to save it or print it easily in text format. The syllabus for a Web-course is usually comprehensive, as this is the main mode of communicating course requirements to students. Consequently, a student in a Web-course may have to refer to the syllabus many times during the semester. It is convenient if a student can retrieve a specific section of the syllabus as needed from any part of the course portal. The link to the syllabus in a CMS, at a minimum, should have the following sub-links: • • • • •

128

Printable Version Course Description Course Introduction Course Goals/Objectives Course Textbooks and Materials

• • • • • •

Grading Information Homework/Project Descriptions Course Schedule Academic Policies Additional Information Customized modules

An option should be available to the instructor to open/use or hide any of the sub-links available.

Announcements Online courses require frequent announcements, reminders, and notifications. A CMS should automatically generate triggers for these important functions. Students generally ignore directions, emails, and postings before the class actually starts. Therefore, it is desirable for an instructor to have an Announcements page. Some CMSs open the course site with the Syllabus page, while others use the Announcements page. While working with the latter option, the authors have used the opening page effectively by posting self-introductions and important instructions to start the course and by directing the students to the syllabus. During the semester this page was used to announce the weekly assignments and important due dates. For illustration, here is a sample of what one of the

Analyzing functionalities of Course Management Systems

authors is currently using for the students of an undergraduate quality management class during the first week: The author also created a permanent announcement area where announcements were posted and maintained for students’ reference throughout the semester. A CMS should enable an instructor to create multiple/recurring announcements, to open and close them according to a schedule, to archive them, and to copy them from one course to another. Podcasting is becoming important. Several researchers (McGarr, 2009; Taylor, et al., 2010) have reported podcasting “added extra information to enhance the student learning experience”. Podcasting allows students to listen to the lectures in real time or download them for later use on their portable device. This capability is becoming more and more important as stakeholders become portable and are constantly on the move. This allows 24/7 access to WBE contents. It is desirable for a CMS to have podcasting and RSS feed capabilities.

Weekly Lectures Content preparation can be a challenge in a Web-course. Online courses require a different approach than face-to-face courses. Aggarwal and Adlakha (2006) provide guidelines on preparing the contents of a Web-course. This is where the

CMS can provide flexibility in terms of linking sites, integration of publisher e-packs, embedded exercises, and hyperlink navigation. Many lectures, especially technical lab-oriented courses, may require plug-ins and multimedia capabilities. A CMS should provide authoring tools to accommodate different teaching styles and different course requirements. Here we discuss features that are necessary and desirable in the CMS to successfully and efficiently prepare a lecture in a Web or Web-enhanced-course, including the following important components: • • •

File Management Editing Capability Content Enhancements (multimedia etc.)

File Management: An efficient file management system in a CMS is crucial for an instructor in preparing weekly lectures. The instructor might provide links to exercises, PowerPoint slides, or solutions to homework problems, etc. This could amount to managing numerous files in the system. It is important that it be easy to post files into the CMS, both for the students and faculty in a variety of file formats like word processing, spreadsheets, presentations, html, xml, statistical, etc. There must also be a system of managing files for locating/inserting or editing at later stages, as well as a systematic way for arranging the files in

Figure 2.

129

Analyzing functionalities of Course Management Systems

the file manager. Flexibility should be provided for sorting the files by creation date, topic, or file names. It is highly desirable for a CMS to be able to upload zip files as well as to have the ability to create folders or subdirectories within the file area. An instructor may want to import files from different locations, both inside and outside the work area. The file management system of CMS should allow for seamless integration. During the delivery of a Web course, students may need to submit files in response to homework assignments, tests, and projects. It is not uncommon for a student to post the wrong file or an earlier draft of a document. The instructor might notice this only while grading the assignment, which could be after the due date. In any case, this creates an extra responsibility for the instructor to communicate with the student, wait for the correct file, and delay posting the feedback for the entire class. A CMS should, therefore, allow for a separate submission area where all assignments are clearly specified. A student should be able to view his/her posting after it is posted to check if the correct file is posted under the appropriate assignment. While students should not have the ability to delete a file after posting, they must be allowed to resubmit the correct file (if needed) before the due date. A CMS should allow an instructor to be able to set opening dates, due dates, and lock dates (after which no assignment or examination may be submitted). Students submit assignments and examinations at different times. An instructor might wish to print or start grading the submitted assignments before the due date. A CMS should provide the ability to mark submitted files as read/unread/graded so that the instructor would know the status of each file at a glance. Without such a feature, an instructor would have to keep a roster of students and manually maintain a record of submission status for each student. In addition, for a large class, it could be sometimes cumbersome to open submissions one by one and save the submitted homework/project files to

130

read/grade. An instructor could save considerable time if files submitted by all students could be loaded on the instructor’s computer for grading with one click/command. On the same note, it is desirable for a CMS to import back all files, with comments, back to individual students with just one click/command. Students often ask faculty members to “look” over their drafts, the logic of their programs or the steps in an analytical problem. To avoid a large number of e-mails, it is recommended that a CMS provide a separate work area for students where they can create drafts, outlines, and preliminary work for their own reference, or to share with faculty. It is an area where students may prepare drafts of assignments. When students use this area to save their drafts, they have the convenience of editing online from any place at any time. Faculty should not be able to see a student’s workbook unless the student submits it for review. One of the authors has used this feature effectively in her classes, with students commenting that they “love” the feature. Students feel comfortable using the work areas as a professor does not see the work in progress unless student is ready to show it to the professor, at which time the professor may read and add comments to steer students in the right direction. Editing Capability: An instructor will typically visit a lecture outline several times in the process of preparing and modifying it. It is therefore critical to have efficient editing capabilities. First, the CMS must have spell-check capabilities. The absence of this feature requires an instructor to work in a word processor, carry out the spell check, and then import the lecture to the Webcourse. Second, an instructor should have a link to edit the lecture from the same window. In some CMS, several screen navigations are required to be able to edit a specific lecture. As mentioned in the syllabus section, it is best to have the lecture outline open in a new window. This allows the student to view the contents of the lecture and

Analyzing functionalities of Course Management Systems

other areas of the Web-course at the same time. Some additional desirable features are:

load only in learning tasks where animations have a good cognitive fit”.

•

Discussion Forum (Asynchronous and Synchronous)

• •

• •

The ability to rearrange sessions during the semester The ability to leave a session intact if not being used in any particular semester The ability to hide sessions until the desired scheduled time or when no longer relevant The ability to specify a date when the lecture notes for a session become visible The ability to link exercises, homework solutions, PowerPoint slides, etc.

In a Web-course, an instructor might schedule new sessions to open at the same time each week. This can impose the burden on the instructor to be near a computer at a specific time on a given day. A CMS should allow the faculty to post lecture notes in advance and have them automatically become available to students at a specified time. This capability allows an instructor to prepare and post lectures ahead of time in case of travel or unforeseen circumstances. In addition, an instructor might want to make notes during the semester about better ways to present something next session but not have students see the notes. Therefore, a CMS should have the capability to hide contents in a document. Content Enhancements: Another important part of content preparation is multimedia capabilities. Many lectures require plug-ins to play modules, simulate experiments or run Java applets. One of the authors created small Java applets to explain various concepts to students. A CMS should support different plug-ins to allow platform flexibility for faculty and students. Teaching by animations also becoming important and a CMS should be able to support animation. Li, Santhanam, and Carswell (2009) reported that animation based learning is superior to text-based representations and “reduces students’ cognitive

Forum discussion is one of the most commonly used pedagogical techniques in an online classroom. Proper attention to the design, facilitation, and maintenance of an online instructional discussion is critical to promoting students’ constructive thinking (Muilenburg and Berge, 2000). This involves two-way communication, where a student can create threads, post responses and ask questions, and where faculty can discuss, create new threads or respond to students’ questions. Discussion forums furnish asynchronous environments, whereas a chat area simulates a synchronous class environment. It is the asynchronous area where facilitation and mentoring occurs. Two types of learning occur in the forum area: • •

Peer to peer Faculty to student

Many researchers (Koppenhaver et al., 2007; Aggarwal, 2003; Paulson, 2002) have discussed the role of faculty in WBE, especially in the forum discussions. A faculty member becomes a facilitator, coach, and mentor, with students learning from their peers under the guidance of the faculty. A CMS should support text, voice, picture, and animation within discussion in a blended but controlled blog-like learning environment. Students can post their comments on topics, ask questions, and engage in productive discussion with peers and faculty in any form or medium they desire. This makes learning enjoyable and productive. Depending on the class size and the number of postings in the forum, “tracking” becomes important and a CMS should allow for various forms of tracing. Tracing involves identification of threads or links that are created by the participants during

131

Analyzing functionalities of Course Management Systems

discussions. A CMS should have capabilities for the following types of automated sorting: • • • • •

Threads by dates Threads by students Threads by topics Duplicate posting Unacceptable postings (like: yes, I agree; duplicate postings; etc.)

Each thread provides insight into the level of students’ participation, their learning process, and their understanding of the course contents. As discussed later in the paper, the tracing of discussion threads is helpful in the evaluation of students. A discussion forum provides a major means of communication for the class. In many cases, faculty may need to constantly monitor and guide students by posting questions to steer thinking in the right direction. Students become motivated if they feel that the instructor is actively participating in the discussions. The forum area should allow for the following partitions: • • • •

Announcements Faculty-initiated topical discussions Student-initiated group discussion Individual postings for clarifications

For all of the discussion areas above, the instructor should be able to decide whether students should be permitted only to read postings; to read and respond to postings; and to create topics for discussion. A CMS should make the faculty member a de facto member of each of these forums and provide him/her with the flexibility to open/hide any of the above forums or to delete any posting as needed. These capabilities are important, as a faculty member may need to occasionally delete offensive postings. There might be times when the instructor might want to comment on a specific post while not wanting to share the comment with other students. Therefore, it should be feasible for the instructor to post a comment to a post that would be seen only by the original author and not 132

by other students. Moreover, students should also have the ability to edit/delete their posts as long as the discussion is open. In addition, an instructor might consider creating a discussion topic for students to post questions relevant to the current session to encourage a dialogue among students. This process benefits the entire class since all students can read the response to a query. Generic e-mails about the course that can benefit the entire class should be answered in the forum. For example, a student may send an e-mail about where to post the solution to an assignment or when a term paper is due. Answers to these questions would benefit all students who have not read the instructions or are confused about the procedures. One of the authors handled these situations by requiring students to post their queries in the discussion forum to the topic of “Questions/Concerns for the Current Session.” The author responded to these questions in a timely manner and encouraged other students to participate in the discussion. Quickly responding to such postings often can be crucial, especially during the examination period. Therefore, a CMS should have an automatic notification feature that alerts the instructor of the submission of new conference posts or of important announcements. The instructor can respond promptly when a posted message is of urgent nature. The instructor should have the option to elect to be notified by e-mail or podcast, turn notification on and off, or set it to digest mode, rather than having a new email sent every time there is action in the course. As with posting lectures, a CMS should allow an instructor to create multiple discussion topics ahead of time and set to become available to students at a later specified time. The instructor should be able to schedule the closing time also whereby the topics are not available to post or visible. In sum, we recommend that a CMS should be able to provide support with the following features in the discussion area: •

Send alert to the instructor when a message is posted to a topic

Analyzing functionalities of Course Management Systems

•

•

• •

•

•

•

Enable the instructor to create topics with read, read/respond, or read/respond/create options Enable the instructor delete one or more posts without having to delete the entire discussion topic Enable the instructor to open and hide discussion topics Enable the instructor to make discussion topics available to students at a specified time Enable the instructor to make discussion topics unavailable to students after the due date Enable the instructor to make private comment (visible only to the author) on a particular post Enable students to edit/delete their posts during the session

Team/Group Formation and Group Discussion Particularly with large classes, it can sometimes become impossible to keep track of threads and corresponding postings. This can result in a discussion overload, making it difficult for faculty and students to follow threads. Moreover, certain topics may not be worthy of discussion by a large group. For example, in analytical courses there maybe one correct solution to a posting and if a student posts the correct solution, discussion becomes redundant. To avoid this it is better to have small group discussions. The authors have taught many classes with different sizes, and based on our experience, the authors have found that it is best to divide an analytical class of more than 20 students into groups in order to generate meaningful non-repetitive contribution from students. Group/team formation may also be necessary to carry out research or project assignments. The authors have also created groups to discuss assigned homework problems. In fact, one of the authors has formed two types of groups in her undergraduate operations management course: In

a class of 28 students, two groups were formed to carry out discussions on assigned topics, and seven groups were formed to discuss and carry out the class project. It is highly desirable for an instructor to be able to see the complete list of students along with the groups to which they have been assigned. This can help identify students who have not been assigned yet when forming new groups and help eliminate a chance of assigning a student to two different groups for the same project. On the other hand, students may be added to multiple study groups and students may only see the contents of groups to which they belong. An instructor should have access to each study group just like all members, with no additional control. In addition, the CMS should automatically flag a student’s name if he/she drops out of a course, alerting other members and the instructor of the change in the group composition. Groups might be formed in any of the following ways all of which should be accommodated by the CMS: • • •

Random Score based Manual

An instructor might be interested in forming groups by a random process. Many instructors give a score to each student based on their educational background, experience, area of expertise and other factors. A query could be used to create groups so as to have equivalent group scores. In the case of different backgrounds, an instructor may want to allow students to create groups on their own. In all of these cases, a CMS should automate the group formation process and should create triggers if a student is not assigned to a group or if a student is assigned to multiple groups. A chat area allows for synchronous discussions among students and with the instructor. A CMS should provide this capability which can also be used by faculty to “simulate” an office hours’ environment.

133

Analyzing functionalities of Course Management Systems

E-Mail Management E-mail, as already mentioned, is an important form of communication between faculty and students. In order to maintain continuity, e-mail should be answered within a reasonable time. The sheer volume of e-mail, however, can be overburdening. A CMS should have capabilities for the following types of communications: • • •

Individual e-mails Group e-mails Broadcast e-mails

Broadcast e-mail is especially useful during the first few weeks of a semester until students become familiar with the workings of the Web-course site. There are also times when it is necessary to send an email to all members of a specific group, for example, in reference to a group project or group activity. In general, feedback to the entire class can be posted on the website. A CMS must provide broadcasting capabilities. Continuous and timely feedback on students’ progress is essential for ensuring students’ awareness of their progress in class. Providing weekly scores to individual students, however, can create a physical burden on the instructor. To reduce the number of e-mails, the authors have tried to group students with the same scores (or same feedback) in order to send one e-mail to the entire group. However, this effort is not feasible if students receiving the email can see all recipients of the email, thereby learning other classmates’ scores in addition to their own score. It is important that such a message is delivered as an individual message rather than a message to the entire group. A CMS must provide security so that only intended recipients receive the e-mail message. It is useful to have a CMS which is supported by its own e-mail server. In the absence of such support, email to students goes through the user’s default email program. This could create a problem if an instructor moves from one computer to

134

another frequently. While using one such CMS, one of the authors went out of the country for an extended period of time while travelling to various places. She had problems sending out email through the CMS when the default email program was not set on the computer that she was using in a business center. In one other case, students just hit “reply” to send her an email with their email going to the owner of the computer the instructor used to send the e-mail to the class. She later improvised the situation by requesting all email addresses from the webmaster. She sent a copy of the email to herself also and then used that email by using “reply all” to send subsequent messages. However, it was not feasible to account for students adding/dropping the course after this date and it was not easy to select email addresses to send email to a select group of students. It should be noted that all e-mail servers need to be continually monitored if a CMS is supported by more than one server. In the absence of such monitoring, it is feasible that one server could be down for days with accumulated unsent e-mail messages and many frustrated students and/or instructors. All email messages sent through a CMS should be logged in the system. In the absence of this feature the authors again improvised by sending a message to their own email addresses and by saving the received messages in a separate folder for each Web-course. In our experience, there is always a student (or two) who would not read the broadcast announcement (or a personal email) and complain later. The instructor can refer to a student’s query or complaint at a later time by using the email log or stored email messages. The following are the desirable features of an e-mail management system in a CMS: • • •

The ability to provide students’ e-mail list in alphabetical order The ability to e-mail the entire class or all members of a group at one time The ability to e-mail any selected group of students at one time, with the e-mail de-

Analyzing functionalities of Course Management Systems

•

livered as an individual message to each student The ability to keep a log of all messages sent to students or received from students

Examinations In a face-to-face class, examinations are typically held in the classroom. However, for WBE, this is not feasible until compressed video becomes a reality. As technology advances, it may become feasible to monitor students remotely at a reasonable cost. However, in the absence of such technology, an instructor has to use online exams. In many courses multiple-choice tests can be used effectively as a tool for assessment. It has been found that well designed objective tests provide an effective alternative to essay and short answer tests, and help measure student learning. For example, Clegg and Cashin (1986) state that well written multiple-choice questions can effectively test all six levels of learning: knowledge, comprehension, application, analysis, synthesis, and evaluation. A CMS should provide this capability by providing templates for creating on-line multiple-choice exams with the convenience of automatic grading and statistics generation. It should be feasible to scramble questions on a multiple-choice exam. It would be good to be able to offer tests that were divided in sections (with scrambling an option within each section). It is desirable for the CMS to have the capability of other kinds of questions, such as fill in the blank, essay, or matching. For take-home exams or on-line exams (not multiple-choice), there should be a time function which can close the exam after the allocated time. It is convenient for an instructor to grade essays either by student or by question, one at a time. A CMS should automatically link an exam to the grade book and provide real time feedback to students, however it should also have the capability to withhold feedback while the exam is open and then later release when

exam deadlines are passed or all students have completed their exams. To facilitate effective testing, a CMS should provide the following capabilities: • • • • • • • • • • • • •

•

Open and close exams at specific times Provide report of time students spent on the exam Easy importing of the questions from a Word document Easy importing of the questions from other (or previous) courses Easy importing of the questions from the text resource material The ability to auto-grade multiple-choice and true-false questions An option to show the correct answer (if an incorrect answer is selected) An option to add comments to provide reasoning for the correct answer The ability to add or delete questions in a test and to manage the order of questions Re-grading of exams, by questions and by students, in case of errors Grading by student or by question Sending scores automatically to the gradebook Providing real time exam assessment but be able to hide answers until posted by the instructor Providing statistics per student as well as per question

One of the authors has used weekly multiplechoice tests to cover the entire chapter with questions arranged in the order of material presented in the book. It is frustrating not to be able to maintain a desirable order of questions upon adding or deleting a question. In addition, as was recently experienced by the author, there are times when, accidentally, the answer to a multiple-choice question might be marked incorrectly. The author took two immediate actions upon realizing the mistake while the final examination was open to students:

135

Analyzing functionalities of Course Management Systems

the answer was corrected and the names of the students who had taken the test up to this point were noted. Now the author needed to view the tests taken so far one-by-one to give credit for the correct answer. Since the answers were hidden from the students, they were hidden from the instructor also, causing frustration in her inability to promptly remedy the situation. However, the Webmaster wrote a separate program to automatically grade all exams again while providing feedback as follows: We look forward to a CMS incorporating such features, thus empowering an instructor to automatically grade (and re-grade if needed) and provide detailed feedback.

Verification In a Web-course, an instructor sees the course portal with features that are available to the instructor. During the development of the Web-course and later during the delivery of the course, it is often desirable to view the course from the student’s perspective. This will often give an instructor insight into improving the course or the course presentation. There are times the instructor might like to view the platform from students’ perspective to guide them properly or just to ensure that they can see the assignments. In addition, limited access might be requested by a colleague to view the course. To facilitate these actions for a Webcourse, the following CMS features are essential: • •

Ability of different view of the course web site to instructor Ability to add a dummy student to a course

Figure 3.

136

•

Ability to add a teaching assistant or a shadow user for limited access to various components of the course

ASSESSMENT AND FEEDBACK A critical part of the learning process is the assessment of student performance during the semester. Student assessment involves all activities that measure student learning and ultimately results in a grade for the course. This may involve activities like examinations, assignments, papers, forum discussions, Web presentations, Web interviews and/or Web demonstrations (Aggarwal, 2003). In WBE, grading requires tracking students and generating statistics to assess relative and absolute performance. There are many different ways of tracking and generating statistics, but it is best when they are automatically generated in real time by the CMS. The following section discusses these options in more details.

Grading An instructor must clearly explain the evaluation process used in the course. This includes what percentage of the final grade accounts for each component of the Web-course and how students’ performance will be evaluated. As stated earlier, students should be provided with continuous feedback as to their performance in the class. A gradebook feature is a convenient tool in a CMS to make students aware of their scores for assignments. For auto-graded tests, students’ scores should be automatically inserted into the gradebook. Besides the auto-graded tests, an in-

Analyzing functionalities of Course Management Systems

structor may want the scores for instructor-graded assignments to be available to the students on the Web-course site. It should be feasible for the instructor to add or delete items in the gradebook during the semester. Items in the gradebook sometimes appear in the chronological order of creation, which can be confusing to everyone. It is therefore important to have the capability to rearrange the order of assessment items in the gradebook to keep it organized and manageable. The names in the gradebook should always appear in alphabetical order, which is convenient for recording the scores. The CMS should be capable of integrating with the campus registration system for importing student rosters. Many instructors, like the authors, are comfortable in recording and performing score analyses in the Excel spreadsheets they keep for their Web-classes. Besides adding points for each individual component in the gradebook, there should be a capability to add percentages to various components. It should be feasible for an instructor to insert a formula (as in Excel) to be able to provide the cumulative scores at any point during the semester and the final score at the end of the semester. This can help students monitor their progress throughout the semester and reduce the number of e-mail inquiries to the instructor. The gradebook should allow instructors to create, grade, and store course components like assignments, exams, forum participation, quizzes, and any other measures used for assessment. A CMS should provide the capability for each component to have an individual weight toward the overall grade, time restrictions (if any), and open/close dates and times. The gradebook should automatically calculate the cumulative grade as the semester progresses. In summary, the desired features of a gradebook in a CMS are as follows: • •

Students’ names in alphabetical order The capability to download and upload to and from spreadsheets

• • • • • •

The capability to override scores and insert comments The capability to add/delete and rearrange the order of assignments The capability to auto-calculate cumulative scores for the students The capability to allocate weights to components The capability to show students their performance relative to the class The capability to automatically export the course grades to the university record management system.

As discussed earlier, multiple-choice autograded exams can be used to instill student learning effectively. A CMS requires several additional features necessary to use multiple-choice tests efficiently and effectively: •

•

•

The ability to get the result statistics for a test, i.e., for each question the percentage of students answering the question incorrectly and the answers they picked: This analysis provides information about the students’ reasoning and guides the instructor to prepare additional feedback to the students, if necessary. Based on this analysis an instructor may reevaluate a question if a majority of students answers the question incorrectly and consider dropping or changing the question. The ability to generate “item analysis” statistic and provide point-biserial correlation between item score and total score. A negative value of this correlation for a question would indicate that good students are doing worse than poor students prompting the instructor to check the answer or revise the question. The ability to grade the multiple-choice test by student or by question: This additional feature helps if an incorrect answer is marked as the correct answer when a

137

Analyzing functionalities of Course Management Systems

•

•

quiz is prepared. There also might be a situation where an instructor would want to give credit to a student for an incorrect answer if he/she justifies the incorrect answer (by email) by acceptable reasoning. The ability to reset the quiz for a particular student: The authors have received a few emails during their Web teaching tenure where students claimed to hit the SUBMIT button by mistake before completing the test. One author once received an email from a student that her four-year old son hit the SUBMIT button while she got up from the computer to receive a phone call. The ability to provide individual feedback automatically: This is particularly important for an examination where the answers are not immediately visible to the student upon submitting the test.

Tracking and Statistics Last but not least, another important feature in a CMS is a tracking feature that allows an instructor to view how much time a student has spent or how often a student has accessed various elements of the course. This feature can be useful in following up on a student after noticing a lack of activity in the course. It can also be helpful for an instructor to get a bird’s eye view of students, especially for evaluating their participation in the discussion topics. One important feature of learning is continuous feedback. Reinforcement is more important in a Web course as compared to a face-to-face course due to the asynchronous nature of the learning environment. This requires an instructor’s capability to provide feedback on: • Participation in terms of • • •

138

Quality Level (frequency) Within group interaction ◦⊦ Initial vs. follow-up postings ◦⊦ Responsiveness to posted questions

One of the CMSs the authors used did not accept letter grades such as A-, B+ etc. Another CMS allowed for integer numbers only. Such limitations can obviously be problematic. A CMS should create triggers/alerts in the case of a student’s poor performance and provide feedback in terms of the student’s scores and possibly his/her relative ranking in the class. In one of the CMS the authors used, it was not possible to gather statistics, and the support personnel had to write programs to gather statistics on student participation in the course, exam grades, and time spent on each module. Therefore, A CMS should be able to: • • • •

Automatically calculate grades after each assessment event Allow for letter grade as well as decimal grades Set triggers for non-participation Set triggers for unsatisfactory progress

It is also important to track and keep statistics for the following events by date, time and duration for future reference: • • • • •

Logs of e-mails Logs of broadcast messages Logs of postings by students Logs of students’ log-ins Duration of student log-ins

In addition, a CMS should generate these statistics automatically. This would allow the instructor to provide timely feedback to students, which is an important step in any learning process.

SUMMARY Course management systems are continually evolving and will keep adding capabilities and functionalities. They will gradually become more potent not only for e-learning but also for e-training for practitioners. Table 2 summarizes

Analyzing functionalities of Course Management Systems

the necessary and desired capabilities of a CMS from the faculty perspective. CMS are likely to become as commonplace as email and the Internet in the process of delivering web education. Increasingly, the boundaries between the CMS and other institutional systems will become blurred. Due to the competitive nature and the number of “for-profit” players, only institutions that can compete efficiently without sacrificing quality will survive. This paper has analyzed the desired functionalities of a CMS needed for effectively developing and delivering a Web-course. We have presented desirable features of a CMS from a faculty member’s perspective based on our own and our colleagues’ Web teaching experiences. Institutions entering WBE or looking to change their current CMS could use the features discussed in this paper to evaluate and compare the CMS proposals under consideration. The discussion could also assist current and future web-course instructors by increasing their awareness of many features and applications that might be available in the current CMS used by their institutions.

The insight into faculty needs provided in this paper should also enable institutions to guide software developers in providing an appropriate CMS tool for effective WBE. As a consensus on the desired functionalities of CMS emerges, it will put a “pull” pressure on vendors to incorporate them in their software. This is already happening in one of the CMSs mentioned in the paper. The vendor of this CMS is taking the initiative, surveying faculty and adding functionalities desired by the faculty. This will put pressure on other vendors to provide additional functionalities in order to avoid losing market share. The list of CMS requirements discussed in this paper is neither complete nor exhaustive, as different instructors will have varying needs for their courses. For example, an instructor teaching an analytical course or a programming course may have a need for a simulation lab or access to an external database requiring video streaming. The authors are currently experimenting with a new CMS system which has some of the above mentioned functionalities

Table 2. Minimal Functionalities of a CMS Functionalities

Capabilities

Basic Functions

Possible Strategies/Tools

Security

Authentication Data Privacy and Protection

• Verification • Validation • Privacy • Protection • Seamless integration • Data privacy

• Streaming multimedia, • Biometrics • Voice recognition • User Id and Password • Large databases • Distributed systems • Limited access

User-Friendliness

User interface Portals €€• Personal €€• Course

• Easy navigation • Stakeholder’s mytube, myspace simulation

• Webserver/browsers • Application server • Multimedia

Web Authoring

Development Management Delivery

• Flexibility in style • E-mail management • Group formation

• Webcasting • Import/export files • Presentation • Communication • Publishing

Assessment and Feedback

Grading Tracking Statistics

• Auto calculations • Triggers/reminders • Participation/exam • Statistics • Timed exams

• Calculators • Spreadsheets • Statistic packages • Timers/Watches

139

Analyzing functionalities of Course Management Systems

REFERENCES Aggarwal, A. K. (2003). A Guide to eCourse Management: Stakeholders’Perspective. Chapter in Web-Based Education: Learning from Experiences. Hershey, PA: Idea Group Pub. Aggarwal, A. K., & Adlakha, V. G. (2006). Quality Management Applied to Web-Based Courses. Total Quality Management & Business Excellence, 17(1). Aggarwal, A. K., & Bento, R. (2000). Web-based Learning and Teaching Technologies: Opportunities and Challenges. ed., A. K. Aggarwal, Hershey, PA: Idea Group Publishing. Bender, B. (2003). Student-Centered Learning: A Personal Journal. ECAR Research Bulletin, Vol. 2003, No. 11. Retrieved from http://www. educause.edu/ir/ library/p df/ERB0311.pdf Clegg, V. L., & Cashin, W. E. (1986). Improving Multiple-Choice Tests. Idea Paper No. 16. Center for Faculty Evaluation and Development, Kansas State University. Demirkan, H., Goul, M., & Gros, M. (2010). A Reference Model for Sustainable E-Learning Service Systems: Experiences with the Joint University/Teradata Consortium . Decision Sciences Journal of Innovative Education, 8(1), 151–189. doi:10.1111/j.1540-4609.2009.00250.x Gallagher, S. (2003). The New Landscape for Course Management Systems. ECAR Research Bulletin, Vol. 2003, No. 11. Goriparthi, T., Das, M. L., & Saxena, A. (2009). An improved bilinear pairing based remote user authentication scheme . Computer Standards & Interfaces, 31(1), 181–185. doi:10.1016/j. csi.2007.11.016 Haag, S., Cummings, M., & Philips, A. (2007). Management Information Systems for the Information Age. New York, NY: McGraw-Hill.

140

Hall, J. (2003). Assessing Learning Management Systems. Chief Learning Officer. Retrieved from http://www.clomedia.com/conten t/ templates/ clo_feature.asp?articl eid=91&zoneid=29 Katz, R. (2003). Balancing Technology and Tradition: The Example of Course Management Systems. EDUCAUSE Review, 38(4). Retrieved from http://www.educause.edu/lr/lib rary/pdf/ erm0343.pdf. Kemery, E. (2000). Developing On-Line Collaboration, Chapter . In Aggarwal, A. K. (Ed.), Web-Based Learning and Teaching Technologies: Opportunities and Challenges. Hershey, PA: Idea Group Publishing. Koppenhaver, G., Blackburn, V., Palan, K., Ravenscroft, S., & Shrader, C. B. (2007). Student/ Faculty connections in the development of teaching. Decision Sciences Journal of Innovative Education, 5(2), 373–378. doi:10.1111/j.15404609.2007.00146.x Lane, L. (2009). Insidious pedagogy: How course management systems affect teaching. First Monday, 14(10). Laudon, K., & Laudon, J. (2010). Management Information Systems – Managing Digital Firm (11th ed.). Upper Saddle River, NJ: Prentice Hall. Li, P., Santhanam, R., & Carswell, C. M. (2009). Effects of Animations in Learning—A Cognitive Fit Perspective. Decision Sciences Journal of Innovative Education, 7(2), 377–410. doi:10.1111/ j.1540-4609.2009.00227.x Madhuri, L., & Nair, T. R. Goplakrishnana, (2010). Authentication and Authorization in Server Systems for Bio-Informatics, International Conference, Teamteach, Bangalore. McGarr, O. (2009). A review of podcasting in higher education: Its influence on the traditional lecture. Australasian Journal of Educational Technology, 25(3), 309–321.

Analyzing functionalities of Course Management Systems

McGovern, G. (2000). Clutter versus clicking in web design, The ClickZ Network. Retrieved from http://www.clickz.com/sh ow Page. html?page=826531

Turoff, M., & Aggarwal, A. Legon, R., & Hackbarth, G. (2004). Panel: Web-Based Education: Diffusion And Issues --The Next Stage, AMCIS, New York, NYC.

Morgan, G. (2003). Faculty Use of Course management Systems. ECAR, Educause Center for Applied Research, May.

Ullman, C., & Rabinowitz, M. (2004). Course Management Systems and the Reinvention of Instruction. Retrieved from http://thejournal. com /magazine/ vault/articleprin tversion. cfm?aid=5070.

Muilenburg, L., & Berge, Z. L. (2000). A Framework for Designing Questions for Online Learning. Retrieved from http://emoderato rs.com/mode rators/muilenburg.html Paulson, K. (2002). Reconfiguring Faculty Role for Virtual Settings, The Journal of Higher Education. Retrieved from http://muse.jhu.edu/demo/ journ al_of_higher_education/v073/73.1paulson. pdf Schiffman, S., Vignare, K., & Geith, C. (2007). Why Do Higher-Education Institutions Pursue Online Education? Journal of Asynchronous Learning, 11(2), Taylor, L., & Clark, S. (2010). Educational design of short, audio-only podcasts: The teacher and student experience . Australian Journal of Educational Technology, 26(3), 386–399.

Valenti, S. Panti, M., & Leo, T. (2003). Relevant Issues for the Design of a Successful Web-Based Instructional System: MODASPECTRA. WebBased Education: Learning from Experience, book edited by A.K.Aggarwal, Info Science pub. Van de Pol, J. (2001). A Look at the Course management Systems. IT Times May/June, online: Retrieved from http://ittimes.ucdavis.edu / june2001/cms/html

141

142

Chapter 8

Α Learning Platform for the Introduction of Remote Sensing Principles in Higher Education in a Blended Learning Collaborative Environment Nektaria Adaktilou University of Athens, Greece Costas Cartalis University of Athens, Greece George Kalkanis University of Athens, Greece

ABSTRACT The purpose of this study was the creation of a pedagogy inclusive electronic platform for the introduction of Remote Sensing principles to University students. In Universities throughout the world, there is a constant research about new and more flexible ways of teaching and organizing learning in all thematic areas. Environmental Remote Sensing is the measurement from a distance, of all the spectral features of the Earth’s surface and the atmosphere. These measurements are usually made by instruments carried by satellites and they are processed to create information concerning regional and global environmental issues. Remote Sensing is an interdisciplinary thematic area that evolves in a very fast manner. This course has been taught at the Physics Department of the University of Athens in the traditional lecturebased manner until now. This study describes the design, development, pilot application and formative evaluation of the learning platform proposed. The indices derived for the educational proposal’s evaluation demonstrated that the platform has a very good potential to support learning in the area of Remote Sensing and act as an interactive digital repository of knowledge that may enhance students’ learning and facilitate the organization and management of the course. DOI: 10.4018/978-1-60960-153-9.ch008 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Α Learning Platform for the Introduction of Remote Sensing

INTRODUCTION Over the last decade the demand for higher education learning has increased dramatically throughout the world. On the one hand, there is a rapidly growing need for the widening of initial access to higher education. Globally the numbers of degree students are estimated to rise from 42 million in 1990 to 97 million in 2010 and 159 million by 2025 (West, 1997). Greece, a member country of the European Union is not at the moment able to accommodate the entire national demand for initial access to higher education. In fact, only around one third of the country’s students can find places in its public institutions. Other students have to go abroad or turn to foreign or private providers which operate in Greece (Patrinos, 1995). In quantitative terms, it has been stated that in order to keep pace with the growing demand for higher education in certain regions of the world, one new university would need to be established every week. The financial and logistical impossibility of this option became symbolic for what was called “the crisis in access to higher education” and formed the main argument for technology supported distance education as a cost-effective alternative (Daniel, 1996). On the other hand there is the increasing need for more diversified and flexible types of higher education. The widespread use of the internet has definitely been a catalyst in the course of events in higher education demand, since this facility opened up a whole new world of easy to use technology that gives the possibility to communicate, investigate and more importantly learn. Information and Communication Technologies (ITC) enhanced environments provide excellent tools and mechanisms to deal with the Higher Education challenges, especially those technologies related to elearning platforms and campuses (Gonzalez et al., 2007). The main goal and concern of instructors is to develop more attractive and efficient ways to communicate up to date scientific knowledge to

students and facilitate in depth understanding of its concepts. A serious challenge for science instructors is to determine how to design science courses in order to integrate effectively the use of technology in an efficient and flexible way (Barab & Luehmann, 2002; Barak & Dori, 2004). According to the constructivist learning theory, students actively construct meaning from their experience, using their existing conceptual framework (Wubbels, 1992). Mental models of how the world works are unique to the observer and not always easily uncovered. Models may be inconsistent and students may be confused in what they believe and verbalize (Glynn & Druit, 1995), perhaps in response to facts they have memorized. Learners’ misconceptions can be very highly resistant to change and are likely to hinder the acquisition of scientifically correct conception (Novak, 1988). Conventional instruction often fails to establish in students’ sufficient understanding of the underlying scientific principles (Hennessy et al.,1995). Thus, science educators are challenged to develop teaching methods so as to help students make conceptual changes in their scientific thinking and acquire information that they are able to critically appraise and utilize in order to acquire knowledge. Computer assisted learning approaches seem to be very suitable to assist lecturers in this task in an effort to better meet the learners’ needs. There has recently been significant attention paid to the ways in which technology can be used to support students in Higher Education (e.g. Laurillard, 1993; Squires et al. 2000; Seale and Rius-Riu, 2001; Seale 2002). As many new technologies are interactive (Greenfield and Cooking, 1996), it is now easier to create environments in which students can learn by doing, receiving feedback and continually refining their understanding and building new knowledge (Barron et al.,1998; Bereiter and Scardamalia, 1993; Kafai, 1995). eLearning in particular, understood as online learning, or web-based learning, has raised expectations as to what sophisticated multimedia

143

Α Learning Platform for the Introduction of Remote Sensing

technologies may contribute to learning and training. eLearning has been defined in the European elearning Action Plan, as the ‘use of new multimedia technologies and the Internet to improve the quality of learning by facilitating access to resources and services as well as remote exchanges and collaboration’ (elearning in Europe-Results and Recommendations, 2003, p.7). The European Union Lisbon, Stockholm and Barcelona Councils called for a sustained action to integrate e-Learning in education and training systems in an effort to make the European Education and Training Systems a world- wide quality reference by 2010. CEDEFOP (Centre Europeen pour le development de la Formation Professionelle), the European Agency for Vocational Training, conducted in 2002 a European Survey on ‘Quality and eLearning’. The report was carried out in five European languages and asked European Training professionals their views on the quality of eLearning. As the results showed, all types of respondents were represented, including higher and further education teachers and trainers. It is worth mentioning that 61% of all respondents rated the overall quality of eLearning as ‘poor’. Only 1% rated it ‘excellent’ and only 5% rated it ‘very good’. The eLearning Group of the Thematic Monitoring under the Leonardo da Vinci Programme set up a work plan for 2003, which included the documentation of some 150 relevant projects and the execution of a study to promote a better understanding of the content, characteristics, strengths and weaknesses of eLearning. The study highlighted that eLearning-related approaches have so far been too technology-and/or media-oriented; the recommendations point out that a strong focus on learning, on the learner and on teacher/trainer is necessary. It should also be mentioned that one of the main recommendations of the study was that ‘projects aiming at eLearning should regard evaluation as one of their most important tasks.’

144

Holistic approaches to eLearning have given new potential for its successful application. The issues to be resolved in future projects are not technological problems, but focus on eLearning’s three apparently main weak points which are learner orientation, training the teachers to benefit from the new medium successfully and evaluation.

KEY CONCEPTS FOR THE DESIGN AND DEVELOPMENT OF THE REMOTE SENSING LEARNING PLATFORM The goal of this work is the design, development and evaluation of a friendly to use and up-to-date learning tool for Satellite Remote Sensing and its applications at an introductory level in Higher Education. The platform may be incorporated in a face-to face- teaching module (a mixed-mode approach), but may be used to support distance learning courses, as well, after some adjustments that may be necessary. Remote Sensing has been so far taught in the Physics Department using traditional methods. So, an eLearning platform, providing up-to-date learning material and learning activities, as well as personalized information (progress tracking, teaching and exams timetables, course outlines, past exam papers) and class e-mail discussion lists and for a, could provide a number of serious advantages for students and staff. The study actually has four main directions of action, which are (not in order of priority): 1. The development of the learning material for Remote Sensing (Space science). 2. The establishment of a learning platform (Informatics). 3. The adoption of a pedagogically driven development schema characterised by the chain: Learner>Learning objective>Categories of

Α Learning Platform for the Introduction of Remote Sensing

learning>Learning Environment> learning media. (Pedagogy/Education). 4. The evaluation of the learning tool as a means to demonstrate its effectiveness and ensure the quality of its academic practice. The study attempts, for all four areas of action, to identify and use the best practice principles and to identify and use the means to support them. The guiding principle for the entire effort was taking the needs of the stakeholders into account: students, academic staff, teaching staff, as well as considering the strategic objectives in relation to the content and quality of knowledge acquisition for the specific thematic area. The working concept followed for each area and the project as a whole may be schematically represented in the following diagram (Figure1). Critical issues for the design and development of the eLearning platform were that: • •

•

The platform functions technically without problems across all users. The subject content for Remote Sensing and its applications is state of the art and maintained up to date. The learning tool has a high level of interactivity.

•

The design principles are clearly pedagogic and appropriate to learning type, needs and context.

Individualisation, meaningful interactivity, shared experience, flexible course design, time and activities for learner reflection and quality scientific information are some of the practice principles that have been adopted to the targeted competencies as far as Remote Sensing and informatics are concerned. Learner’s autonomy combined with collaborative learning, project based learning and high level cognitive skills/ knowledge are the pedagogic practice principles that are being adopted in the study. Finally, the project’s targeted competencies as well as the pedagogy considerations shall provide the framework for the evaluation of the learning tool. The complete evaluation of the project is expected to give interesting outcomes that will assess its progress, allow to correct errors and support the learning strategies that prove to be appropriate.

Learning Material The development of web-based learning, the development of learning objects and the move to more learner-centered approaches are difficult

Figure 1. The working concept of the study, aiming at its continuous evolution and improved quality

145

Α Learning Platform for the Introduction of Remote Sensing

tasks. Smith et al. (2001) interviewed 21 instructors of both online and traditional courses offered at state Universities in New York, California and Indiana to determine differences between teaching online and face to face courses. The study attributed increased preparation time in order to produce high quality and up-to- date material. Τhe preparation of an online course for Remote Sensing to the detail required to develop unambiguous material on the web requires increased effort, due to the fact that Remote Sensing is an interdisciplinary thematic area that combines principles from physics, chemistry, informatics, etc. and it is also a rapidly evolving technique with applications in numerous sectors. Remote Sensing may be considered as the acquisition and interpretation of measurements of electromagnetic energy reflected from or emitted by a target from a vantage-point that is distant from the target (Mather, 1999). Satellite Remote Sensing for Earth Observation refers to sensors mounted on satellite platforms, which record the amount of energy reflected from or emitted by the Earth’s surface.

Satellite remote sensors are major sources of consistent, continuous data for atmospheric, ocean, and land studies at a variety of spatial and temporal scales. Satellite sensor data analysis techniques have proven to be valuable tools for the identification of environmental attributes and the monitoring of physical and biological processes relevant to global change research. Remote Sensing instruments have played a vital role in providing data concerning the impact of human activities on the environment, which is in turn needed to make informed decisions. Digital image processing allows a scientist to manipulate and analyse the image data produced by the remote sensors in such a way as to reveal information that may not be immediately recognizable in the original form. To understand the relationship of digital image processing to remotely sensed data, it is useful to have a clear concept of the steps involved in the remote sensing process. These steps are illustrated in Figure 2. The first step in remote sensing, as in any scientific study, is the definition of a problem. Due to its multidisciplinary nature, the problems

Figure 2. The Remote Sensing Process (Adapted from Jensen, 1996)

146

Α Learning Platform for the Introduction of Remote Sensing

that Remote Sensing can be applied to are numerous and diverse. In spite of this, the approaches to Remote Sensing can be categorized as being either scientific or technological in nature. Scientific approaches are driven by ‘curiosity or whim’ (Curan, 1987), while technological approaches are driven by human need. The methodology used to solve the problem naturally depends upon its origin. There are three basic types of logic that can be applied to a problem; inductive, deductive, and technologic. The steps in each of these logic methodologies in Remote Sensing can be seen in Figure 3. Satellite Image processing is the transformation and exploitation of 2d data, that is images, in order to extract all the necessary information. In order to perform the required tasks students should be familiar with radiation and its interactions with matter and should learn theories of image processing and the application of image processing techniques. Remote Sensing requires techniques from a variety of disciplines and has a strong element of research training that makes

it attractive to an increasing number of students over the years. The skills that are gained are also quite attractive to many industrial, commercial and governmental employers. The context of the Earth System Science in which much of the technique’s rationale evolves makes the course even more appealing to numerous students. From the authors’ experience at The Department of Physics of the University of Athens, many students who take the Remote Sensing course often struggle to comprehend in depth basic concepts of the technique, such as digital image characteristics, spectral signatures, image processing and image arithmetic, for example. Although they are able to answer questions in tests, students have significant problems when trying to apply the knowledge they have acquired and perform combined processes using satellite image processing software. This is to a great extent due to the fact that the learning material used, as well as the professional processing programmes are quite complex and often overwhelming for

Figure 3. The basic types of logic that can be applied to Remote Sensing

147

Α Learning Platform for the Introduction of Remote Sensing

beginners and instructions are not tailored to their specific needs. The learning material of the platform created in the present study covers several topics of Remote Sensing. The modules contain detailed information about the physical principles, data acquisition techniques, satellite platforms and sensors, as well as information about how and where to obtain satellite images. Interest is focused on online catalogues maintained by the different data suppliers. Data analysis (such as visual interpretation, image enhancement techniques, image corrections, classification techniques) form a main focus of the learning tool. Each module consists of the theory part and the learning activities. The last module is an overview of applications in several selected fields and the presentation of case studies (coastal zone management, urban issues, climatology, industrial accidents, marine applications). Independent but consistent small segmented modules have been developed. Each chapter is divided into sub-chapters, which are again divided into several pages illustrating the logical context. Text, image and sound support the learning process. Interesting links with up-to-date information

and applications on the topics covered are provided in the material. The content demonstrates how new knowledge and skill can be applied to real problems. For example, students may acquire information on environmental issues from different sectors of every day life, such as urban matters in their home–town, environmental hazards in distant locations and several more. Web-based learning, as well as conventional learning is considered to be successful if knowledge is applied correctly. Testing the knowledge acquired is of fundamental contribution to the assessment of course participants. So, at the end of each module unity, the student finds the relative learning activities and is instructed on a step by step basis so as to perform the necessary processing. All the processing is performed with ERDAS Imagine (Leica), which is one of the most commonly used image processing software in Remote Sensing applications (Figure 4). The student’s knowledge is tested during the performance of the learning activities and the results of the processing are discussed and analysed. At the completion of each module, students are asked to fill an online questionnaire, in order

Figure 4. Processing techniques are presented in detail in a step-by-step logic, in order to allow students to become familiar with the processing software. The figure demonstrates the application of a method that reduces data dimensionality by performing a covariance analysis between factors.

148

Α Learning Platform for the Introduction of Remote Sensing

to evaluate the quality and efficiency of the learning material. This process will provide information that is expected to be an important component of the evaluation process.

The Learning Platform In a knowledge–based society, there is a need for skills such as seeking, analysing and applying information, independent and life-long learning, problem solving, creative thinking and teamwork. Learners must be encouraged to analyze and criticize, to offer alternative solutions and approaches. This kind of learning may not be easily achieved in large lecture classes where students act as an audience (Bates, 2000).The main educational rationale for web-based learning is that it enables students to learn in a different way from traditional classroom teaching. The purpose of this study is to create an effective learning environment that may be embedded in the working practices of a Remote Sensing course for University students and offer a wide range of potential benefits to learners and instructors, by extending the possibilities of ‘old’ but still useful practices such as books and blackboards. The learning platform’s website was created with the Active Server Pages (ASP) technology and more specifically with the latest version ASP. Net 2.0 Microsoft with the use of the Microsoft Visual Studio 2005 development platform. The programming language that supports these pages is Visual Basic’s latest edition (2005). New characteristics have been introduced in the ASP.Net 2.0 version, such as the ‘masterpages’ through which the maintenance of the uniformity of the site’s pages is facilitated. Another important element is the simplification of the user creation and administration process. The personal data of the users (including the usernames and passwords that they use to access the site) are saved in a Microsoft SQL Server or in the freeware MSDN version which is included in Microsoft Office 2003.

The site may be installed in a Microsoft Windows Server or a Microsoft Windows XP Professional operating system, where the Internet Information Server (IIS) version 5.0 (or more recent) and the Net Framework 2.0 must be installed as well. In order to access the learning platform, students need to fill a form with personal information. The platform’s administrator (that may be the course’s instructor) gives permission to access the material, providing students with a login and password. The Remote Sensing learning material described in the previous paragraph is naturally a central part of the platform. Other elements that are of significant importance for the holistic approach of eLeaning attempted are: • • • • • • • •

Interesting links with resources for Remote Sensing . A forum where students may be able to exchange views on the course. Email contact with the course’s instructor. Announcements concerning the course (deadlines, results, etc). Announcements for relative seminars and conferences. Chat that allows the students’on line communication. An interactive whiteboard. Student tracking to have early signs of their progress.

Content and navigation are not linear in design and allow the learner to reflect on, review and digest new learning and not just collect facts. The learning tool must be clear and self-explanatory to the learners. An unambiguous screen design is an important requirement for successful learning using the platform. The screen is divided into different sections. The left frame includes the table of contents. Its appearance may vary depending on the selected chapter and is modified when moving from one chapter to another.

149

Α Learning Platform for the Introduction of Remote Sensing

It is important to state that the work is not technology driven. Technology is used as a means to achieve the goals set for the learner. For example, the interactivity of the environment was a very important feature for the design of the platform, since interactivity makes it easy for students to revisit specific parts of the environment to explore them more fully, to test ideas and to receive feedback. Another important element of the work is to connect students among them as well as with working scientists. These collaborative experiences may help students understand complex systems and concepts, such as multiple causes and interactions among different variables. It is worth mentioning that as instructors use technology, their own learning has implications for the ways in which they assist students to learn more generally, in the sense that they must be partners in innovation. Finally, it is important to state that an effort was made to utilize the teaching and learning principles that prove to work in traditional learning and apply them in the electronic tool in order to produce quality results. Thus, the purpose was not to recreate the classroom material and offer it in an online environment, but to exploit technological possibilities in order to create a learning tool that may support tutors and learners in their ways of working towards promoting expertise in the specific scientific field.

Pedagogical Frame Research has been extensively involved in scoping the possibility of modelling learning and eLearning in more systematic terms and providing some conceptual frameworks. Information and communication technologies allow various ways of adopting eLearning environments to individual learning approaches. The pedagogical frameworks that underpin these technologies, need therefore to be flexible in order to effectively support the individual learning of the target learners (Dimitrova et. al., 2004).

150

eLearning offers new opportunities that are underutilised or ineffective when they have been appended to courses that are rooted in pedagogic models and practices with which they are not alligned (Kirkwood and Price, 2006). When considering online pedagogical issues, two questions need to be addressed (Chimar and Williams, 1996): • •

What pedagogy should be used? Will the pedagogy work over the Internet using a variety of Internet delivery techniques?

The second question is subordinate to the first. The pedagogy should drive the choices of the instructional technology to be used. In this study an effort is being made to link the preparation of materials and resources for the teaching and learning, to the interaction of students with those materials and with their instructor. The structure of the learning activities has a totally different philosophy from the one-way flow of information and ideas from experts/teachers to learners- encouraging opportunities for dialogue to take place. The learning tools’ design is therefore oriented at a different direction that the “Industrial Model”, adopted by many Universities applying eLearning, that focuses on the construction of materials rather than the processing of learning (early critiques by Harris and Holmes 1976; Northedge, 1976). Being able to identify which framework is best suited to the subject matter and learning context is a truly difficult task, requiring testing in the evaluation process. The philosophy of the present study was that effective teaching should be guided by seven principles (Chickering and Gamson, 1987) that have proven to work successfully independent of and beyond teaching and learning styles. These principles are as follows: 1. Encourage contacts between learners and faculty.

Α Learning Platform for the Introduction of Remote Sensing

2. Develop reciprocity and cooperation among learners. 3. Use active learning techniques (online simulations, interactive tools, quizzes). 4. Give prompt feedback (online tutorial, assessment). 5. Emphasize time on task (flexible course design, scheduling and completion, monitoring students’ progress). 6. Communicate high expectations. 7. Respect diverse talents and ways of learning (‘personalizable’ online environment). Based on the above - mentioned principles, students are encouraged to work in small groups on collaborative tasks, where the Internet may be used to find information resources and conferencing or e-mail will be used as a means to communicate and construct joint projects, which will be assessed. The same means are used for frequent learner – instructor contact, which plays a vital role in learner motivation and involvement. In this way, the use of new technologies has a clear pedagogic role. A model lecture following the above mentioned philosophy will be video- taped and included in the material as guide for potential users of the platform. The pedagogy considerations discussed shall provide a framework for the evaluation process, which is expected to demonstrate the effectiveness of the selected approach for the support of the learning process.

A single model for evaluating eLearning is hard to define, since learning technology is still a fairly new field. Understanding the pedagogy that underpins the use of technology is constantly being revisited in the research community. Developing e-approaches is therefore compounded by ‘the absence of a widely established and practiced methodology by which rigorously to evaluate eLearning, and through which to develop the secure body of knowledge on which to build learning technology as a discipline’ (ALT JIG, 2003). The learning situation in the present study involves a complex range of interacting factors, such as subject study, student motivation, tutor input, resource availability e.t.c. Any data collected will therefore give only a snapshot of a much more complex picture. However, if different kinds of data, at different points in the learning cycle and from different perspectives are collected, then the interrelated elements that make the whole picture are far more likely to be seen. Triangulation, as described above, is they key concept in the evaluation framework of this study. With regard to the value of triangulation, Breen et al. (1998) in their investigation of the IT learning environment in a large modern University suggest a number of potential benefits: • • •

EVALUATION

it helps to ensure adequate coverage of all aspects in the evaluation focus it can help to fill in gaps that might occur if relatively few methods are used findings from one method that may be difficult to interpret can often be viewed and resolved in the light of findings from other methods it can enhance the validity of findings (which is often the single quoted purpose).

Evaluation Strategy Design

•

There are many debates in the literature on appropriate methods and paradigms for evaluation (Guba and Lincoln, 1989; Calder, 1994; Hammersley, 1993, Draper, 1996; Oliver, 1998). ELearning is by its nature innovative: it introduces new modes of teaching, learning and assessment.

The evaluation strategy is being designed so as to encompass both the content of the course and the ability of students to understand the teaching, as well as the way that media has been used to communicate those teaching aims. The charac-

151

Α Learning Platform for the Introduction of Remote Sensing

teristics of the technology, the pedagogic design, the context within which learning takes place, students’ characteristics and their prior experience and learners’ familiarity with technologies involved are issues to be addressed. The evaluation process is planned to have two phases: the first - formative evaluation – has to do with the developmental testing required to establish that the pedagogy and use of media are robust. In the second phase, that is the summative evaluation, the entire course across its first year of presentation will be evaluated. The results will allow the project’s follow up in the second year, so as to validate the decisions made and provide useful data regarding student and faculty satisfaction levels. The plan is to collect data using a range of methods (questionnaires, interviews, dialogues and narratives), involving a number of stakeholders or evaluators (students, tutors, Remote Sensing experts, informatics specialists) and over a period of time (formative and summative evaluation) in order to overcome the problem of bias and present a more complete picture of the situation investigated.

In the formative evaluation phase a relatively small number of people- as usual in formative evaluation processes- were engaged. Those people were willing to take this role and commit to properly studying the learning material and the platform. More specifically, nine students, all coming from the Physics Department were involved in the process. Six of them are about to obtain their BSc, specializing in either education or environmental studies. One student is completing his MSc in environmental physics and two students are PhD candidates in the Division of Applied Physics and Meteorology. All students attended an approximately thirty- hour course in order to get acquainted with the material as thoroughly as possible, so as to be able to evaluate its quality and effectiveness. The instructor was the corresponding author, who has significant experience in the field of Remote Sensing both as a research scientist and as a tutor. The students participating in the process were asked to complete a detailed questionnaire (Figure 5 and Figure 6) concerning their experience in using new technologies in their studies and a –hopefully- useful database shall be created. During the course, students and instructors were

Figure 5. Students specify the kinds of online facilities that they use in their studies

152

Α Learning Platform for the Introduction of Remote Sensing

asked to complete several online questionnaires concerning their level of satisfaction with as far as the content and the functionality of the platform are concerned. During the course the students were asked to complete more questionnaires that concern several aspects of the learning tool and the way it is being used. The formative evaluation was expected to be the most useful tool for the learning tools’ reform. The evaluation’s objectives were as follows: •

•

• •

•

to identify the strongest and the weakest elements of the platform from the perspective of use by the learners. to identify typical scenarios as far as the platform usage is concerned (time and place). to collect information on the elements of the platform considered most useful. to judge the value of the platform and to prepare guidelines and suggestions for the platform’s further development. to collect information about the practical integration of the computer technology into curricula.

Some of the challenges we were prepared to face were: •

Computer illiteracy among prospective resource users

•

• •

Cost of implementation and maintenance (although there cost and time savings overall). Attitudes towards new technology. Institution constraints.

The summative evaluation will indicate whether the core aim of the project, which is to provide the higher education community with a useful application on the use of new technologies to enhance learning, has been fulfilled. We would not expect to make major changes to the course on the basis of the summative evaluation, provided that the developmental testing has gone well.

The First Stage of the Formative Evaluation A series of features that characterized the learning platform have been considered in order to make a first evaluation of the function and potential usability of the learning platform, both from its pedagogical and technological aspect. The evaluation framework used, is a combination of evaluation model elements that have been proposed by Colace et. Al.,(2003, 2006). These models have been used to make comparative evaluations of a significant sample of existing learning platforms. In the study presented the learning platform was first assessed for its system requisites on the basis of three parameters:

Figure 6. Students explain in detail the use of new technologies in their studies

153

Α Learning Platform for the Introduction of Remote Sensing

a. Web-based architecture (students may access the learning tool by using the web browser, without installing other software to the computer). b. Modular organization of the material (compatibility with standards that allows to import/export courses and adaptation of training paths to specific learning needs). c. Portability (the possibility for a platform to work correctly independent of the computer and the operating system on which it runs). Table 1 shows the results, using the evaluation grids presented with it. Following this, an indicator was used to estimate if the platform makes available a satisfactory number of services. According to Colace et. Al. (2003), the services necessary for on-line training to be efficient are: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

e-mail textual or vocal chat whiteboard discussion forum live or pre-recorded audio/video stream reproducer virtual classroom content research application sharing progress tracking auto-evaluation tests integration between progress record and didactic material delivery.

The Remote Sensing platform offers 1,2,4,5,7,9,10 and 11 and thus obtained 8 as a score, which was considered quite satisfactory compared to the majority of commercial platforms that were examined in the Colace et. Al. study mentioned earlier. Only 47% of the platforms examined in the study had scores equal to or greater than 8. A series of indicators, in the framework of the Colace et. Al. Models, concerning the functional elements of the platform were then examined, in order to get a more complete picture of its potential to best satisfy students’ training needs (Adaktilou et. Al, 2007). The first indicator was the ‘Management Index’ .This index proposed by Colace et. Al.(2006), aims to evaluate the number of services for the management of students and their progress available in the learning platform. The weights assigned indicate the relative importance of each feature.

Management Index= Obtained Value for the Supported Tools/Max Value The platforms that were tested in the Colace et. Al study were 5 and had index values equal to 1, 0.917, 0.750 and 0.875. The second index was the Collaborative index, which aims to evaluate how many collaborative services are available in a learning platform (Colace et. Al, 2006). That is, services that allow the interaction among students and/or teachers.

Table 1. System requisites System requisites Web-based platfrom Modular system Portable system Supported characteristic Partially supported characteristic Non-supported characteristic

154

Α Learning Platform for the Introduction of Remote Sensing

Table2. Results for the Management Index Tool

Weight

Remote Sensing Platform

Progress Tracking

3

3

Course Management

2

2

Groups Management

2

2

Contents Management

1

1

Contents Sharing

2

-

Import Standard Contents

1

-

Import Contents

2

2

New Courses Management

1

1

Course Index

1

1

Report

2

2

Assessment

1

2

Courses Catalogue

1

1

Multiple Question Test

1

1

Assessment Report

2

2

On line Registration

1

1

User Management

1

1

Total

24

21

Index value

Collaborative Index= Obtained Value for the Supported Tools/Max Value The scores obtained by the 4 platforms tested in the Colace et. Al study were: 1, 0.5, 1 and 0.47. The next index used was for the ‘Management and enjoyment of interactive learning objects’. Its title fully describes its aim and the index may be calculated (Colace et. Al., 2006) as:

Management and Enjoyment of Interactive Learning Objects Index=Obtained Value for the Supported Tools/Max Value The scores obtained by the 4 platforms tested in the Colace et. Al study were:1, 0.22, 1 and 0.22 respectively. Finally, the ‘Adaptation of users formative learning path’Index was used. This index evaluates

0.875

how many services exist that allow the creation of personalized learning paths and the continuous assessment of students (Colace et al. 2006).

Adaptation of Users Formative Learning Path Index= Obtained Value for the Supported Tools/Max Value The former constituted a preliminary formative evaluation of the Remote Sensing learning platform, that allows the comparison of several of its features to the functions provided by existing, known and widely used platforms. The scores obtained show that the learning tool proposed may be considered quite satisfactory as far as the possibilities it gives for a successful on-line training are concerned. The next phase of the evaluation aimed at identifying the students’ satisfaction with the learning tool and the pedagogic frame proposed. During

155

Α Learning Platform for the Introduction of Remote Sensing

Table 3. Obtained results for the Collaborative Index Tool

Weight

Remote Sensing Platform

E-mail

1

1

Forum

2

2

Chat

2

2

Whiteboard

2

2

Streaming A/V

2

2

Contents Download

2

2

Application Sharing

2

-

Virtual Classroom

3

-

Total

16

11

Index

0.68

the pilot use of the platform students were asked to complete several questionnaires concerning:

c. The correlation of functions offered by the platform (ex. easy navigation, forum, email, extra sources, links, etc.) with certain elements that have to do with interaction processes (participation, trust, cooperation) and social – technical attitudes (cohesion,

a. The technical characteristics of the platform. b. The educational content of the learning platform.

Table 4. Results for the Management and enjoyment of interactive learning objects Index Tool

Weight

Remote Sensing Platform

Streaming A/V

2

2

Contents Download

2

2

Application Sharing

2

-

Virtual Classroom

3

-

Total

9

4

Index

0.44

Table 5. Adaptation of users formative learning path Index The scores obtained by the 4 platforms tested in the Colace et. Al study were: 0.818, 0.818, 1 and 0.818 Tools

Weight

Remote Sensing Platform

Progress Tracking

3

3

User Groups Management

2

2

Report

2

2

Assessment

1

1

Multiple Question Test

1

1

Assessment Report

2

2

Total

11

11

Index

156

1

Α Learning Platform for the Introduction of Remote Sensing

Table 6. The indices deriving from the self –evaluation of the leaning platform and its formative evaluation by the students Indices

Maximum value

Remote Sensing Learning Platform

Management

1

0.88

Collaborative

1

0.68

Management and enjoyment of interactive learning objects

1

0.44

Adaptation of users formative learning path

1

1

Platform satisfaction

1

0.68

Learning material

1

0.82

Pedagogic benefit/ value (based on Chang et. Al. model)

1

0.70

Students’ perceptions about Collaborative practices

1

0.80

Instructor’s performance

1

0.92

Total

9

6.92

‘Effectiveness of the remote sensing learning platform in a blended learning collaborative context’ Index.

conflict, concept of the learning media) developed by the students, according to the model proposed by Chang et. al.(2006). d. Students’ attitudes towards the practice of collaborative learning. e. The performance of the instructor in the specific learning environment (using this educational practice). All the questionnaires had the same philosophy. The total scores obtained for each function were divided by the maximum score that may be obtained. This way, the maximum score for all indices is equal to one (1) and all indices may be incorporated in a common descriptor used to denote the electronic tool’s level of mastery.

0.77

The indices derived for all the functions aforementioned are presented in Table 6. The next step was to express the levels of “mastery” or the gradations of quality from 0 to 1, so as to better describe the electronic tool’s performance and thus make the research more useful for judgement of or reflection on the progress of the work towards the valued objectives. There are a number of descriptors that are used to denote the levels of mastery, to the excellent to poor scale and several examples may be found in relevant literature. The scaled level of achievement used this study is presented in Table 7 that follows. The total score achieved by the ‘Remote Sensing’ Platform places the learning tool in class 4

Table 7. The classification used for the assessment of the learning tool’s level of achievement Class

Level of achievement for the learning tool

Value of index

1

Well below the standard

0.0-0.19

2

Below the standard

0.20-0.39

3

Meets the standard

0.40-0.59

4

Exceeds the standard

0.60-0.79

5

Distinguished

0.80-1

157

Α Learning Platform for the Introduction of Remote Sensing

and very close to class 5 lower limit, meaning that it is considered to be an accomplished learning approach, with the potential to become a distinguished one. The results reflect to a great extent the priorities of the designing approach and offer the opportunity for further study and reflection that will allow for all the necessary actions to improve the quality and functionality of the learning tool.

CONCLUSION AND FUTURE WORK The use of Information and Communication Technology in education at a University level often reveals a discrepancy between expectations and the results achieved. This discrepancy may be attributed to two problems: the tools’ inadequate didactical inclusion and the technical and organizational efforts involved. Experience proves that there is no simple and easy way to adopt eLearning practices, since the process is complex and there is no knowledge of doing it absolutely right.. The present study, which is still under development, proposes the use of technologies, and more specifically a learning platform, for the introduction of Remote Sensing principles to University students. Τhis learning platform aims to act as a centralized active digital “repository” that may simplify the learner’s work and boost learning efficiency through interactivity and live communication tools. Emphasis was put on the creation of a learner-centered environment that could prioritize the possibility to create personalized learning paths to support various learning styles and skills. The instructor will act as a facilitator who helps the students frame their experiences, encourages further exploration and removes potential obstacles. Since technologies do not guarantee effective learning, one of the main elements of the study is the evaluation of the learning tool. Its completion will allow the provision of evidence that will demonstrate whether learning in this scientific

158

field has been enabled, enriched or enhanced through the tool’s use. The study is at its pilot phase; the material and the learning platform, as well as the tools for the formative evaluation have been completed. A first approach to the formative evaluation has taken place, on the basis of indices that aim to describe and characterize aspects and services provided by the platform created. The platform’s scores showed that its overall design and structure indicate its potential as a good learning tool for the distribution of knowledge in a computer assisted manner. The group of students who performed the formative evaluation gave feedback that allowed the extraction of indices that described and characterized several aspects and services provided by the platform. The overall performance of the learning tool was quite positive and actions are already taking place to incorporate changes and improvements that will allow the learning tool’s further evolution. The first application of the learning platform will shortly take place at the Physics Department of the University of Athens. The evaluation of this experience will provide the material necessary for the platform’s workgroup to make the modifications and adjustments and follow it up in a next phase to validate decisions made.

REFERENCES Adaktilou, N., & Cartalis, C. (2007). A Learning Platform for the Introduction of Remote Sensing Principles and Applications: A pilot Phase. In Proceedings of the 6th European Conference on e-Learning, Copenhagen, Denmark. Barab, S. A., & Luehmann, A. L. (2002). Building sustainable science curriculum: Acknowledging and accommodating local adaptation. Science Education, 87, 454–467. doi:10.1002/sce.10083

Α Learning Platform for the Introduction of Remote Sensing

Barak, M., & Dori, Y. J. (2004). Enhancing undergraduate students’ chemistry understanding through project-based learning in an IT environment. Science Education, 89, 117–149. doi:10.1002/sce.20027

Cohen, D. K., & Ball, D. L. (1999). Instruction, capacity, and improvement. (CPRE Research Report No. RR-043). Philadelphia: University of Pennsylvania, Consortium for Policy Research in Education.

Bates, A. W. (2000). Managing technological change. Strategies for College and University Leaders. San Francisco: Jossey – Bass.

Colace, F., De Santo, M., & Pietrosanto, A. (2006). Evaluation for E-Learning Platform: an APH approach. In Proceedings of the 36th ASEE?IEEE Frontiers in Education Conference.

Beetham, H. (2001). The evaluation Cycle, Embedding Learning Technologies. Retrieved from http://www.elt.ac.uk/ Beetham, H. (2005). Evaluating an e-tools project: some guidelines. http://www.jisc.ac.uk/uploaded _documents/Guidelines.doc Bleek, W. G., & Jackewitz, I. (2004). Providing an E-Learning Platform in a University Context – Balancing the Organisational Frame for Application Service Providing. In Proceedings of the 37th Hawaii International Conference on System Sciences - 2004 Bransford, J., Brown, A., & Cocking, R. (2000). How people learn: Brain, mind, experience and school. Committee on development in the science of learning, National Research Council. National Academy Press. Breen, R., Jenkins, A., Lindsay, R., & Smith, P. (1998). Insights through riangulation . In Oliver, M. (Ed.), Innovation in the Evaluation of Learning Technology (pp. 151–168). London: University of North London. Calder, J. (1994). Programme Evaluation and Quality. London: Kogan Page. Chang, K., & Lim, J. (2006). The role of Interface Elements in Web-Mediated Interaction and Group Learning: Theoretical and Empirical Analysis. International Journal of Web-Based Learning and Teaching Technologies, 1(Issue 1),

Colace, F., De Santo, M., & Vento, M. (2003). Evaluating On-line Learning Platforms:a case study. In Proceedings of the 36th Hawaii International Conference on System Sciences. Daniel, J. S. (1996). Mega Universities and Knowledge Media. Technology Strategies for Higher Education. London: Kogan Page. Dimitrova, M., Mimirinis, M., & Murphy, A. (2004). Evaluating the Flexibility of a Pedagogical Framework for e-Learning. In Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT). Dobrovolny, J. (2002). Learning strategies. Retrieved from http://www.learningcircuits.org /200 3/oct2003/dobrovolny.htm Draper, S., Brown, M. I., Henderson, F. P., & McAteer, E. (1996). Integrative Evaluation: An Emerging Role for Classroom Studies of CAL. Computers & Education, 26(1-3), 17–32. doi:10.1016/0360-1315(95)00068-2 European Agency for Vocational Training, (2002). Quality and e-Learning in Europe. Survey report. Evaluating eLearning (n.d.). Why evaluate? Warwick University. Retrieved from http://www2. warwick.ac.uk/services/ cap/resources/egui des/ evaluation/eLearning Evaluation of Learning Management System Software, Part II of LMS Evaluation. (2004). Open source eLearning Environment and Community Platform Project.

159

Α Learning Platform for the Introduction of Remote Sensing

Friedrich, J., & Karslioglou, M. O. (2003). A Remote Sensing computer assisted learning tool developed using the unified modelling language. Journal of Photogrammetry & Remote Sensing, 58, 265–274. doi:10.1016/S0924-2716(03)00022-4

Hislop, G. W., & Ellis, H. J. C. (2004). A study of faculty effort in online teaching. The Internet and higher education. The Internet and Higher Education, 7(1), 15–31. doi:10.1016/j.iheduc.2003.10.001

Garrison, D. R., & Anderson, T. (2003). e-Learning in the 21 st century: A framework for research and practice. Routledge, London.

Jensen, J. R. (1996). Introductory Digital Image Processing: A Remote Sensing Perspective (2nd ed.). Upper Saddle River, NJ: Prentice Hall.

Glynn, S. M., & Druit, R. (1995). Learning science in the schools: Research reforming practice. Mahwah, NJ: Elbaum.

Jensen, J. R., & Jackson, M. The Remote Sensing Process. Retrieved from http://www.cas.sc.edu/ geog/r slab/Rscc/fmod1.html

Gonzalez, E. E., Garcia, F. B., & Jorge, H. A. (2007). Using a quality framework to evaluate e-Learning based Experiences. 6th European Conference on e-learning, Copenhagen.

JISC eLearning Programme (2003). Designing for eLearning, an overview of the eLearning and Pedagogy Strand.

Greenfield, P. M., & Cocking, R. (1996). Interacting with video. Norwood, NJ: Ablex. Guba, E., & Lincoln, Y. (1989). Fourth Generation Evaluation. London: Sage. Hammersley, M. (1993). Educational Research: current issues. London: Paul Chapman in association with the Open University. Harris, D., & Holmes, J. (1976). Open-ness and control in higher education: towards a critique of the Open University . In Dale, R., Esland, G., & MacDonald, M. (Eds.), Schooling and Capitalism: A sociological reader. London: Routledge and Kogan Page.

Kirkwood, A., & Price, L. (2006). Adaptation for a Changing Environment: Developing learning and teaching with information and communication technologies. International Review of Research in Open and Distance Learning, 7(2). Koenig, G., & Weser, Th. A (n.d.). Servlet based training course for Remote Sensing. Commission VI, WG VI/2-4-1. Laurillard, D. (1993). Rethinking University Teaching a Framework for the Effective Use of Educational Technology. London: Routledge. Mather, P. (1999). Computer processing of remotely sensed images, An introduction. New York: Wiley.

Hassanien, A. (2006). Using Webquest to Support Learning with Technology in Higher Education . Journal of Hospitality, Leisure, Sport and Tourism Education, 5(1), 41–49. doi:10.3794/johlste.51.96

Northedge, A. (1976). Examining our implicit analogies for learning processes. Programmed Learning and Educational Technology, 13(4), 67–78.

Henessy, S., Twigger, D., Driver, R., O’Malley, C. E., Byard, M., & Draper, S. (1995). Design of a computer-augmented curriculum for mechanics. International Journal of Science Education, 17(1), 75–92. doi:10.1080/0950069950170106

Novak, J. D. (1988). Learning science and the science of learning. Studies in Science Education, 15, 77–101. doi:10.1080/03057268808559949

160

Oliver, M. (1998). Innovation in the Evaluation of Learning Technology. London: University of North London press.

Α Learning Platform for the Introduction of Remote Sensing

Patrinos, H. A. (1995). The Private Origins of Public Higher Education in Greece. Journal of Modern Greek Studies, 13, 179–200. Seale, J., & Rius-Riu, M. (2001) An introduction to learning technology within tertiary education in the UK: A Handbook for Learning Technologist [online]. Oxford: ALT. Retrieved from http:// www.alt.ac.uk/alt_lt _handbook.asp Shaw, M., & Corazzi, S. (2000). Avoiding holes in holistic evaluation . Journal of Educational Technology & Society, 3(4). Smith, G. G., Ferguson, D., & Caris, M. (2001). Teaching college courses online vs. face-to-face. THE Journal ONLINE. Retrieved from http:// www.thejournal.com/ magazine/vault/A3407.cfm Squires, D., Conole, G., & Jacobs, G. (2000). The Changing Face of Learning Technologies. Cardiff: University of Wales Press.

Taylor, J., Sumner, T., & Tosunoglu, C. (2000). Peering Through a Glass Darkly: Integrative evaluation of an on-line course . Journal of Educational Technology & Society, 3(4). The eLearning Developers Journal, (2003). Learning Measurement: It is not how much you train, but how well. Retrieved from http://www. eLearningGuild.com West, R. (1997). Review of Higher Education Financing an Policy. (Report of the West Review). Canberra: Department of Education, Training and Youth Affairs. Wubbels, T. (1992). Taking account of student teachers’ preconceptions. Teaching and Teacher Education, 8, 137–149. doi:10.1016/0742051X(92)90004-M

161

162

Chapter 9

An Evaluation of Blending Technology with Pedagogy for Teaching Educators and its Implication for their Classroom Teaching Carol Kahan Kennedy Fordham University, USA Maureen Hinkley Fairfield University, USA

ABSTRACT Although research has been conducted on the benefits and drawbacks of online courses, more is specifically needed in teacher-education to increase understanding of the transfer process from technology integration learning to the classroom. This study was designed to evaluate a model for blending technology with traditional classroom methods in preparing teachers to do the same. A combination of qualitative and quantitative methods was used to examine the collaborative and scaffolding approaches to the teacher-learners construction of meaning in the online discourse. Data has been collected from blended graduate-level courses taught in the area of educational technology for in-service and preservice teachers from 2001 through 2006. These findings will be used to help identify best-practices for technology integration with teacher-education through informed applied research, and to create a new model for more comprehensive future blended course design.

INTRODUCTION This study is intended to inform the construct for teacher-learners’ transfer of technology first to their teaching dogma, secondly to their pedagogi-

cal praxis and ultimately for the students’ learning environment.. What evidence does the situated praxis of online discussions in the teaching of teachers offer to further the research of meaningful technology transfer into their classrooms?

DOI: 10.4018/978-1-60960-153-9.ch009 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

The data accumulated from blended course online discussions with in-service and pre-service teachers was examined on the basis of the topics of threaded discourses, content of responses, identification of originator of a thread, and occurrences of collaboration in forming meaning. This in-depth evaluation of the online interactions and subject of discussions will contribute to creation of a model for teacher-learners as participant practitioners in online learning.

LITERATURE REVIEW Rourke, Anderson, Garrison and Archer (2001) have focused on one specific element, “Social Presence,” of the Community of Inquiry Model, (Garrison, Anderson & Archer, 2000) and created a template for assessing how students actually project themselves socially into an online conferencing environment such as an online class. In the model three components are identified: the cognitive presence of students, the teaching presence of the instructor and the social presence of the students. The authors tested the template, utilizing content analysis of transcripts to assess students’ social presence density in a conferencing environment. Their study indicates that this is a good way to provide quantitative description of the effectiveness of an online environment, and to examine the suggested relationship interactions and changes that are affected by the instructor’s, the students’ and cognitive presence. Angers and Machtmes’(2005) qualitative study identifies the “adoption and use of technology in the classroom is determined by teachers’ attitudes and beliefs.” (Angers, 2005, p.780). Their findings regarding that “Teachers beliefs about classroom practice appear to shape their goals for technology, ” (Angers, p.789). This evaluation examines how these intrinsic beliefs are expressed, changed over time and influenced by participating in online classes, thereby guiding the teacher-learners to become expert-practitioners. How can an instructor

design a teacher’s learning experience to achieve these results? Stephenson’s (2002) work includes a collection of articles with numerous authors focusing on how to transition from theory to practice, create effective online learning environments using theoretical frameworks and evidence-based research and pedagogy to assist learners in maximizing the creation of knowledge from online learning. Each of these articles talked about a transformative shift in the pedagogical paradigm from the instructormanaged classroom construct to a learner-centric online pedagogy. Several features of learning online that are identified as important for both instructors and learners include the following: access to resources, heuristics, attention to different learning styles and needs, access to experts, both online and offline, tracking and recording of dialogue, transactions among students, teachers, student-student, a variety of types of engagement, including synchronous and asynchronous, feedback, good design of the web environment, easy links to multimedia, universal design, opportunities for telementoring and interaction with experts both within and outside of the institution, an the opportunity to work in collaboration with peers and groups online and globally. Each of these features is also expected to be flexible and learner-controlled. Also important, as Stevenson’s (2002) work indicates, students must be informed of the difference in the online environment as offering more than a lecture delivered online, as well as encouraged to use the interactivity, and to take responsibility for their own learning and participation in order for the paradigm to shift from classroom teacher to a multi-media learner centric environment. While Kozleski (2004) emphasizes the economic contribution of technology as being imbedded in education, she identifies changes to teachers’ dogma and pedagogy as critical for the transference of technology in education. A central effort of this study was to identify discrete teacher learning which would underscore, “rather than har-

163

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

nessing the curriculum, understanding education as a technology transfer activity opens the dialogue about how and what to teach.” (Kozleski, p.191). Borko (2004) identifies elements of a situated analysis of teacher learning as a learning program, with teachers as the learners, the instructors become the guides for the teachers as they construct new learning along with the context in which the teachers learning occurs. The impetus for this study came as a response to the meta-analysis done by Mary Tallent-Runnels, Julie A. Thomspons, William Y. Lan and Sandi Cooper (2006). Their research suggests that courses taught totally online are called “online courses” and those taught partially online be labeled “blended courses.” While many researchers have studied some combination of these relationships and the factors that influence them. This study is intended to further our understanding of what and when meaning is being situated in the teachers understanding of the technology for the new role it will now play in their teaching within their classrooms. Kotrlik and Redman (2005) examine the “Extent of Technology Integration In Instruction By Adult Basic Education Teachers,” researching how much adult basic education teachers integrate technology into their curriculum and have learned how to use technology themselves, recommending the four methods cited by Ginsburg,(1998). These methods include considering technology as specific curriculum learning digital literacy skills, technology as an instructional delivery system, as another component to instruction for learning skills, and as a tool to enhance heuristic skills, write, and comprehend. The authors cite the process of learning to integrate technology from learning to adapt to using technology to construct new learning environments. There are several discreet barriers for adult learners as teachers: how to integrate technology, including the lack of opportunity to learn from their peers, ask and answer teaching-related questions, and actual practice in online discourse. Teacherlearners do not generally engage technology on

164

a higher level, and lack the opportunity to make innovative integrative use of it in their practices. According to this study, not much progress has been made since the 1995 Office of Technology Assessment report. Yet his study illuminates more about the online component of blended courses potential to greater opportunity for teacher-learners to participate in discourse, learn from the instructor and their peers, and gain knowledge along with insights on how to better integrate technology into their curriculum, thereby overcoming these barriers. As opposed to how teachers are facing impediments to technology integration, Ertmer, Ottenbreit-Leftwich and York (2006-2007) have examined “Exemplary Technology-Using Teachers: Perceptions of Factors Influencing Success.” This study examines teachers who actually use technology meaningfully in their classrooms despite internal and external challenges, including lack of time, resources, technophobia, access and institutional support. While other articles cite the barriers that lead to full implementation of technology, this study’s emphasis is the most important indicators that may help teachers overcome these known obstacles. Interestingly, one of the findings suggests that digital immigrants, those teachers with more than five years of teaching experience, but less technology savvy and confidence, are actually more likely to direct their students to use technology in a more effective, meaningful way to enhance learning than their less-experienced, digital native colleagues who have more technology experience and confidence, but lack the expertise and management skills of more seasoned educators. The more experienced teachers appreciated the value of the use of technology more than the more novice teachers who felt more at ease using the technology, but used it less effectively. This supports the data-analysis in this study particularly in the Introduction to Technology MD 400 course section with fewer digital natives, but more experienced teachers who are digital immigrants

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

and contributed a larger number of transactional postings. The Ertmer, et al. (2006-2007) study also examined what intrinsic and extrinsic factors affected the use of technology to identify which characteristics were more likely determinants for the use of technology in the classroom. The results of the study indicated that the teachers who used technology in the most exemplary way felt that the factors such as confidence and experience (intrinsic) rather than extrinsic factors such as availability, quality of resources and their own time were most influential in their effectiveness.

CONCEPTUAL FRAMEWORK While Swan (2004) examines the relationships that exist between online interactions and learning in the online environment, she adapts a model that visually presents the interface, learning and supporting discourse when looking at teacherlearners’ interactions with their peers, content and instructors that takes place in online discussion forum. Her supporting Meta-analysis methods and the creation of a succinct chart, comparing research findings related to implications for practice became the template for representing the data of this study. Taking a slightly different approach from Swan’s model, Rourke, Anderson, Garrison, and Archer (2001) focused on creating a model of cognitive presence, as relates to the text-based online learning environment, drawing upon their previous model of Community of Inquiry (Garrison et. al., 2000), expanding it to include the element of “Social Presence”. Thus, they created a template for assessing how students actually project themselves socially in an online conferencing environment. The new model used for this study has four stages; the first stage, “critical inquiry” uses triggering events in the online discourse, where the instructor explains expectations. Second is the “exploration phase” where students are asked to

understand the nature of the problem or issue and explore it in a relevant manner. This is followed by the “integration phase” where students are expected to construct new meaning extrapolated from the exploration phase and make a contribution to the discourse within the online learning community of inquiry. In the final phase a resolution is reached regarding the issue that was proposed by the triggering events, marking the transition from the initial hypothesis to practical application within real practice, thus demonstrating true understanding and knowledge acquisition. These four phases are the elements identified, and analyzed in the collection of data amongst the 14 blended courses over a period of five years.

EVALUATION METHODOLOGY Sample Population: Characteristics and Description The sample population is comprised of adult students who are participants in a Graduate Teacher Education Program at a Jesuit university. Some of these sample teacher-learners were majoring in educational technology, while others were taking their required educational technology course and electives. The teacher-learners range in age from recent graduates of a Bachelor’s program, to older, returning students who are making career changes or enhancements. The majority of the students are either pre-service or in-service teachers pursuing a Master’s Degree. The instructors’ combined population demographics included a total number of 188 students, 14 blended classes, conducted from the Fall of 2001 through the Summer of 2006. A representative sample of the courses evaluated may be found in the Appendices. Both instructors have eight years of experience teaching on-site, online and blended courses in educational technology for graduate-level teacher education.

165

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

The Role of the Instructor The course design along with the instructors’ pedagogical praxis and paradigm choices were also examined. For example, both instructors made use of inquiry-based teaching methods in class and online. Each instructor utilized constructivist modeling, with methods such as scaffolding and fading throughout all of the courses and online blended components. Supporting the pedagogical role for the instructors is the creation of a social/ emotional presence that sets a climate for cognitive presence while supporting discourse stitches together the community of inquiry modeled by Garrison’s et al. (2003) “Community of Inquiry Model”.

Online Discussions

(see details below) were created to more closely align with the first three phases of the Rourke, Anderson, Garrison, and Archer (2001) model for the online discussions formative assessment (critical inquiry), knowledge-transfer (exploration phase) and summative assessment (integration phase) of the online component.

Parameters Examined Formative assessment: prior knowledge • •

Initial analysis of the data suggests the Instructor/Teacher-Mentor’s pedagogical approach to the online setting show movement from leading to some combination of modeling online behavior and heuristics for teacher-learners. Knowledge transfer: making meaning of the process of learning

The online postings were evaluated using methods amongst quantitative and qualitative techniques in terms of topics, and content. Particular attention was given to teacher-learners’ references to prior experiences and knowledge in connection to their new learning within the content and topics of the online discussions. Special interest was paid toward whether or not the online portion of the courses contained evidence of the teacher learners situating technology in their future pedagogical praxis.

•

Processing of Data

•

The analysis of the data consisted of several steps. The first set of coding was used initially to break down the responses and dialogue into discernable categories. However, after the first analysis, it became evident that this coding was not descriptive or telling enough of what we were seeing. There was clearly an apparent progression of engagement in the online community. Next the total number of postings per class, were examined as well as each posting in terms of quality of these postings and any related syllabi criteria. The second set of codes

•

166

FA-SC comments situated in the classroom FA-NSC comments situated in other than the classroom- e.g. Theory, hypothetical

• •

•

•

MM-PC meaning being made from peers from online collaboration (this may appear conjointly with other codes) MM-SC meaning making is situated in classroom connections MM-SM meaning-making is situated in course materials/content MM-SMC meaning is being constructed from both classroom and course materials Summative assessment-critical thought; re-engineered approach to teaching and/or learning SA-NET other, learning is evidenced, for example new teaching and/or learning dogma SA-NET vision for teaching is situated with technology applied to practice

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

DISCUSSION OF THE EVALUATION RESULTS Identification of Characteristics for Online Pedagogical Practices The evidence of the online postings allowed for more in-depth assessment of teacher-learners’ levels of engagement with material as well as analysis of teacher-learners’ construction and integration of meaning for learning.

Instructor’s Role The role of instructor evolved over all of the courses in the online component from being the leader/authority with a strong presence to the role of the facilitator. This was due to intentional modeling scaffolding and fading by both instructors. Teacher-learners’ interest and willingness to participate and take on more directive roles increased in all courses as they became more familiar with their classmates, and more at ease with the online environment. The students’ interactions were more collaborative online in the learning process, ultimately generating ideas on their own. In essence, collaborative learning had moved beyond both the content and the classroom. Thus suggesting strong support for the element of ‘social presence’ that Rourke, Anderson, Garrison, and Archer (2001) had added to the Garrison et al. (2000) Community of Inquiry Model.

Course Design How to Structure Online Same/ Different Course Requirements? In all courses evaluated the students were required to log on and participate in a meaningful manner over the course of the semester. For some courses online participation was a minimum of 8 meaningful postings required with the online discussion comprising 5% of their grade in other courses once

a week of 15 meaningful postings were required for as much as 10% of the final assessment. Both seemed somewhat effective in keeping students actively participating. Each instructer noted that in the future, perhaps some guidelines for the timing of postings would be given in order to avoid ‘bunching’ or students waited until the last minute to complete their required postings.

Learning Affects The online environment provided a shared experience for the learners, while extending the opportunity to situate the new technological teaching in the teacher-learners praxis for their future pedagogy. And most importantly, it was an authentic activity where teacher-learners, who were learning how to use technology in the classroom, were actively participating in using technology in the online format. By the end of the courses the teacherlearners appeared to have evolved from novice to expert practitioners, knowing how to use the online environment effectively for learning. Many reflected that they liked the online environment and would consider taking online courses in the future. Not one teacher-learner objected to blended component in any of the courses. Rather the following quote is reflective of an overall very enthusiastic outcome, “I was able to collaborate with colleagues in WebCt which was something I had never participated in.” From the coded data three general types of interactions emerged as mechanisms for the transfer of knowledge in the online learning component; interaction with content, interaction amongst the teacher-learners, and interactions with the instructor.

Interaction with Content From the examination of the data we were able to see how the online component helped to relate to the content provided in the actual classroom and required text and readings.

167

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

The online electronic text and resources were relevant to the themes of the classroom discussions and supported them in a different modality. The blended component provided a way to clarify content and in-class discussions, help teacher-learners relate to content presented in both the classrooms texts and electronic texts. Eventually the enculturated students were able to emulate the model and identify additional supporting electronic materials for their classmates to consider, discuss and use in their own practices. Example of Discussion Topic- Reflection of a hands-on in-class workshop with guest Educational Video Center instructor–using video making projects in the classroom. “The use of videos and cameras in the classroom is an additional resource that educators can use to enhance their curriculum. Presently, I believe that many teachers use documentary videos in their classroom. Wouldn’t it be exciting for the teacher and student to produce their own documentary? I do not believe that video and video-making are widely used in my school district. Possibly cost is a determining factor… The workshop on “Street Interviewing” was very educational to me. What questions to ask, how to ask them and who will ask the questions are key discussion areas that a group must deal with before the actual taping can begin. The entire process was a whole new experience to me. The entire process involves preparation and team work as well as self evaluations. No individual members of the group were unimportant. This is extremely important for those of us who are in teaching and use group work as a way to engage our students. Participation and involvement are criteria that I encourage in my classroom…” MD 546 Spring 06.

“I agree with most everyone (in the discussion online) that purchasing technology is something that should be a well thought out process. Not all teachers in all classes need the newest and latest technology. Sure it helps to aid in learning and caters to different styles however as they said in the article, many teachers are not experienced with using all of the technology out lately. It is important first to consider the need, the purpose, the usefulness, etc. Everyday something new is coming out, to just spend money carelessly (with good intentions) does not make sense.” MD 40001 Spring 06.

Interactions Amongst Teacher-Students

After hearing all of the positive reassurance, I am considering taking an online class this summer. It seems that if you are able to manage your time efficiently and can work independently, an online course is a great solution for those needing flexibility. (posting from MD 400-01 spring 06)

Discussion Topic- the dilemma of purchasing equipment and resources for the classroom and school-article initially posted by Instructor A

168

Examples of Shared Experience One teacher student responding to another’s point e.g.-“(so and so)made an interesting point here about the …” very affirming. Then the teacherstudent goes on to give an example specific to their experience that might overcome the classmates difficult experience. This was a very common sequence to teacher-students’ online discourse behavior; approaches repeating a pedagogical teaching, coaching model used in many classrooms and seeing much evidence of creating a similar paradigm with an online format for praxis. Because this study is specific to teacher-learners in educational technology courses evidence is not conclusive for other student demographics of online populations for having such strong ‘native’ teaching/learning/collaborative behaviors. In a number of online segments teacher-students address responses to a specific classmate(s); ‘to so & so’…”I wonder if your priorities are in the wrong place. As I see it, content and learning material doesn’t have to be complex…”

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Sharing on WebCt has been a wonderful venue to communicate ideas and thoughtful comments. This is my first class with this type of dialogue, I think it is so enriching and beneficial to all. In addition, I have learned so much from others in the class, demonstrated by our projects and presentations and web interactions. Reflecting on the end of the semester we truly have evolved into a warm community of learners supporting technology cross curriculum, and integrating each person’s interest and background. (posting from MD 400-02 Fall 05)

Interactions with the Instructor Phrasing of instructor-posed questions was important to elicit responses that were relevant to the theme, topic, discussion and any collaborative projects. The majority of responses were on-topic, and demonstrated that the students were able to make meaning of the themes and the context presented. Other trends we noted in the findings revealed that the teacher-learners were not simply addressing only one person in their responses, indicating a higher level of participation. The less instructormodeling there was, the more collaborative, open discussion there was among the teacher-learners. The majority of the students had less difficulty with the technology interface of WebCt, thereby enabling them to participate in the discussion earlier and more fully in the term. The majority of these students came in with some basic understanding of media, including online learning. They were not necessarily Digital Natives, but they were not “newbies” either. Overwhelmingly the majority of data coded from all class postings was found for the knowledge transfer phase of the online discussions. Teacher-students most frequently used this component of the course to make meaning, sort their new learning and finally to revision of their teaching methods. For example, students were

frequently sorting out the meaning of the text assignment and sharing online what they further researched on the internet. This type and level of engagement with the learning is just not possible during an in-class discussion. One unanticipated finding consistent with all of the courses was the high totals for Hits versus Read versus Posted. It is difficult to determine the reason for this outcome. Are the teacher-learners spending more time surveying and reading material, reflecting, assimilating prior to critical participation as a precursor to the occurrence of sharing critical thought? The evidence suggests further study is needed in this area. There was, however, little evidence of the fourth or final phase of the Community of Inquiry Model, “resolution” or enculturation within the online component. Very few teacher-learners actually stated they had tried some new technology teaching techniques in their classrooms. It was noted that the online discussions ended with the onset of the final papers and project portions of the courses which did require some curricula plans designed to incorporate technology. In any form of teaching teachers, whether it is online or onsite, we recognize that “learning by doing” is the most effective, impacting them the most when applied directly to their ability to transfer to the classroom. By design, the hybrid environment combining face-to-face and online learning reinforces and offers opportunities for more in depth meaning making. Through participation in this format, a different dynamic is created, allowing teacher-learners to relate to their own experience and background knowledge, while also affording them opportunity to construct new knowledge. They also function as expert practitioners, as was the case in MD 546 when Instructor A asked her students to review one of the textbooks, “Tech Tactics.” In the online forum they were asked to present their own review of the book and recommendations for use by teachers. They offered excellent, authentic reviews in the collaborative environment. By the end of this

169

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

course, the online interface became seamless and invisible, allowing the teacher-learners to participate effortlessly, and to create their own meanings that were transferable to others in their profession.

What Were the Differences Among Classes? Instructor A’s MD 546, Integrating the Arts, Technology and Music into the K-12 classroom showed some different results from the more novice classes. This class required the entry level, MD 400 be completed in order to enroll, therefore the students were more tech-savvy and experienced. These students needed no time to get right into the discussion, necessitating less moderating. However, there were fewer postings and less participation online than in the MD 400 classes. Students worked more collaboratively in class and online throughout the semester and attended many hands-on workshops. This was a small class; many of the teacher-learners already knew each other, had taken previous classes together and were much more at ease using technology in any format. Their final projects required some online collaboration. The blended component featured less prominently for them. One other finding indicated that in the introduction-level class where there were only females, who were less technology savvy but had more classroom experience, with far greater number of postings and more substantive content (375 postings) than those of the class with males, who were more tech savvy but with less pedagogical experience (232). This raises the question of whether the all-female class, which included many ELL/ESL teacher-learners, felt freer to participate in the discussion and express their views than the mixed-sex class. The Community of Inquiry Model in either form (Garrison et al 2000 or Rourke et al (2001) do not appear to account for the learning affects amongst the levels of interaction.

170

CONCLUSION The combination of constructivist and online learning models has great potential to inform outcomes for teacher learning and knowledge transfer to the classroom. Additionally, we recommend examining the actual methods and time it takes to develop collaborative community, or community of practice online, including assessment of depth of social presence Evaluating the construction of knowledge utilizing technology requires a multi- dimensional modeling approach. The comparative analysis in these hybrid course designs focused on the online environment with teacher-student participants who are constructing meaning for learning methods to incorporate technology into their own curricula. This layered construct is also thought to be fluid with continuous looping through elements of the learning environment. For example, the teacherlearner, while participating in the online discourse, may be either reflecting on a prior classroom teaching experience and/or imagining a different lesson with some technology enhancement or vehemently rejecting it’s relevance. In any case, the teacher-learner in the online discussions, for the purposes of this evaluation, is understood to be taking some course content and collaborating, creating meaning with fellow colleagues while collecting, organizing, summarizing, analyzing, and synthesizing information. All of which will lead the teacher-learners themselves to some decision-making and knowledge about the educational experience they will construct for their students. What evidence can online discourses provide for illuminating the signaling for transfer to the teacher-learners own pedagogy?

FUTURE WORK Giving teacher-learners experiences online increases their confidence and directly exposes

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

them to collaborative learning from their peers and instructors. There is further need to examine ways to deepen learners’ social and cognitive presence as well as their interactions with the instructor in the online environment that can enhance the use of technology in actual classroom activities. As engagement and technology awareness increases, the teacher-learners become more effective in the planning of curricula using technology for their own students. These are all intrinsic factors which will influence their success regardless of their access to resources, time availability and other extrinsic factors which they cannot control. After careful analysis there were several categories that might be included in a future evaluative study; “Generative” wherein students generated new ideas, proposed other links to materials, posed questions and constructed new knowledge. The other category was “Clarification” where students were asking for clarification of ideas, assignments and collaborations. As in most research endeavors new questions emerged from the process: Include the examination of final projects as part of the assessment of technology transfer and enculturation to the teaching praxis? Would these projects reveal some level of transfer from the online environment to use of technology in actual classrooms? How do we create more generative postings, whereby the students construct their own meaning? How do course instructors facilitate to deepen social presence online? What is the role of scaffold instruction and when should the instructor fade? One goal would be to build on the evidence for teacher-learners’ use of the online discourse in making meaning for the transfer of technology to their teaching in their classrooms through better-informed curricula design and pedagogical methods in the construction of technology learning environments for teachers’ education. This present study illustrates how a closer examination of student online data can help to inform online curriculum, teaching practices and effective learning in a blended course environ-

ment for teacher-students to increase technology enriched curricula transfer to their classroom praxis. With this data and results, a new model for assessing online learning may emerge to help construct the most meaningful online experience for teacher-learners. Perhaps it is more than just taking the Community of Practice Model one step further to include technology awareness. Any new paradigm would need to embrace a more multifaceted scope to outline the intersecting layers and levels of ‘social’ presence and their implications for the actual inquiry outcomes.

REFERENCES Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing environment. Journal of Asynchronous Learning Networks, 5(2). Angers, J., & Machtmes, K. (2005). An Ethnographic-Case Study of Beliefs, Context Factors, and Practices of Teachers Integrating Technology. Qualitative Report, 10(4), 771–794. Ausbel, D. (1963). The psychology of meaningful learning. New York: Grune & Stratton. Borko, H. (2004). Professional Development and Teacher Learning: Mapping the terrain. Educational Researcher, 33(8), 3–15. doi:10.3102/0013189X033008003 Brown, J., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Research, 18, 32–42. Ertmer, P., Ottenbreti-Leftwich, A., & York, C. (2006-07). Exemplary Technology - using Teachers: Perceptions of Factors Influencing Success. Journal of Computing Education, 23(2), 55–61. Garrison, D. R., & Anderson, T. (2003). [st Century: A framework for research and practice. London: RoutledgerFalmer.]. E-learning, 21.

171

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Garrison, R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(3), 87–105. doi:10.1016/S1096-7516(00)00016-6

Office of Technology Assessment. U.S. Congress. (1995). Teachers and technology: Making the connection. OTA report summary. Washington, DC: Government Printing Office. (ERIC Document Reproduction Service No. ED 386 154)

Ginsburg, L. (1998). Integrating technology into adult learning. In C. Hopey (Ed.), Technology, basic skills, and adult education: Getting ready and moving forward (Information Series No. 372, pp. 37-45). Columbus, OH: Center on Education and Training for Employment. (ERIC Document Reproduction Service No. ED 423 420)

Qi, J., & Vandersall, K. (2007). Facilitating reflective practice for pre-service teachers through electronic portfolio development. In C. Crawford et al. (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference 2007 (pp. 2609-2616). Chesapeake, VA: AACE.

Herrington, A., Herrington, J., Kervin, L., & Ferry, B. (2006). The design of an online community of practice for beginning teachers. Contemporary Issues in Teacher Education, 6(1). http://www. citejournal.org/ vol6/ iss1/general/aricle1.cfm

Resnick, L. (1987). Education and learning to think. Washington, DC: National Academy Press.

Joia, L. (2001). Evaluation of a Hybrid SocioConstructivist Model for Teacher Training. [Norfolk, VA: AACE.]. Journal of Technology and Teacher Education, 9(4), 519–549. Kotrlik, J., & Redmann, D. (2005). Extent of technology integration in instruction by adult basic education teachers. Adult Education Quarterly, 55(3), 200–219. doi:10.1177/0741713605274630 Kozleski, E. (2004, August). Technology Transfer and the Field of Education. Comparative Technology Transfer and Society, 2(2), 176–194. doi:10.1353/ctt.2004.0017 McCrory, R., Putnam, R., & Jansen, A. (2008). Interaction in Online Courses for Teacher Education: Subject Matter and Pedagogy. [Chesapeake, VA: AACE.]. Journal of Technology and Teacher Education, 16(2), 155–180. Miles, M., & Huberman, A. M. (2004). Qualitative Data Analysis. Thousand Oaks, CA: Sage Publications.

172

Rouke, L., Anderson, T., Garrison, D. R., & Archer, W. (2001). Assessing Social Presence in Asynchronous Text-based Computer Conferencing. Journal of Distance Education, http://cade.athabascau. ca/vol14.2 /rouke_et_al.html. Retreived 6/28/08. Steinbronn, P., & Merideth, E. (2008, March). Perceived Utility of Methods and Instructional Strategies Used in Online and Face-to-face Teaching Environments. Innovative Higher Education, 265(14). Stephenson, J. (Ed.). (2002). Teaching & Learning Online: Pedagogies for new technologies. VA: Stylus Publishing. Swan, K. (2004). Relationships Between Interactions and Learning . In Online Environments. The Sloan Consortium, Sloan-C. Tallent-Runnells, M., Thompsons, J., Lan, Y., & Cooper, S. (2006, Spring). Teaching courses online: A review of the research. Review of Educational Research, 76, 93–135. doi:10.3102/00346543076001093 Wakefield, J. (1996). Educational Psychology: Learning to be a problem-solver. Boston: Houghton Mifflin.

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

APPENDIX A Table 1. CS/MD 475 Empowering computers for best educational practices Spring 2003 Hits

Read

Posted

Student 1

417

168

33

Student 2

369

133

38

Student 3

331

138

35

Student 4

307

168

26

Student 5

364

110

25

Totals

1788

717

157

Requirements for online participation: On-line contribution 120 (possible 10 each week) No timing for postings, no requirement for number or amount of participation.

Table 2. CS/MD 475 Empowering computers for best educational practices Summer 2004 Hits

Read

Posted

Student 1

82

52

4

Student 2

107

70

1

Student 3

145

85

10

Student 4

104

41

7

Student 5

163

98

12

Student 6

105

27

5

Student 7

54

27

3

Student 8

142

71

23

Student 9

229

83

4

Student 10

162

63

7

Student 11

161

51

5

Student 12

126

34

5

Student 13

190

87

6

Student 14

198

99

5

Totals

1968

888

97

Course requirements for online participation: On-line weekly contribution 80 (possible 20 pts/@wk post by Sunday)

173

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Table 3. CS/MD 475 Empowering computers for best educational practices Summer 2005 User ID

Hits

Read

Posted

Student 1

128

42

11

Student 2

71

34

2

Student 3

139

67

13

Student 4

181

65

10

Student 5

183

67

5

Student 6

51

24

2

Student 7

211

67

11

Student 8

196

66

4

Totals

1160

432

58

Course requirements for online participation: On-line weekly contribution 80 (possible 20 pts/@wk post by Sunday)

Table 4. CS/MD490 Achieving an interdisciplinary approach to teaching through technology Fall 2003 User ID

Hits

Read

Posted

Student 1

154

83

12

Student 2

68

27

11

Student 3

158

82

15

Student 4

54

30

2

Student 5

146

51

11

Student 6

68

26

6

Student 7

184

82

12

Totals

832

381

69

Course requirements for online participation: On-line contribution 120 (possible 10 @ week)

Table 5. CS/MD490 achieving an interdisciplinary approach to teaching through technology Fall 2005 User ID

Hits

Read

Posted

Student 1

488

279

30

Student 2

149

88

14

Student 3

672

279

55

Student 4

516

314

32

Student 5

331

177

25

Student 6

491

244

23

Student 7

629

322

42

Student 8

128

38

1

Student 9

474

250

71

Student 10

699

291

18

Totals

4577

2282

311

Course requirements for online participation: On-line contribution 120 (possible 10 @ week) participate in on-line discussion group, due Tuesday by midnight.

174

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Table 6. CS/MD490 Achieving an interdisciplinary approach to teaching through technology Fall 2006 Student 1

Hits

Read

Posted

926

241

35

Student 2

399

237

24

Student 3

305

146

19

Student 4

447

224

17

Student 5

696

240

19

Student 6

446

224

32

Student 7

229

141

22

Student 8

261

145

15

Student 9

278

154

31

Student 10

928

224

20

Totals

4915

1976

234

Course requirements for online participation: On-line contribution 120 (possible 10 @ week) participate in on-line discussion group, due Tuesday by midnight.

Table 7. ED/MD 546 integrating the arts, music and technology into the K-12 curriculum Spring 06 Hits

Read

Posted

Student 1

165

116

15

Student 2

38

30

1

Student 3

63

36

16

35

0

Student 4

71

53

10

Student 5

190

90

11

Student 6

176

116

7

Student 7

180

120

18

Totals

883

596

78

Requirements for online participation: On-line contribution Total 78 postings At least 8 postings for the semester, weekly reading of online postings. No timing for postings. Observed large discrepancies between hits, read and actual posting

175

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Table 8. MD 400-01 Introduction to educational technology Spring 06 Hits

Read

Posted

Student 1

272

231

14

Student 2

73

55

1

Student 3

528

368

17

Student 4

532

374

17

Student 5

334

251

15

Student 6

475

374

18

Student 7

416

338

18

Student 8

397

304

13

Student 9

564

375

25

Student 10

321

237

16

Student 11

388

307

23

Student 12

555

387

27

Student 13

296

175

20

Student 14

573

333

25

Student 15

296

175

20

Student 16

536

373

19

Student 17

347

277

21

Student 18

374

304

10

Totals

7277

5274

312

Course requirements for online participation: On-line contribution Postings A minimum of 8 postings, weekly reading of online postings Professor followed closely, especially for students who not participating regularly Large discrepancies between hits, read and actual postings One student did not meet required postings

176

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Table 9. ED/MD 400-02 introduction to educational technology Spring 2006 Student 1

Hits

Read

Posted

0

0

0

Student 2

266

215

4

Student 3

218

140

13

Student 4

294

107

17

Student 5

289

189

14

Student 6

301

209

5

Student 7

202

89

15

Student 8

36

16

1

Student 9

409

239

15

Student 10

324

144

6

Student 11

337

150

14

Student 12

300

211

15

Student 12

364

239

15

Student 13

286

153

10

Student 14

120

47

9

Student 15

357

226

15

Student 16

167

103

9

Student 17

236

199

15

Student 18

215

143

10

Totals

4721

2189

202

Requirements for online participation: On-line contribution 202 Postings 8 Postings for the semester, weekly reading of the online postings No time requirement, but professor followed up regularly, especially students who were not participating enough. Large discrepancies between hits, read, and actual postings. Four students did not meet required postings.

177

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

APPENDIX B Table 10. Hybrid model template for assessment of technology enculturation in teacher-student learning Category

Formative Assessment

Knowledge Transfer

Indicators

Evaluation

Finding Example

Expression of prior learning, understanding of uses for technology in education

Stated previous use and/or learning of technology

When asked online by the instructor about their impressions for a curricula proposed in the text teacher-students responded with specific reference to the pieces they liked and disliked as they related to their teaching demographics e.g., “As a middle school teacher I have a hard time agreeing this strategy would be effective for a young teenage mind”

Comments situated in current classroom teaching praxis

Presents details of classroom teaching/learning prior to course experience

“Since my teaching career started 3 years ago I have been offered little training regarding using new technologies.”

Expression of new understanding for use of technology in teaching

Comments suggesting meaning being made from course materials

“I enjoyed the first chapter of the textbook. The ideas were great ones but I was a bit curious as to how we can implement these ideas.”

Comments suggesting meaning being made from peer-to peer online

“I’m not all together sure whether to accept (so & so’s) approach to student problem solving ……..It seems very laissez-faire and doesn’t give much guidance to the student. I was curious ….,

Comments suggesting meaning being made from instructor to teacherstudent online

I went online to find more information about (so & so) and found some (so & so) Unit plans that could probably be applied to any subject. (gives url reference) By seeing it in context it gave me a better understanding of the process of (so & so)…”

Comments suggesting meaning being made from course materials

“I went on the TEA website to see how their long range plan was going, and I was impressed to see that they have been modifying it as needed. I think part of being successful with technology is being flexible.”

Comments suggesting meaning being made from peer-to peer online

“Regarding the statement “purposes and plans are those of the learners” I think we can take this to mean that we need to consider what the learner needs to take away from the lesson, rather than just putting a lesson out there. If one reads Kilpatrick’s words another way, they can be taken to mean that educators must take into consideration the needs and interests of the learners and adapt the lessons accordingly. Does anyone else agree (or disagree) with (so & so) philosophies?”

Expression of new understanding for use of technology for student learning

continued on following page

178

An Evaluation of Blending Technology with Pedagogy for Teaching Educators

Table 10. continued

Summative Assessment

Critical thinking

Comments suggesting meaning being made from instructor to teacherstudent online

When instructor asked about, ‘ the impact of Computers in the efforts toward Social Equity?’….teacher student responded with a question that challenged the premise of the instructor’s question-“Do you think it is true that technology has had an effect on “civic agenda”, “addressing equality” and creating desire for more education?”

Offers new perception of technology and uses for classroom pedagogy

I do agree with his statement, “we learn what we live.” Rather than endorsing a laissex-faire attitude for the educator I think it puts more of an onus on the educator to connect the learning to the students’ lives. In essence, this is what we have been discussing, to create context for students to help them apply what they are learning.”

Offers different view of technological mechanisms and uses for student learning

One student who was traveling and missed the in-class session contributes on line – “In the spirit of best educational practices, the aesthetic concept is doomed if educational technology is infused with an “on task”, asynchronous point of view. Allowing for innovation, collaboration and creative thinking will lead to new and exciting uses of educational technologies. If that happens, then many new examples of best educational practices will begin to emerge.”

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 61-79, copyright 2009 by Information Science Reference (an imprint of IGI Global)

179

Section 3

181

Chapter 10

Redefining Web Users’ Optimal Flow Experiences In Online Environments: An Empirical Analysis Anshu Saxena Arora Savannah State University-Savannah, USA Mahesh S. Raisinghani TWU School of Management, USA

ABSTRACT The chapter highlights a research study on consumer navigation behavior through the Web users’ optimal Flow experiences in the online environments. The research study establishes the empirical groundwork for measuring Web users’ Flow experiences in the Web environment. The chapter proposes a comprehensive definition of Flow on the basis of Comprehensive Process (Flow) Model of Network Navigation, considering that the Flow concept is a multidimensional concept in the “multi-activity” medium of the Web. Flow has been defined as a multi-dimensional and context-specific concept. Furthermore, the research chapter proposes that there are 10 Flow constructs (also called “the antecedents of Flow”) along with the three states of Flow, namely, Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow. Consumer Behavior on the Web is studied using the Flow concept for three categories of Flow users, namely, Perfect and Imperfect-Intensive Flow (PIIF) users, Imperfect Flow (IF) users, and Non-Flow (NF) users. These users achieve Flow depending on 10 Flow-constructs and three Flow states. Empirical results suggest a direct relationship between the Flow states and the Flow user categories and between expected Web user in the future (EXPUSE) and the Flow user categories. This research study provides a basis for future researchers to study consumer navigation behavior on the Web using the Flow concept for three categories of Flow users through 10 Flow constructs and three Flow states. The research has significant implications for theory and practice. DOI: 10.4018/978-1-60960-153-9.ch010 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Redefining Web Users’ Optimal Flow Experiences In Online Environments

THE FLOW CONCEPT IN THE “MULTI-ACTIVITY” MEDIUM OF THE WEB The idea of Flow was conceptualized by Csikszentmihalyi (1977, p. 36), who defined “Flow” as “the holistic sensation that people feel when they act with total involvement.” Researchers have suggested that Flow can be used to study consumer behavior on the Web, especially the way consumer perceives the Web environment and engages himself/herself in the process of network navigation, and that the Web is an activity that can facilitate the occurrence of Flow (Chen, Wigand, & Nilan, 1998; Hoffman & Novak, 1996; Novak, Hoffman, & Yung, 1998). By definition, Flow is a psychological state in which an individual feels cognitively efficient, motivated, and happy (Moneta & Csikszentmihalyi, 1996, p. 277). When in the Flow state, people become absorbed in their activities, while irrelevant thoughts and perceptions are screened out. If Flow were absent in humans’ experience, “there would be little purpose in living” (Csikszentmihalyi, 1982, p. 13). Saxena, Kothari, Jain, and Khurana (2003) demonstrated Flow as a combination of hypertext, telepresence, machine interactivity and time distortion. In terms of consumer navigation behavior or analyzing the buying patterns of consumers on the Web, the principle of “duplication” results in repeat visits to the Web environment and hence, repeat consumption behavior (RCB). This has a direct impact on expected Web use in the future (EXPUSE). This research study aims to analyze “Flow” in the online environments and presents “Flow” as a context-specific concept with multiple Flow states (and not a single Flow state, as described by previous researchers) within the multi-activity medium of communication of the Web. The objective of redefining Flow is two-fold: 1) to establish and develop a conceptual framework (Comprehensive Process Model of Network Navigation) for the understanding of Consumer Navigation

182

Behavior (CNB) in online environments, and 2) to measure Flow on the basis of the Flow constructs and Web use variables derived from the Comprehensive Flow Model of Network Navigation for investigating CNB in online environments. Flow should be considered as a complex multidimensional context-specific concept, characterized by relationships among a large set of unidimensional constructs of Flow. Also, the Flow constructs can be neatly categorized into sets of antecedents and consequences of Flow.

OPTIMAL FLOW EXPERIENCE Flow is defined as the congruence of high skills and high challenges of the users above a critical threshold level (Csikszentmihalyi & Csikszentmihalyi, 1988), and the rationality behind the concept of “multi-activity” applies to the dynamic perceptions of challenges perceived in a given situation and the skills a person brings to it. Web as a multi-activity medium of communication was established by Chen et al. (1998). In addition to the concept of “multi-activity” for Flow concept, there is a need to address the problem of conflict between generic and context specific Web Flow. All the researches in the area of Web Flow demonstrates Flow as a concept occurring during network navigation where the person is engrossed in the process of navigating the Web or the mediated perception of the environment called “telepresence” (Steuer, 1992) rather than being present in his / her physical world of tensions, anxieties and frustrations. Hence, network navigation becomes an intrinsically enjoyable and self-reinforcing source of mental relaxation accompanied by the loss of self-consciousness and characterized by a seamless sequence of responses facilitated by machine interactivity (Hoffman & Novak, 1996). Thus, previous research has defined Flow as a generic concept rather than a context specific one. There is no clarity whether e-mail, Internet chat sessions, or Web conferencing are

Redefining Web Users’ Optimal Flow Experiences In Online Environments

the Flow activities or whether using Web for a specific purpose of searching information for business or educational purposes are the activities that result in Flow. This problem or dispute area of the conflict between generic and context specific Flow is addressed in this empirical study and the Flow activities are categorized as high-Flow and low-Flow activities resulting in a context specific nature of Flow rather than a generic one as described in the previous research. Next we define the Flow states Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow and discuss the comprehensive process model of network navigation.

COMPREHENSIVE PROCESS MODEL OF NETWORK NAVIGATION Hoffman and Novak (1996) proposed that creating a commercially compelling Web site depends on facilitating a state of flow (Csikszentmihalyi, 1977) for its consumers, and suggest that an important objective for online marketers is to provide for these “flow opportunities” (Hoffman & Novak, 1996, p. 66). Previous researchers (e.g., Csikszentmihalyi, 1990; Ghani, Supnick, & Rooney, 1991; Trevino & Webster, 1992; Webster, Trevino, & Ryan, 1993) had noted that flow is a useful construct for describing more general humancomputer interactions. Hoffman and Novak (1996) provided, but did not empirically test, a conceptual model of flow that detailed its antecedents and consequences. A general conceptual model of flow in interactive computer-mediated environments (CME) is described in detail in Hoffman and Novak (1996). Their model contained skill, challenge, arousal, control, focused attention, interactive speed, importance, telepresence, and time distortion as Flow-antecedents; and Positive affect and exploratory behavior as Flow-consequences. A later empirical study by Novak, Hoffman, and Yung (2000) added a few Flow constructs—Web navigational importance, enduring involvement and optimum stimulation level (OSL), and Web

use variables. Also, the study emphasized on “Playfulness” as an indicator of Flow. However, all these researches described Flow as a singular mental or cognitive state happening due to the Flow-antecedents or Flow-constructs. In our comprehensive model, we will define Flow not as a singular state but as multiple states, depending on human behavior. Furthermore, we will explore the consequences of Flow as both positive (increased learning, expected Web use) and negative consequences (physical and cognitive fatigue, health of the user, and negligence of alternative work). Past researchers have not focused on the negative consequences of Flow. Considering the shortcomings of the Flow theories, Figure 1 illustrates the comprehensive process model of network navigation that overcomes the limitations of the past work where Flow is considered to be unidirectional. Flow is defined to be a multi-dimensional state in a multi-activity medium of the Web characterized by 10 Flow-constructs, three Web use variables, and 10 Flow states. There are various states of Web Flow, that is, Perfect and Imperfect Flow states. Perfect Flow is defined as a state occurring during network navigation which is characterized by a seamless sequence of responses facilitated by machine interactivity, loss of self-consciousness, which is self-reinforcing and carries on forever with no time dimension, as defined by Hoffman and Novak (1996). Such a state where “nothing else seems to matter,” is called Perfect State of Flow. Perfect Flow is thus described as a process of optimal experience that is practically impossible to attain, unachievable due to psychological reasons inherent to an individual’s psyche wherein external, uncontrollable environmental factors play a distinct role in destroying the occurrence of Perfect Flow. From a pragmatic perspective, the Imperfect Flow is an achievable and practical state of Flow that is: a) intrinsically enjoyable; b) self-reinforcing; c) facilitated by machine interactivity; d) a state where “nothing else seems to

183

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Figure 1. Comprehensive process model of network navigation

matter”; and e) has time dimension limits and carries on for a specified time interval known to an individual. Consumer Segments - Adventurers and Wanderers (Kothari, Jain, Khurana, & Saxena, 2001) experience Perfect Flow for Experiential Web activities while Expert and Investigators (Kothari et al., 2001) experience Imperfect Flow for GoalDirected or task oriented Web activities. Hoffman and Novak (1996) describe the difference between experiential and goal-directed activities in detail. On the basis of consumer segments, one can also distinguish between high-Flow and low-Flow segments or activities. The interesting discovery is that both perfect and imperfect Flow states result in EXPUSE,

184

which means, the expected Web use in the future. Both of them result in repeat visits to the Web, also known as Repeat Consumption Behavior (RCB), though the procedures and motives are entirely different in both cases. Therefore, this would lead to the following research proposition and hypothesis: Consumers attaining Perfect and Imperfect Flow will have repeat consumption behavior (RCB) and expected Web use in future (EXPUSE) while those consumers who do not attain flow will not experience RCB / EXPUSE. The above research proposition is on the basis of differential Flow states. Consumers mov-

Redefining Web Users’ Optimal Flow Experiences In Online Environments

ing from Imperfect Flow to Perfect Flow will experience an intermediary state of Flow called “Imperfect-Intensive Flow,” which is defined as “the process of optimal experience, which is achievable with time limits.” This state occurs when an individual moves from Imperfect to Perfect Flow State. For instance, John, a working executive in a multinational company knows that he has just one hour of lunch time where he can use the Internet for fun activities on the Web and engages himself on a virtual joy-ride of a car company’s Website dealing with different models of cars. While he is enjoying his Flow state, he is also keeping a tab on time by using a watch buzzer that buzzes exactly after an hour. While he is in the process of losing self-consciousness and forgetting his mental tensions, frustrations and worries, he rejoins the real world after an hour with the sound of buzzer. This means that for an hour, he was in a Perfect Flow state but returns to Imperfect Flow state after an hour with the sound of buzzer (external stimulus). Similarly, there can be various examples illustrating these Flow states. Whether an individual achieves Perfect Flow state first or Imperfect Flow state first, or he moves from Perfect to Imperfect Flow as follows: Perfect Flow → Imperfect-Intensive Flow → Imperfect Flow or vice versa as: Imperfect Flow → Imperfect-Intensive Flow → Perfect Flow This varies from individual to individual, as human behaviors are basically unpredictable. This is one area that needs to be further explored and researched. Figure 1 illustrates Comprehensive Process Model of Network Navigation along with Flow-constructs and Flow-states.

THE FLOW CONCEPT: FLOW CONSTRUCTS AND FLOW STATES According to our Comprehensive Model of Network Navigation, Flow is defined as a multidimensional, context-specific state of mind that consists of directed relationships among a set of 10 uni-dimensional constructs and three key Web use variables (see Figure 1) and has both positive consequences (e.g., increased learning, exploratory behavior, perceived behavioral control, and positive subjective experience) and negative consequences (e.g., physical and cognitive fatigue, time distortion, and negligence of alternative work). In Figure 1, Flow has further been defined in terms of an indicator called “Playfulness.” Playfulness refers to the level of imagination, invention, experimentation, originality, discovery, creativity, spontaneity, and flexibility (leading to playfulness of user’s attitude) of the user during the Web navigation. All these attributes contribute to Flow. Past researches have not defined the Flow-constructs and Web use variables. We will define them for simplicity and ease of use. The definitions of Flow constructs and Web use variables shown in Figure 1 are as follows: 1. Skills: “Skills” is defined as the level of knowledge and understanding on the part of the user. It broadly refers to the area of user’s skills and ability to comprehend the information available on the Web. 2. Challenges: “Challenges” refers to the information provided by Web use. During Web navigation, the user comes across various challenges in the form of information available to him or her through the Web sites. 3. Interactive Speed: This refers to the level of interaction of the Web sites and the speed of downloads during the Web navigation. 4. Enduring Involvement: This refers to level of involvement of the user with the Web. It also shows the level of importance of the

185

Redefining Web Users’ Optimal Flow Experiences In Online Environments

5.

6.

7.

8.

9.

10.

Web to the user. “Enduring” refers to degree of usefulness, importance, and strength (longevity) of the Web use. Control: “Control” refers to the extent by which the Web controls the user actions. Even the vice-versa is also true. It also refers to the extent by which the user controls the Web. This depends on the user’s skills and the challenges provided by the Web environment. Arousal: “Arousal” refers to the degree and extent of user’s excitement leading to the stimulation of user’s emotions while using the Web. Telepresence: This refers to the strength of the Web environment, often referred to as “COMPUTER WORLD” whereby user forgets about his/her own physical environment and surroundings during the Web navigation. Focussed Attention: This refers to the user’s level of attention to the Web contents of the Web sites during the Web navigation. Optimum Stimulation Level (OSL): This refers to the optimum/threshold level of stimulation and excitement that is “just right” to attract the user’s attention during Web navigation. Web Navigational Importance: This refers to the importance of the Web and its activities to the user during network navigation.

DEFINITION OF WEB USE VARIABLES 1. Log-in duration: This refers to the total time duration of the network navigation, from the time the user logs on to the Web until the time he or she exits the Web navigation experience completely. 2. PC Vintage: PC Vintage means that the recent or new Personal Computers have better speeds and precision than the initial ones. Pentium IV is faster than Pentium III,

186

Pentium III is faster than Pentium II, and Pentium II is faster than Pentium I and so on. This means that the speed of downloads depend on the PC Vintage and Consumer Navigation Behavior (CNB) depends on the speed of downloads. Hence, CNB depends on the PC Vintage. The more the speed, the more will be the CNB and the better will be the process of optimal experience or Flow. 3. EXPUSE: This refers to the expected Web use in the future on the basis of users’ experience, understanding, use, and utilization of the Web navigation.

We believe that the three states of Flow—Perfect Flow, Imperfect Flow and Imperfect Intensive Flow—have a direct relationship with EXPUSE and repeat consumption behavior (RCB). This means that the respondents who experience Perfect Flow will exhibit different behavior for expected Web use in the future and repeat visits to the Web (EXPUSE and RCB) from the respondents who experience Imperfect-Intensive Flow and Imperfect Flow exhibit EXPUSE and RCB. This needs to be further established during empirical investigation on Flow.

FLOW STATES AND USER CATEGORIES: RESEARCH ON FLOW Flow has been defined as a multi-dimensional, context specific concept with three Flow states— Perfect Flow, Imperfect Flow, and ImperfectIntensive Flow. On the basis of the Comprehensive Process Model of Network Navigation, illustrated in Figure 1, a Flow questionnaire (Appendix A) is developed. The questions are referenced for 10 antecedents of Flow shown in Figure 1, namely, Skill, Challenge, Focussed Attention, Enduring Involvement, Interactive Speed, Control, Tele-

Redefining Web Users’ Optimal Flow Experiences In Online Environments

presence, Optimum Stimulation Level (OSL), Arousal, Web Navigational Importance. Appendix A shows 63 Flow questions of the questionnaire representing 10 antecedents or constructs of Flow. A likert scale of 1 to 7 has been used where 1 indicates “Strongly Disagree” and 7 represents “Strongly Agree.” A sample of 50 respondents was taken randomly and they were administered the questionnaire. The research study is confined to the regular Internet users primarily located in the national capital territory (NCT) of Delhi, India. According to a research study by the Gartner Group, a regular Internet user is one who accesses the Internet for 5 hours per week. The Web site awareness, perceptions, and preferences of the regular Internet users are considered, as they are generally aware of more Websites. The sample consists of healthy mix of regular Indian Internet users comprising 19 Masters of Business Administration graduates (MBAs), 10 doctorates (PhDs), 10 academicians, and 11 managers working in the private sector firms in the automobiles, airlines, and information technology fields. Flow concept was explained to these fifty valid respondents in a classroom environment without any bias to the questions given in the questionnaire. This was important so that they can relate to the Web world in a better way and may give a correct perception of their feelings during network navigation in the online environments. The questionnaire would help in interpretation of Flow Achievement in terms of “Expected Web use in the future” (EXPUSE) and “Repeat Consumption Behavior” (RCB) by three user categories of Flow—Perfect to Imperfect-Intensive Flow (PIIF) user, Imperfect Flow (IF) user, and Non Flow (NF) user. The user categories are required for exploration of three Flow states proposed by authors. These three user categories of Flow exist on the basis of three Flow states already discussed in previous sections as Perfect Flow, Imperfect Flow and Imperfect-Intensive

Flow. The user category of Perfect to ImperfectIntensive Flow represents a mix of two states, that is, Perfect and Imperfect-Intensive Flow (PIIF), that are combined to show that the PIIF user achieves highest degree of Flow with relatively less time distortion and maximum playfulness, and hence, maximum loss of self consciousness during Web navigation. On the other hand, Flow achievement level is relatively less for Imperfect Flow (IF) user as this user is quite conscious of his environment, his alternate work and visits Web for fun, enjoyment, learning or other goal-directed activities and leave Web after a stipulated pre-determined time period with time distortion related to an individual’s demands and needs. For the last category of Non-Flow (NF) user, the time distortion is maximum as he or she is unable to enjoy the Web navigation or engross himself/herself in the Web navigational process, even though the user may be surfing the Web for some period. PIIF and IF users experience Playfulness during Web navigation, whereas NF users do not experience any fun or play during Web navigation. The above mentioned categories of Flow achieve Flow as “Playfulness” where Play is an indicator of the individual’s 10 antecedents of Flow, namely, Skill, Challenge, Focussed Attention, Enduring Involvement, Interactive Speed, Control, Telepresence, Optimum Stimulation Level (OSL), Arousal, and Web Navigational Importance. Hence for any user—PIIF, IF, or NF—the 10 antecedents of Flow will exist. The decision tree illustrated in Figure 2 shows the final result/outcome. The values and probabilities in Figure 2 are derived from respondents’ responses to the 63 questions which have been tabulated as a likert scale indicator ranging from 1 to 7 where 1 means “Strongly Disagree” with the question and 7 means “Strongly Agree” to the question. The Palisade Decision Tools software suite was used for decision and sensitivity analyses of the responses since we can explicitly include the uncertainty present in our estimates to generate

187

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Figure 2. Decision tree representing flow achievement by different user categories

188

Redefining Web Users’ Optimal Flow Experiences In Online Environments

results that show all possible outcomes using both Monte Carlo and Latin Hypercube simulation sampling techniques. This tool allowed us to combine all the uncertainties identified in our model and include all we know about the variable, including its full range of possible values and some measure of the likelihood of occurrence for each possible value, to analyze every possible outcome. Using @Risk software from Palisade DecisionTools Suite, the data distribution details have been obtained for 10 antecedents of Flow and illustrated in Table 1. From the questionnaire (see Appendix A), it was found that on an average basis, PIIF user navigates the Web for approximately 30 hours per week while IF user uses Web for 20 hours per week and NF user navigates Web for 10 hours per week. Table 1 shows the distribution details of 10 Flow antecedents/constructs on the basis of the responses obtained from 50 respondents on 63 questions of the questionnaire in Appendix A. These 63 Flow questions reflect the 10 Flow constructs/antecedents and clearly outline a respondent’s indulgence in these 10 Flow-constructs respectively. Also, a lecture model session on the Flow concept was arranged and imparted to the 50 respondents before filling the questionnaire. Hence, it was easier for them to categorize themselves as PIIF, IF, and NF users, respectively. For the purpose of data analyses of 50 respondents’ questionnaires, it was found that PIIF user’s response on a positive statement (all 63 questions of the questionnaire of Appendix A are “statements”) of the questionnaire lies anywhere between 6 and 7 (including both 6 and 7) of the likert scale, indicating the highest agreement with the positive statement and hence, highest Flow achievement. Also, it was further assumed that a NF user’s response for any positive statement lies between 1 and 3 (including both 1 and 3) of the likert scale, indicating the lowest possible agreement with the positive statement and hence, lowest (or nil) Flow achievement. Intermediate

vales of 4 to 6 (including 4 and excluding 6) of the likert scale shows Imperfect Flow achievement for IF users. Appendix B illustrates the validity of the data based on the Chi-Squared, Anderson Darling, and the Kolmogorov-Smirnov statistics. On the basis of data obtained from the sample through the questionnaire, it was found that Flow is achieved differently for different user categories. Table 2 depicts the percentage of the time, Flow is achieved for PIIF, IF and NF users respectively vis-à-vis the 10 antecedents/constructs of Flow. As mentioned earlier, on an average basis, PIIF users log-in to the Web for about 30 hours per week, IF users navigate for 20 hours per week, and NF users use the Web for 10 hours per week. On the basis of this assumption, Table 3 indicates the time spent by three user categories for different Flow antecedents. There will be overlaps in the achievement of Flow constructs by users as we are indulging into fuzzy consumer navigation behavior on the Web. A respondent may experience a combination of skill, enduring involvement, control, arousal, and focused attention during Web navigation. The combinations of the 10 Flow constructs achievement by different respondents will be different from one and another. This is evident in Table 3. Using the Tables 2 and 3, the values are used as inputs into the decision tree structure to find out the favourable outcomes and also the EXPUSE and RCB in the future. Figure 2 shows the decision tree output using the PrecisionTree software. From Figure 2, it is found that EXPUSE for PIIF is 23.43 hours, EXPUSE for IF user is 12.32 hours, and EXPUSE for NF user is the minimum at 6.51 hours. When computing the maximum Flow achieved by PIIF category of user, the dependence of Flow on time spent during Web navigation was evaluated and a sensitivity analysis was performed. The same analyses were performed for IF and NF users as well. Figure 3 shows various graphs of sensitivity analyses of Flow by different user categories. Login Perfect User represents the log-in time by

189

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Table 1. Data distribution details using @Risk for 10 antecedents of Flow Values (from 50 respondents on a likert scale of 1 to 7 using @ Risk output of @Risk software)

Data Distribution Assessment using @Risk software

Skill

3.99

Uniform Distribution with minimum of 0.87755, maximum of 7.1224, Mean = 3.999, Std Deviation = 1.8027, total values lying between 1.0000 to 7.0000 = 96.1%, Outliers outside the range of 1 to 7 are 100-96.1 = 3.9%

Challenge

1.45

Beta General Distribution with minimum of 1.0000, maximum of 2.0000, Mean = 1.4488, Std Deviation = 0.45181, total values lying between 1.0000 to 7.0000 = 90%, Outliers outside the range of 1 to 7 are 100-90 = 10%

Focussed Attention

5.03

External Value Distribution with minimum of -Infinity, maximum of +Infinity, Mean = 5.0277, Std Deviation = 1.6245, total values lying between 1.0000 to 7.0000 = 88.6%, Outliers outside the range of 1 to 7 are 100-88.6 = 11.4%

4.04

Beta General Distribution with minimum of 2.0000, maximum of 7.0000, Mean = 4.0401, Std Deviation = 1.9556, total values lying between 1.0000 to 7.0000 = 90%, Outliers outside the range of 1 to 7 are 100-90 = 10%

3.99

Uniform Distribution with minimum of 0.87755, maximum of 7.1224, Mean = 3.999, Std Deviation = 1.8027, total values lying between 1.0000 to 7.0000 = 96.1%, Outliers outside the range of 1 to 7 are 100-96.1 = 3.9%

6.5

Beta General Distribution with minimum of 6.0000, maximum of 7.0000, Mean = 6.5000, Std Deviation = 0.45496, total values lying between 1.0000 to 7.0000 = 90%, Outliers outside the range of 1 to 7 are 100-90 = 10%

Telepresence

3.99

Uniform Distribution with minimum of 0.87755, maximum of 7.1224, Mean = 3.999, Std Deviation = 1.8027, total values lying between 1.0000 to 7.0000 = 96.1%, Outliers outside the range of 1 to 7 are 100-96.1 = 3.9%

Optimum Stimulation Level (OSL)

3.39

Beta General Distribution with minimum of 3.0000, maximum of 4.0000, Mean = 3.3941, Std Deviation = 0.44138, total values lying between 1.0000 to 7.0000 = 90%, Outliers outside the range of 1 to 7 are 100-90 = 10%

Arousal

4.47

Beta General Distribution with minimum of 4.0000, maximum of 5.0000, Mean = 4.4797, Std Deviation = 0.45447, total values lying between 1.0000 to 7.0000 = 90%, Outliers outside the range of 1 to 7 are 100-90 = 10%

3.99

Uniform Distribution with minimum of 0.87755, maximum of 7.1224, Mean = 3.999, Std Deviation = 1.8027, total values lying between 1.0000 to 7.0000 = 96.1%, Outliers outside the range of 1 to 7 are 100-96.1 = 3.9%

Antecedents of Flow

Enduring Involvement

Interactive Speed

Control

Web Navigational Importance

Perfect & Imperfect-Intensive Flow (PIIF) users as 30 hours per week. Login Imperfect User represents the log-in time by an Imperfect Flow (IF) users as 20 hours per week. Login Non Flow User represents the log-in time by the users who do not achieve Flow during Web navigation or Non-Flow (NF) users, as 10 hours per week.

190

The results, which are an output of the decision tree using PrecisionTree software and the output from @Risk software using @Riskoutput function, show that given the similar conditions and constraints of Web navigation, PIIF users would be using the Web for 23.43 hours (78% of the present Web use) per week, IF user would navigate

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Table 2. Percentage time for flow achievement for different user categories Antecedents of Flow Skill

PIIF Users

IF Users

NF Users

4.76

11.3

10.7

Challenge

0.0

0

19.9

Interactive Speed

4.76

11.3

10.7

Enduring Involvement

4.76

6.1

11.2

Web Navigational Importance

4.76

11.3

10.7

Control

71.44

0

0

Arousal

0.0

31.6

0

Telepresence

4.76

11.3

10.7

Focussed Attention

4.76

17.1

6.2

Optimum Stimulation Level (OSL)

0.0

0

19.9

Note: Total % time for each category would come out to be 100%. PIIF users have marked 6 – 7 on the likert scale; IF users’ responses lie between 4–6 (including 4 and excluding 6) on the likert scale; while NF users have marked 1–3 on the likert scale of the questionnaire comprising of 63 questions as 63 statements on Flow antecedents resulting into three Flow states—Perfect Flow, Imperfect-Intensive Flow, and Imperfect Flow

for 12.32 hours (62% of the current Web use) per week and NF user would navigate for 6.51 hours (6.5% of the current Web use) per week vis-à-vis the 10 antecedents of Flow. This shows that Flow would be achieved by all categories of users. The

conditions and constraints of Web navigation process represents Web use variables like log-in, and PC vintage (indicating that the user would be using the same PC with the same configuration in the future). Also, we had found out from our

Table 3. Time spent for Flow antecedents by different user categories Percentage

Time spent with Flow constructs

overlapping

% Time spent for each Flow antecedent by regular Web users (50 respondents)

PIIF Users

IF Users

NF Users

Skill

48

14.4

9.6

4.8

Challenge

90

27

18

9

Antecedents of Flow

Interactive Speed

48.8

14.4

9.6

4.8

Enduring Involvement

50.7

15.21

10.14

5.07

Web Navigational Importance

48

14.4

9.6

4.8

Control

90

27

18

9

Arousal

48

27

18

9

Telepresence

90

14.4

9.6

4.8

Focussed Attention

90

14.64

9.76

4.88

Optimum Stimulation Level (OSL)

48

27

18

9

Note: The table above shows overlaps of percentage of time spent by users under 10 Flow constructs. For example, a user may experience focused attention, OSL, enduring involvement and challenge at the same time while performing some activity of e-mail, chatting, and so forth on the Web.

191

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Figure 3. Sensitivity (Spider) graphs highlighting dependence Perfect & Imperfect-Intensive Flow (PIIF) users, Imperfect Flow (IF) users and Non Flow (NF) users vis-à-vis Expected Web usage in future (EXPUSE)

survey that PIIF users normally use the Web for 30 hours per week, IF users navigate for 20 hours per week, and NF users navigate for 10 hours per week. Contradictory to the popular proposition that EXPUSE and RCB would be constant or even more for PIIF and IF users, it has turned out to be much less than the present use. Hence, the hypothesis is rejected. Also, the hypothesis that NF users would not be using the Web for EXPUSE

192

and RCB has also been rejected as the results show an increase in Web use by NF users by 6.5%. The only hypothesis that is accepted is that the PIIF category of users would attain more EXPUSE and RCB than IF users. This clearly illustrates that the users who do not achieve Flow today or at present, will achieve Flow in the future showing the dynamic qualities of Flow represented through 10 Flow constructs. Hence, the user

Redefining Web Users’ Optimal Flow Experiences In Online Environments

category shifts from NF users to IF users or even PIIF users are both quite evident and inadvertent because even a user will constantly learn and improve his Web knowledge and skills, highlighting the ever-changing dynamic consumer navigation behvaiour leading to a change in his or her set of 10 Flow constructs: skills, challenges, control, arousal, telepresence, focussed attention, interactive speed, enduring involvement, Web navigational importance, and optimum stimulation level. Flow, thus, can be seen as a technological instrument of Web navigation and Web measurement of EXPUSE and RCB. Many researchers (e.g., Choi, Jeoungkun, & Soung, 2007; Hsu & Lu, 2003; Sicilia, Ruiz, & Munuera, 2005; Novak, Hoffman, & Yung, 2000; Novak, Hoffman, & Duhachek, 2003) working in Flow theory view flow as a unidimensional construct with a set of ancillary constructs that serve as antecedents and consequences of flow. Other authors have incorporated some of the antecedents and consequences of flow directly into the flow construct, and have developed and utilized multidimensional definitions of flow. Pace (2003) views flow as a multi-dimensional construct comprised of the joy of discovery, reduced awareness of surroundings, time distortion, merging of action and awareness, a sense of control, mental alertness, and telepresence. Some of these constructs are considered by Hoffman and Novak (1996) to be antecedents of flow (i.e., control, telepresence, and time distortion), whereas others are considered to be consequences (i.e., joy of discovery). Agarwal and Karahanna (2000) conceptualized Flow as cognitive absorption leading to greater usefulness and perceived ease of use, which leads to behavioral intention to use. Their model incorporates the Technology Acceptance Model (TAM), widely used to predict technology adoption. Cognitive absorption provides the user with a sense of being in command. Our research has highlighted the fact that Flow enhances learning, willingness to learn and increase cognitive abilities. This is proven in the

accepted hypothesis, whereby a person who is not experiencing Flow currently (Non-Flow user) is likely to experience Flow and perform more Web use (EXPUSE) in the future due to his own increase in online cognitive behavior. Flow is related to key marketing variables, including online browsing behavior, purchase, and repeat purchase (Dailey, 2004; Hoffman & Novak, 1996; Smith & Sivakumar, 2004). A significant finding in our chapter is that people experiencing considerable amount of Flow currently may not experience the same amount of Flow in the future. This means Web site Marketing, and more importantly Web sites, must focus on the Flow concept regularly and dynamically. They must track consumer behavior from time to time in order to change their content periodically as per the needs, wants, and aspiration of their target market. This will help them retain their customers and inculcate repeat visits to their Web sites leading to RCB and EXPUSE. Future research may focus on the area of marketing for Web sites leading to a relationship between Flow and key marketing variables leading to an increase in online shopping behavior.

CONCLUSION This research chapter has developed a comprehensive process model of network navigation and conducted an empirical study in which constructs are developed and validated that correspond to the underlying structure of Flow. The Flow concept integrates skills, challenges, control, arousal, telepresence, focussed attention, interactive speed, enduring involvement, Web navigational importance, and optimum stimulation level as 10 antecedents of Flow, also called Flow constructs, and three Flow states—Perfect Flow, ImperfectIntensive Flow, and Imperfect Flow—for three categories of users—PIIF, IF, and NF users. The present research has not delved in the area of Web site designing that facilitate the consumer experience of Flow and the variations of Flow

193

Redefining Web Users’ Optimal Flow Experiences In Online Environments

across the wide range of commercial sites found on the Web today. It is our hope that this research will result in a more comprehensive understanding of the nature of the Flow experience than has been provided by previous research and provide a basis for future research on user navigation behavior in online shopping environments.

REFERENCES Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24, 665–694. doi:10.2307/3250951 Chen, H., Wigand, R. T., & Nilan, M. (1998, May 17-19). Optimal flow experience in Web navigation. In Effective utilization and management of emerging information technologies: Proceedings of the 9th Information Resources Management Association International Conference, Boston (pp. 633-636). Hershey, PA: Idea Group Publishing. Choi, D. H., Jeoungkun, K., & Soung, H. K. (2007). ERP training with a Web-based electronic learning system: The flow theory perspective. International Journal of Human-Computer Studies, 65, 223–243. doi:10.1016/j.ijhcs.2006.10.002 Csikszentmihalyi, M. (1977). Beyond boredom and anxiety (2nd ed.). San Francisco: Jossey-Bass. Csikszentmihalyi, M. (1982). Towards a psychology of optimal experience. In L. Wheeler (Ed.), Annual review of personality and social psychology (Vol. 3, pp. 13-36). Beverly Hills, CA: Sage. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper and Row. Csikszentmihalyi, M., & Csikszentmihalyi, I. (Eds.). (1988). Optimal experience: Psychological studies of flow in consciousness. Cambridge, UK: Cambridge University Press.

194

Dailey, L. (2004). Navigational Web atmospherics: Explaining the influence of restrictive navigation cues. Journal of Business Research, 57, 795–803. doi:10.1016/S0148-2963(02)00364-8 Ghani, J. A., Supnick, R., & Rooney, P. (1991, December 16-18). The experience of flow in computer-mediated and in face-to-face groups. In J. I. DeGross, I. Benbasat, G. DeSanctis, & C. M. Beath (Eds.), Proceedings of the Twelfth International Conference on Information Systems, New York (pp. 229-237). ACM Publishing. Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60, 50–68. doi:10.2307/1251841 Hsu, C.-L., & Lu, H.-P. (2003). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41, 853–868. doi:10.1016/j. im.2003.08.014 Kothari, D. P., Jain, S. K., Khurana, A., & Saxena, A. (2001). Developing a Marketing Strategy for Global Online Customers . International Journal of E-Business Strategy Management, 2(4), 301–305. Moneta, G. B., & Csikszentmihalyi, M. (1996). The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality, 64(2), 275–310. doi:10.1111/j.1467-6494.1996.tb00512.x Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13(1,2), 3-16. Novak, T. P., Hoffman, D. L., & Yung, Y. F. (1998). Modeling the structure of the flow experience. Paper presented at the INFORMS Marketing Science and the Internet Mini-Conference, Boston, MA.

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–44. doi:10.1287/ mksc.19.1.22.15184

Smith, D. N., & Sivakumar, K. (2004). Flow and Internet shopping behavior: A conceptual model and research propositions. Journal of Business Research, 57, 1199–1208. doi:10.1016/S01482963(02)00330-2

Pace, S. (2003). A grounded theory of the flow experiences of Web users. International Journal of Human-Computer Studies, 60, 327–363. doi:10.1016/j.ijhcs.2003.08.005

Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. The Journal of Communication, 42, 73–93. doi:10.1111/j.1460-2466.1992.tb00812.x

Saxena, A., Kothari, D. P., Jain, S. K., & Khurana, A. (2002). Analyzing the business models on the Web for internet commerce. International Journal of e-Business Strategy Management, 3(3), 229-241.

Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication. Communication Research, 19(5), 539–573. doi:10.1177/009365092019005001

Saxena, A., Kothari, D. P., Jain, S. K., & Khurana, A. (2003). Development of a “flow process scale” to measure flow among Web users. Journal of Internet Commerce, 2(4), 55–86. doi:10.1300/ J179v02n04_04

Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human computer interactions. Computers in Human Behavior, 9(4), 411–426. doi:10.1016/07475632(93)90032-N

Sicilia, M., Ruiz, S., & Munuera, J. L. (2005). Effects of interactivity in a Web Site. Journal of Advertising, 34, 31–45.

195

Redefining Web Users’ Optimal Flow Experiences In Online Environments

APPENDIX A QUESTIONNAIRE Please indicate your response by a tickmark () wherever applicable 1. How long have you been using the Internet / World Wide Web (WWW)? Less than 1 year 1 – 2 years 2 – 5 years More than 5 years 2. On an average, what is the duration and frequency of your Internet usage? Duration: …………. Hours per day week month Frequency: ………… Times per day week month 3. Please indicate your degree of agreement with the following statements: Table 4. In this Questionnaire, “Web” implies Usage of the Web (www/internet) S.No

Flow Constructs and Activities

Strongly Disagree 1

1)

I consider myself knowledgeable about internet utilities and web usage.

2)

It is possible to cross-verify the information on one website with other similar websites.

3)

It is easy to use the web with available search techniques.

4)

Intimate Web knowledge encourages cyber crimes.

5)

Fabricating the information by using the web to develop a new write-up, is challenging.

6)

Web poses a good challenge to my web skills and web knowledge.

7)

Web usage challenges my performance.

8)

Searching specific information on the web is challenging.

9)

Increase in speed of downloads enhances my web usage.

10)

Web navigation is a tedious process.

11)

Web navigation is a slow process.

12)

I feel extremely bored if the waiting time between my actions and the computer’s response is high.

13)

While using the web, the speed of downloads helps in improving the web interaction experience.

14)

While using the web, I am totally involved and absorbed in what I am doing.

15)

Web is a nuisance.

16)

My involvement with web is mostly not useful to me.

17)

Web navigation is the most useful activity for me.

18)

Web plays a very important role in my life.

19)

I cannot imagine my life without web.

Strongly Agree 2

3

4

5

6

7

continued on following page 196

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Table 4. continued S.No

Flow Constructs and Activities

Strongly Disagree 1

20)

I am not an “Internet addict”.

21)

I cannot help myself being glued to the web.

22)

I am obsessed with the web.

23)

Web controls my actions.

24)

I feel relaxed while using the web.

25)

Web excites me.

26)

There is too much information available on the web to digest.

27)

Web attracts me a lot.

28)

Web provides me a lot of entertainment.

29)

I feel lonely and sad while using the web.

30)

The web arouses me to know more than what I really know.

31)

I forget myself and the physical environment surrounding me, while using the web.

32)

I feel, the “Web environment/COMPUTER WORLD” makes me idle.

33)

While using the web, I am taken over by the “COMPUTER WORLD”.

34)

While using the web, the “REAL WORLD” becomes irrelevant to me.

35)

While using the web, I feel, I am in a different world altogether.

36)

While using the web, I cannot concentrate on each and everything available on the web.

37)

Whenever web searching/browsing becomes time consuming, I tend to loose attention.

38)

I pay attention to only those web contents, which are required by me.

39)

It is not possible to have focused attention on the web.

40)

Web does not give me any value addition.

41)

Web does not stimulate me too much.

42)

The stimulation level that I derive from the web is “just right” for me.

43)

I discover new things while using the web.

44)

I like to discover useful things through the web.

45)

Web does not offer anything new to me.

46)

Web makes me creative.

47)

Web makes me imaginative.

48)

Web provides a refreshing change.

49)

I love to make friends on the web.

50)

I like to click on a new link because it makes me feel happy.

51)

Web usage provides me a lot of experimentation.

Strongly Agree 2

3

4

5

6

7

continued on following page

197

Redefining Web Users’ Optimal Flow Experiences In Online Environments

Table 4. Continued S.No

Flow Constructs and Activities

Strongly Disagree 1

52)

I feel totally immersed and engrossed in some web activities and lose track of time.

53)

Time seems to go by quickly and swiftly while using the web.

54)

I feel engrossed in some web activities and still keep track of time.

55)

While using the web, I am aware of what I am doing.

56)

Web usage increases my learning.

57)

Web usage enhances my exploring abilities.

58)

Web usage leads to negligence of other important tasks.

59)

I feel, web usage adversely affects my health.

60)

I cannot keep a check on time while using the web.

61)

Unless and until I am stopped from using the web, I can navigate the web for hours together.

62)

I use the web for a fixed period of time.

63)

Excess of web usage can lead to a lot of pending work.

Strongly Agree 2

3

4

5

6

7

APPENDIX B Please see the attached Excel spreadsheet P.S. The distributions listed in the columns illustrate the samples within a given range of values for the respective distribution based on the traditional arguments used by the distribution. Three different fit statistics, i.e., chi-squared, Kolmogorov-Smirnov (K-S), and Anderson-Darling (A-D), are reported since they measure how well the distribution fits the input data and how confident we can be that the data was produced by the distribution function. The chi-squared statistic is the best known goodness-of-fit statistic. P-value/”observed significance level” of the test are reported . As the P-value decreases to zero, we are less and less confident that the fitted distribution could possibly have generated our original data set. Conversely, as the P-value approaches one, we have no basis to reject the hypothesis that the fitted distribution actually generated our data set. The K-S statistic does not require binning, which makes it less arbitrary than the chi-squared statistic. A weakness of the K-S statistic is that it does not detect tail discrepancies very well. Like the K-S statistic, the A-D statistic does not require binning. But unlike the K-S statistic, which focuses in the middle of the distribution, the A-D statistic highlights differences between the tails of the fitted distribution and input data.

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 1-21, copyright 2009 by Information Science Reference (an imprint of IGI Global)

198

199

Chapter 11

Addressing Contemporary Challenges in CognitivelyComplex Collaboration with CoPe_it! Nikos Karacapilidis University of Patras & Research Academic Computer Technology Institute, Greece Manolis Tzagarakis University of Patras & Research Academic Computer Technology Institute, Greece Nikos Karousos Hellenic Open University, Greece George Gkotsis University of Patras, Greece Vassilis Kallistros Research Academic Computer Technology Institute, Greece Spyros Christodoulou Research Academic Computer Technology Institute, Greece Christos Mettouris Research Academic Computer Technology Institute, Greece Dora Nousia Research Academic Computer Technology Institute, Greece

ABSTRACT In this article, we demonstrate how CoPe_it! – a web-based argumentative collaboration support tool – enables one to manage cognitively-complex collaboration settings, that is settings characterized by big volumes of interrelated data obtained from diverse sources and knowledge expressed by diverse participants. The CoPe_it! approach focuses on issues related to the representation of such settings and DOI: 10.4018/978-1-60960-153-9.ch011 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

aims at making it easier for participants to follow the evolution of a collaboration, comprehend it in its entirety, and meaningfully aggregate data in order to resolve the issue under consideration.

Introduction Recent advances in computing and Internet technologies, together with the advent of the Web 2.0 era, resulted to the development of a plethora of online, publicly available environments such as blogs, discussion forums, wikis, and social networking applications. These offer people an unprecedented level of flexibility and convenience to participate in complex collaborative activities, such as long online debates of public interest about the greening of our planet through renewable energy sources or the design of a new product in a multinational company. Information found in these environments is considered as a valuable resource for individuals and organizations to solve problems they encounter or get advice towards making a decision. In any case, people have to go through some type of sorting, filtering, ranking and aggregation of the existing resources in order to facilitate sense-making. Yet, these activities are far from being easy. This is because collaboration settings are often associated with ever-increasing amounts of multiple types of data, obtained from diverse sources that often have a low signal-tonoise ratio for addressing the problem at hand. In turn, these data may vary in terms of subjectivity, ranging from individual opinions and estimations to broadly accepted practices and indisputable measurements and scientific results. Their types can be of diverse level as far as human understanding and machine interpretation are concerned. They can be put forward by people having diverse or even conflicting interests. At the same time, the associated data are in most cases interconnected, in a vague or explicit way. Data and their interconnections often reveal social networks and social interactions of different patterns. The above bring up the need for innovative software tools that can appropriately capture,

200

represent and process the associated data and knowledge. Such tools should shift in focus from the collection and representation of information to its meaningful assessment and utilization. They should facilitate argumentation (i.e. “discussion in which reasoning and disagreements exist, not only discourse for persuasion, logical proof and evidence-based belief” (Kunz & Rittel, 1970)), the ultimate aim being to augment collaborative sense-making and/or decision-making. This can be seen as a special type of social computing where various computations concerning the associated context and group’s behavior need to be supported. Recent studies on Cognitive Load Theory clearly indicate that the abovementioned objectives are particularly relevant and important in cognitively complex situations (Ayres & van Gog, 2009; Kirschner, Paas, & Kirschner, 2009; Leutner, Leopold, & Sumfleth, 2009; Kalyuga, 2009). Designing software systems that can adequately address users’ needs to express, share, interpret and reason about knowledge during an argumentative collaboration session has been a major research and development activity for more than twenty years. Technologies supporting argumentative collaboration usually provide the means for discussion structuring and visualization, sharing of documents, and user administration (Karacapilidis & Tzagarakis, 2009; Stegmann, Weinberger & Fischer, 2007). They support argumentative collaboration at various levels and have been tested through diverse user groups and contexts. Furthermore, they aim at exploring argumentation as a means to establish a common ground between diverse stakeholders, to understand positions on issues, to surface assumptions and criteria, and to collectively construct consensus. While helpful in particular settings, the above solutions prove to be inadequate in cognitively-

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

complex situations. In this context, our work focuses on the development of a web-based tool, namely CoPe_it! (http://copeit.cti.gr), which is capable to tackle the diversity and complexity of the above issues, the ultimate goals being to make it easier for users to follow the evolution of an ongoing collaboration, comprehend it in its entirety, and meaningfully aggregate data in order to resolve the issue under consideration.

Existing approaches Existing approaches to support argumentative collaboration vary in terms of the problem dimension they principally address and the context they particularly target. One category, focusing on a meaningful representation of the related items and their interconnections, builds on the concepts of IBIS (Issue Based Information System), introduced back in 1970 (Kunz & Rittel, 1970). For instance, gIBIS (Conklin & Begeman, 1989) is a pioneer argumentation structuring tool that allows users to create issues, assert positions on these issues, and make arguments in favor or against them. QuestMap (Conklin, Selvin, Buckingham Shum & Sierhuis, 2001) resembles to a ‘whiteboard’ where all messages, documents and reference material for a project, together with their relationships, are graphically displayed, the aim being to capture the key issues and ideas during meetings and create a shared understanding in a knowledge team. Hermes (Karacapilidis & Papadias, 2001) builds on concepts from the areas of Decision Theory, Non-Monotonic Reasoning, Constraint Satisfaction and Truth Maintenance, and offers an integrated consideration of classical decision making and argumentation principles. Compendium (http://www.compendiuminstitute. org) is a tool that supports dialogue mapping and conceptual modeling in a meeting scenario, and can be used to gather a semantic group memory. In the same context, Belvedere (Suthers, Weiner, Connelly & Paolucci, 1995) is used for construct-

ing and reflecting on diagrams of one’s ideas, such as evidence maps and concept maps. It represents various logical and rhetorical relations within a debate and supports problem-based collaborative learning scenarios through the use of a graphical language. In the context of argumentation theory, systems supporting the visualization of argumentation have played a considerable educational role by supporting the teaching of critical thinking and reasoning skills. For instance, Araucaria (Reed & Rowe, 2004) supports the contextual analysis of a written text and provides a tree view of the premises and conclusions, also reflecting stereotypical patterns of reasoning. In the same line, ArguMed (Verheij, 2003) builds on a formal argumentation approach to addresses the issues of argument mapping. The Reason!Able argumentation tool (van Gelder, 2002) provides a well structured and user-friendly environment for reasoning. Through the use of an argumentation tree, a problem can be decomposed to its logically related parts, whereas missing elements can also be identified. Athena Standard and Athena Negotiator (http:// www.athenasoft.org) are two more examples of argument mapping software. Athena Standard is designed to support reasoning and argumentation, while Athena Negotiator is designed to facilitate analysis of decisions and two-party negotiations. The last two systems are efficient argumentation structuring tools, but do not employ any knowledge management features. Recently, some interesting approaches that rely on the Web and Web 2.0 technologies were designed to provide sharing capabilities, online collaboration, and common map-based workspaces to individuals or social networks. For instance, MindDraw (http://info.cwru.edu/minddraw/) is an educational software providing assistance towards the creation and sharing of visual images of ideas; it enables users to produce maps of causal relationships and has been proven to be useful for students and learners of all ages. bCisive online (http://www.bcisiveonline.com) is another web

201

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

application that supports collaboration in visual workspaces using a common visual languages for decision making and planning, while it can produce compelling PowerPoint presentations. Similarly, debategraph (http://debategraph.org/) tries to visualize wiki debates in a graph-based way, which can clearly represent discussions and decisions. Another approach of collaboration support comes from truthmapping (http:// www.truthmapping.com), in which arguments are broken down into their component parts and are allowed to be criticized and revised in order to be re-evolved in the whole argumentation. Finally, Cohere (http://cohere.open.ac.uk) facilitates sense-making and argumentation by allowing the creation of meaningful connections between ideas for personal, team or social use. As derives from the above, the majority of existing argumentative collaboration support systems mainly focus on the expression and visualization of arguments. Generally speaking, existing approaches provide a cognitive argumentation environment that stimulates reflection and discussion among participants. However, their features and functionalities are limited, they pay no or limited attention to data and knowledge management issues (Nonaka, 2005), they are not interconnected with other tools, and they do not efficiently tackle the technological and social dimensions of cognitively-complex collaboration. They receive criticism related to their adequacy to clearly display each collaboration instance to all parties involved (usability and ease-of-use issues), as well as to the formal structure used for the representation of collaboration. In most cases, they merely provide a sort of threaded discussion forums, where messages are linked passively. This usually leads to an unsorted collection of vaguely associated positions, which is extremely difficult to be exploited in future collaboration settings. Also important, they do not integrate, in most cases, any reasoning mechanisms to (semi)automate the underlying decision making processes required in a collaboration setting. Thus, there is a lack of

202

alternative formalization, consensus seeking and decision-making support abilities. It has been also admitted that these solutions often require that users carry out activities that do not naturally belong to their work, or they support activities which are infrequent in normal work; thus, such activities are often considered artificial or insignificant by users. As a result, traditional argumentation software approaches are no longer sufficient to support contemporary communication and collaboration needs (de Moor & Aakhus, 2006). There is a need to provide alternative representational features in order to demonstrate a significant effect on the users’ collaborative knowledge building process.

Requirements and challenges The approach presented in this paper is the result of action research studies (Checkland & Holwell, 1998) concerning the improvement of practices, strategies and knowledge in diverse cognitivelycomplex collaborative environments. Design of a smart solution to improve a community’s understanding and productivity in such environments is certainly a big challenge. Towards meeting it, we have first performed a series of interviews with members of diverse communities in order to identify the major issues they face during their ordinary practices. Twelve communities, coming from three distinct work environment types (management, engineering and learning), and ranging in size from a few decades to a few hundreds of members, were involved (7 of these communities were moderated). In total, 37 people went through a semi-structured interview (the vast majority of them were ‘early adopters’ with more than 5 years hands-on experience with collaborative technologies). All people selected were highly active members in their communities and/ or they were having a moderator role. Major issues identified were (these issues delineated categories of crucial, problem-specific requirements to be met during the development of CoPe_it!):

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

Cognitive overhead and management of information overload: This is primarily due to the extensive and uncontrolled exchange of diverse types of data and knowledge resources. For instance, such a situation may appear during the exchange of numerous ideas about the solution of a public issue, which is accompanied by the exchange of big volumes of positions and arguments in favor or against each solution. In such cases, individuals usually have to spend much effort to conceptualize the current state of the collaboration and grasp its contents (Hollan, Hutchins & Kirsh, 2000). The need to consider an overwhelming amount of resources may ultimately harm a community’s objectives (Wenger, 1999). To avoid that, functionalities for scalable filtering and timely processing of the associated big amounts of data need to be offered. Social behavior: The representation and visualization of social structures, relationships and interactions taking place in a collaborative environment with multiple stakeholders are also of major importance. This is associated to the perception and modeling of actors, groups and organizations in the diversity of collaborative contexts. A problem to be addressed is to provide the means to appropriately represent and manage user and group profiles, as well as social relationships. However, neither relationships nor contexts are static; they are emerging and change over time, which necessitates the development of adaptive services Collaboration modes: Interviews indicated that the evolution of the collaboration proceeds incrementally; ideas, comments, or any other type of collaboration objects are exchanged and elaborated, and new knowledge emerges slowly (Wenger, 1999; Hollan, Hutchins & Kirsh, 2000). When members of a community participate in a collaborative session, enforced formality may require them to specify their knowledge before it is fully formed. Such emergence cannot be attained when the collaborative environment enforces a formal model from the beginning. On

the other hand, formalization is required in order to ensure the environment’s capability to support and aid the collaboration efforts. In particular, the abilities to support decision making or estimation of the present state benefit greatly from formal representations of the information units and relationships. Generally speaking, solutions to the problem under consideration should be generic enough to address diverse collaboration modes and paradigms. Expression of tacit knowledge: A community of people is actually an environment where tacit knowledge (i.e. knowledge that the members do not know they possess or knowledge that members cannot express with the means provided) predominantly exists and dynamically evolves. Such knowledge must be efficiently and effectively represented in order to be further exploited in a collaborative environment. Integration of legacy resources: Many resources required during a collaborative session have either been used in previous sessions or reside outside the members’ working environment (e.g. in e-mailing lists or web forums). Moreover, outcomes of past collaboration activities should be able to be reused as input in subsequent collaborative sessions. The inherent issues of liability and preservation of intellectual rights need particular attention in such cases. Data processing and decision making support: In the settings under consideration, timely processing of data related to both the social context and social behavior is required. Such processing will significantly aid the members of a community to conclude the issue at hand, extract meaningful knowledge and reach a decision. This means that their environment (i.e. the tool used) needs to interpret the knowledge item types and their interrelationships in order to proactively suggest trends or even aggregate data and calculate the outcome of a collaborative session.

203

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

The proposed solution CoPe_it! allows for distributed, synchronous or asynchronous, collaboration over the Web. To appropriately tackle the issues identified in the previous section, CoPe_it! builds on an integrated consideration and exploitation of the concepts listed below.

Incremental Formalization When engaged in the use of existing technologies and systems supporting argumentative collaboration, users have to follow a specific formalism. More specifically, their interaction is regulated by procedures that prescribe and - at the same time - constrain their work. This may refer to both the system-supported actions a user may perform (e.g. types of discourse or collaboration acts), and the system-supported types of argumentative collaboration objects (e.g. one has to strictly characterize a collaboration object as an idea or a position). In many cases, users have also to fine-tune, align, amend or even fully change their usual way of collaborating in order to be able to exploit the system’s features and functionalities. Such formalisms are necessary towards making the system interpret and reason about human actions (and the associated resources), thus offering advanced computational services. However, there is much evidence that sophisticated approaches and techniques often resulted in failures (Shipman & Marshall, 1994; Shipman & McCall, 1994). This is often due to the extra time and effort that users need to spend in order to get acquainted with the system, the associated disruption of the users’ usual workflow (Fischer, Lemke, McCall & Morch, 1991), as well as to the “error prone and difficult to correct when done wrong” character of formal approaches (Halasz, 1988). Complex contexts imply additional disadvantages when using formal approaches. Such approaches impose a structure which is not mature enough to accommodate the management of huge

204

amounts of data coming from diverse sources. They do not allow users to elaborate and digest these data at their own pace, according to the evolution of the collaboration. Instead, a varying level of formality should be considered. This variation may either be imposed by the nature of the task at hand (e.g. decision making, deliberation, persuasion, negotiation, conflict resolution), the particular context of the collaboration (e.g. medical decision making, public policy making), or the group of people who collaborate each time (i.e. how comfortable people feel with the use of a certain technology or formalism). The above advocate an incremental formalization approach, which has been adopted in the development of CoPe_it!. In our approach, formality and the level of knowledge structuring is not considered as a predefined and rigid property, but rather as an adaptable aspect that can be modified to meet the needs of the tasks at hand. By the term formality, we refer to the rules enforced by the system, with which all user actions must comply. Allowing formality to vary within the collaboration space, incremental formalization, i.e. a stepwise and controlled evolution from a mere collection of individual ideas and resources to the production of highly contextualized and interrelated knowledge artifacts, can be achieved. As shown in Figure 1 (bottom part), this evolution is associated with a set of functionalities that are ordered in terms of formality level.

Visualization and Reasoning It has been widely argued that visualization of argumentation conducted by a group of experts working collaboratively towards solving a problem can facilitate the overall process in many ways, such as in explicating and sharing individual representations of the problem, in maintaining focus on the overall process, as well as in maintaining consistency and in increasing plausibility and accuracy (Kirschner, Buckingham Shum & Carr, 2003). For the above reasons, visualization

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

Figure 1. The proposed incremental formalization approach

issues received much attention while shaping the proposed solution. In CoPe_it!, projections constitute the ‘vehicle’ that permits incremental formalization of argumentative collaboration (see Figure 1). A projection can be defined as a particular representation of the collaboration space, in which a consistent set of abstractions able to solve a particular organizational problem during argumentative collaboration is available. With the term abstraction, we refer to the particular data and knowledge items, relationships and actions that are supported through a particular projection, and with which a particular problem can be represented, elaborated and be solved. CoPe_it! enables switching from a projection to another, during which abstractions of a certain formality level are transformed to the appropriate abstractions of another formality level. This transformation is rule-based; such rules can be defined by users and/or the facilitator of the collaboration and reflect the evolution of a community’s collaboration needs. It is up to the community to exploit one or more projections of a

collaboration space (upon users’ needs and expertise, as well as the overall collaboration context). Each projection of the collaboration space provides the necessary mechanisms to support a particular level of formality (e.g. projection_1 may cover only needs concerning collection of knowledge items and exploitation of legacy resources, whereas projection_n may cover the full spectrum of the functionalities shown at the bottom part of Figure 1). The more informal a projection is, the more easiness-of-use is implied; at the same time, the actions that users may perform are intuitive and not time consuming (e.g. drag-and-drop a document to a shared collaboration space). Informality is associated with generic types of actions and resources, as well as implicit relationships between them. However, the overall context is more human (and less system) interpretable. As derives from the above, the aim of an informal projection of the collaboration space is to provide users the means to structure and organize data and knowledge items easily, and in a way that conveys semantics to them. Generally speaking, informal projections may support an unbound number of

205

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

data and knowledge item types. Moreover, users may create any relationship among these items; hence, relationship types may express agreement, disagreement, support, request for refinement, contradiction etc. While such a way of dealing with data and knowledge resources is conceptually close to practices that humans use in their everyday environment, it is inconvenient in situations where support for advanced decision making processes must be provided. Such capabilities require resources and structuring facilities with fixed semantics, which should be understandable and interpretable not only by the users but also by the tool. Hence, decision making processes can be better supported in environments that exhibit a high level of formality. The more formal projections of a collaboration space come to serve such needs. The more formal a projection is, easiness-of-use is reduced; actions permitted are less intuitive and more time consuming. Formality is associated with fixed types of actions, as well as explicit relationships between them. However, a switch to a more formal projection is highly desirable when (some members of) a community need to further elaborate the data and knowledge items considered so far. Such functionalities are provided by projections that may enable the formal exploitation of collaboration items patterns and the deployment of appropriate formal argumentation and reasoning mechanisms. A switch to a projection of a higher level of formality disregards less meaningful data and knowledge items, resulting to a more compact and tangible representation of the collaboration space. This effect is highly desirable in cognitively-complex situations.

Information Triage Our solution builds extensively on the information triage process (Marshall & Shipman, 1997), i.e. the process of sorting and organizing through numerous relevant materials and organizing them to meet the task at hand. During such a process,

206

users must effortlessly scan, locate, browse, update and structure knowledge resources that may be incomplete, while the resulting structures may be subject to rapid and numerous changes. Information triage related functionalities enable users to meaningfully organize the big volumes of data and knowledge items in a collaborative setting. The informal projection of a collaborative workspace in CoPe_it! is fully in line with the above. Drawing upon successful technologies coming from the area of spatial hypertext (Marshall & Shipman, 1997), the informal projection of CoPe_it! adopts a spatial metaphor to depict collaboration in a 2.5-dimensional space (the space is considered 2.5-dimensional, and not 2-dimensional, because it permits overlap of the items; the tool is aware of which items overlap, as well as of various spatial proximity issues). Spatial hypertext is admittedly a promising approach to address issues in argumentative environments, as it introduces a visual language in an attempt to take advantage of the humans’ visual memory and their ability to recognize patterns. Exploiting these human capabilities can greatly reduce the negative impacts of cognitively-complex environments. Spatial hypertext removes the barrier between reading and writing processes enabling articulation of tacit knowledge and ambiguity (Marshall & Shipman, 1995), as well as establishment of emerged problem-solving strategies. Thus, users are incrementally processing information and are not forced to predefined structural commitments. The related features and functionalities of CoPe_it! enable users to create and organize information by making use of spatial relationships and structures, giving them the freedom to express relationships among information items through spatial proximity and visual cues. Such cues are related to the linking of collaboration items (e.g. coloring and thickness of the respective links) and the drawing of colored rectangles to cluster related items. As highlighted above, the informal projection of a collaborative workspace in CoPe_it! permits an ordinary and unconditioned evolution of data

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

and knowledge structures. This projection also provides abstraction mechanisms that allow the creation of new abstractions out of existing ones. Abstraction mechanisms include: (i) annotation and metadata (i.e. the ability to annotate instances of various knowledge items and add or modify metadata); (ii) aggregation (i.e. the ability to group a set of data and knowledge items so as to be handled as a single conceptual entity); (iii) generalization/specialization (i.e. the ability to create semantically coarse or more detailed knowledge items in order to help users manage information pollution of the collaboration space); (iv) patterns (i.e. the ability to specify instances of interconnections between knowledge items of the same or a different type, and accordingly define collaboration templates). Information triage related activities can be conducted in CoPe_it! either collaboratively (a moderator may be required in some cases) or individually. The tool permits individuals to copy a collaborative workspace, paste all of its items in a private one and work on it at their pace. In such a way, individual reflections and experimentations can be conducted and evaluated before being made public. By doing so, individuals may also ask for filtered views of a workspace. Such filters may involve the actors participating in a collaborative setting, the types of items shared (together with the corresponding links), keywords in their title and body, annotations made on them, etc.

Exploitation of Legacy Resources CoPe_it! reduces the overhead of entering information by allowing the reuse of existing resources. Generally speaking, when legacy resources have to be reused during a collaborative session, complexity is increased. This is not only due to the additional amount of data involved, but also to the conceptual overhead and distractions imposed to the user from switching among applications and environments. One way of dealing with this situation is to enable the ubiquitous access of

legacy resources from within the collaboration environment by seamlessly integrating the systems involved. Towards this direction, we have achieved interoperability between CoPe_it! and a number of applications that include Web-based forums, search engines and existing argumentative collaboration tools (e.g. Compendium).

Social Networking Management of social structures, interactions and relationships is also critical in a complex e-collaboration framework. Applications and projects dealing with social relationships mainly support explicit and abstract structures. However, social structures may gain from the expertise of structure domain research, including various structure abstractions or ways for implicit structuring. Another issue to be addressed concerns the elaboration of social relationships in their contexts, that is, how they relate to assets, locations, or change over time. Social network analysis (Castells, 2004) has to be extensively used to find who is depending on whom in a network. Such an analysis will also help to detect hidden hierarchy of social networks. Other requirements of this category concern the (semi)automatic role-specific cognitive mapping for each participant, based on his/her overall behavior, and the development of artifacts-related collaboration metrics. CoPe_it! integrates a sophisticated user and role modeling module to tackle the above issues. The module builds on an explicit representation of the notion of user/group, which is based on a predefined attribute hierarchy. The associated attributes can be domain-specific. They are categorized, depending on how they are populated and who may modify them, as explicit (their values are provided by users themselves and include personal data such as name, address, birth date, preferences, competencies, skills etc.) or implicit (their values are not provided by users explicitly, but implicitly, by observing their behavior within the system). User/group modeling is also associated

207

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

with mechanisms for the acquisition of the abovementioned implicit information of users/groups. These mechanisms observe and log the operations and discourse moves of users within the system and record them in the user’s profile. Finally, the user and role modeling module of CoPe_it! offers inference engines. The role of these engines is to analyze all data present in the profile, together with data from the collaborative workspaces, to extract meaningful information about social structures, interactions and relationships. Contrary to most user modeling approaches, our approach pays much attention to community-related aspects (i.e. relationships between individual users and relationships between users and artifacts).

USING CoPe_it! This section demonstrates the applicability of CoPe_it! in a real and complex debate that took place at the 5663rd Meeting of the United Nations Security Council (UNSC). An accurate representation of this debate has been incrementally built in CoPe_it! by using its minutes (the official press release is available at: http://www.un.org/News/ Press/docs/2007/sc9000.doc.htm). Additional data sources, corresponding to previous debates and information that is strongly related to the issue at hand, have been uploaded and appropriately linked in the corresponding workspace. The context of this debate is as follows: United Kingdom, holding the presidency of the UNSC for April 2007, raised the issue of whether climate change has an impact on peace and security. Over fifty delegates from the UN Member States collaborated by expressing their points of view through various statements and arguments of legal, environmental, scientific and political content. Some delegates welcomed the initiative, while others expressed their doubts on the mandate of the UNSC to discuss such issues. Some arguments were in favor or against an idea or a previously asserted argument. In some cases,

208

delegates were speaking on behalf of more than one member states (cases of geographically, politically or economically related states). Last but not least, delegates often referred to diverse sources of massive and complicated data such as data on territorial changes and maps, meteorological data, facts and figures related to energy resources, data concerning international agreements and protocols, financial data of different nature and complexity, records of similar debates conducted inside and outside UNSC, etc. In the following, we sketch an emulation of the above debate through CoPe_it! to show the tool’s capabilities in tackling such collaboration settings. The particular emulation was conducted in an asynchronous way, among geographically dispersed participants (taking the roles and using the wording of the real delegates). The layout of the tool’s informal projection is shown in Figure 2. The left hand side bar enables participants to open a new browser, search for related information, and be aware of other online members of their community. Participants may easily create and upload various types of data and knowledge items (a predefined set of item types is given; participants may enrich this set by defining additional ones). These can be either dedicated item types such as ideas (depicted as light bulbs), notes and comments, or existing multimedia resources. Ideas stand for items that deserve further exploitation; they may correspond to an alternative solution to the issue under consideration and they usually trigger the evolution of the collaboration. Notes are generally considered as items expressing one’s knowledge about the overall issue, an already asserted idea or note. Finally, comments are items that usually express less strong statements; they are uploaded to express some explanatory text or point to some potentially useful information. Knowledge item types may change upon the evolution of the collaboration (e.g. a user that has asserted a particular comment may elaborate it further and change its type to an idea). All the above items can be interrelated. When interrelat-

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

ing items, participants may select the color of the connecting arrow and provide a legend describing the interrelationship they conceive. These legends are intentionally arbitrary. CoPe_it! enables participants to spatially arrange the uploaded items and organize them in a meaningful way. Figure 2 corresponds to an early instance of the collaborative workspace created for the needs of our example. As shown, some stakeholders have contributed so far by uploading on the workspace some useful resources (including a video), proposing two concrete ideas (“Climate change is a security issue, thus it concerns Security Council” by the ‘British Foreign Secretary’, and “Essentially, it is an issue of sustainable development” by the ‘China Representative’), and interrelating one idea with four additional items. Figure 3 illustrates a second instance of the collaborative workspace under consideration (the left-hand side bar is closed for visualization pur-

poses). As shown, this is a highly data-intensive instance where many delegates have been contributed their ideas and positions. Four ideas are now expressed, which are highly interconnected with multiple data and knowledge artifacts. More multimedia resources, particularly relevant to some items, have been also uploaded. Beyond coloring of the arrows that interrelate knowledge items (in the example given, green arrows declare support, red ones declare opposition, whereas the other colors just denote an unjustified relation), another visual cue that appears in Figure 3 concerns the colored rectangles that have been created by participants to cluster related items. Other visual cues bear additional semantics (e.g. the thickness of an edge may express how strongly an item objects another one). The spatial arrangement of the collaboration artifacts aid users have a neat and quick view of the alternative ideas considered so far as well as the underlying

Figure 2. An early instance of the collaboration

209

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

argumentation. Since the process of gathering and sharing resources about the particular debate is unstructured, highly dynamic and thus rapidly evolving, this projection provides an appropriate environment to support collaboration at this stage. The aim is to bring the session to a point where main trends crystallize. Filtered views may be of additional help towards this direction. Figure 4 illustrates a view that has been produced after a participant’s request to visualize the workspace shown in Figure 3 according to some filtering. In the particular instance, a participant requested to visualize only the ideas expressed so far together with all the related argumentation in favor and against them (the filtering process invokes an algorithm for the better spatial arrangement of a workspace’s items). Apart from filtered views, alternative projections are also supported to facilitate sense-making according to participants’ requests. Towards this

direction, CoPe_it! enables collaboration through commonly met structures such as forums or ordered item lists. For the example elaborated in this section, Figure 5 depicts an item list view, in which a particular participant views a creation time ordered view. Some contexts necessitate a further elaboration of the knowledge items considered so far, and exploitation of additional functionalities such as formal argumentation and reasoning mechanisms. A formal projection in CoPe_it! is able to cover such needs by providing a fixed set of discourse element and relationship types, with predetermined, system-interpretable semantics. Further elaborating our example, let us assume that the collaboration has reached a point where a switch to a more formal projection is needed. This implies that selected knowledge items’ and relationships’ types have to be transformed. The above are determined by the underlying visualization and

Figure 3. A data-intensive instance of the collaboration

210

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

reasoning model of the formal projection (this process can be semi- or fully automated). An instance of the workspace’s formal projection (corresponding to both the data-intensive view of Figure 3, the filtered view of Figure 4 and the list view of Figure 5) is shown in Figure 6. This projection adopts an IBIS-like formalism (item types supported are issues, alternatives and positions) and provides a structured language for argumentative discourse together with a mechanism for the evaluation of alternatives. More specifically, the ideas appearing in the informal projection have been transformed to alternatives (alternatives correspond to solutions to the issue under consideration). Other knowledge items have been transformed to positions in favor or against exploiting the coloring and the legends of the interrelating arrows. Additional reasoning can be performed through the expression of preferences, which provide participants with a qualitative way to weigh reasons for and against the selection of

an alternative. Further to the argumentation- based structuring of a collaborative session, this projection integrates a reasoning and scoring mechanism (for details, see (Karacapilidis & Papadias, 2001)), which determines the status of each discourse entry (according to broadly accepted argumentation rules), the ultimate aim being to keep users aware of the most prominent alternative. In the instance of Figure 6, the alternative “Climate change is a security issue, thus it concerns Security Council” wins; this can be changed in another instance of the collaboration, depending on the underlying argumentation. Collaboration through CoPe_it! may continue at the informal projection, where users are able to exploit a richer set of features and functionalities. Alternative projections of a collaboration workspace should be considered jointly, in that a switch from one to the other can further facilitate the argumentative collaboration process. Moreover, a particular collaboration context may be

Figure 4. A filtered view

211

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

Figure 5. A list view

Figure 6. An instance of the formal projection of the collaboration

212

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

better handled through a less or more formal projection. One may also consider the case where decrease of formality is desirable. For instance, while collaboration proceeds through a formal projection, some discourse elements need to be further justified, refined and elucidated. It is at this point that the collaboration session could switch to a more informal view in order to provide participants with the appropriate environment to better shape their minds.

EVAluation ISSUES and Concluding remarks CoPe_it! has been already introduced in diverse collaborative settings (from the management, engineering and learning domains) for a series of pilot applications. The results of the first evaluation phase were very encouraging. So far, the tool has been evaluated by 67 users (belonging to the 12 communities mentioned in a previous section of this paper). The above evaluation was conducted through questionnaires that contained: (i) two sets of closed-ended questions, aiming at evaluating the tool’s ‘perceived usefulness’ and ‘perceived ease-of-use’, and (ii) a number of open-ended questions, through which users were asked to comment on the tool’s advantages, disadvantages and/or limitations, as well as to suggest areas of improvement (Creswell, 2008). A typical fivelevel Likert item (strongly disagree, disagree, neither agree nor disagree, agree, strongly agree) was used for the closed-ended questions. With respect to the questions related to the tool’s perceived usefulness, the percentage of the positive answers (sum of the ‘strongly agree’ and ‘agree’ percentages) in the majority of the questions was very promising. More specifically, 66.1% of the users confirmed that the tool helped them organize the collaboration efficiently, 73.6% that the tool was easy to learn, 71.1% that it was easy to use, 72.5% enjoyed its use, while 66.1% admitted that it was worth the effort. Furthermore,

users have admitted that it stimulates interaction (63%), makes them more accountable for their contributions (64.3%), while it aids them to conceive, document and analyze the overall collaboration context in a holistic manner, by facilitating a shift from divergence to convergence (59.4%). However, users were skeptical about whether they will definitely consider the tool as their first choice for supporting their future collaboration (37.3%). Having further elaborated their answers to this last issue, we concluded that this was due to the change of the way they were accustomed to work. Similar results were obtained for the questions concerning the tool’s perceived ease-ofuse. 82.6% of the users answered positively that were able to easily understand the tool’s features and functionalities, 79.3% found it easy to use all available options, while 75% agreed that the achieved results (after a user’s action) were clear. Nevertheless, only 52.3% could easily understand the contents of a workspace (we have identified that this happens in data-intensive situations; efforts to provide more intuitive workspace icons are underway). The open-ended questions revealed that users considered the ability of the tool to represent and manipulate the structure of an argumentative collaboration, along with its various visualization options, as its strongest features, setting it apart from Web-based forums. Respondents also commented positively on the tool’s ability to provide multiple views of a particular collaborative session. When asked for the tool’s disadvantages, respondents mentioned the cluttering of the workspace (basically due to the numerous arrows that appear in some workspaces), and the inability to make references from a workspace to another. With respect to improvements, most comments were around the need of providing awareness mechanisms that can inform on changes that happen within a workspace, the ability to reuse items between workspaces (by copy-pasting), and the integra-

213

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

tion of video/audio conference tools in order to enhance real time collaboration. Summarizing, we argue that the proposed approach covers fully the user requirements analyzed in this article. Due to its inherent scalability, it is able to fully support the evolution of a cognitively-complex collaboration, while it provides the means for addressing the issues related to the formality needed in collaborative knowledge building systems. It aims at contributing to the field of social software, by supporting argumentative interaction between people and groups, enabling social feedback, and facilitating the building and maintenance of social networks. Future work directions include revision of both tool’s functionalities and user interface according to usability evaluation studies, the development of additional projections, the enhancement of interconnection capabilities with other tools, as well as the experimentation with and integration of additional visualization cues, aiming at further facilitating and augmenting the information triage process.

REFERENCES Ayres, P., & van Gog, T. (2009). State of the art research into Cognitive Load Theory. Computers in Human Behavior, 25(2), 253–257. doi:10.1016/j. chb.2008.12.007 Castells, M. (2004). The Network Society: A Crosscultural Perspective. Edward Elgar. Checkland, P., & Holwell, S. (1998). Action Research: Its Nature and Validity. Systemic Practice and Action Research, 11(1), 9–21. doi:10.1023/A:1022908820784

214

Conklin, J., & Begeman, M. (1989). gIBIS: A tool for all reasons. Journal of the American Society for Information Science American Society for Information Science, 40(3), 200–213. doi:10.1002/ (SICI)1097-4571(198905)40:33.0.CO;2-U Conklin, J., Selvin, A. M., Buckingham Shum, S., & Sierhuis, M. (2001). Facilitated hypertext for collective sense-making: 15 years on from gIBIS. In Proceedings of the 12th ACM Conference on Hypertext and Hypermedia, ACM Press, pp. 123-124. Creswell, J. W. (2008). Educational research: planning, conducting and evaluating quantitative and qualitative research (3rd ed.). Pearson. de Moor, A., & Aakhus, M. (2006). Argumentation support: from technologies to tools. Communications of the ACM, 49(3), 93–98. Fischer, G., Lemke, A. C., McCall, R., & Morch, A. (1991). Making Argumentation Serve Design. Human-Computer Interaction, 6(3-4), 393–419. doi:10.1207/s15327051hci0603&4_7 Halasz, F. (1988). Reflections on NoteCards: Seven Issues for the Next Generation of Hypermedia Systems. Communications of the ACM, 31(7), 836–852. doi:10.1145/48511.48514 Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed Cognition: Toward a New Foundation for Human-Computer Interaction Research. ACM Transactions on Computer-Human Interaction, 7(2), 174–196. doi:10.1145/353485.353487 Kalyuga, S. (2009). Instructional designs for the development of transferable knowledge and skills: A cognitive load perspective. Computers in Human Behavior, 25(2), 332–338. doi:10.1016/j. chb.2008.12.019

Addressing Contemporary Challenges in Cognitively-Complex Collaboration with CoPe_it!

Karacapilidis, N., & Papadias, D. (2001). Computer supported argumentation and collaborative decision making: The HERMES System. Information Systems, 26(4), 259–277. doi:10.1016/ S0306-4379(01)00020-5 Karacapilidis, N., & Tzagarakis, M. (2009). Supporting Argumentative Collaboration in Communities of Practice: The CoPe_it! approach . In Karacapilidis, N. (Ed.), Solutions and Innovations in Web-Based Technologies for Augmented Learning: Improved Platforms, Tools and Applications (pp. 245–257). Hershey, PA: IGI Global. Kirschner, F., Paas, F., & Kirschner, P. A. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25(2), 306–314. doi:10.1016/j.chb.2008.12.008 Kirschner, P., Buckingham Shum, S., & Carr, C. (2003). Visualizing Argumentation: Software Tools for Collaborative and Educational Sense-Making. New York: Springer. Kunz, W., & Rittel, H. (1970). Issues as Elements of Information Systems. Technical Report 0131, Universität Stuttgart, Institut für Grundlagen der Planning. Leutner, D., Leopold, C., & Sumfleth, E. (2009). Cognitive load and science text comprehension: Effects of drawing and mentally imagining text content. Computers in Human Behavior, 25(2), 284–289. doi:10.1016/j.chb.2008.12.010 Marshall, C., & Shipman, F. M. (1995). Spatial hypertext: designing for change. Communications of the ACM, 38(8), 88–97. doi:10.1145/208344.208350 Marshall, C., & Shipman, F. M. (1997). Spatial Hypertext and the Practice of Information Triage. In Proceedings of the 8th ACM Conference on Hypertext, pp. 124-133.

Nonaka, I. (2005). Knowledge management: critical perspectives on business and management. Boca Raton, FL: Taylor & Francis. Reed, C. A., & Rowe, G. W. A. (2004). Araucaria: Software for Argument Analysis, Diagramming and Representation. International Journal of AI Tools, 14(3-4), 961–980. doi:10.1142/ S0218213004001922 Shipman, F. M., & Marshall, C. C. (1994). Formality Considered Harmful: Issues, Experiences, Emerging Themes, and Directions. Technical Report ISTL-CSA-94-08-02, Xerox Palo Alto Research Center. Shipman, F. M., & McCall, R. (1994). Supporting knowledge-base evolution with incremental formalization. In Proceedings of the CHI ’94 Conference, pp. 285-291. Stegmann, K., Weinberger, A., & Fischer, F. (2007). Facilitating argumentative knowledge construction with computer-supported collaboration scripts. International Journal of ComputerSupported Collaborative Learning, 2(4), 421–447. doi:10.1007/s11412-007-9028-y Suthers, D., Weiner, A., Connelly, J., & Paolucci, M. (1995). Belvedere: Engaging students in critical discussion of science and public policy issues. In Proceedings of the 7th World Conference on Artificial Intelligence in Education, pp. 266-273. van Gelder, T.J. (2002). Argument mapping with Reason!Able. The American Philosophical Association Newsletter on Philosophy and Computers, 85-90. Verheij, B. (2003). Artificial argument assistants for defeasible argumentation. Artificial Intelligence, 150(1-2), 291–324. doi:10.1016/S00043702(03)00107-3 Wenger, E. (1999). Communities of Practice: Learning, Meaning and Identity. Cambridge, UK: Cambridge University Press.

215

216

Chapter 12

Integrating XML Technologies and Open Source Software for Personalization in E-Learning Hsun-Ming Lee Texas State University-San Marcos, USA Robert A. Davis Texas State University-San Marcos, USA Yu-Liang Chi Chung Yuan Christian University, Taiwan

ABSTRACT E-learning that emphasizes learner-centered activity and system interactivity provides a pedagogic opportunity to deliver a context for individual learning options. In the past decade, e-catalog standards based on learning object models have facilitated the design of e-learning systems. This study addresses issues for e-learning in a professional setting to foster the development of computer skills in students. In particular, personalized templates generated according to student and learning object models are proposed for instructors to provide practice exercises. Standardized XML technologies and open source software are integrated to create information filters and user interfaces to achieve personalization. The students use open source software that acts as a new type of Web client other than a browser. A case study that applies personalized templates for the learning of computer programming students with different skill levels is presented.

INTRODUCTION Web-based distance learning, which is commonly referred to as e-learning, emphasizes learnercentered activity and system interactivity. Therefore, remote learners can potentially outperform DOI: 10.4018/978-1-60960-153-9.ch012

traditional classroom students (Zhang, Zhao, Zhou, & Nunamaker, 2004). The development of an e-learning system typically requires the use of standardized Web technologies to transmit dynamic content to students. To facilitate content creation and customization on the Web, it has been suggested that course materials be edited with XML (Extensible Markup Language)

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

tools (Li, Shi, Shang, & Chen, 2003; Koohang, 2004). XML specifies learning objects that are used systematically to form teaching units, modules, or courses. The key advantage of learning objects is their potential sharability, which has motivated organizations to develop standards for their large-scale application. Following this trend, the Advanced Distributed Learning (ADL) initiative of the U.S. Department of Defense has taken the XML specification further and provided the Shareable Content Object Reference Model (SCORM) standard to enable the interoperability, accessibility, and reusability of Web-based learning content (Lee & Su, 2006; Wang & Hsu, 2006). The requirements of e-learning standards for educational institutions are similar to those of e-catalog standards that address the inter-organizational exchange of catalog data in e-business (Schmitz & Leukel, 2005). However, instead of profitability, a key emphasis in the development of e-learning systems is personalization to help every student succeed. For example, the University of Hong Kong has developed the Web-based SmartTutor to provide personalized advice to students based on their individual backgrounds and experience (Cheung, Hui, Zhang, & Yiu, 2003). Personalization refers to information that is customized for each user and is personally relevant. Kamba, Sakagami, and Koseki (1997) reported a project in which personalization was applied to an online newspaper, and they highlighted the importance of user interfaces and information filtering in achieving this. In their personalized newspaper system, a Web server managed the article data and each user’s profile, scored all of the articles, and sent an interaction agent to run in a client’s browser. This agent monitored user operations and created personalized newspaper pages automatically. Recently, the research on Web-based personalization has advanced to apply personal information to the generation of individual paths of reading material or assessments in e-learning systems (Ceri, Dolog, Matera, & Nejdl, 2005; Chen, Lee, & Chen, 2005).

To support the personalization of Web applications, technology is usually employed to store as much historical user data as possible and then to query that data as users navigate through a Web site (Datta, Dutta, VanderMeer, Ramamritham, & Navathe, 2001). However, the implementation of personalization in e-learning systems is still challenging because of the following technological issues. •

•

Although the configuration of personalized services can be developed, it lacks flexibility in the accommodation of domainspecific requirements (Ardissono, Goy, Petrone, & Segnan, 2005). Although reading on the Web can be personalized to provide effective learning through the adaptation of navigation directions to the abilities of learners, browseroriented Web systems limit learning activities to reading.

These issues are evident when an e-learning system is constructed to teach advanced computer skills because (a) the teaching of constantly changing computer technologies requires flexibility for the frequent update of curricula, and (b) computer skills are developed and learned by doing. These constraints of the personalization technologies used in conventional e-learning systems are addressed in this study. The solution is system architecture that generates personalized templates (custom learning objects) on the open source software that is used as a learning tool. In this architecture, the personalized templates are created through the application of emerging XML tools. This template-based approach emphasizes learning by doing, which motivates students to learn and produces more effective learning outcomes than do passive approaches, such as traditional lectures (Wang, 2003). The architecture provides valuable features for both instructors and students. Instructors are able to set up XML-based rules to determine dynami-

217

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

cally the skill levels of individual students, and the students are then able to create personalized templates in open-source software.

TECHNOLOGY OVERVIEW XML technologies and open-source software are involved in the development of personalization functions for the proposed system architecture. Each of these technologies is further discussed to provide the necessary foundation for understanding this architecture.

XML Technologies Today’s Web increasingly uses XML to encode information and services. The power of XML lies in its ability to enable interoperability and simplify the sharing and reuse of information (Glushko, Tenenbaum, & Meltzer, 1999). However, XML is not a cure-all for system interoperability, but rather a widely accepted foundation layer on which to build (Smith & Poulter, 1999). To address the needs of the future Web, advanced XML-based tools, such as OWL (Web Ontology Language), have recently been developed as standards to represent human concepts (W3C, 2004a). OWL, which provides vocabulary along with formal semantics, facilitates greater machine interpretability of Web content than that supported by XML. Using the OWL syntax, the Semantic Web Rule Language (SWRL) allows the formal definition of an if-then rule to develop intelligent Web systems (W3C, 2004b). For the sake of readability, an SWRL rule is often written in the form antecedent ⇒ consequent, where both antecedent and consequent are conjunctions of atoms that are written a1 ∧...∧ an. Literals, names, and variables are used in these atoms. The literals are numbers, strings, or Boolean values; the names identify Web resources expressed in Web ontology, such as the “Mary-20” named object of the “Student” class; and the variables are indicated using the standard

218

convention of prefixing them with a question mark (e.g., ?x). There are various types of atoms, examples of which are as follows. •

•

•

Class atoms are used to determine whether the variable or named resource is a member of the specified OWL class. Individual property atoms are constructed from an OWL object property, which represents relations between the objects of two OWL classes. Two parameters are required, and each parameter is either a variable or a named resource. Data-valued property atoms are represented in the same way as individual property atoms. The second parameter must be either a literal value or a variable that represents the value.

For an e-learning server, XML-coded messages can be sent from, received by, and transformed in any client software that readily understands their structures and semantics.

Open Source Software Many of today’s most innovative computer technology products and solutions, which include operating systems, databases, Web servers, and development tools, are developed on the basis of free and open source software (Ebert, 2008). Open source communities have created several successful Web-based learning systems, such as .LRN and Sakai, that are widely used for higher education. The University of Valencia in Spain uses the .LRN platform to support traditional classroom learning for nearly 40,000 students and 250 professors (Escobedo del Cid, de la Fuente Valentín, Gutiérrez, Pardo, & Kloos, 2007). Sakai is an online collaboration and learning environment that has been deployed to support teaching and learning, collaboration, and research collaboration for more than 20,000 students at Texas State University - San Marcos, USA (Muniz-Solari &

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Coats, 2009). The main advantage of using open source e-learning systems is the access to source code, providing almost limitless opportunities for system modification and integration to extend the software components, content libraries, and teaching and learning tools (Stephenson, 2006). As the popularity and functionality of the elearning servers grows, many open source tools are continuously enhanced and developed as standalone clients running on personal computers (PCs) or workstations. For example, Eclipse (eclipse.org) and NetBeans (netbeans.org) have been used to teach students who are working on the modeling, programming, and testing of application development in their college classes. However, the form-based editors that allow the students to write and submit assignments via Web browsers seem to be more convenient than open source software in providing computer education tools for e-learning systems (Mitrovic, 2003; Sandvig, 2004). Frustration is often the result in browser-based environments, though, because the user interfaces provide very little in the way of editing capability, and they certainly have no facilities to help students to correct syntactical errors (Sloane & Waite, 2005). Moreover, many professional skills have to be developed with the use of sophisticated software tools that are often installed in PCs or workstations. To prepare students for their work environments, college professors have created various courses that emphasize hands-on exercises with non-Web-based open source software, such as the Weka machine learning workbench for Data Mining (Witten & Frank, 2005) and IPCop Firewall for Network Security (Balan, 2009). Open source tools installed on a PC or workstation provide a rich user interface and considerable built-in functionality. In addition, it is also possible to extend open source software through plug-ins to connect to the e-learning servers, and to process XML messages on the Web. A plugin is a functional unit that can be developed and delivered separately—even after the open source

software has been installed. For example, the Eclipse plug-in development environment (PDE) provides extended points of views, editors, and wizards that make it easier to build plug-ins for Eclipse. The software tools that are coded and plugged into Eclipse supply the specific features that make the Eclipse PDE suitable for developing new kinds of applications (Guyon, Moreau, & Reilles, 2004).

LEARNING TEMPLATE PERSONALIZATION Our Learning Template Personalization (LTP) system architecture, which is illustrated in Figure 1, is designed to allow instructors to implement tutoring strategies in distance education through the provision of tutorials. Zachary (1994) suggested that an ideal tutorial-based system for introductory computer classes would operate as follows. • • •

The teacher explains the material carefully. The teacher designs and implements demonstrations to reinforce the explanations. The student practices the material that has just been learned via hands-on experimentation (exercises).

Explanations, demonstrations, and practice lead the student to ask questions, which the teacher then answers. Following this description, we develop system architecture that is made up of (a) legacy modules, which commonly exist in traditional or online classes, and (b) the personalization modules that are proposed in this study to generate and deliver personalized practices (templates) to online learners. Templates are typical examples that are prepared by the instructor for the class. Students are expected to modify the templates to create their assignment solutions using an open source tool. To get the students ready for their as-

219

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Figure 1. Learning template personalization (LTP) system

signments, the critical task of the instructor is to provide templates in a format that is appropriate to the learner’s current state of understanding. The legacy modules are described as follows. •

•

•

A learning object repository stores instruction units that include the reading materials of the lessons and complete exercises to demonstrate those lessons. The open source software on a PC provides students with the tools to practice the computer concepts. Student assessment databases record information on students, the courses (or instruction units) they have taken, and the grades they have received in the courses. XML tools are used to represent this student performance data to determine the skill levels of students in a personalization module.

Students ask questions in an online discussion forum that is created by the instructor or send emails directly to the instructor.

220

The challenging aspects of architecture implementation are the modules that generate personalized templates on the server (the learning object filter) and then send these templates to open-source software on the PC through the Internet (Web connector). •

•

A learning object filter in the server creates personalized templates that match the skill levels of the individual students who practice the computer exercises in open source software. This filter reads the learning objects of a complete demonstration and then removes parts of the content according to the model that is designed in this study to determine the student skill level and the corresponding template. This model is presented in the later sections of the article. A Web connector allows the students to acquire a partially finished exercise (template) to start a practice session. Within the open-source software, the students start the Web connector, load a personalized

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

template, and interact with the software to achieve the assignment goal—the originally completed demonstration. The connector facilitates the learning process by seamlessly establishing an information channel for the separated education resources: the e-learning servers and the PC-based open source software.

subjects, courses, materials, and exams. There are hierarchal and sequential relationships, as follows. •

•

PERSONALIZED TEMPLATES Personalized templates mean that only parts of the content of the learning objects are transported to the open source software through the Web. Our LTP architecture supports the creation and delivery by teachers of lab assignments with various difficulty levels. The criteria for the determination of the difficulty level may vary from class to class. To filter and transfer data on the Web, a student model is developed as a common information standard for LTP.

Student Model In the LTP architecture, the student model is intended to be an open interface that links the assessment data to the learning objects that are contained in various courses. The model is mainly used to track learning progress by maintaining learning paths for individual students. The learning objects are created through a Content Repository Management System (CRMS) that consists of an authoring tool, administrative tools, and a learning object repository (Yang, Yu, Chen, Tsai, Lee, & Shih, 2005). Learning paths, which allow learners to achieve their learning goals gradually, can be built with a knowledge framework based on OWL (Chi & Lee, 2006). Briefly, the learning paths in the framework are developed into a knowledge base that consists of the knowledge acquired from domain experts (instructors). The OWL knowledge representation captures the relations of learning objects, such as

The hierarchal relationships form learning objects in a taxonomy, like an organizational chart. For example, a course has many subjects, and each subject has many exams. The sequential relationships denote the dependencies among subjects. For example, students must have learned a programming language before taking a data structure subject in Computer Science.

To facilitate the development of learning paths, patterns that describe the sequential relationships are also introduced in the framework, as follows. •

•

•

Sequence: after the completion of one subject, another subject is made available to the student. Merge: after the completion of multiple subjects, one subject is made available to the student. Split: after the completion of one subject, multiple subjects are made available to the student.

A sample network of learning paths is illustrated in Figure 2, which is created using the patterns. A subject in the path is marked (with an X in Figure 2) to indicate that the student has mastered the subject material, based on his or her evaluation results and grades in the assessment database. Typically, a group of students shares a learning path structure with a common instructor. Given the different marks on the individual paths, the instructor is able to write model-embedded rules that dynamically determine the student skill levels according to criteria that assist them in various curricula.

221

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Figure 2. An example of learning paths

Learning Object Filter When the learning path of an individual student is available, a personalized template can be created by the filter. This filter is intelligent in the sense that it is capable of interpreting the human concepts that are represented in the student model. Moreover, it is an agent that acts on the rules that are set up by instructors. It should be noted that the learning path is defined by the OWL language. Thus, SWRL is utilized by the filter to reason about the learning path. To compute the skill level, general rules that apply to any learning path are defined, as follows. • •

•

222

Initialization rule: the start node must be marked. Progress rule: the student progresses to a subject if two nodes that have a sequential relationship are both marked. Transitive rule: the student makes progress from subject A to subject B and from subject B to subject C; then, it is also true that

•

the student makes progress from subject A to subject C. Error rule: the learning path has an error if some subjects are merged with a more difficult subject that is marked; however, one of the subjects before the merger is not marked.

Based on these general rules, instructors create their own rules to determine the skill levels of their students. These SWRL-expressed rules are stated as: a student learning path indicates a certain skill level if (1) it is initialized; (2) it has no errors; and (3) the student has progressed through a list of subjects. A table (see Table 1) is designed to allow instructors to set up the skilllevel rules conveniently. Computer software can be easily developed to generate SWRL rules from the table, in which each column represents a skill level. A student qualifies for a level if he or she has progressed through all of the subjects that are checked in the corresponding column. It should be noted that it is not necessary to check all of the subjects that are required by the level.

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Table 1. Use of learning paths for determining student skill levels Beginner Java Concepts

X

Database Concepts

X

Essential Java Classes

Intermediate

Advanced

X X

X

Data Structure

X

ER Diagram

X

Java Networking J2EE Application Development

Often, a student has to comprehend a sequence of subjects before studying a difficult subject. If the difficult subject is checked in the column, then it is implied that the sequence of subjects is required. For example, the “Essential Java Classes” subject is required for the intermediate level. Therefore, the “Java Concepts” subject is also implicitly required, although it is not checked in the “Intermediate” column (see Figure 2 for the learning sequence). To generate a personalized template, the LPT system must provide pre-built functions that filter the content of a complete exercise (learning object). The instructor who owns the learning object specifies the personalized templates for the students in different difficulty levels in terms of what content has been removed from the complete program. The implementation of a learning object filter is described in the case study.

Web Connector A Web connection is established by the plug-in of open source software and the application of Web service technologies. A Web service describes any application that exposes its functionality to other applications through the use of the aforementioned open standards. Web services are developed with existing software applications to create “new” integrated applications. In this LTP environment, Web services are used as interfaces for the filter to offer learner skill levels and templates. The

plug-in software connects to the Web service through Simple Object Access Protocol (SOAP), which provides the standards for exchanging XML-structured information in a decentralized computing environment. An example of the plugin is presented in the case study. Next, we present the case study to test the feasibility of this system design.

CASE STUDY Based on the opinions of a group of information systems instructors, Java Database Connectivity (JDBC) is useful for demonstrating the applications of various subjects. Thus, a set of Java database programming labs (templates) is developed for the case study. Figure 3 shows the complete version of a program that uses the JDBC library to connect to a Microsoft Access database. The program transfers data from a database record to a simple employee object in Java. A prototype of the LTP system is developed to assist the teaching of application development at a comprehensive university. It includes an e-learning site that provides the personalized labs with the program in Figure 3 as a learning object. This case study simulates the e-learning of a group of students that followed the same learning path as that shown in Figure 2. Three traditional classes of students were chosen to represent online students with the beginner, intermediate, and

223

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Figure 3. A complete Java database application program

advanced levels of skills, as defined in Table 1. The first level consisted of 49 beginners who were taking their first programming class; the second level was considered to be intermediate because it consisted of 37 sophomores who had passed their first programming course when they learned data structure concepts; and the advanced level consisted of 15 students who had been admitted to a graduate information systems program. Based on the hierarchal relationships of the learning objects, the JDBC lab can be included in any subject. With the student model, an online

224

instructor can assign the lab flexibly to emphasize the connection between the computer programs and the databases in covering the subject. Thus, each student is given reading material and the lab to learn a particular topic in the selected subject at his or her level. The students in the same level have identical assignments. We provided online presentations, sample programs, and Eclipse to all of the students who were to study the assignment in a fixed period. The selected students were randomly assigned to a treatment or control group. The former group could generate personalized labs

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

in Eclipse to study the given topic, and the latter could use Eclipse to create the labs completely from scratch. The Eclipse tools provide students the necessary facilities that are not available on the Web-based learning servers, such as automatic syntax correction, fast program compilation, configurable connectivity to databases, and sophisticated debugging tools. Learners in the beginner level of the treatment group were offered two exercises that provided all of the sources except for the parameter values in Steps 3 or 5. In other words, learners had to enter the database connection string (“jdbc:odbc:employee”) or construct a simple Structured Query Language (SQL) string to execute the program successfully and correctly. There were two intermediate-level lab exercises. One was created by the removal of entire statements in Steps 2, 3, and 8, which focused on writing code to set up and close a database connection. The other covered object concepts with the code in Step 7 removed. Learners in the advanced level received a template without the statements in Steps 4, 5, 6, and 7; therefore, they had to apply the object concepts and the JDBC data retrieval mechanism together to finish the lab exercise. The personalization feature of this prototype system is described as follows. The filter includes the pre-built functions that remove parts of a state-

ment or a few lines of the program. Two tables (see Table 2 and 3) are used to set up the generation of the personalized templates. Table 2 allows the instructor to remove the code in a statement. There are name, level, file, line, and string columns. For each row in Table 2, the string is removed in the specified line from the file to generate a named template. Similarly, Table 3 is designed to remove code from the start line to the end line. Note that there may be several templates in the same level. To use the prototype system, online learners are required to have open source Eclipse as a programming tool on their computers to connect to the Internet. They can then acquire and install the Eclipse plug-in wizard that is offered by this system to link to the e-learning site via the Internet. The plug-in was developed specifically for this prototype system, which is a Web connector that requests the personalized templates offered by the site. The views of the wizard created for this case study are shown in Figure 4. The overall system operates in the following way. 1. The learner configures the plug-in in Eclipse by entering a user name and the address of the targeted Web site. 2. The learner starts the plug-in (wizard), and the first view in Figure 4 is then displayed.

Table 2. Setup for removing strings in computer programs Name

Level

File

Line

String

Connection

Beginner

DbLab.java

22

jdbc:odbc:employee

Instantiation

Intermediate

DbLab.java

32

new employee()

SQL

Beginner

DbLab.java

27

select * from employee

Table 3. Setup for removing lines in computer programs Name

Level

File

Start Line

End Line

Conn-Stat

Intermediate

DbLab.java

19

20

Instantiation

Intermediate

DbLab.java

33

35

225

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

3. The learner selects a lab (e.g., JDBC Example) and clicks the “next” button, and the plug-in then connects to the Web service to obtain the learner’s skill level. 4. The plug-in also uses the Web service to retrieve all of the possible levels that are displayed in the second view. 5. The plug-in highlights and selects the learner’s level in the second view. 6. The learner confirms the skill level and clicks the “next” button, and the plug-in then retrieves a list of the templates in that level and displays it in the third view. 7. The learner selects a template (e.g., Setting up a connection string) and clicks the “finish” button. 8. The Web service is activated and requests the selected template from the object filter and passes it to the plug-in. 9. The plug-in receives the template and generates its files for a new project in Eclipse. 10. The learner starts working on the project as a lab assignment.

After the three classes in the case study had completed the learning sessions, all of the students answered a questionnaire. The questionnaire was based on a seven-point Likert scale of student perceptions of their learning experiences. The scale ranged from “strongly disagree” (1) to “strongly agree” (7). The 14 questions in the questionnaire were placed into two categories: interest and satisfaction. The results of a comparison between the students in the three classes who used the personalized templates and those who did not are shown in Table 4. Remark: the symbol n is the number of students. The treatment (A) and control (B) groups consisted of students who learned with and without the personalized templates, respectively.

DISCUSSION AND LIMITATIONS The preliminary evaluation on the effectiveness of the LTP system is encouraging. The student surveys show positive feedback from the treatment

Figure 4. The forms of the Eclipse plug-in wizard that were developed to create personalized templates

226

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Table 4. Results of the learning sessions with and without the personalized labs Beginner (n=49) A (n=25)

Intermediate (n=37) B (n=24)

A (n=18)

Advanced (n=15)

B (n=19)

A (n=8)

B (n=7)

Mean ± (S.D.) Interest

5.6 (1.06)

3.63 (0.78)

4.86 (0.73)

3.21 (0.72)

4.05 (1.14)

3.31 (0.64)

Satisfaction

5.1 (1.02)

3.13 (0.55)

4.44 (0.65)

3.37 (0.78)

3.8 (0.93)

2.94 (0.78)

group who learned with personalized exercises. In general, the LTP system is useful in increasing student interest and satisfaction in learning computer programming. There is direct interaction between the student and the LTP’s Web site, which is tailored to meet the specific needs of the participants in the course being considered, and this is seen as crucial to improving students’ satisfaction with e-learning (Bouhnik & Marcus, 2006). Based on the scores, it seems that the system is more effective for beginner and intermediate learners than for advanced learners. However, the current case study is limited, and the effective-

ness of the LTP system for learning performance remains an open question. We find that related studies (Cheung et al., 2003; Esmahi, 2007) of e-learning personalization have not reported any evidence for improvements in student performance. Thus, a full-scale case study that observes performance across semesters and subject areas is planned for the future. Although it is still in prototype, the LTP system has a lot of potential and can be qualitatively compared with related systems to show its benefits. The results of comparisons are summarized in Table 5. First, SmartTutor is an intelligent tutor-

Table 5. Comparing LTP, SmartTutor, ALEKS and the Athabasca system Features

LTP System

SmartTutor

Athabasca

ALEKS

Content & Connectivity Content Domain

Technologies (Prototype)

Across domains (For a Single University)

No implementation

Math. (Commercial)

Browser to server

No

Yes

Yes

Yes

Server to server

Yes

No

Yes

No

Mobile devices to server

No

No

Yes

No

Client tools to server

Yes

No

No

No

Course Authoring

Yes (but only integrates materials in existing servers)

Yes (but uses integration with an e-learning platform)

Yes

No

Course Study Plan

Yes

Yes (generated by teachers and students)

Yes

No (but can provide many topics)

Test Generator

No

Yes (based on students’ knowledge background)

No

Yes

Problem Generator

Yes

No

No

Yes

Personalization

227

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

ing system implemented for distance learning in Hong Kong (Cheung et al., 2003). Second, Esmahi (2007) designs a multi-agent system for delivering adaptive e-learning at Athabasca University in Canada. Finally, ALEKS is an artificially intelligent assessment and learning system that uses adaptive questioning to quickly and accurately determine exactly what a student does and doesn’t know in a course (ALEKS Corporation, 2009). LTP, SmartTutor and the Athabasca system have tools for authoring course material and relationships among concepts across courses. As a result, teachers can develop a study plan that defines the sequencing of course content. Moreover, SmartTutor allows the student to select the topics he or she wants to learn, and subsequently generate the proper parts of the whole content structure. In contrast, ALEKS provides courses and their contents as products, making it easy to monitor student, class, school, and district progress toward mathematics standard for grades 3–12 in the USA. The ALEKS assessment function, which is based on Knowledge Space Theory developed since 1983 by Professor Jean-Claude Falmagne and other scientists in the United States and Europe, is the heart of the ALEKS system (ALEKS Corporation, 2008). The teacher’s menu indicates that a test is scheduled and is automatically generated after 20 new items have been learned, or after 10 hours have been spent in learning or 60 days have passed since the last assessment,. The ALEKS system is able to quickly and accurately determine a student’s knowledge using an adaptive assessment; that is, problems are selected based on all of the previous answers the student has given. It appears that LTP, SmartTutor and the Athabasca system are better suited for e-learning at universities, where professors have greater freedom to independently develop and maintain their own curricula. The personalization allowed by these systems focuses on giving appropriate levels of challenge on relevant learning material to individual students. Of course, assessment is

228

required to determine the learning progress. SmartTutor generates test papers based on students’ knowledge background, testing goals, and learning stages. Although they do not include any assessment features, FLP and the Athabasca system are XML-based and are open to integrate available computer-based assessment or grade management tools. The test produced by these systems is not adaptive as is ALEKS, which may be due to the difficulty of standardizing the courses for programs in higher education. All of the systems discussed here are built on the Web infrastructure, and client software is used to connect to e-learning servers on the Internet. SmartTutor and ALEKS solely consider the connection from browser-based clients to a single e-learning server. However, openness to third-party content providers and user-side device independence for Web content should be provided in the personalization process of future e-learning systems (Esmahi, 2007). In the Athabasca system, a tutor agent ensures the adaptation and packaging of external course content, and an XML transformation service generates a rendering format that depends on the mobile device’s features. In a similar fashion, the LTP system separates content generation from the distribution to a client. Thus, the personalization offered by LTP can involve any open source tool (application) installed in any computing machine or device. The LTP system is not designed for the use of browsers. It is intended to supplement existing e-learning systems and is especially suitable for the education of technologies such as computer programming, data mining, and network security. In these areas, short presentations and lectures interlaced with a great deal of hands-on activities are the preferred methods of learning for careeroriented students (Balan, 2009). Personalized, hands-on lab problems are generated in LTP, the key technology advantages of which are (a) accessibility (the XML technique allows the flexible integration and configuration of Web-based course content into a personalization process), and

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

(b) availability (personalized content is directly transmitted to open source software with which students interact).

CONCLUSION E-learning systems provide a learner-centered and interactive environment that foster learning without the restrictions of geographical boundaries. We argue that learning computer technology skills via the Web requires an integrated system to view browser content and practice professional tools. We have therefore applied emerging XML technologies, including OWL, semantic Web rules, and Web services, to develop user interfaces and information filters, and thus provide personalized templates. With the use of open source tools, online learners are able to practice concepts through the creation of custom templates that are personalized based on their skill level. This system stores an instruction unit as a set of OWL objects on the Web. The content is filtered by semantic Web rules and delivered through Web services. A plug-in is developed to act as a Web service client and allows direct access to the personalized program templates from the open source software. The filter uses semantic Web rules on top of Web ontology to configure the difficulty levels of the templates. The configuration is flexible, due to the separate standardization of the content definition and the logic of the content delivery. Such an XML-based design allows the implementation of more personalization features on existing elearning systems. It requires only the small cost of changing them with: (1) a free and open-sourced learning tool; (2) lightweight plug-in software that seamlessly transfers personalized material from the e-learning servers to student computers, and (3) shared learning objects for reading the material on the Web browsers and the downloaded assignments in the tools. More importantly, the system demonstrates that it is feasible and valuable to

build a Web-based structure for the personalization of hands-on practice exercises. This study focuses on the integration of open technologies that support the development of personalized templates. The student models and filtering rules that are keys to the implementation provide XML-based knowledge representation. Thus, this system has the potential to use e-learning standardization (such as SCORM) to allow the referencing of personalized templates across multiple educational institutions.

ACKNOWLEDGMENT The authors thank the anonymous reviewers for their valuable comments.

REFERENCES W3C. (2004a). OWL Web ontology language reference. Retrieved August 20, 2009, from http:// www.w3.org/TR/2004/R EC-owl-ref-20040210/. W3C. (2004b). SWRL: A semantic Web rule language combining OWL and RuleML. Retrieved August 20, 2009, from http://www.w3.org/ Submission/SWRL. ALEKS Corporation. (2008). ALEKS teacher’s menu for K-12 (Version 3.8). Retrieved August 20, 2009, from http://www.aleks.com/k12/ user_guides ALEKS Corporation. (2009). ALEKS Corporation Web site. Retrieved August 20, 2009, http:// www.aleks.com Ardissono, L., Goy, A., Petrone, G., & Segnan, M. (2005). A multi-agent infrastructure for developing personalized Web-based systems. ACM Transactions on Internet Technology, 5(1), 47–69. doi:10.1145/1052934.1052936

229

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Balan, C. (2009). Teaching security concepts using hands-on and open source products. Journal of Computing Sciences in Colleges, 24(6), 144–145. Bouhnik, D., & Marcus, T. (2006). Interaction in distance-learning courses. Journal of the American Society for Information Science and Technology, 57(3), 299–305. doi:10.1002/asi.20277 Ceri, S., Dolog, P., Matera, M., & Nejdl, W. (2005). Adding client-side adaptation to the conceptual design of e-learning Web applications. Journal of Web Engineering, 4(1), 21–37. Chen, C.-M., Lee, H.-M., & Chen, Y.-H. (2005). Personalized e-learning system using item response theory. Computers & Education, 44(3), 237–255. doi:10.1016/j.compedu.2004.01.006 Cheung, B., Hui, L., Zhang, J., & Yiu, S. M. (2003). SmartTutor: An intelligent tutoring system in Web-based adult education. Journal of Systems and Software, 68(1), 11–25. doi:10.1016/S01641212(02)00133-4 Chi, Y.-L., & Lee, H.-M. (2006). Building conceptual knowledge for managing learning paths in e-learning. Lecture Notes in Artificial Intelligence, 4092, 66–77.

Esmahi, L. (2007). An agent-based framework for personalized e-learning services. International Journal of Web-Based Learning and Teaching Technologies, 2(4), 1–11. Glushko, R. J., Tenenbaum, J. M., & Meltzer, B. (1999). An XML framework for agent-based ecommerce. Communications of the ACM, 42(3), 106–114. doi:10.1145/295685.295720 Guyon, J., Moreau, P.-E., & Reilles, A. (2004). An integrated development environment for pattern matching programming. Electronic Notes in Theoretical Computer Science, 107, 33–49. doi:10.1016/j.entcs.2004.02.045 Kamba, T., Sakagami, H., & Koseki, Y. (1997). ANATAGONOMY: A personalized newspaper on the World Wide Web. International Journal of Human-Computer Studies, 46(6), 789–803. doi:10.1006/ijhc.1996.0113 Koohang, A. (2004). Creating learning objects in collaborative e-learning settings. Issues in Information Systems, 5(2), 584–590. Lee, G., & Su, S. Y. W. (2006). Learning object models and an e-learning service infrastructure. International Journal of Distance Education Technologies, 4(1), 1–16.

Datta, A., Dutta, K., VanderMeer, D., Ramamritham, K., & Navathe, S. B. (2001). An architecture to support scalable online personalization on the Web. The International Journal on Very Large Data Bases, 10(1), 104–117.

Li, L., Shi, H., Shang, Y., & Chen, S.-S. (2003). Open learning objects for data structure course. Journal of Computing Sciences in Colleges, 18(4), 56–64.

Ebart, C. (2008). Open source software in industry. IEEE Software, 25(3), 52–53. doi:10.1109/ MS.2008.67

Mitrovic, A. (2003). An intelligent SQL tutor on the Web. International Journal of Artificial Intelligence in Education, 13, 173–197.

Escobedo del Cid, J. P., de la Fuente Valentín, L., Gutiérrez, S., Pardo, A., & Kloos, C. D. (2007). Implementation of a learning design run-time environment for the. LRN learning management system. Journal of Interactive Media in Education. Retrieved August 20, 2009, from http://jime. open.ac.uk/2007/07

Muniz-Solaris, O. A., & Coats, C. (2009). Integrated networks: National and international online experiences. The International Review of Research in Open and Distance Learning, 10(1). Retrieved August 20, 2009, from http://www.irrodl.org/ index.php /irrodl/issue/view/33

230

Integrating XML Technologies and Open Source Software for Personalization in E-Learning

Sandvig, J. C. (2004). ASPEN—a Web-based application for managing student server accounts. Campus-Wide Information Systems, 21(4), 157– 162. doi:10.1108/10650740410555034 Schmitz, V., & Leukel, J. (2005). Findings and recommendations from a Pan-European research project: Comparative analysis of e-catalog standards. International Journal of IT Standards and Standardization Research, 3(2), 51–65. Sloane, A. M., & Waite, W. M. (2005). Eclipse support for using Eli and teaching programming languages. Electronic Notes in Theoretical Computer Science, 141(4), 189–194. doi:10.1016/j. entcs.2005.02.058 Smith, H., & Poulter, P. (1999). Share the ontology in XML-based trading architectures. Communications of the ACM, 42(3), 110–111. doi:10.1145/295685.295891 Stephenson, D. (2006). Futures in e-learning. Campus-Wide Information Systems, 23(2), 102–103.

Wang, M. (2003). Teaching Web-driven database application with templates. Information Systems Education Journal, 1(11), 1–8. Witten, I. H., & Frank, E. (2005). Data mining: Practical machine learning tools and techniques (2nd ed.). San Francisco: Elsevier. Yang, J. T., Yu, P. T., Chen, N. S., Tsai, C. Y., Lee, C. C., & Shih, T. K. (2005). Using ontology as scaffolding for authoring teaching materials. International Journal of Distance Education Technologies, 3(1), 81–96. Zachary, J. (1994, March). Tutorial-based teaching of introductory programming classes. In Proceedings of the 25th SIGCSE Symposium on Computer Science Education,Phoenix, AZ (pp. 136-140). ACM Publishing. Zhang, D., Zhao, J. L., Zhou, L., & Nunamaker, J. F. (2004). Can e-learning replace classroom learning? Communications of the ACM, 47(5), 75–79. doi:10.1145/986213.986216

Wang, H.-C., & Hsu, C.-W. (2006). Teachingmaterial design center: An ontology-based system for customizing reusable e-materials. Computers & Education, 46(3), 458–470. doi:10.1016/j. compedu.2005.09.005

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 39-54, copyright 2009 by Information Science Reference (an imprint of IGI Global)

231

232

Chapter 13

Autism and Family Interventions Through Technology: A Description of a Web-Based Tool to Educate Fathers of Children with Autism Richard E. Ferdig Kent State University, USA Hilary G. Amberg University of Florida, USA Jennifer H. Elder University of Florida, USA Susan A. Donaldson University of Florida, USA Gregory Valcante University of Florida, USA Roxanna Bendixen University of Florida, USA

ABSTRACT Most research on family interventions of children with autism has focused on the role of the mother, and little is known about the effects of training fathers. Through a series of National Institutes of Health– funded studies we have demonstrated treatment success by focusing on fathers who are trained at home. Although our research has been successful, this work introduces questions related to how best to train fathers when on-site, in-home training is not a viable option due to geographical distance or a variety of other logistical constraints. This article describes the development and initial use of an Internetbased tool to offer this training more broadly. We briefly describe past research as well as the need for the implementation of an Internet-based tool. We then describe the system, document early indicators of success, and discuss metrics we are using with our fathers. The article concludes with a discussion of future goals and research needs. DOI: 10.4018/978-1-60960-153-9.ch013 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Autism and Family Interventions Through Technology

INTRODUCTION Recent research has indicated that 1 of every 150 children is diagnosed with autism (http://www. autism.com). The developmental disorder has become so commonly diagnosed that April has been designated Autism Awareness Month, and April 2 is World Autism Awareness Day (http:// www.worldautismawarenessday.org). Although there are a wide variety of treatment options for autism, including educational and behavioral interventions, medications, and therapies, some may lead to great improvement while others may have little or no effect (Elder, 2002). As the number of reported cases of autism has increased, the amount of autism-related research has also increased (Rapin, 2002). In addition to research related to the possible causes of autism, researchers are also interested in finding successful and appropriate ways to help children with autism learn and function better in society.

Understanding the Involvement of the Family One significant area of current research is the involvement of the family. Calabrese (2006) reports that, in general, when schools, parents and students communicate and work together, children benefit academically, socially, and emotionally, leading to a young child’s success in school. Children whose parents are involved in their academic life have a more positive attitude about school, improved attendance, and show better homework habits than other students with less involved parents. Also, parents involved in school related activities report having more self-confidence in parenting as well as an expanding understanding of the home as an environment for student learning (Calabrese, 2006). Lastly, teachers more involved with parents report a greater understanding of a family’s culture and a deeper appreciation of parents’ time and abilities

This is also true for research on autism. While it was once common to separate parents and children in order to focus treatment, now the role of the parent is emphasized as an important part of a child’s treatment (Harris, 1984; Harris & Glasberg, 2003). Researchers discovered parental involvement in home intervention programs were successful, especially in helping children with autism function more independently in the community as adults (Ozonoff & Cathcart, 1998). Children with autism appear to be more likely to benefit from interventions that are initiated at an early age, are intensive in frequency and duration, target various developmental areas including language, behavior management, and social skills, and include the children’s parents1, who can facilitate the generalization process of learned skills (Levy, Kim, & Olive, 2006). It has also been shown that children in intervention programs with parental involvement benefited from increases in their measured intelligence, which in turn improved their ability to participate in general education (Levy et al., 2006). Parents are effective intervention agents for multiple reasons. First, parents can provide additional hours of treatment at low cost. Also, while it is impossible for a child’s therapist or agency to provide service throughout a child’s lifetime, a parent can be involved for many years, providing consistency that is needed (Ozonoff & Cathcart, 1998). Lastly, parents involved in their child’s intervention report increased feelings of competence and success, as well as decreased feelings of depression, stress, and ineffectiveness (Ozonoff & Cathcart, 1998). Much of the research on parental involvement has come from examining mothers as the primary caregivers. Even in training programs that involve both parents, usually it is left to the mothers to train the fathers (Seung, Ashwell, Elder, & Valcante, 2006). Recent work, however, has focused on fathers and the effect of their involvement on child development (Lamb, 1987; Tiedge & Darling-Fisher, 1996). Researchers suggest that

233

Autism and Family Interventions Through Technology

when fathers are involved in their children’s lives, the children have enhanced well-being, increased cognitive development and higher levels of empathy (Bellotti et al., 2003). Father involvement may also be associated with less depression and more child initiative when compared to children who grow up in households where the father is not involved (Seung et al., 2006). In our own in-home work with fathers, we have provided evidence that fathers acquired and successfully implemented the training skills they were taught and children with autism exhibited improvement in their pre-communication skills (Elder, Valcante, Won, & Zylis, 2003; Seung et al., 2006). Additionally, when fathers of children with autism are involved in their children’s lives, they report increased feelings of parental competence, self-worth, and marital satisfaction than fathers who are not as involved (Seung et al., 2006). The same study demonstrated that almost every child continued to produce more words in the maintenance phase with a father-focused intervention versus one that trained mothers. In sum, results of our research indicate that the in-home training for fathers of children with autism was effective and valued by the participating families.

Family Intervention Challenges While research suggests that parental involvement in an autistic child’s intervention is effective, research also identifies some negative aspects of parental involvement in interventions. Evidence indicates a problem of maintenance of appropriate intervention behavior (Harris & Glasberg, 2003). In follow up research with past intervention families, researchers have found that although the parents remembered how to teach their children and the children had retained the skills they had initially acquired, most of the parents had stopped their formal teaching sessions (Harris, 1984). Another limiting factor, particularly within our work, is that it requires in-home visits. This becomes potentially problematic at two levels.

234

First, we have a successfully demonstrated intervention; however, if the father does not acquire all of the requisite skills, or the father’s skill level remediates over time, it requires another at-home visit for re-training. Second, success should equate to the delivery of this intervention to multiple households; staffing issues prevents such issues. The challenge, therefore, is to develop a system that trains fathers, provides opportunities for fathers to work with other family members, helps fathers remediate their skills and knowledge when necessary, and impacts multiple families. In this article, we will describe such a system that has been built and is currently being pilot-tested with fathers. We will explain the specific features of the system, highlighting both parent and researcher use. Although the Web-based project is still in its early stages, the article concludes with the proposed methodology and initial findings.

ADAPTING A SUCCESSFUL INTERNET-BASED INTERVENTION FOR FAMILIES OF CHILDREN WITH AUTISM To respond to this challenge, a novel, online system has been built to provide a technology-based intervention for fathers of children with autism. Past research has demonstrated the success of adults and children learning through technology and learning online (Hartshorne & Ferdig, 2006; Ferdig, 2006). Perhaps the most salient example comes from the work on educating pre-service teachers (Ferdig, Roehler, & Pearson, 2006). Educators found that many of the classrooms where they sent pre-service teachers to observe, learn, and teach did not contain master teachers who practiced reform-oriented literacy instruction. Therefore, pre-service teachers would often resort back to unsuccessful teaching strategies. Even in classrooms with exemplary instruction, it was difficult to give pre-service teachers experience with the pedagogical and student diversity they would

Autism and Family Interventions Through Technology

eventually experience in their own classrooms. Finally, even in the best case scenario of a diverse and pedagogically strong classroom, there was no guarantee that the pre-service teacher would know what to pay attention to (Ferdig, Roehler, & Pearson, 2002). To meet this need, researchers developed a Web-based system where pre-service teachers could explore—and re-explore—reform oriented literacy instruction. Researchers found that preservice teachers excelled given the opportunity to see exemplary models of instruction, particularly in areas of understanding pedagogical and student diversity (Ferdig et al., 2006). Moreover, preservice teachers could use the online experience to re-investigate areas of interest over time; they could also introduce their in-service counterparts to video-based examples justifying their teaching practice. Finally, pre-service teachers who utilized the system left with a deeper understanding of literacy instruction and overall pedagogy (Ferdig et al., 2002). Based on the success of these Web-based

projects, we set out to develop a Web-based system to work with fathers of children with autism.

Description of the System The Autism Family Training project is a project created to train fathers of children with autism and is funded by the National Institutes of Health. Upon first entering the project Web site (Figure 1; http://autism.coe.ufl.edu), users can learn more about the project, the team, and how to participate in the research. Registered users can also log-in to the system. There are two main types of users for the system. First and most obvious, there are parents. The site is first used by the father in the family; once he is trained, the mother receives training (usually by the father) as well as access to the site. A second main user for the site is the researcher. Further explanations of both roles are provided in the remainder of this section.2

Figure 1. Screenshot of homepage

235

Autism and Family Interventions Through Technology

Description of the System: Parent Log-in Once parents log-in, they are provided with a number of options to support their training. First, parents can check the latest news or calendar events posted by researchers. News items mainly include changes to the site and the highlighting of new features for parents. Calendar items remind parents of upcoming events with researchers such as phone calls and in-home visits. Second, parents logging in have the opportunity to have a shared file center with researchers. Parents might upload test results, pictures, or other materials for the researchers to see. Researchers, conversely, might post specific analyses, instructions, or news material for that specific parent. The third feature, and the most important for the training, is the use of instructional and personal videos (Figure 3). There are three sets of instructional videos related to skills the father will learn in working with his child. Areas covered include: “Imitation With Animation & Following the Figure 2. Parent log-in and event calendar

236

Child’s Lead”, “Expected Waiting & Commenting on the Child”, and “Putting It All Together.” Each set contains an instructional video as well as two example videos, showing the parents exemplary instruction related to that set of skills. There are also personal videos in the system. Personal videos are videos of the actual father interacting with his child. Where the instructional video collection is available to any registered user, these videos are only available to the father and eventually the mother of the child. Personal videos provide an opportunity for researchers to demonstrate examples of the father’s positive efforts. They also obviously represent a way to highlight areas that need improvement. At this time, personal videos are filmed by researchers during home visits, brought back to the research office, analyzed, and put online. A future goal is for parents to be able to send in their own videos or to set-up web cameras in the home to interact with researchers. Privacy is obviously critical. Personal videos are only accessible by the families that uploaded them or by the families that are

Autism and Family Interventions Through Technology

Figure 3. Instructional videos

present in the video. To maintain privacy, we not only use password protection, but we also ensure privacy through Secure Socket Layer (SSL) encryption. The videos are distributed via a Real® video server (http://www.real.com). With the Real® platform, videos begin streaming to home users within a few seconds, regardless of the length of the video. The videos are converted in such a way as to be “smart” to the server. In other words, the server can differentiate when a person logs in with a high speed or low speed connection and adjust the video accordingly. Others have chosen to send out videos via CD-ROM. We chose to use a Web-based approach for a number of reasons. First, we can instantly update videos as we find better examples of the instructional approaches. Second, as highlighted, we can adapt the user’s connection speed and provide either smaller videos or full-screen videos if they have capability. Third, CD-ROM based videos require parents

to have the videos in hand. And, after the father trains the mother, they would both need access to the videos. Delivering Web-based videos gives almost ubiquitous access, provided the father or mother has access to the Internet. However, this could be at home just as easily as it could be at an Internet café. Finally, although we are not currently piloting our work internationally, Internet-based videos give us instant access to participants without worrying about mailing videos. The use of videos for instruction was important because it has been one of the most effective approaches researched thus far related to increasing family and educator communication is the use of technology. For instance, in a study conducted by Calabrese, students were sent home with videos pertaining to the school’s policies and curriculum, as well as messages to the parents that help them with their children. The video also included ways parents can contribute to their children’s success in school (Calabrese, 2006). Parent surveys

237

Autism and Family Interventions Through Technology

indicated students and their families enjoyed the videos, watching them more than once, and the parents also learned new information about their children’s school programs (Calabrese, 2006). In another study, videos served as a shared context for the users and researchers (Ferdig et al., 2002). That same study provided evidence that the users went back to the videos as a way to refresh their knowledge and skill sets. On each video page, users have the ability to take notes on videos. This provides fathers with an opportunity to reflect upon the instructional videos; they can also take notes to remember what went well or what needed to be worked on in specific personal videos. At any point in time, they can see their entire collection of notes listed chronologically, viewing growth and progress over time. Research has indicated that providing an opportunity to write about the videos encourages reflection and thus potential change by the user (Ferdig et al., 2006). If a parent wishes to communicate with a researcher about videos or about the research process, we have provided an online discussion forum (in addition to phone calls and e-mails). The discussion forum is also used by researchers as a way to initiate parent inquiry and reflection on instructional and personal videos, resources, and shared files. At this present time, as to not confound the research study, parents may only communicate with the researcher and vice versa. Once a parent has completed the study, a goal is to open up communication between all parents. Multi-family communication (with our without video) may encourage continued reflection, encouragement, and support with training difficulties. A final component to the parent side of the Web site is the resource library (Figure 4). The goal for this section of the site is to provide parents with supporting material, either related or unrelated to the instructional and personal videos. If, for instance, researchers have created an assistance worksheet to go with a certain video, it would appear in two places. First, it would appear in the

238

actual video itself. Notice in Figure 3 that there are no resources directly tied to this video. Any resources used to support the training of this particular set of skills would appear here. The second place a resource would appear is in the resource library. Any resources that are not tied to videos obviously appear here as well. Resources may include word processing documents, pictures, PDFs, and Web sites. At any point in time, parents may also seek Web site help, change their password and other information, and log-out.

Description of the System: Researcher Log-in The second main group of users is researchers. The researchers have three main functions on their side of the Web site. Those functions include: a) managing families; b) managing content; and c) managing research. Managing families relates to the day-to-day interactions with family members. This begins by researchers adding families to the Web site. Notice in Figure 5 that a researcher sees the username, family name, access level, and first & last names3. The username is obviously the name that the parent uses to access the site. When a researcher adds the parent, s/he adds an email contact and a temporary password. We use a family name so that personal files and videos can be sent out to groups of parents or caregivers. We do not use last name as a grouping function as some parents obviously have different last names. Finally, the researcher decides and frequently changes the access level. There are six options for access level that define what a person is able to see on the site; those are described in Table 1. The basic idea behind access levels is that both parents have usernames created with an access level of 0. Once the father has completed the face-to-face, in-home training with the researchers, he is given an access level of 1 to view and review the video and accompanying materials.

Autism and Family Interventions Through Technology

Figure 4. Resource library

After he has successfully completed the materials and has moved on to level 2, the mother gains access to level 1. In this way, she is a step behind so that the father can train her on what he is learning. Her access is mainly for review purposes after she has worked with the father, much like the father’s access is for review after being trained by the researcher. In addition to adding and editing families, “managing family” functions also include scheduling events, adding news, interacting with families

through the discussion forum, and adding files. The news function is to announce things globally to all users. The discussion forum is used much like a message board to communicate back and forth between parents. We decided to use a discussion forum instead of a message board so that at a certain level (e.g., 4), we would have the option of opening up the conversation to all parents (inter- and intra-parental conversations). There are two types of files added to the Web site that are specific to family groupings. The first

Table 1. Definitions of access levels Access Level

Definition of Access Level

0

User has rights to log-in but cannot access Training.

1

User has rights to log-in and complete/review Training #1

2

User has rights to log-in and complete/review Training #1 or #2

3

User has rights to log-in and complete/review Training #1 or #2 or #3

4

User has rights to log-in and complete/review all training modules

9

Reserved for researchers on the site to test all parent functions

239

Autism and Family Interventions Through Technology

set is called “parent files” and refers to any file that the researcher would want to share with the parent. This could include documents, training materials, or test results, although all three would again be specific to that parent. The second set of files is called the “personal videos.” These are videos that are currently captured in-home by researchers, analyzed, and then uploaded back to the specific parent grouping. Where adding files refers to family files and thus falls under the category of “managing families,” there is other content that is distributed to all users and thus falls under the category of “managing content.” Researchers needed the ability to be able to dynamically and frequently add content without being forced to program or hardcode the Web site. Therefore, the researcher site provides the opportunity to upload two different types of content dynamically to the Web site—instructional videos and resources.

Figure 5. Researcher management of users

240

The Real® video server is obviously located on a different machine. Therefore, the researcher wanting to add videos first has to upload the content via file transfer to the server. Once the video is in place, the researcher logs-in to the Web site and clicks to add an instructional video. The researcher lists the official video name, the filename it is listed as, and a main grouping. We currently have three groupings related to instructional strategies (Imitation With Animation & Following the Child’s Lead, Expected Waiting & Commenting on the Child, and Putting It All Together). The researcher can also designate the order of the videos under the given grouping. Researchers can also upload resources. There are two locations for a researcher to upload resources. First, if a resources is related to a specific video, they can upload the resource on the add/ edit video page. Or, they can add a stand-alone resource (see Figure 6).

Autism and Family Interventions Through Technology

Figure 6. Researcher/instructor addition of resources

Both videos and resources have access levels tied to them. As previously discussed, an access level of 0 means that the resources are available from the first second the user has been created. Higher access levels require training to be completed before the resource or video can be viewed. The final category of the researcher side of the Web site is “managing research.” Our research has already demonstrated positive results of working with fathers of children with autism. However, we know less about the role of technology in supporting this work. Therefore, the researcher site contains two tools to support the evaluation and analysis of the use of this site. First, researchers can examine parents’ notes. Much like a “think aloud” protocol in qualitative methodologies, the notes section reveals parent thinking as they watch videos. Because parents have different usernames, researchers can not only investigate user inquiry and reflection, they can also explore various facets of family dynamics. The second tool gives the researchers the opportunity to check parent access logs. A researcher selects a username and a timeframe (e.g., all time,

last week, yesterday, etc.). Using built-in features of SQL (we specifically chose to use SQL due to onsite expertise; others have had similarly positive experiences with other database tools), a report is created that highlights an overview of the use of the site as well as a specific list of when the parent was on, which pages they visited, and how long they stayed on each page (see Figure 7). This “click-stream” analysis’ gives researchers an insight into whether parents are engaged and what specific features are engaging parents.

RESEARCH AND EVALUATION Research description. Our research has already demonstrated the positive impact on children with autism after working with their fathers (Seung et al., 2006; Elder et al., 2003). The purpose of this project is to build upon that research and to ask and answer three important questions.

241

Autism and Family Interventions Through Technology

Figure 7. Researcher evaluation of user access

1. Can fathers who receive in-home training be re-trained using only a Web-based intervention? 2. Can fathers use this system to scaffold their interaction with other family members (e.g., mothers, siblings)? 3. How does the sole use of an online system with the fathers impact their children with autism compared to an in-home only or an in-home/online hybrid model? The first two questions will help us understand the role of this tool for impacting the development of children with autism. More important than asking if this tool works, we will use the first two questions to help us answer how this tool can best be used. From that analyses, we will be able to assess the viability of offering this training tool to fathers (and families) from around the world that do not have access to in-home researchers. Research metrics. There are three sets of metrics used to measure the use of this system:

242

outcome measures, online measures, and technology survey instruments. Outcome measures used to determine the efficacy of the intervention include direct observations of parent and child behaviors and several established instruments. These are summarized in the Table 2. The second set of metrics relate to online measures. As previously discussed, the system provides an opportunity to view parental thinking through analyses of the notes taken by parents as they watch training and personal videos. The system also provides access to the discussion forum, providing an evaluation of the interactions between parents and researchers. Finally, the site provides data to help understand when parents logged in, what features of the site they used, and how long they used each feature. A final set of measures comes from two technology surveys given4. One of our hypotheses is that parents who have technology experience and expertise will use the system differently than those parents who are relative novices to computers or at

Autism and Family Interventions Through Technology

Table 2. Variables, instruments, and measurement for outcome measures Variable

Instrumentation

Measurement

Social turn-taking of father and child

Ecological Communication Orientation (ECO) Language Sampling Summary (Gillette & MacDonald, 1989)

Parent-child interactions evaluated and recorded by a speech/language pathologist using a Likert scale

Parent Skills* imitating/animating, following child’s lead, expectant waiting, commenting versus questioning Parent Behavior Responses Classes* initiating, responding (videotaped) Child Behavior Response Classes: initiating, responding Other Child Behaviors non-speech vocalizations, intelligible words, stereotypy, tantrums (video)

Recorded using The Observer computerized observation program

Frequency counts of target behaviors.

Parental satisfaction with process and outcome of parent training

Therapy Attitude Inventory

Parental self-report questionnaire using a Likert-type scale

Parental views of training process with preliminary information

Semi-structured interview

Assessment using parent self-report

Parental stress

Parenting Stress Index-SF (PSI)

Parental self-report questionnaire using a Likert-type scale

Family cohesion

Family Adaptability and Cohesion Evaluation Scales II

Parental self-report using a Likert-type scale

Web-based Feedback System (WFS) Feasibility

Parent Training (PT) Online Satisfaction Survey # of Web-site hits

Parental self-report using a computerized Likert-type scale & computer-tracked objective data regarding WFS use

least to online tools. Therefore, the first technology measure we give them is a pre-test understanding of their computer knowledge. The instrument is called the Technology and Semantic Web Based Application Survey; it was developed at Oxford (White, 2007). The TSWBAS asks questions about users’ knowledge and experience with online and social networking tools. After they have finished with the training, we also wanted to know more about their evaluation of the online system. Although we have data to describe their use of the system, a post-test instrument would let us know more about their feelings regarding their online experiences. The instrument we used is called the Post Study System Usability Questionnaire (Lewis, 1995). The instrument, which is in the public domain, is essentially a satisfaction questionnaire that allows us to test usability of the system.

CONCLUSION AND FUTURE DIRECTIONS As discussed, autism has gained unprecedented public attention in recent years and poses challenges, not only for the children and their families, but society at large. Responding to this need, we have developed a promising Internet-based tool to equip and empower families of children with autism by engaging fathers. As noted, our current research design includes working in a blended situation with fathers. Future plans include working with Internet-only families and comparing their results with those obtained with our traditional training approach. If effective, this new training delivery method will reach a larger audience and ultimately improve of lives of this most population of children and families. Although we are only in our pilot stages of research

243

Autism and Family Interventions Through Technology

in use of the tool, we have provided the methods and initial results of our study.

Methods There are two main stages of this federally-funded study. In the first stage, a total of 24 families will receive father-focused in-home training. Five of these families will also receive online experiences. As an example, Family XYZ receives a visit from the researchers to collect baseline video and other data. The parents are given access to the pre-test technology survey; once they have completed it, they are given usernames with access levels set to 0. During visit 2, the researchers train the father on a specific technique, using general video and also specific examples from the baseline video taken in visit 1. After the training is completed, the fathers are given an access level of 1 and are encouraged to train the mothers. More video is taken of the father’s interactions with his child. During visit 3, the father receives the second level of training, again using general videos as well as personal videos taken in visit 2. After training, he is moved to level 2 and the mother is moved to level 1. This continues for all three training visits. After the father has completed all the training, the mother is then given her final access level of 4. The first stage of the four-year research project is nearing completion. The second stage will commence within the year. The goal of the second stage is to repeat the process with five additional families, but without the in-home training. The goal is to take what has been learned from working with the in-home group and apply it to the online only families.

Early Results The research is still in process. Early results indicate, as can be expected, that most parents are spending their time online watching the videos. Due to the fact that these parents are in a blended situation and see the researchers frequently, the

244

relative non-use of the discussion forum can be expected. Additionally, although past research has demonstrated the importance of the notes section (Ferdig et al., 2002), our parents have yet to use this feature. It is an early indicator to us that as we begin to work with our online only parents, we will need to find a way to engage them in both the discussion forum and the notes posting. They may do this automatically as they will not have face-to-face access to the researchers. Current fathers may also engage more with the system after they have finished their training and time has passed (for remediation purposes).

Implications In this article, we have presented a Web-based tool to engage fathers of children with autism. We have provided a thorough description of the tool as well as metrics and our pilot data. Often when we think about Web-based learning and teaching, we think about teachers and students in K-12 or post-secondary education. However, the move to Web-based instruction has opened the opportunity to engage others into the discussion. The adage that it takes the entire village to raise a child is often widely accepted, but difficult to implement. Web-based tools provide opportunities to open instruction directly to those that influence our students on a daily basis. In our study, the Web-based instruction is a supplement to the face-to-face environment. Further research needs to first explore the support structure necessary to engage busy parents and caregivers. Second, we need further exploration of the kinds of metrics used in said scenarios. Finally, we need further practical investigations of how to best utilize video. Webcams, pocket cameras, and online video hosting sites have made sharing information easy; we need to know more about privacy in these situations. We end this article with an open call for parents of children with autism who wish to join us on this journey.

Autism and Family Interventions Through Technology

REFERENCES Bellotti, J., Vogel, C., Burwick, A., Nagatoshi, C., Ford, C., Schiff, B., et al. (2003, October). Dedicated to dads: Lessons from the Early Head Start Fatherhood Demonstration. Report to the Head Start Bureau, Administration on Children, Youth and Families. Princeton, NJ: Mathematica Policy Research. Calabrese, N. M. (2006). Video technology: A vehicle for educators to enhance relationships with families. Education, 127(1), 155–160. Elder, J. H. (2002). Current treatments in autism: Examining the scientific evidence and clinical implications. The Journal of Neuroscience Nursing, 34, 67–73.

Gillette, Y., & MacDonald, J. D. (1989). ECO resources. San Antonio, TX: Special Press. Harris, S. L. (1994). Siblings of children with autism: A guide for families. Bethesda, MD: Woodbine House. Harris, S. L., & Glasberg, B. A. (2003). Siblings of children with autism: A guide for families (2nd ed.). Bethesda, MD: Woodbine House. Hartshorne, R., & Ferdig, R. E. (2006). Hypermedia applications in web-based teaching and learning environments: The role of databases as intermediaries. Electronic Journal for the Integration of Technology in Education, 5, 63–76. Lamb, M. E. (1987). The father’s role: Crosscultural perspectives. Hillsdale, NJ: Erlbaum.

Elder, J. H., Valcante, G., Won, D., & Zylis, R. (2003). Effects of in-home training for culturally diverse fathers of children with autism. Issues in Mental Health Nursing, 24(3), 273–295. doi:10.1080/01612840305276

Levy, S., Kim, A., & Olive, M. L. (2006). Interventions for young children with autism: A synthesis of the literature. Focus on Autism and Other Developmental Disabilities, 21(1), 55–62. doi:10.1177/10883576060210010701

Ferdig, R. E. (2006). Assessing technologies for teaching and learning: Understanding the importance of technological-pedagogical content knowledge. British Journal of Educational Technology, 37(5), 749–760. doi:10.1111/j.14678535.2006.00559.x

Lewis, J. R. (1995). IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. International Journal of Human-Computer Interaction, 7(1), 57–78.

Ferdig, R. E., Roehler, L., & Pearson, P. D. (2002). Scaffolding preservice teacher learning through web-based discussion forums: An examination of online conversations in the Reading Classroom Explorer. Journal of Computing in Teacher Education, 18(3), 87–94. Ferdig, R. E., Roehler, L. R., & Pearson, P. D. (2006). Video and database-driven web environments for pre-service literacy teaching and learning. In M. C. McKenna, L. D. Labbo, R. D. Kieffer, & D. Reinking (Eds.), International handbook of literacy and technology (Vol. 2, pp. 235-256). Mahwah, NJ: Lawrence Erlbaum Associates.

Ozonoff, S., & Cathcart, K. (1998). Effectiveness of a home program intervention for young children with autism. Journal of Autism and Developmental Disorders, 28, 25–32. doi:10.1023/A:1026006818310 Rapin, I. (2002). The autistic-spectrum disorders. The New England Journal of Medicine, 347(5), 302–303. doi:10.1056/NEJMp020062 Seung, H. K., Ashwell, S., Elder, J. H., & Valcante, G. (2006). Verbal communication outcomes of children with autism after in-home father training. Journal of Intellectual Disability Research, 50, 139–150. doi:10.1111/j.1365-2788.2005.00767.x

245

Autism and Family Interventions Through Technology

Tiedge, L. B., & Darling-Fisher, C. (1996). Fatherhood reconsidered: A critical review. Research in Nursing & Health, 19(4), 471–484. White, D. (2007). Results of the ‘Online Tool Use Survey’ undertaken by the JISC funded SPIRE project. Oxford, UK: Author.

ENDNOTES 1



2



3



4

We have developed the back end of the system using ASP.Net® (http://msdn2.microsoft.com/en-us/asp.net/default.aspx) as the programming language and SQL (http:// www.sql.org/) as the database. Names are blurred for privacy. Special thanks to Erik W. Black at the University of Florida for helping select and create online versions of both instruments.

Italics added.

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 55-69, copyright 2009 by Information Science Reference (an imprint of IGI Global)

246

Section 4

248

Chapter 14

Learner-Centered Teaching and the Use of Technology Annette Greer East Carolina University, USA Vivian W. Mott East Carolina University, USA

ABSTRACT This article explores the use of various learning technologies as tools for facilitating learner-centered teaching. The article offers another perspective on the scholarship of teaching with technology—through discussion of various theoretical models of learner-centered teaching, the role of technology on the student/instructor relationships, the impact on technology in different educational settings and contexts, and learners’ cultural differences. The article concludes with a brief discussion of future trends, cautions, and speculations related to technology use in learner-centered teaching.

INTRODUCTION A mere mention the word “technology” often renders anxiety in instructors and students alike. However, the term “technology” can represent the simplest of tools to aid the learning process. For instance, a pencil with an eraser on the end, a chalk board and chalk, or even a Chinese abacus are instrumental technologies that we have used across time to facilitate the learning process. Relative to technology in the 21st century, the difference is the speed at which we are experiencing growth in both hardware (the pencil vs. computer) and DOI: 10.4018/978-1-60960-153-9.ch014

software (writing vs. applications) in technological tools (Saba, 2001). Where do we find these technological tools in use in higher education? Kennedy, Judd, Churchward, Gray, and Krause (2008) found that individuals who embrace emerging technologies in everyday life were more apt to be early adopters, using those same technologies in educational settings. In higher education, we find technological tools inside the traditional classroom and among various created virtual learning environments generated by the technology itself—in a place we often call cyberspace. Technology permeates our global environment, offering tools that assist us in economic, social, and political dimensions.

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Learner-Centered Teaching and the Use of Technology

Technological tools are one of many elements that can aid communications and application, in education. A closer look at the elements of education will help us in understanding the positive and negative value of technology as an educational resource and sometimes as the environment of learning. The purposes of this article are threefold: first, to explore critical educational elements and the role educational technologies play in these elements; second, to consider how key theoretical models of learning are impacted by technology; and, third, to examine how instructors and learners variously respond to educational technologies and the impact of technological use on both instructor/ learner relationships and learning. Ultimately, the article seeks to add to the scholarship of teaching through an evidence-based review of the contextual influence of technology in education.

BACKGROUND: EDUCATIONAL ELEMENTS There are many elements to be considered in any educational environment: instructors, learners, content, delivery, application, context, environment, and resources. Not only are the elements essential to understand; further, the interaction of these elements, within the context of time and the roles that each of these elements play, have varied across historical time as higher education has evolved as well. The relationship between the elements of education changes rapidly as the elements themselves have transformed with time and as knowledge has both become obsolete and expanded exponentially (Billings & Halstead, 2005; Mott, 2009). It is the changing relationship among the educational elements of instructors, students, content, environment, all influenced by the application of technology resources, that have stimulated this article. Demonstration of technological competencies is central to the ability of instructors to meet the diverse learning needs of students. Technological

competencies are based on the same continuum as the technology itself from simple to complex according to the International Society for Technology in Education (ISTE, 2008). ISTE has set national technology competency standards for instructors and students. As early as 1995, ISTE commissioned a white paper regarding the technological literacy skills needed for the 21st century (Thomas & Knezek, 1995). Technological literacy includes: (a) understanding math and science concepts underlying technological systems, (b) operability relative to various systems, (c) utilization and evaluation of diverse applications, (d) ability to innovate technology to solve emerging science problems, (e) awareness of the role of technology to any given career, (f) responsiveness to critical factors that lend success to any given career, and (g) appreciation of the role technology has on the various cultures of our global society. As with any competency, technological competency can be considered as three distinct skill areas: basic, professional, and application of technology in instruction. Basic technological skills include the introductory level of function that is the operation of applications for personal communications. These applications can include e-mail, basic blogs, word processing, spreadsheets for home use, and simple presentations, for example. Professional technological skills include higher, intermediate levels for professional communications. E-mails, for example, used professionally require knowledge of embedded applications such as certified signature use, timed release, tracking delivery and opened status, and automation of e-mail rules for organization and management. Another example would be use of the word processing at the professional level to track changes, merge documents, insert citations and references, automate a table of contents, and import from other applications into the word processor. At the advanced competency level, professionals using technology to teach would have evolved from basic to professional intermediate, and are poised to expand and transfer existing skills into

249

Learner-Centered Teaching and the Use of Technology

instructional design. It is at the advanced applied level that innovation in educational design occurs, when technological competency of instructors approximates or matches the progression of the technological tools created. Innovative use of technology facilitates the development of instructor-student relationships to promote positive learning outcomes and thus the scholarship of teaching. Boyer (1990) noted the following examples of teaching scholarship: innovative curricula (organization of disciplinary content), teaching methods that engage students in learning, collaborative interactions among instructors, students, and peers, and exploration of the efficacy of learning. The relationship between instructors and student is at the core students’ engaged learning; as such, technology should augment—not inhibit—the formation of that valuable relationship. Mentoring, cultural influence, effective communication, and feedback are primary to relationship building and professional socialization. When used effectively, any number of instructional technologies can facilitate processes of communication, and so enhance the development of learning relationships. Assessment of the students’ technological skills is essential to determining if the curricular design allows for variability in skills and learner styles that will be found in most learning environments. The technological literacy level and the technological competency of students will vary widely and may be inconsistent with the level of the instructor designing the curriculum and learning environment. Hence, if the student is at an advanced level and the instructor at a basic level, the design may cause students to become bored and distracted. If the instructor designs the learner environment only for advanced users and assumes a high level of resource availability—when student resources are low and skills are basic—the student is greatly disadvantaged in terms of access and achievement. In either of these cases, the instructor-learner relationship is encumbered and learning jeopardized.

250

THEORETICAL LEARNING MODELS IN EDUCATION There are a multitude of theoretical models that focus on teaching and learning. This section will explore only a few of those, models which deal primarily with learners’ increased responsibility for, and even control of, their learning processes and outcomes.

Self-Directed Learning Theory Self-directed learning or the individual pursuit of learning based upon independent motivation supports the selection of advanced distributed learning technologies. O’Lawrence (2007) reported that self-directed learning was a key factor in the selection of distance education environments. The flexibility offered to adult learners in distance education environments was the motivator that allowed them to make adaptations to balance family, career, and transportation further facilitating completion of higher education programs. Various technological tools, such as discussion groups can provide a forum for self-directed learners to self-assess, to highlight the value of the individual contributions to the learning community, and provide a means to reflect on the meaning of the learning experienced (Kayler & Weller, 2007). Du and Wagner (2005), as well, studied outcomes of self-directed learners’ use of weblogs as a learning reflection aid. Weblogs are a form of journaling that are published online as Web pages. Their research outcomes suggested a positive predictive association between the use of weblog journaling and improved course outcomes that could not be accounted for through traditional coursework. Bonk, Wisher, and Lee (2004) maintained that Web-based technologies allow for increased learner responsibility and control with meaningful engagement activities, which is not only attractive to self-directed learners, but aids in transfer of learning as well. Self-directed and responsible learners become peer instructors,

Learner-Centered Teaching and the Use of Technology

emerge as leaders in the educational process, and facilitate self-learning and critical reflection through teaching. Technologies seem to impact the manner in which leadership emerges with text facilitating task-orientation and video-audio conferencing facilitating a relationship orientation. A shared learning process is established that allows for self, peer, and instructor reflection and assessment driving self-directed learning to higher levels of development. Derntl and MotschnigPitrik (2004) found that blended or hybrid learning environments (face-to-face and Web-based combination) help to establish patterns for alternating the teaching strategies and technologies that are applied to enhance the processes of learning, further advancing self-directed learning. Knowledge management also becomes more powerful, organized, and expansive using the technological tools such as blogs, wikis, and management systems for concept mapping. Further, integration applications offered through various software companies promotes organizational knowledge building and transfer. This knowledge control shift further places the learner at the center of the learning process. Technology, then, helps bring about a shift in educational philosophy, one that is learner-centered and can maximize the benefit to both learner and stake-holders (Schaffert, Bischof, Bürger, Gruber, Hilzensauer, & Schaffert, 2006).

A Learner-Centered Framework and Technology The American Psychological Association’s Board of Educational Affairs work group, after a thorough systematic review of existing research, first published fourteen distinct learner-centered principles in 1993 (1997). Publication of these principles significantly influenced educational agendas at the end of the twentieth century and resulted in defining a new learning paradigm, one that is learner-centered (Barr & Tagg, 1995). Previous to the publication of these principles,

the paradigm for education was an instruction paradigm, and reflected an instructor-centered and content approach to education. McCombs and Vakili (2005) proposed that learner-centered approaches can serve as a theoretical or conceptual framework for educators using distance education technologies. Implementation of learner-centered approaches that use technology includes: (a) building an environment that connects learners’ need for interpersonal relationships, (b) using strategies that meets diverse learner styles, (c) tailoring strategies that allow for learners’ enhanced control over learning, and (d) assessing technological efficacy to meet needs of individual learners and community of learners. Instructors need to be provided with the skills to create effective learner-centered environments that offer both context and opportunities for inquiry and collaboration (McCombs & Lauer, 1997). Among the most well-cited and utilized learner-centered framework was that offered by Weimer (2002). Her efforts to advance instructors’ effectiveness in the various educational settings was proposed in a seminal book that recommended five concepts, or “key changes to practice” (p. xvii) needed for instructors to transition to a learner-centered approach to teaching. Weimer’s key changes are based on research and theory, both formal theory and theories-inuse, and include “action learning, self-directed learning, constructivism, critical and feminist pedagogies, and reflective practice” (Mott, 2004, p. 244). Weimer’s five key concepts include: (a) balance of power, (b) function of content, (c) role of instructors, (d) responsibility for learning, and (e) purposes and processes of evaluation.

Power One learner-centered value is that of shared power between instructors and learners. Technology and the level of skills required to use technology as a tool for learning can alter the balance of power in an educational setting. According to the Com-

251

Learner-Centered Teaching and the Use of Technology

monwealth of Learning (Farrell, 2001) there are several global forces that generate a sense of exigency to adopt new technologies, among them the impetus of the “post-industrial information age and the explosive growth and distributed nature of new knowledge” (p. 10). It is this explosive change that generates a level of anxiety that can often result in rushing to include technologies that may not fit a curriculum. The dynamics of technological change can position both learners and instructors to share the experience of learning technology, an upgrade in a course management software mid-semester, for example. Krichen (2004) suggested that technical support systems for instructors and students should be learning platforms that offer 24-7 availability to resolve technological issues. Further, that these support systems should offer ongoing training for instructors and students to meet the cycle of evolutions in hardware and software. The vulnerability shared by instructors and learners can stabilize power differentials in learning environments. Diekelmann, Schuster, and Nosek (1998) researched new pedagogies, particularly ways online technologies may change the relationship between instructors/student. They found that some pedagogies can reverses the power and expertise fields for learning. This places the instructors in a position of learner in order to remain current with the technology used by younger, often more technologically proficient learners. Pettitt (2002) studied the possession and negotiation of power in an online undergraduate business management course. The structure of an online course was found to be just as important as flexibility in providing stability in organizing time and setting routines. Routines were a positive factor in the relational system needed to maneuver the variable roles of worker, spouse, parent, family member, and student/peer learner. Distance education provided the learners power, or control over time, space, and proximity of learning, and allowed learners a negotiation tool within their relational systems. Thus, the power differential

252

can shift from content- or instruction-centered to student-centered when students request that instructor availability match the asynchronous flexibility of the course’s right of entry. Issues with power and access regarding the implementation of technology as a teaching and learning tool can also produce disparities among students that are economically or otherwise disadvantaged. Magjuka, Shi, and Bonk, (2005) noted that there is a wide range of cost both to the educational institution and to the students based on administrative decisions for commercial or open source (freeware) systems of course delivery. Administrators and educators should take into consideration the simplest and most cost-effective measures of technology that will serve to empower rather than to oppress diverse student populations. Essential to the balance of power in the learning context is institutional support for instructors and students that creates equity in knowledge and skills in operating the technology used in or as the learning environment. From a learner-centered philosophy, this balance of shared power must be based on relationship (Cornelius-White, 2007). Technology should serve to ease the development of educator-learner relationship, not impede it.

Function of Content and Technology According to Weimer (2002), with one’s move to greater learner-centeredness, content becomes less important than the process of learning. Reynard (2009) reinforced the value of process versus content-driven design, noting that the focus for learning should be on how, why, as well as emerging disciplinary trends rather than on what, when, and current practices. The learner has to be prepared to function in a knowledge economy that is in dynamic change and be able to relate existing knowledge to new and emerging knowledge. Novak (2003) noted that learners are searching for relationships between their current knowledge and the generation of new knowledge. Educators promote meaningful learning by using learner-

Learner-Centered Teaching and the Use of Technology

centered strategies that actively engage learners with the content. Technology has proven a useful tool to providing a venue for learner engagement. Concept maps created online in a collaborative team manner augment engagement with knowledge/content for learning (Novak). Thus, learners become active participants in co-constructing higher order thinking skills and increase cognitive, affective, and psychomotor abilities. Discussion threads found in variable applications allow for multiple reflections that merge diverse cultural knowledge perspectives. Content then is in constant flux and the process of learning gains greater importance. The pathway for learning content when using technologies such as concept mapping may become more non-linear, less systematic (Hartley & Bendixen, 2001). Open systems of learning that are technology-based support construction of learner knowledge. Content accessibility is heightened with the ever-present World Wide Web where emerging knowledge is immediately available versus the delayed accessibility of print. These open content systems of accessibility do present issues of reliability and validity of knowledge, however. This issue is compounded as knowledge is hyperlinked to exponentially expanding and integrated knowledge bases. Content is generated rapidly as new knowledge is constructed, but often without older information integrated, corrected, or removed. Hartley and Bendixen noted that learners’ beliefs about the nature of knowledge are linked to cognitive processes and comprehension. Learners have to be taught how to ascertain the accuracy of the information they access, or risk a compromised or erroneous knowledge base. Weimer’s (2002) learner-centered framework emphasizes the role of the instructor to provide a learning design that will assist the learner in gaining discriminate skills to advance their autonomy and their ability to maneuver 21st century open-ended learning environments.

Role of the Instructor In an online learning environment, it is the responsibility of the instructor to select the types and patterns of technology use that are consistent with the content/context for learning. O’Lawrence (2007) noted that, “instructional strategies are what really make a difference in how adults learn online, not technology” (p.¶ 437). Hence, it is the use of the instructor’s selection of the types of technology that make the learning interesting and meaningful to the learner. Technology (the tool) should augment an assignment with the flexibility that allows the learner comfort at the level and in the style that is consistent with individual development. In a learner-centered framework, the role of the instructor is to facilitate learning as an open system that supports learner autonomy (Weimer, 2002). Koper and Olivier (2004) noted that electronic, or e-learning is a learner-centered, non-linear, and self-directed personalized approach to education that requires intentional learning design. Educators designing online educational opportunities have to consider the variability within a diverse set of learners without making assumptions regarding technological skill levels. In fact, Hartley and Bendixen (2001) noted that too much flexibility offered to learners in online environments can be counter-productive to successful learning when the learners’ belief systems are based on simple knowledge and the educational design is complex with multiple levels of links to definitions, graphs, and readings. Designs that do not provide a direct pathway from the facts needed to facilitate learning are seen by learners as pointless and unnecessary. Thus, the role of the instructors is to keep the designs as simple as possible with technologies that complement the content of the course with consideration of learner styles. Kolb’s learning style (1984) has been linked to computer mediated instruction in numerous studies (Lu, Jia, Gong, & Clark, 2007) since the advent of instructional technologies. Various

253

Learner-Centered Teaching and the Use of Technology

recommendations have included the need for more research in the application of design and development of appropriate instructional strategies and virtual materials, but in created educational environments as well. Researchers have also noted that more work is needed in determining what educational strategies and instructional methods would best match learning styles, and the necessity of advocating for learner assessments using Kolb’s learning style inventories and other assessments. All of these recommendations are aimed at the increased attention to learners’ visual, auditory, kinesthetic and tactual learning styles in virtual learning environments. With these critical considerations, computer mediated education and training venues can become fluid environments that can be adapted to the learner, providing opportunities for beneficial interaction and engagement (Kolb, 1984; Lu et al., 2007; Quinsee & Hurst, 2005). Koehler and Mishra (2005a,b) found that the issues surrounding design of technological based learning environments serve as the context for instructors’ continuing professional education. They offered seminars for instructors that focused on the design of online courses which actively engaged instructors in the process of inquiry and design using collaborative learning groups. Participants’ learning outcomes were technological designs for use in online courses: Web sites, syllabi, and adapted teaching approaches/strategies (Koehler & Mishra, 2005a,b). The design process is anything but static, as the technology evolves, as Web links expire, as upgrades are implemented for specific applications, or as new courseware is adopted by institutions, for example. Therefore, the role of the instructors is to seek professional development on a continuous basis, regularly solicit feedback on their instruction, and to revise curricula as warranted. As an additional benefit, the instructors’ modeling of behavior and selfdirectedness as learners is another way to prepare student learners to be accountable and self-directed in their learning (Weimer, 2002).

254

Responsibility for Learning Learners must also self-assess their own technological readiness and resources for learning. Criteria for required technology should be included in the syllabus to allow learners to access, plan for, and learn to use the needed learning resources. Many higher education institutions publish these criteria prior to student enrollment and offer funding through financial aid to cover costs, assist with loan programs, or offer computer labs with the needed resources for use during a given semester. Once the technology is accessible, learners must also assume responsibility for acquiring and maintaining skills to support learning. Communication with the instructor, tutorials, and institutional “help desks” are imperative when any technological issues arise that conflict with the ability to learn. Learners have to be their own advocates at times to insure the instructor or computer lab technician are alerted when technologies are not functional or available. Huang (2002) noted that learners can learn to self-assess the quality and authenticity of the learning in a more rigorous manner when using online environments. Many online designs incorporate high levels of peer learner interaction, which if not facilitated appropriately by the instructors, may lead to misinformation that deters authentic learning. Hence, learners must learn how to assess the accuracy of exchanges when shared peer learning is used as an online teaching strategy.

Purpose of Evaluation Fundamental to Weimer’s (2002) learner-centered values is how evaluation can be used to expand and reinforce learning. Online learning environments offer strategies that balance these values. Barrett (2007) discusses the use of portfolios as a strategy of evaluation that is both a measure of learner outcomes and a means by which deeper learning can occur through reflection based on the learning journey. In the traditional classroom,

Learner-Centered Teaching and the Use of Technology

portfolios can be created with computer software and placed on CD-ROM, Flash-drives, DVD, or can be text, photographs, or video-audio productions. These same portfolios can be published to online environments, such as a blog, a Wiki, or a personalized Web page. Permissions can be restricted for privacy or can be published with open access for social networking. The advantages of using more sophisticated levels of technology for portfolio development include the ability to archive, to link, and to publish (Barrett, 2007).

TECHNOLOGY’S INFLUENCE ON INSTRUCTOR/STUDENT RELATIONSHIPS The influence of the instructor/student relationship is profound in the socialization process of a personal and professional becoming. MacIntosh wrote that “professional socialization is the process whereby individuals acquire and integrate into their lives the expected knowledge, behaviors, skills, attitudes, values, roles, and norms” (2003, p. 725) of their discipline. Socialization has benefits in that it perpetuates the historical values and norms of a profession (Kenny, Potin, & Moore, 2004; MacIntosh, 2003). Instructors should serve to model the essence of their disciplines in a myriad of activities that contribute to learning experiences. Often, this modeling is done through either classical or instructional mentoring. Gender, socioeconomic, and cultural attributes influence characteristics of both instructors and students. These attributes blend in any given individual to make them unique in their approach to teaching or learning. This instructors/student diversity is further complicated by the preference for learning styles (Kolb, 1984). Kolb describes four major types of learners: accommodators, divergers, assimilators, and convergers. These types are based on the learning modes that are preferred by individuals, best portrayed in a humanistic frame as feeling, watching, thinking, and doing,

respectively. These modes are influenced by the cultural phenomena of communication, personal space, social organization, time, environmental control, and biological variation (Bastable, 2003; Merriam, Caffarella, & Baumgartner, 2007; Mott, 2009). Each factor can also be mediated by technology and impact the ability of instructors to relate to students in the learning context. One reason for the inability to relate to students may pivot on generational issues. Oblinger and Oblinger (2005) defined the generational variability within the academic arena among instructors. She stated that most instructors in the university institutions are usually Baby Boomers—optimistic workaholics who assume that responsibility is an element of their work ethic and can-do attitude. They disdain laziness and fear aging. Boomers, born between 1946 and 1964, are usually administrated by Traditionals (born between 1920 and 1945) who represent control and self-sacrifice. Traditionals are focused on family, community, and respect for authority. And, while typically thought to dislike technology, we cannot “assume that older [Traditionals] are uniformly anxious, resistant, or under-skilled where e-learning is concerned” (Mott, 2009, p. 785). Current students, on the other hand, may yield from several generations including later Baby Boomers, Generation Xers (born between 1965 and roughly 1985), or the Millennials (birth years beyond the mid- to late-1980s). These later generations are thought to be more liberal in values, flexible to change, open to technology, and more prone to consumerism. However, as Mott noted elsewhere: It is perhaps misguided to assume that younger learners are all comfortable with e-learning. Most Generation-X and Millennial learners have grown up with information and communication technologies; many would, in fact, be lost without their iPhonesTM and BlackberriesTM…. More learners of every age have grown accustomed to the presence and even necessity of technology in

255

Learner-Centered Teaching and the Use of Technology

their lives and readily embrace its use in their continued learning, both on and off the job. (Mott, 2009, p. 785) The divergence in values, ideas, ethics and cultural phenomena makes the establishment of relationship between instructors/students more difficult across generations increasing the complexity of learning potentials (Johnson & Romanello, 2005). Instructors are called to become adept at recognizing generational differences and value them to broaden learning opportunities. Further research in instructor/student relationship was conducted by Gillespie (2005). She concluded that the instructor/student relationship was so imperative to student learning that it raised implications for the preparation and evaluation of educators and educational practice. The research of Johnson and Romanello (2005) resulted in the development of an educational activities model that represents a cross-generation framework designed to assist relational development between instructors, students, and peers. Their work, like that of Gillespie encourages educators to consider personal beliefs, actions, and influences that are exerted on relationships with students through the educational process. The connection of instructors and student acting in relationship is influenced by the manner in which technology is applied. The technological connection between instructors and students must be transparent (Krichen, 2004). Technology should not impede development of the relational system between instructors and students, nor among students, but should enhance its progress. Russo and Benson (2005) found that the instructors’ presence in online teaching environments was positively correlated to students’ satisfaction levels and to their affective learning outcomes. They also determined that students’ self perception relative to cognitive learning was positively correlated to grade performance and self-evaluation of learning progress (Russo & Benson, 2005). Their findings reinforce the concept that it is not the technology, but the

256

dynamic social interaction among the instructors and students and the engagement of the students with the knowledge that enhance the learning outcomes. One technology that allows for synchronous relational presence among instructors and students is an online “chat.” Chats allow for real time online dialogue between instructors and students, and student to student. Use of chats to supplement and add clarity to learning through the use of text is realized through the process of reciprocity (Kreijns, Kirschner, Jochems, & Van Buuren, 2004). In this reciprocal process, the learning interaction between instructors and students includes clarifying, questioning, predicting, and summarizing in a collaborative learning manner based on the cognitive development level of students (Kreijns et al., 2004). A relational presence is experienced in the collaborative interaction of reciprocity during use of synchronous chats and serves to sustain virtual learning genres, which are complex media that allow for similar collaborative interactions for learning. Mikropoulos and Strouboulis (2004) defined factors that influence presence in educational virtual environments. Using six different input devices with 29 adolescents they were able to produce three distinct kinds of presence: personal, social, and environmental. Presence is strongly tied to identity and establishing an identity in a traditional classroom or online environment and can be facilitated by technology (Flores, 1998). Identity is established as a result of physical attributes, pattern of behaviors, and adherence to commitments all of which can be represented in realistic or symbolic ways using technology (Flores, 1998). Identity and learning styles can be masked or less transparent based upon educators technological designs for the learning setting and environment.

Learner-Centered Teaching and the Use of Technology

TECHNOLOGY’S INFLUENCE ON EDUCATIONAL ENVIRONMENTS As previously discussed, instructors must take into account the readiness level of students to learn, as well as their learning styles. Information alone does not insure learning; rather it is the manipulation of the learning environment by the educator that provides an opportunity for interaction with the affective, cognitive, and behavioral domains of learning (Bastable, 2003). Traditional instructional settings have been classroom, internship or field work in industry of the discipline, and in laboratory settings. The curriculum design and the instructional methods are adapted to the setting or environment. The setting/environment determines the instructional strategies and materials for learning based on impacting factors or elements (Bastable, 2003). Impacting factors include, but are not limited to, organizational or administrative structures, time and resource constraints, collegial and clientele support for participation in the educational process, and environmental or structural confines. Pervasive in all educational settings is the escalation of technology for the delivery of education. Comparisons of traditional classrooms and online learning environments yield student satisfaction levels that are analogous one to the other when controlled for instructor and content (Cooper, Taft, & Thelen, 2004; Schoech & Helton, 2002). Examination of the technological factors that affect student outcomes of learning as well as satisfaction levels requires greater scrutiny. The biological stimulus that occurs in virtual environments (physical imagery, sight, and sound) add realistic attributes to the learning environment that mimic real life stimulating brain responses (Mikropoulos & Strouboulis, 2004). One could compare this level of technological complexity to a child playing with a cardboard box (simple technology) versus playing with an elaborately made dollhouse or tree house. We have not yet researched using matched controls to compare the value of learning outcomes when applying

the simple technology to the complex technology. Therefore, we cannot make assumptions at this point that virtual multimedia environments are better than (say for example), synchronous chat using text. We can say, however, that technological generated virtual environments are different while achieving the desired outcomes for learning. Another virtual technology that is used increasingly in traditional learning settings is achieved through simulators. Simulators are used in the classroom, training laboratories, and other traditional settings. Simulators in health care are life size mannequins realistically representing the biology of human form and equipped with sensors that provide computer feedback to stimulators as programmed scenarios. In the military and airline industry, simulators are the monitors and indicators of a given aircraft to train pilots before an actual flight occurs. Simulators are most often used in health care, disaster training for service personnel, or in safety training in industry, among others (Holcomb, Dumire, Crommett, Stamateris, Fagert, & Cleveland, 2002). Thus, the range for interaction either at an individual level of learning or for collaborative shared learning can be augmented in virtual or traditional learning environments. Environments for use of technologies can be traditional, blended (a combination of Web-based virtual and traditional face-to-face), or Web-based virtual online. Research has also been conducted that provided insights into the rapid expansion of technology as a platform for learning. Allen and Seaman (2003) reported that in public institutions of higher education, approximately 97% offered one course fully online or blended, and 49% offered a complete degree program online. Further, 67% of the higher education institutions surveyed projected that online education is a long-term strategy for educational delivery. The survey noted that an additional critical issue was the readiness of the instructors to deliver online education. Another noteworthy aspect found was that only 59.6% reported that instructors accepted the value and legitimacy of

257

Learner-Centered Teaching and the Use of Technology

online education. In an updated survey report in 2008, Allen and Seaman suggested that enrollment in online programs continues to grow at rates that exceeds traditional higher education programs. They maintain that enrollment will increase even during economic downturns as more unemployed seek to develop and enhance job skills through online education. Bourne and Moore (2004) cited that most students will be educated in a blended model of learning using a mix of technologies and educational activities, and where learning is focused from a systems thinking approach.

TECHNOLOGIES FOR LEARNERS The technologies that are currently employed in higher education range from smart boards in traditional classrooms to virtual learning environments like Second LifeTM. Smart boards replace the traditional blackboard and are integrated with computer programming to applications used by the instructors, such as Excel, PowerPoint, or Word. For instance, a power point presentation designed by the instructor is projected on the smart board and then concepts are outlined or highlighted as a lesson progresses. The changes are then saved and electronically distributed to learners in hard copy, note format. Interactive “clicker” systems engage the students in responding silently and simultaneously to the instructor in an electronic manner that synchronously displays the results in a graphed manner. Instructors review learner understanding and redirect misconceptions reinforcing accuracy in learning. These systems are often costly; thus some educators have taken advantage of the common use of cell phones integrated to an internet site to achieve the same end as the clicker system. IpodTM and MP3 player technologies, universally used by many for listening to music, have now been adapted to include auditory learning sessions such as lectures and can now accommodate video lectures. These learning sessions can be posted

258

and distributed through YouTubeTM or ItunesTM for immediate download by learners creating the ultimate in mobile learning. Course management software such as Web CTTM or BlackboardTM offer complex, yet sophisticated and highly adaptable learning systems. These programs have embedded applications that integrate with external sources for linking learning objects and others which expand learning strategies. Blogs, wikis, audio-video applications such as CentraTM and ElluminateTM increase the ability of course management software to facilitate learning socialization. These learning systems are taking a rapid leap forward as Web 3.0 approaches. Communications software that extends the use of technology such as SKYPETM allows a computer to serve as a videophone connecting to anywhere in the world. Use of this phone system and other communication tools could allow instructors to have virtual office hours with distributed learners. Social Web applications like FacebookTM and My SpaceTM are being integrated in learning environments for learner interaction, portfolio development, and social networking for job opportunities (Batson, 2009). Campus Technology featured East Carolina University’s (ECU) use of Second LifeTM, a virtual world economy (Harrison, 2009). Land is purchased; campuses, towns, and business are set up. The currency of exchange is linden dollars. Classes are conducted using avitars, digitized images designed to allow for human-like mobility. At East Carolina University, ten classes are on-going and other services for library, bookstore, career services, and undergraduate support can be accessed via Second LifeTM. Some of the disciplines offering classes include interior design, computer management, counseling, business management, and business information technology education. Some like interior design meet both in a traditional classroom and in Second LifeTM while others, like business management only hold class within Second Life TM. Second LifeTM can facilitate lecture formats but also allows for auditory exchange

Learner-Centered Teaching and the Use of Technology

between the instructors and learners. Use of these technologies provides learners with skills that will be used as they leave an academic environment to progress into the work environment. Learning currently available and emerging technology is crucial for the preparation of tomorrow’s workforce. Organizational consultants note that since 2004, our virtual workforce has increased by 800% (Gargiulo, 2009). Gargiulo predicted that in 2011 the mobile workforce will comprise 73% of the total U.S. workforce (2009). This means that workers must be competent in working from various locations while maintaining relationships for collaborative workflow and management to deliver the work required. E-mail, instant text messaging, Web-conferencing enable communications for virtual team functions. Word documents, spreadsheets, and other software applications become the tools indispensable for collaboration. In 2006, small to medium enterprises were using Web-conferencing 41% of the time to include persons who could not previously attend, enable meeting not previously held, and to solve problems they were unable to address without the collaborative input (Nilssen & Greenberg, 2006). Technology is fundamental to small to medium businesses for customer presentations, demonstrations, training/e-learning, and internal/ external team function. The rationale for use of Web-conferencing includes economic savings, improved time management, scheduling flexibility, increased personnel productivity, and advance work flow (Nilssen & Greenberg, 2006). Thus, teaching with technology is not just an option, but is vital to preparing workers who have the skills to compete in current work environments.

FUTURE TRENDS One can barely imagine what future educational technologies may eventually be commonplace in our daily lives, much less in education. We will surely employ more realistic virtual environ-

ments such as Second LifeTM, more educational materials on demand via our ever smaller and faster personal digital assistants, increased virtual networking and communications, and even holographic models on which to apply the theories and concepts learned. These possibilities are already present in our laboratories and think tanks today, if not yet readily available to us as instructors and learners. But, might we also explore more direct means of transfer of knowledge in – and out – of our minds, similar to the ways in which PET scans and EEG now monitor our brain waves in medical diagnoses. We are already on the edge of enhanced understanding of the incredible power of our sleep and unconscious mental states in learning. We will surely continue this exploration of ways to maximize these alternative states of consciousness in knowledge capture and transfer. What other instructional technologies are already budding in the minds of our youngest learners? The possibilities of next generation technological tools that await us as educators and learners are virtually unimaginable. Other future trends that await us will surely be impacted by increasingly complex global economies, changing political pressures, environmental concerns, and ever changing demographics. We may see continued interest in a single worldwide language, for instance, at least for business and educational transactions. Technologies will surely support improved multicultural understanding and perhaps somehow ease international communications and travel among people of the world, hopefully while protecting both our individual cultural selves and the environment. And, the demographic realities of longer, healthier working lives will undoubtedly influence not only what we learn, but how instructional technologies can facilitate that learning and application to our future workplaces. Other demographic and cultural attributes will also impact the use of various instructional technologies, as we consider not just race, gender, and age, but other critical issues such as language, abilities, and other aspects of culture.

259

Learner-Centered Teaching and the Use of Technology

But, given the focus of this article on the use of educational technologies in learner-centered instruction, we must also continue to consider the impact of these future trends and emerging technologies on both learning processes and outcomes. How will educators ensure that future instructional technologies narrow, instead of widen the access and achievement gap of learners? How might the technologies of the future continue to balance the power dynamic in our learning environments? Can learners continue to develop self-directed capacity and autonomy so that the technologies in place help us learn how to learn, and so capture ever increasing and necessary knowledge available? Can the instructional technologies aid instructors in alternative and improved ways to consider content and evaluation in service of learning. The inevitable growing knowledge obsolescence, expansion, and development of the future demand that instructors and learners alike be able to develop and master instructional technologies. By doing so, we may continue to empower learners toward greater personal autonomy, critical thinking and reflection, and self-actualization.

CONCLUSION Instructional technologies, as tools for learning in the classroom and as generators of created environments, are artifacts of human existence (Bruce, Feng, Nishizawaumiko, Palulis, Russel, & Worthing 2003). Technology holds meaning within the educational experience and via interaction to facilitate the acquisition of knowledge, to share knowledge, and to create new knowledge. Throughout history, we have come to know the meaning of many cultures through the technologies used to depict drawing on cave walls and symbols on stone tablets. The technologies of the 21st century will, at some point in the future, be viewed as primitive as those ancient cultures that came before us. Neal and Winnipeg (1995) noted that technology becomes the way a culture expresses

260

itself and is a reflection of its societal values. Future societies may also judge our educational use of technology in the same way. Technological tools of learning must allow for tone and emotion, human connection, and presence to transmit contextual meaning—especially as they relate to the further development of learner-centered instruction. It is important that we document the legacy of current learning technologies and continue to study the most effective use of these evolutions of time.

REFERENCES Allen, I. E., & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States. Needham, MA: Sloan & Sloan Center for Online Education (SCOLE). Allen, I. E., & Seaman, J. (2008). Staying the course: Online education in the United States, 2008. Needham, MA: Babson Survey Research Group, The Sloan Consortium. American PsychologicalAssociation. (1997). Learner-centered psychological principles: A framework for school redesign and reform. Retrieved April 20, 2009, http://www.apa.org/ed/lcp.html Barr, R. B., & Tagg, J. (1995). From teaching to learning—a new paradigm for undergraduate education. Change, 27(6), 12–25. Barrett, H. C. (2007). Researching electronic portfolios and learner engagement: The REFLECT initiative. Journal of Adolescent & Adult Literacy, 50(6), 436–449. doi:10.1598/JAAL.50.6.2 Bastable, S. B. (2003). Nurse as educator: Principles of teaching and learning for nursing practice (2nd ed.). Sudbury, MA: Jones & Bartlett. Billings, D. M., & Halstead, J. A. (2005). Teaching in nursing: A guide for instructors (2nd ed.). St. Louis, MO: Elsevier Saunders.

Learner-Centered Teaching and the Use of Technology

Bonk, C. J., Wisher, R. A., & Lee, J. Y. (2004). Moderating learner-centered e-learning: Problems and solutions, benefits and implications. In T. S. Roberts (Ed.), Online collaborative learning: Theory and practice (pp. 54-85). Hershey, PA: IGI Global.

Du, H., & Wagner, C. (2005). Learning with weblogs: An empirical investigation. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05), Big Island, Hawaii (pp. 7). IEEE.

Bourne, J., & Moore, J. (2004). Elements of quality online education: Into the mainstream. Needham, MA: Sloan Consortium.

Farrell, G. M. (2001). The changing faces of virtual education. London: Commonwealth of Learning.

Boyer, E. (1990). Scholarship reconsidered: Priorities for the professoriate. Princeton, NJ: The Carnegie Foundation for the Advancement of Teaching. Bruce, A., Feng, F., Nishizawaumiko, S., Palulis, P., Russel, B. D., & Worthing, C. (2003). Provoking signs: Un/canny moments as curriculum theorizing. Educational Insights, 8(2), 1–20. Cooper, C., Taft, L. B., & Thelen, M. (2004). Examining the role of technology in learning: An evaluation of online clinical conferencing. Journal of Professional Nursing, 20(3), 160–166. doi:10.1016/j. profnurs.2004.04.003 Cornelius-White, J. (2007). Learner-centered instructors-student relationships are effective: A meta-analysis. Review of Educational Research, 77(1), 113. doi:10.3102/003465430298563 Derntl, M., & Motschnig-Pitrik, R. (2004, March 1417). Patterns for blended, person-centered learning: Strategy, concepts, experiences, and evaluation. In Proceedings of the 2004 ACM Symposium on Applied Computing, Nicosia, Cyprus (pp. 916-923). ACM Publishing. Diekelmann, N., Schuster, R., & Nosek, C. (1998). Creating new pedagogies at the millennium: The common experiences of University of WisconsinMadison instructors using distance education technologies (commissioned final report to University System of Wisconsin no. 1). Madison, WI: University of Wisconsin.

Flores, F. (1998). Information technology and the institution of identity. Information Technology & People, 11(4), 351–372. doi:10.1108/09593849810246156 Gargiulo, T. L. (2009). The top ten strategies for managers of mobile workers. Retrieved April 10, 2009, from http://makingstories.net Gillespie, M. (2005). Student-instructors connection: A place of possibility. Journal of Advanced Nursing, 52(2), 211–219. doi:10.1111/j.13652648.2005.03581.x Harrison, D. (2009). Engaging students in virtual learning. Retrieved April 23, 2009, from http:// campustechnology.com/Articles/2009/04 /22/ Engaging-Students-in-Virtual-Learning Hartley, K., & Bendixen, L. D. (2001). Educational research in the Internet age: Examining the role of individual characteristics. Educational Researcher, 30(9), 22. doi:10.3102/0013189X030009022 Holcomb, J. B., Dumire, R. D., Crommett, J. W., Stamateris, C. E., Fagert, M. A., & Cleveland, J. A. (2002). Evaluation of trauma team performance using an advanced human patient simulator for resuscitation training. The Journal of Trauma Injury Infection and Critical Care, 52(6), 1078. doi:10.1097/00005373-200206000-00009 Huang, U. (2002). Toward constructivism for adult learners in online learning environments. British Journal of Educational Technology, 33(1), 27–37. doi:10.1111/1467-8535.00236

261

Learner-Centered Teaching and the Use of Technology

Johnson, S. A., & Romanello, M. L. (2005). Generational diversity: Teaching and learning approaches. Nurse Educator, 30(5), 212–216. doi:10.1097/00006223-200509000-00009 Kayler, M., & Weller, K. (2007). Pedagogy, selfassessment, and online discussion groups. Journal of Educational Technology & Society, 10(1), 136. Kennedy, G. E., Judd, T. S., Churchward, A., Gray, K., & Krause, K. L. (2008). First year students’ experiences with technology: Are they really digital natives. Australasian Journal of Educational Technology, 24(1), 108–122. Kenny, G., Pontin, D., & Moore, L. (2004). Negotiating socialisation: The journey of novice nurse academics into higher education. Nurse Education Today, 24(8), 629–637. Koehler, M. J., & Mishra, P. (2005a). Instructors learning technology by design. Journal of Computing in Instructors Education, 21(3), 94–102. Koehler, M. J., & Mishra, P. (2005b). What happens when instructors design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131–152. doi:10.2190/0EW701WB-BKHL-QDYV Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall. Koper, R. (2004). Use of the semantic web to solve some basic problems in education. Journal of Interactive Media in Education, 6, 1–23. Koper, R., & Olivier, B. (2004). Representing the learning design of units of learning. Journal of Educational Technology & Society, 7, 97–111. Koper, R., & Tattersall, C. (2004). New directions for lifelong learning using network technologies. British Journal of Educational Technology, 35(6), 689–700. doi:10.1111/j.1467-8535.2004.00427.x

262

Kreijns, K., Kirschner, P. A., Jochems, W., & Van Buuren, H. (2004). Determining sociability, social space, and social presence in (a) synchronous collaborative groups. Cyber-psychology & Behavior: The Impact of the Internet . Multimedia and Virtual Reality on Behavior and Society, 7(2), 155–172. Krichen, J. P. (2004). Online university administration: Impacts on instructors’management and course delivery. Retrieved from http://www.decadeconsulting.com/ decade/images/Jkrichen.pdf Lu, H., Jia, L., Gong, S., & Clark, B. (2007). The relationship of Kolb Learning Styles, online learning behaviors, and learning outcomes. Educational Technology & Society, 10(4), 187–196. MacIntosh, J. (2003). Reworking professional nursing identity. Western Journal of Nursing Research, 25(6), 725–741. doi:10.1177/0193945903252419 Magjuka, R. J., Shi, M., & Bonk, C. J. (2005). Critical design and administrative issues in online education. Online Journal of Distance Learning Administration, 8(4), Article 4. Retrieved April 28, 2009, from http://www.westga.edu/~distance/ojdla /winter84/magjuka84.htm McCombs, B. L., & Lauer, P. A. (1997). Development and validation of the learner-centered battery: Self-assessment tools for teacher reflection and professional development. Professional Educator, 20(1), 1–21. McCombs, B. L., & Vakili, D. (2005). A learnercentered framework for e-learning. Teachers College Record, 107(8), 1582–1600. doi:10.1111/j.14679620.2005.00534.x Merriam, S., Caffarella, R., & Baumgartner, L. (2007). Learning in adulthood: A comprehensive guide (3rd ed.). San Francisco: Jossey-Bass. Mikropoulos, T. A., & Strouboulis, V. (2004). Factors that influence presence in educational virtual environments. Cyberpsychology & Behavior, 7(5), 582–591.

Learner-Centered Teaching and the Use of Technology

Mott, V. W. (2004). Book review: Learnercentered teaching: Five key changes to practice. Adult Education Quarterly, 54(3), 244–245. doi:10.1177/0741713604263058

Reynard, R. (2009). Can we gauge technology’s impact on learning outcomes? Retrieved April 23, 2009, from http://campustechnology.com/Articles/ 2009/03/25/Does-Technology-Improve-Learning

Mott, V. W. (2009). Evolution of adult education: Is our future in e-learning? In V. C. X. Wang (Ed.), Handbook of research on e-learning applications for career and technical education: Technologies for technical training (pp. 778-791). Hershey, PA: IGI Global.

Russo, T., & Benson, S. (2005). Learning with invisible others: Perceptions of online presence and their relationship to cognitive and affective learning. Educational Technology & Society, 8(1), 54–62.

Neal, A., & Winnipeg, M. (1995). Group apraxia: The phenomenology of acculturalism. The Canadian Journal of Native Studies, 10(2), 219–242. Nilssen, A., & Greenberg, A. (July 2006). The vital role of web conferencing in small and medium enterprises. Live Oak, FL: Wainwright Research. Novak, J. D. (2003). The promise of new ideas and new technology for improving teaching and learning. Life Sciences Education, 2(2), 122–132. O’Lawrence, H. (2007). An overview of the influences of distance learning on adult learners. Journal of Education and Human Development, 1(1), 7. Retrieved March 12, 2009, from http://www.scientificjournals.org /journals2007/articles/1041.htm Oblinger, D., & Oblinger, J. (2005). Educating the net generation (1st ed.). Retrieved from http://www. educause.edu /educatingthenetgen Pettitt, J. M. (2002). Power relationships in two web-based courses. Raleigh, NC: North Carolina State University. (ERIC Document Reproduction Service No. ED471832) Quinsee, S., & Hurst, J. (2005). Blurring the boundaries? Supporting students and staff within an online learning environment (ERIC Document Reproduction Service No. ED494786). Retrieved on April 28, 2009, from http://www.eric.ed.gov/ ERICWebPortal/Home.portal?_ nfpb=true&_ pageLabel=basic&Clearme=true

Saba, V. K. (2001). Nursing informatics: Yesterday, today and tomorrow. International Nursing Review, 48(3), 177–187. doi:10.1046/j.14667657.2001.00064.x Schaffert, S., Bischof, D., Bürger, T., Gruber, A., Hilzensauer, W., & Schaffert, S. (2006, June 11-14). Learning with semantic wikis. Paper presented at the 1st Workshop on From Wiki to Semantics, 3rd Annual European Semantic Web Conference (ESWC), Budva, Montenegro. Retrieved April 29, 2009, from http://www.salzburgresearch.at/res earch/gfx/ semantic_wiki_elearning.pdf Schoech, D., & Helton, D. (2002). Qualitative and quantitative analysis of a course taught via classroom and internet chatroom. Qualitative Social Work, 1(1), 111–124. doi:10.1177/1473325002001001748 Task Force on Distance Education and Training in Professional Psychology American Psychological Association. (2002). Principals of good practice in distance education and their application to professional education and training in psychology. Washington, DC: American Psychological Association, Task Force on Distance Education. Thomas, L., & Knezek, D. (1995). Technology literacy for the nation and for its citizens. Retrieved April 28, 2009, from http://www.iste.org/AM/PrinterTemplate. cfm?Section=Technology_Literacy Weimer, M. (2002). Learner centered teaching (1st ed.). San Francisco: Jossey-Bass.

This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 1-16, copyright 2009 by Information Science Reference (an imprint of IGI Global) 263

264

Chapter 15

Teaching with Technology: Crucial Factors not to be Neglected Victor C. X. Wang Northcentral University, USA

ABSTRACT Successful teaching with technology in adult education stems from many factors. Technology is only used to enhance learning. Not only are teachers of adult learners required to study the tools related to the use of technology, but are also required to study the nature of knowledge, the nature of learning, constructivism and various kinds of teaching philosophies. Without thorough knowledge of these factors, successful teaching with technology cannot occur in adult education, let alone other educational fields. This article is comprehensive concerning successful teaching with technology in adult education because it also addresses the interrelationships between the use of technologies and the teaching and learning process.

INTRODUCTION Using technology for education and training of adult learners offers many challenges. However, the greatest challenge is to focus not on technology itself but on the learner and learning (Olgren, 2000). Olgren argues that technology invites a tools-first emphasis, but technology is only as good as our knowledge of how to use it to enhance learning (p. 7). Her point is well taken in the field of adult education whose focus is placed on the DOI: 10.4018/978-1-60960-153-9.ch015

education and training of adult learners in the 21st century. One of the characteristics of adult learners is that they have multiple work/family responsibilities (Wang, 2008). Because of this characteristic, adult learners find it hard to attend face-to-face meetings in a traditional classroom on a physical campus at the end of a week day or on a weekend. Universities and colleges have seized this great opportunity to accommodate the needs of adult learning by moving their courses onto computer screens, hence the issue of effective or successful teaching with technology in adult education. Knowles, the father of adult education,

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Teaching with Technology

predicted in the early 1970s that education, especially the education of adults in the 21st century would be delivered electronically. His predication came true as universities and colleges began to address adult learning by using WebCT or Blackboard programs or any other course rooms. These educational programs were purchased in the late 1990s. Adult learners have been taking advantage of these educational programs by taking courses online to meet their needs of upgrading their work skills, getting a college degree/diploma/ credentials or simply satisfying their sheer joy of learning. Giant online universities, such as the University of Phoenix, have emerged to launch massive online educational programs to address the learning needs of adult learners. Bash (2003) noted, “In 2002, the University of Phoenix, part of the Apollo Group, saw its enrollment surpass 100,000 students—making it the largest institution of higher learning in the United States” (p. 50). Other online universities do not want to lag behind. For example, Northcentral University in Arizona has been actively seeking accreditation from the national accreditation bodies and the university has successfully maintained its accreditation over the years. Because of this fact alone, Northcentral University’s enrollment has been on the increase. Their goal is to offer quality education through technology to working adults throughout the world. Due to the trend of teaching with technology in the new century, enrollment can be much higher especially when universities and colleges have the need to do more with less. As our student numbers are expected to grow, our budgets continually are shorn. It is a not a matter of whether faculty enjoy teaching with technology. Again, we are talking about the new trend, that is, teaching successfully with technology to accommodate the needs of learners and to help universities save money to achieve cost-effectiveness in managing their tightened budgets. Gone are the days when faculty could argue that they are philosophically against teaching with technology. Currently, faculty is required to embrace with open arms the biggest change in their lives to

integrate at least some measure of teaching with technology in their practice. See Wang’s newest release titled Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches (2010). This book embodies the new trend in this new century for both teachers and learners. It is not surprising when we hear that a certain university has put one third of its courses online. Teaching with technology has emerged as a new trend in this new century. As Brookfield (2006) noted, ↜“These days no college teacher can avoid teaching in a hybrid manner, combining electronic and face-to-face communication. The only question remaining is the degree to which electronic communication is integrated into course activities” (p. 191). As I write, I am teaching over 100 adult learners in four different classes via either hybrid format or entire online format. Here, I am not trying to say that face-to-face education with adult learners would be marginalized with the advent of Internet technology. Rather, teaching with technology like regular teaching in university settings seems to treat learning as a commodity, turning it into an external object marketed for a hefty price to save cash-strapped programs trying to stay afloat (Brookfield, 2006, p. 192). Perhaps this is where pragmatism comes into play. Where there is learning with technology, there is teaching with technology. After all, programmed instruction with computers was popularized even in the 1960s by behaviorists. Who is not to say that the virtual environment is not a teaching and learning environment? It is not a vacuum; rather it is filled with human interaction. That is where teaching and learning can be achieved 24/7 (anywhere and anytime). Pedagogically, faculty is worried about the fact that teaching with technology would take the personal dimension out of teaching, or remove the relational element. The fundamental question that can be asked is how can students always trust someone they have never seen in person or spoken to directly? Or another question can be asked is can students learn with technology in an isolated environment?

265

Teaching with Technology

To address such pedagogical questions, let’s turn to the advantages of teaching with technology as summarized by Brookfield (2006): •

•

•

•

•

Teaching with technology is not necessarily qualitatively different from its face-toface counterpart. Indeed, various introductory guides to e-teaching explore many of the exact same problems (how to engage students, respond to racial differences, take account of different learning styles, and so on) that engage the attention of teachers in face-to-face classrooms (Conrad & Donaldson, 2004; Palloff & Pratt, 1999, 2003). In asynchronous discussion learners would have the time to think through their responses without the pressure to come up with an impromptu contribution or response to a teacher’s question that would make them look good in class. Students who struggled with language, who were introverts, or who needed time to process information and create meaning, as well as those who were intimidated by the theater of the classroom (particularly having to play the role of the smart, capable, committed student), would all benefit from learning with technology’s privacy. Learning with technology also placed a greater degree of control into the students’ hands over when and how fast learning happened, something Piskurich (2003) argues increases both retention and selfdirected learning. Finally, in learning with technology, students stressed the importance of feeling a member of some type of learning community in exactly the way that students in face-to-face classrooms did.

Although a case can be made about the benefits of teaching/learning with technology, there are potential problems associated with teaching

266

with technology that equally deserve our attention. The first issue is the learner’s physical isolation which may pose problems with learning. How can a teacher evaluate the learner’s learning? Will the learner do the learning on his or her own in an isolated environment? The second issue is teaching with technology is time consuming. The time spent in giving extensive feedback is considerable. The third issue is impossible for teachers to read and give visual and tonal cues when teaching with technology. Although smiley faces, exclamation points, dots for pauses, boldface and capitals can be used to express importance, the possibility for misunderstanding does exist. There is a delay between the individual typing the words he/she wants to convey and all other chat participants seeing the words projected on the computer screen. The similar delay also exists when students try to communicate with each via microphones. Finally, as Brookfield points out that students from cultures in which collective decision making is the norm, will find it hard to sit by themselves, stare at their screen, and respond to words typed by others at a different time and in a different place (2006, p. 195). While acknowledging the benefits and problems of teaching with technology, the purpose of this article is to show our readers how we can capitalize on the known benefits and address the problems associated with teaching with technology so that successful teaching with technology in adult education will occur. Teaching with technology should enable users to exercise maximum control and freedom to create or do what they intend. Helping adults learn with the use of technology involves innovative approaches such as adopting useful teaching philosophies, problemsolving models, constructivist model or critical thinking skills. It is these innovative approaches or instructional methods that will enhance adult teaching and learning with the use of technology. As technology is used to enhance learning, it must be used to with innovative approaches. Otherwise, successful teaching with technology

Teaching with Technology

in adult education would not occur. Next, I will provide broad definitions and discussions of this article that will incorporate view of others regarding our topic under discussion.

BACKGROUND Burge (2000) defines technology as any tool that requires informed design and appropriate use in order to enhance an adult’s ability to learn; that is, to enhance the use of various information processing strategies and learning activities alone, with peers, and with appropriate advisers and educators (p. 1). Teaching with technology is characterized by a physical separation between learner and instructor and by the use of media for communications and content resources. These characteristics have important effects on the learner. First, teachers have the responsibility for carrying out the teaching process. Second, teachers must be able to use technology to access resources and communicate with others. Third, teachers need to find ways to motivate learners to learn in an isolated setting. Since we mentioned media and technology here, it is necessary for us to make a distinction between the two. According to Bates and Poole (2003), speech, writing, drama, radio and television programming, computer programming, and Web-based courses are all media, or more strictly, symbol systems that uniquely define specific media. Classrooms, books, theaters, cinemas, radio sets and transmitters, cable, satellites, television monitors, computers, computer software, and computer networks are all technologies (2003, p. 48). This is a good definition of technologies. In addition, they indicate that technologies are physical things whereas media are means of communication. In our everyday use of the term media, we usually refer to the whole organization of a communications industry, such as television, newspapers, publishing, and the Internet. Without definitive definitions of technologies, we may fail to understand the interrelationship between

teaching and technologies. We know more about teaching than about technologies. Speaking of the history of teaching, we can trace back to Socrates, Plato or Confucius. How about the role of technology in education? The role of technology in education goes back to 25 centuries ago. For the ancient Greeks, oratory and speech were the means by which people learned and passed on learning. Likewise, the ancient Chinese learned and passed on learning by the means of Confucius’s analects. People in the past learned basically by listening, not by reading or writing. People learned by recitation (Bates & Poole, 2003). After paper and printing were invented, books emerged as early as the fifth century B. C. Later, people realized although writing would not help memory, it would act as a reminder. To the Chinese, teaching embraces twin goals: to teach books and to teach people (Wang, 2007). Naturally, teaching through a computer is not the same as teaching from a book or teaching from a lecture. These activities are all different forms of teaching and each results in a slightly different way of students’ learning about something. Deep understanding occurs when all forms of knowing developed by a learner are internally reconciled and integrated by the learner (Bates & Poole, 2003). Therefore, we need to focus on how media can be used to facilitate knowledgeconstruction and meaning-making on the part of the learner (Cranton, 1994; Mezirow, 1985, 1990, 1991, 2000; King, 2005; Wang & King, 2006, 2007). The goal of teaching with technology is to facilitate learning, not to inhibit learning on the part of adult learners, and learning leads to knowing. Educators are interested in knowing whether students’ performance objectives can be achieved and how much information learners can retain. Bates and Poole (2003) argue that teaching with technology is not necessarily better or worse than face-to-face education; it is, though, different. They further argue that once we come to accept that different is not necessarily better

267

Teaching with Technology

or worse, we change the nature of the argument about teaching technologies. The fundamental question then is not are they better or worse, but in what contexts and for what purposes are technologies best used? I agree with Bates and Poole on their insights regarding the use of technology as these two scholars have been keeping up with the latest development of technology. Technology should be used as a tool for successful education to maximize learning on the part of learners although doing more with less should be just the by product of teaching with technology. Having defined technology, we want to know: what exactly are technologies that can be used in teaching adult learners and learners of any kind? Bates and Poole indicate that five media represent different clusters of symbol systems and ways of mediating and interpreting knowledge and these five primary education media are listed below: • • • • •

Direct face-to-face contact Text (including still graphics) (Analogue) audio (Analogue) video Digital multimedia

To educators of adults, the distinction between synchronous and asynchronous technologies is important. While synchronous technologies require all participants to participate at the same time, asynchronous technologies allow participants to access the technology at any time of their choosing. While bringing everyone together for an educational event can create a sense of community, asynchronous technologies provide flexibility and convenience for both teachers and learners. As I write this article and this book, I have found that most adult learners prefer the asynchronous technologies to synchronous technologies simply because their family and work responsibilities do not allow them to be brought together for an educational event. Below, I have modified Bates and Poole’s 2003 table to illustrate when to teach

268

with technology to maximize learning. The questions that are worth asking can be: 1. When can we use technology to replace direct personal contact without educational loss or with educational gain? 2. When can we combine face-to-face with technology based teaching for the best results? 3. When can we teach with technology alone? It can be seen that various technologies differ significantly on key structural characteristics that are of potential importance for educational purposes. The challenge is to decide when to use which technology for what educational purposes. The strength of technology comes from the combination of different media. No single medium is likely to be sufficient for any university-level subject (Bates & Poole, 2003). Poorly-designed applications of multimedia can frustrate learners. Well-designed applications of multimedia can, according to Bates and Poole (2003): •

• •

•

Enable learners to come to understandings more quickly than through more conventional verbal or textual media. Help students develop and practice skills. Change how we come to know or to understand and hence what we know and understand. In other words, through the use of multimedia, a learner may have an image or a mental construction that is far richer than an abstract verbal understanding. Enable a learner to move from concrete, specific examples to more general abstractions, and vice versa.

Without knowing some background information about technology and media, how technology has evolved, the difference between technology and media, and a detailed classification of technologies, teachers cannot help adult learners learn successfully or achieve students’ performance

Teaching with Technology

Table 1. A classification of educational technologies by structural characteristics Technologies Broadcast (one-way) Applications

Communication (two-way) Applications

Media

Synchronous

Asynchronous

Synchronous

Face-to-face

Lectures

Lecture notes

Seminars

Text

Books

Asynchronous Mail

Audio

Radio

Audio-cassettes

Telephone tutoring AudioConferencing

Video

Broadcast TV Cable TV Satellite TV

Video-cassettes

Videoconferencing

Digital multimedia

Webcasting AudioStreaming VideoStreaming Discussion board forum

Web sites CD-ROMs DVDs Learning objects Multimedia Clips Discussion board forum

Chat MUDs WebConferencing Whiteboard via WebCT/Blackboard Discussion board

E-mail Discussion Forums Whiteboard via WebCT/Blackboard Discussion board

Adopted and adapted from Bates and Poole (2003, p. 55).

ojectives. The goal of teaching with technology is to facilitate learning, not to inhibit learning. To know some background information about technology and media is just the first step towards teaching successfully with technology. Our next section will address issues such as the nature of knowledge, the nature of learning, and one’s teaching philosophies, all of which will contribute to teaching successfully with technology. Teaching with technology requires teachers to know something about the nature of knowledge. The nature of knowledge focuses on the question of how we know what we know. Epistemology is a branch of philosophy concerned with the nature and justification of knowledge (Hofer & Pintrich, 1997). In other articles, scholars indicated that adults and children learn differently. This distinction was made by the father of adult education, Malcolm Knowles in the early 1970s (Knowles, 1975). This distinction alone will require teachers to use technology differently. It is natural that one’s teaching philosophies predetermine one’s teaching methods including the use of technol-

ogy. Our next section will specifically address the nature of knowledge, the nature of learning and teacher’s teaching philosophies. More importantly, we will address how these elements influence the use of technology, particularly, the successful use of technology so that the goal of teaching with technology can be achieved. If the use of technology can not be justified, then, technology should be abandoned.

THE NATURE OF KNOWLEDGE CONCERNING ADULT LEARNING An important part of adult education is aimed at developing students’ understanding, within this academic discipline, of the criteria and values that underpin academic study of this discipline. These criteria and values include questions of what constitutes valid knowledge in this subject area. Or what is the core body of knowledge in the subject area? Valid knowledge in adult education consists of not only instructional strategies, but

269

Teaching with Technology

also content of the field. For these two kinds of knowledge bases, instructional strategies and content of the field, both teachers and adult students are required to know the nature of knowledge in the field. Do adults approach their knowledge differently from children? How can technology be used to help adults approach their knowledge? These are the first two questions teachers should ask themselves before delving into the nature of knowledge. Two dominant epistemological positions that exist today are worth discussing for our purpose— objectivism and constructivism (Creswell, 2009; Clark & Creswell, 2008). First objectivists believe that there exists an objective and reliable set of facts, principles, and theories that either have been or will be discovered and delineated over the course of time. Bates and Poole write in 2003, This position is linked to the belief that truth exists outside the human mind or independently of what an individual may or may not believe. The laws of physics are thus constant, although our knowledge of them may evolve as we discover the “truth” out there. (p. 28) Their argument stems from Habermas’s (1971) book titled Knowledge and Human Interests (Cranton, 2010). Do teachers of adults view themselves as objectivists in the field of adult education? In fact, a large number of teachers of adults are labeled as objectivists who still believe that a course must present a core body of knowledge to be learned on the part of adult students. Their courses may consist of formulas, terminology, theories, and the like. The successful transmission of this core body of knowledge becomes of central importance. Instructors prefer lectures and standardized textbooks to discussions. Their courses are well organized and clear and instructors like to be considered as authoritative figures in the field (Wang, 2007-2008). Course assignments and exams require students to find the right answers and

270

justify them. When it comes to using technology to teach courses to adult students, these objectivist instructors normally set ground rules regarding online discussions. Their online course may be well laid out, mapped out, and well designed. Exams are usually timed. Course instructors grade students’ work according to rubrics. I am not saying this approach to teaching adults is wrong. Rather, it is predetermined by multiple factors. Often times, instructors have no choice but to follow objectivist approaches to teaching and to teaching with technology. First and foremost, if instructors believe that there exists an objective and reliable set of facts, principles, and theories that either have been or will be discovered and delineated over the course of time, they are bound to use objectivist approaches including objectivist approaches to using technology. Also, the nature of course may determine such approaches to teaching. For example, in adult basic education, students do not have the basic knowledge, skills or attitudes in the field. Instructors have to use this approach. One more factor that needs our attention is the fact that some institutions may require instructors to conform to objectivist approaches to teaching even adult learners. What if you have a department chair who has an advanced degree obtained from the field of K-12 education and who is so comfortable with approaches of teaching children? If this chair requires that the objectivist approaches be the main instructional methods in the department, teachers of adults would have no other choices but to follow this norm. If you read books by Knowles, Holton, and Swanson (2005), they would probably tell you that it depends on your learners’ experience with a subject matter. They would say, “Use objectivist approaches if you believe your adult learners are inexperienced with a subject matter and if they depend on instructors for speed and convenience.” Is there a better approach than the objectivist approach to teaching with technology in the field of adult education? The answer lies in a different epistemology, that is, constructivism in adult education. Constructiv-

Teaching with Technology

ists believe that knowledge is essentially subjective in nature, constructed from our perceptions and mutually agreed upon conventions. Bates and Poole (2003) explain this epistemology as follows: We construct new knowledge rather than simply acquire it via memorization or through transmission from those who know to those who did not know. We construct meaning by assimilating information, relating it to our existing knowledge, and cognitively processing it (that is, thinking about it). Social constructivists believe that this process works best through discussion and social interaction, allowing us to test and challenge our own understanding with those of others. For a constructivist, even physical laws exist because they have been constructed by people from evidence, observation, and deductive or intuitive thinking and, most important, because certain communities of people (in our example, scientists) have mutually agreed what constitutes valid knowledge. (p. 28) Constructivism falls squarely in line with one of the principles of adult learning, namely, adult learners’ rich reservoir of experience. Knowles (1990, p. 45) stated, “as adults mature, they accumulate an increasing reservoir of experience that becomes an increasingly rich resource for learning.” Without prior experience, adult learners can not construct meaning by assimilating information, relating it to their existing knowledge, and cognitively processing it. Mott (2008) takes prior experience a step further by linking it to instruction. She indicates that our experience is important not only as a basis for greater and more meaningful learning, but also because such experience provides links and connections that teachers can use in instruction. When using technology to teach adult learners, definitely instructors can create an online discussion forum where adult learners’ rich experience is included. Discussion topics can revolve around adult learners’ prior experience. By discussing learners’ prior experience, new knowledge can be generated regarding

a certain subject in adult education. For example, for a course titled Curriculum Development for Auto Mechanics, instructors can arrange for students (auto mechanics) to discuss their prior experience and make a summary of their prior experience. This rich reservoir of experience can be translated into task analysis which may serve as an important part of curriculum development for auto mechanics. And video clips showing how these auto mechanics repair vehicles on a day to day basis will help students learn via learning with technology. Video clips on CD-ROMs and DVDs will also help students learn according to their individualized learning pace. Constructivism also works with Mezirow’s (1985, 1990, 1991, 2000) theory or transformative learning as discussed in our other articles. The central theme of transformative learning theory is change of adult learners’ perspectives by giving meaning to their prior experience. In other words, adult learners need to make sense of their own prior experience. Again, we can give meaning to our experience by assimilating information, relating it to our existing knowledge, and cognitively processing it (i.e., thinking about it). Translated into instructional approaches, constructivism requires instructors to ask their students to read about the experience of other people in the field and relate these experiences to their own. Students are asked to work in small groups to identify common themes, and important differences, within the experiences of both the subjects of their required readings and those studying in each group. Students then report back to the whole group, which provides feedback and discussion on each individual group’s report. Later, students are asked to summarize their own feelings and opinions on what they have read and discussed. Then, instructors may check whether this learning experience can lead to change in their perspectives. Such is the constructivist approach to teaching if instructors have adopted a constructivist view on epistemology.

271

Teaching with Technology

Another important principle of adult learning is self-directedness. Knowles (1990, p. 45) posits that adults approach their learning in a more independent and self-directed manner as opposed to being dependent on a teacher for one’s learning, resources, strategies, and evaluation of outcomes. Knowles went on to explain that self-directedness is always present on a continuum—that all learners, children and adults alike, are more or less self-directed depending on maturity, preexisting knowledge, motivation, and risk involved in the learning experience. If we take into consideration this prominent adult learning principle, we must admit that students can automatically construct knowledge through argument and discussion with their peers and through self-directed study (Laurillard, 1993; Tough, 1967, 1971). Then the role of the teacher is to help students understand not just the facts or concepts of a subject discipline, but also the rules and conventions for acquiring and validating knowledge within that subject discipline. According to Bates and Poole (2003), the notion of academic knowledge requiring mediation has major significance for the use of technology. They further argue that language (i.e., reading and speaking) is only one channel for mediating knowledge. Media such as video, audio, and computing can provide teachers with alternative channels of mediation. In summary, one’s epistemological positions predetermine one’s teaching approaches, especially one’s use of technology. As an objectivist approach works with adult learners in the field based on different factors, constructivist approaches enhanced by adult learning principles and Mezirow’s theory of transformative learning work even better with adult learners when it comes to teaching with technology. In the final analysis, Bates and Poole (2003) remind us that technology can accommodate a wide variety of epistemological positions. Because a teacher’s preferred epistemology has such an influence on the design not just of technology-based teaching but all forms of teaching, we need to illustrate how

272

technology design can accommodate different epistemological positions.

THE NATURE OF LEARNING There has been a great deal of research into how adults learn in the field of adult education. One of the principles of adult learning is internal motivation as popularized by Knowles in the 1970s. According to Knowles (1990), adults are more often internally or intrinsically motivated to learn. Even though virtually all of formal education includes some external motivation in the form of grades, better jobs, or higher salaries, adults are more likely to focus on the knowledge gained, the experience itself, rather than any extrinsic reward that accrues. That is, even when learning is problem-focused or performance-centered, adults understand that learning is valuable and often its own reward, that the learning will add value to their lives, and that it will improve their tomorrows. Because of this well reasoned principle stated by Knowles, does this mean that behaviorism has nothing to do with adult learners? If you read further books by Knowles and his associates, you will find out that he and his associates indicated it was okay to switch from an andragogical model of teaching to the pedagogical model of teaching (embraced by behaviorism) if your students are inexperienced with a subject matter and would like to depend on their instructors for a course content because of speed and convenience or learning styles. The reason I raised this issue of behaviorism here is that programmed instruction became such a norm as early as the 1960s in North America. Whenever talking about teaching technology, both scholars and practitioners will address programmed instruction. In fact, behaviorism has led to the creation of programmed instruction in teaching and learning in any academic field. As we know, behaviorist psychology arose in the 1920s and 1930s from an attempt to model the study of human behavior on the methods of the physical sciences. At the heart

Teaching with Technology

of behaviorism is the idea that certain behavioral responses become associated in mechanistic and invariant way with specific stimuli. It is obvious that a certain stimulus will evoke a particular response. According to behaviorists (Skinner, 1968; Watson, 1960-1961, 1967), it is possible to reinforce through reward or punishment the association between any particular stimulus or event and a particular event. Bates and Poole (2003) explains that, The bond formed between a stimulus and response will depend on the existence of an appropriate means of reinforcement at the time of association between stimulus and response. Behavior therefore can be modified or controlled by appropriately reinforcing random behavior (trial and error) as it occurs. (p. 31) Underlying behaviorism is the belief that human behavior is predicable and controllable. Behaviorism stems from a strongly objectivist epistemological position as discussed earlier in this article. Clearly, behaviorism has led to programmed instruction, such as observable and measurable learning objectives, and computerassisted instruction. Although there has been a strong movement away from behaviorist approaches to teaching in adult education, the reality is a large number of adult educators still use behaviorist approaches in teaching. Influenced by behaviorism, Tyler (1950) developed a definitive model of teaching which has been adopted by adult educators in the field of adult education. It must be pointed out that Tyler’s model is still in print even to this day. Based on Tyler’s model, teaching and evaluation revolve around four basic issues: identifying objectives, selecting the means for attaining those objectives, organizing those means, and evaluating the outcomes. Specifically, Tyler advocated that, •

In the syllabus, the question that must be answered is “What educational purposes

•

•

•

should the school seek to attain?” these educational objectives can first be identified by examining three sources: studies of the learners themselves, studies of contemporary life outside of school, and suggestions from subject specialists. The second question is “How can learning experiences be selected that are likely to be useful in attaining these experiences?” Here he argued for several general principles that should guide teachers in selecting objectives. The third question is, “How can learning experiences be organized for successful/effective instruction?” In making determinations about the organization of experiences, teachers should consider three criteria: continuity, sequence, and integration. The final question is, “How can the effectiveness of learning experiences be evaluated?” Valid and reliable tests should be developed and the results used to improve the teaching (Glatthorn, Boschee, & Whitehead, 2006, p. 43)

Although there has been a movement away from behaviorism in adult education, there is no way adult learners can say goodbye to this approach to teaching permanently. It is so common sense that adult learners do respond to external stimuli such as economic crisis, family crises, downsizing at work and critical incidents in life (Brookfield, 2005). When these situations occur, adult learners turn to learning. As I write this article, I can tell for sure that every time we have an economic recession, we have more adult learners seeking teaching credentials to teach their occupations to others as some of them are laid off from their employment in both public and private industries. When our economy recovers, we will have less adult learners seeking state certification. On the contrary, cognitivists believe otherwise. They insist that there are mental processes— internal and conscious representations of the

273

Teaching with Technology

world—that are essential for human learning. To behaviorists, learning is determined by external environmental structures that lead to reinforcement of behavior. Fontana (1981, p. 148) explains cognitive approach as follows: The cognitive approach… holds that if we are to understand learning, we cannot confine ourselves to observable behavior, but must also concern ourselves with the learner’s ability mentally to reorganize his psychological field (i.e., his inner world of concepts, memories, etc.) in response to experience. This latter approach therefore lays stress not only on the environment, but upon the way in which the individual interprets and tries to make sense of the environment. It sees the individual not as the somewhat mechanical product of his environment, but as an active agent in the learning process, deliberately trying to process and categorize the stream of information fed into him by the external world. Clearly, instructors who place emphasis on learners’ developing personal meaning through reflection, analysis, and construction of knowledge through conscience mental processing rely on the constructivist epistemological position. On the other hand, instructors who place emphasis on artificial intelligence to provide mechanical, electronic, and physical representations of mental process via the use of computer technology would depend on an objectivist or behaviorist epistemological position. I would suggest for successful adult education to occur, use a combination of a behaviorist and constructivist approaches. Although adults are basically internally motivated to learn, they are also externally motivated to learn. There is no denying that external structures such as economic crises, critical incidents trigger new learning of any kind.

274

RELATIONSHIP BETWEEN ONE’S PHILOSOPHIES AND THE USE OF TECHNOLOGY To teach successfully with technology requires teachers to adopt the right teaching philosophies. The aim of philosophy is, after all, to explain, to make sense of the world (Merriam & Brockett, 2007, p. 28). Above all, teaching philosophies teachers adopt and adapt influence their decisions regarding the use of technology to facilitate adult learning. Based on Elias and Merriam’s original framework (1995, 2005), it consists of six orientations of liberal education, progressivism, humanism, behaviorism, radicalism, and philosophical analysis. Later, they added another philosophical orientation, which is post modern philosophy. While liberal adult education values the acquisition of knowledge, the development of a rational perspective, and the ability to analyze critically, the progressive adult education places more value in knowledge derived from observation and experience than from tradition and authority. When it comes to teaching with technology, we can conclude that liberal adult educators involve heavy use of lectures via online teaching. Instructors may arrange more audio clips, text-based lectures, and assigned readings. On the other hand, progressive instructors may arrange online discussion forums where participants can discuss their prior experience or other people’s experience related to their subject under study. As discussed earlier in this article, behaviorists believe that human actions are the result of prior conditioning and the way in which a person’s external environment is arranged. To humanistic adult educators, their focus is on developing the potential of the learner. Further, their education is learner-centered and the role of the instructors is that of a learning facilitator. No need to repeat here that behaviorist will arrange artificial intelligence for their teaching with technology. Humanistic adult educators would serve as facilitators, linking their students to learning resources. They

Teaching with Technology

don’t believe in being treated by their students as authority figures. Students are considered by humanistic adult educators as capable of teaching themselves given their rich reservoir of prior experience and internal motivation. Independent study via CD-ROMs and DVDs is not a bad idea for humanistic adult educators. Asynchronous teaching is another channel humanistic adult educators can use to post pertinent information for adult learners so that students may access it anywhere, any time. To Freire (1970), the role of adult education is, through dialogue with learners, to facilitate acquisition of critical consciousness. Once learners become conscience of the forces that control their lives, they become empowered, and empowerment leads to action (p. 47). As Newman (2006) explains this philosophy, he advocates that we should teach defiance. As to analytic philosophy, Elias and Merriam (1995, 2005) posit that analytic teachers seek to clarify concepts, arguments, and policy statements used in adult education. Finally, they explain post modern philosophy as questioning such fundamental concepts as truth, theory, reality, knowledge and power. The fundamental question that needs to be asked is “What is the relationship between one’s philosophies and the use of technology?” As discussed in this section, teachers’ philosophical positions determine their teaching approaches and the use of technology.

FUTURE TRENDS Although adult education has tended to distance itself from K-12 and higher education (Merriam & Brockett, 2007), it has pioneered the use of technology to deliver instructional programs to students. From the University of Phoenix, the Northcentral University to all other traditional universities and colleges in North America, they all have used technology to teach even their traditional age students. Brilliant or outstanding

teaching is in your face-to-face context, faculty is required to do more with less. It is not a matter of whether faculty like teaching with technology. Teaching in the new century has become a matter of whether faculty is able to teach successfully with technology. Teaching requires many things on the part of the faculty. Mastery of the subject matter, skill, hard work and practice are just not enough. Successful technology-based teaching is particularly demanding as more and more adult learners juggle between school and employment. WebCT and Blackboard (recently merged) will continue to dominate the educational settings as these two learning resource management systems allow for the loading and storing of content in the form of text, graphics, or multimedia objects, the design of asynchronous discussion forms, online testing and the use of some course management tools (Bates & Poole, 2003). As soon as Elluminate. Com launched its service to provide synchronous interaction between faculty and students in 2007, many universities purchased an unlimited license. Regarding the Internet, it will continue to spread at a rapid rate around the world. Wideband access has already replaced narrow-band access. As universities and colleges in developed countries are teaching more than one third of all their courses with technology, this trend will sooner or later spread to developing countries that are still undecided as to whether they would deliver instructional programs via technology. Once they overcome their prejudice against technology, they will start to deliver teaching via technology by leaps and bounds as their student population is formidable. I agree with Bates and Poole on their insights regarding whether technology can change face-to-face formats or vice versa. Their argument has been technology does not really transform the traditional formats of face-to-face teaching. Rather, face-to-face formats transfer very easily to technology. In addition, they projected that as a result of technology, we may see a shift in the future to more project work and problem-based learning, the creation by students of multimedia

275

Teaching with Technology

projects and assignments, and more student choice in learning and curriculum. Indeed, innovative teachers will discover new ways or formats that will exploit the potential of technology. In adult education, faculty is concerned with whether there is enough technology available to support their methods of teaching because methods of teaching ultimately affect student learning outcomes. The answer is there is more than enough technology to support any methods of teaching in the field. Adult learning principles and methods are not just something only adult educational professionals know and practice. Instructional designers, librarians, university administrators and even software engineers are familiar with these principles and methods. Design teams are aware of academic goals for a university that will enhance the following: • • • • • • •

Learner-centered teaching Problem-based learning Collaborative learning Use of departmental research in undergraduate teaching Teaching linked to the community Lifelong learning Use of information technology in teaching (Bates & Poole, 2003, p. 271)

If we take a closer look at these academic goals, we know that they are derived from adult learning principles and methods. The next question can be: will technology refine the principles of adult learning, that is, andragogical assumptions about adult learners? As adult learning professionals apply andragogical assumptions in practice, they may find that technology when used carefully and thoughtfully by university and college teachers can not only facilitate the development of academic rigor, rational thinking, and evidencebased research, but can also help learners apply their learning to real-world contexts, understand more deeply and more quickly complex ideas, and construct new personal meanings (Bates

276

& Poole, 2003, p. 274). This may mean that principles of adult learning cannot become more powerful without the proper use of technology. As we talk about self-directed learning in adult education, technology can provide this mode of learning by providing self-controlled activities. Future research may answer the question of what asynchronous learning can be considered as selfcontrolled activities. As lifelong learners, part time students enjoy access and flexibility that technology can provide; traditional age students will find it more beneficial to learn with technology in the future.

CONCLUSION I have made an attempt to illustrate that technology cannot replace face-to-face teaching. Rather, it does drive change. When used carefully and thoughtfully, technology will increase not only access and flexibility, but also facilitate and make the learning process more efficient and more successful. The reason is simple: technology can provide more opportunities for practice and access to a wider range of materials. I still remember how I learned to drive a manual vehicle in Kansas when I attended a university there in the late 1990s as a graduate student. I was also teaching the Chinese language to American students as a visiting scholar at a Foreign Language Department. Two students offered me verbal instructions and helped me practice driving on a university parking lot. After two hours of practice, I still failed to learn to drive a manual vehicle. Then one student took me to a computer game in a local mall. He told me the importance of practicing to drive with computer games in order to get the right feel. I did what I was told and the next day, I did learn how to drive a manual vehicle. This example manifests the fact that technology even via computer games does enhance learning. Also technology enables teachers to offer alternative approaches to learning that suit the needs of different kinds of learners.

Teaching with Technology

When we talk about linking students to learning resources because of an adult learning principle, technology is the one that can offer access to resources that would not otherwise be available in a traditional classroom. To access an online library from an online class, this is just a mouse click away. Technology will save your money and trips to a physical university library. Indeed, technology can add value to the process of teaching and learning by creating richer or more authentic learning environments (Bates & Poole, 2003). When we think of benefits and disadvantages of teaching with technology, benefits will definitely outweigh disadvantages. Bates and Poole made a summary of the benefits that technology can bring to both faculty and students:

approaches to using technology. Evidently, these factors cannot be neglected. Rather, they must be taken into consideration if teachers want to teach with technology successfully. Although an objectivist (behaviorist) epistemological position works well with artificial intelligence, a combination of this approach with a constructivist approach may further facilitate learning on the part of students. After all, technology may enhance one dimension of learning, successful learning occurs when faculty are innovative with instructional approaches.

Technology provides teachers and students with opportunities to organize their teaching and learning in radically different ways. Neither teachers nor students have to be (always) present in the classroom. They can be freed from the requirement to be at a specific place at a specific time in order to teach or study. Technology allows for access to materials that would otherwise not be available in a classroom, and allows teachers and students to structure learning materials in a variety of ways. Technology enables various preferences for learning to be more easily accommodated, and makes it easier for part-time or working students to access learning. In particular, technology provides lifelong learners with a flexible and convenient way to continue to study and learn throughout their lives. (p. 269-270)

Bates, A. W., & Poole, G. (2003). teaching with technology in higher education: Foundations for success. San Francisco: Jossey-Bass.

This article has also demonstrated that deciding to use educational technologies can be challenging. Successful teaching with technology in adult education is even more challenging. Successful teaching with technology requires faculty to adopt and adapt not only their epistemological positions, but also their teaching philosophies. These factors and others such as nature of learning may predetermine one’s instructional approaches, especially

Cranton, P. (1994). Understanding and promoting transformative learning. San Francisco: JosseyBass.

REFERENCES Bash, L. (2003). Adult learners in the academy. Bolton, MA: Anker Publishing.

Brookfield, S. D. (2006). The skillful teacher: On techniques, trust, and responsiveness in the classroom (2nd ed.). San Francisco: Jossey-Bass. Burge, E. J. (2000). Editor’s notes . In Burge, E. J. (Ed.), The strategic use of learning technologies: New directions for adult continuing education, no. 88 (pp. 1–5). San Francisco: Jossey-Bass. Clark, V. L., & Creswell, J. (2008). The mixed methods reader. Thousand Oaks, CA: Sage. Conrad, R. M., & Donaldson, J. A. (2004). Engaging the online learner: Activities and resources for creative instruction. San Francisco: Jossey-Bass.

Cranton, P. (2010). Working toward self-evaluation . In Wang, V. C. X. (Ed.), Assessing and evaluating adult learning in career and technical education (pp. 1–11).

277

Teaching with Technology

Creswell, J. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage.

Laurillard, D. (1993). Rethinking university teaching: A framework for the effective use of educational technology. London: Routledge.

Elias, J. L., & Merriam, S. B. (1995). Philosophical foundations of adult education. Malabar, FL: Krieger Publishing Company.

Merriam, S. B., & Brockett, R. G. (2007). The profession and practice of adult education: An introduction. San Francisco: Jossey-Bass.

Elias, J. L., & Merriam, S. B. (2005). Philosophical foundations of adult education (3rd ed.). Malabar, FL: Krieger Publishing Company.

Mezirow, J. (1985). A critical theory of selfdirected learning . In Brookfield, S. (Ed.), Selfdirected learning: From theory to practice: New directions for continuing education, no. 25. San Francisco: Jossey-Bass.

Fontana, D. (1981). Psychology for teachers. London: Macmillan/British Psychological Society. Freire, P. (1970). Pedagogy of the oppressed. New York: Seabury Press. Glatthorn, A. A., Boschee, F., & Whitehead, B. M. (2006). Curriculum leadership: Development and implementation. Thousand Oaks, CA: SAGE Publications. Habermas, J. (1971). Knowledge and human interests. Boston: Beacon Press. Hangzhou, China; Hershey, PA: ZUP and Information Science Reference. Hofer, B., & Pintrich, P. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88–140. King, K. P. (2005). Bringing transformative learning to life. Malabar, FL: Krieger Publishing Company. Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press. Knowles, M. S. (1990). The modern practice of adult education: From pedagogy to andragogy. New York: Cambridge. Knowles, M. S., Holton, E., & Swanson, A. (2005). The adult learner (6th ed.). Boston: Elsevier Butterworth Heinemann.

278

Mezirow, J. (1990). Fostering critical reflection in adulthood: A guide to transformative and emancipatory learning. San Francisco: Jossey-Bass. Mezirow, J. (1991). Transformative dimensions of adult learning. San Francisco: Jossey-Bass. Mezirow, J. (Ed.). (2000). Learning as transformation: Critical perspectives on a theory in progress. San Francisco: Jossey-Bass. Mott, V. W. (2008). Learner-derived curriculum development. In V. C. X. Wang (Ed.), Curriculum development for adult learners in the global community volume I: Strategic approaches (pp. 5878). Malabar, FL: Krieger Publishing Company. Newman, M. (2006). Teaching defiance. San Francisco: Jossey-Bass. Olgren, C. H. (2000). Learning strategies for learning technologies . In Burge, E. J. (Ed.), The strategic use of learning technologies: New directions for adult continuing education, no. 88 (pp. 7–16). San Francisco: Jossey-Bass. Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace. San Francisco: Jossey-Bass. Palloff, R. M., & Pratt, K. (2003). The virtual student: A profile and guide to working with online learners. San Francisco: Jossey-Bass.

Teaching with Technology

Piskurich, G. M. (Ed.). (2003). Preparing learners for e-learning. San Francisco: Jossey-Bass. Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century-Crofts. Tough, A. (1967). Learning without a teacher. Educational research series, no. 3. Toronto, Ontario, Canada: Ontario Institute for Studies in Education. Tough, A. (1971). The adult’s learning project. Toronto, Ontario, Canada: Ontario Institute for Studies in Education. Tyler, R. W. (1950). Basic principles of curriculum and instruction. Chicago: University of Chicago Press. Wang, V. C. X. (2007). Chinese knowledge transmitters or western learning facilitators adult teaching methods compared . In King, K. P., & Wang, V. C. X. (Eds.), Comparative adult education around the globe (pp. 113–1370). Hangzhou, China: Zhejiang University Press. Wang, V. C. X. (2007-2008). Chinese knowledge transmitters or western learning facilitators adult teaching methods compared. Perspectives: The New York Journal of Adult Learning, 6(2), 15–40.

Wang, V. C. X. (2008). Facilitating adult learning: A comprehensive guide for successful instruction. Boston: Pearson Education. Wang, V. C. X. (Ed.). (2010). Integrating adult learning and technologies for effective education: Strategic approaches. Hershey, PA: INFORMATION SCIENCE REFERENCE. Wang, V. C. X., & King, K. P. (2006). Understanding Mezirow’s theory of reflectivity from Confucian perspectives: A model and perspective. Radical Pedagogy, 8(1), 1–17. Wang, V. C. X., & King, K. P. (2007). Confucius and Mezirow—understanding Mezirow’s theory of reflectivity from Confucian perspectives: A model and perspective . In King, K. P., & Wang, V. C. X. (Eds.), Comparative adult education around the globe (pp. 253–275). Hangzhou, China: Zhejiang University Press. Watson, G. (1960-1961). What do we know about learning? Teachers College Record, 253–257. Watson, G. (Ed.). (1967). Concepts for social change. Washington, DC: National Training Laboratories Institute for Applied Behavioral Science, NEA.

279

280

Chapter 16

The Role of Adult Education in Online Delivery of Career and Technical Education Victor M. Hernández-Gantes University of South Florida, USA

ABSTRACT As online education continues to grow, there is a consensus that online courses and programs should be designed based on the needs of adult learners. This premise is also relevant to growing career and technical education (CTE) programs offered online. However, much of the literature in online CTE lacks implicit connections to emerging notions of adult development and learning. This article provides an overview of the status of online education in CTE offered in higher education, and discusses adult learning development as a means to inform curriculum design and instruction. The article concludes with an outline of emerging trends bridging adult learning and online education relevant to career and technical education.

INTRODUCTION For years, the rise of online education was seen as another fad that would eventually fade away like many other non-traditional instructional methods. Online education was largely spearheaded by proprietary colleges set to deliver educational programs for a small market of working adults interested in further education largely ignored by traditional institutions in higher education (Washburn, 2005). As online programs became DOI: 10.4018/978-1-60960-153-9.ch016

more prominent in the 1990s, they were often derided as diploma mills and traditional universities were cautious in embracing this delivery system (Johnson, 2006). However, with information technology serving as the catalyst for anytimeanywhere access, the growth of online education has been dramatic in the last decade. This time, mainstream higher education is paying attention and is also vying for a share of the growing enrollments in online courses and degree programs (Johnson, 2006). Presently, practically all institutions of higher education offer online education opportunities to

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Role of Adult Education in Online Delivery of Career and Technical Education

meet the demand from students seeking alternatives to traditional classroom instruction (Allen & Seaman, 2008). Career and technical education (CTE) is no exception to this trend as the field has experienced similar growth at the undergraduate and graduate education level including doctoral programs (Flowers & Baltzer, 2006b; Havice & Havice, 2005). However, as online education continues to grow, there are lingering concerns about the quality of curriculum and instruction, student experiences, and use of technology (Hernandez, Kirby, & McGee, 2004; Flowers, 2001; Kim & Bonk, 2006). Furthermore, although the adult population is the target audience for CTE in teacher preparation and graduate degree programs, there is limited literature examining the connections to adult development and learning principles. Much of the literature focuses on demand for online education, related curriculum and program development, and perceptions about quality and barriers and opportunities for adoption (Flowers, 2005; Flowers & Baltzer, 2006b; Schmidt & Gallegos, 2001). As such, there is a need for an examination of adult learning principles in the context of online education and the implications for curriculum development, teaching, and use of technology (Ausburn & Brown, 2006; Wonacott, 2002). To this end, the objectives of this article are to review the status of online education with an emphasis in career and technical education, highlight adult learning developments with potential to inform curriculum design and instruction, and outline emerging trends in online delivery relevant to teaching adult learners in higher education.

BACKGROUND Distance education encompasses a wide array of formal and informal strategies bridging physical separation between instructors and students (King, 2008). Online education represents a formal asynchronous instructional system offered by educational institutions through courses and

entire programs. Online education is characterized by the use of communication networks building upon varying combinations of online technology such as the Internet, electronic libraries, web-based conferencing, virtual discussions, and e-mail communication. Typically, the delivery of online education is organized through a web-based management system (e.g., Blackboard, WebCT) with many variations in delivery and support services depending on institutional resources and the nature of individual courses (e.g., size of student enrollment) (Aragon, 2003; Conrad, 2008; Paloff & Pratt, 2001). Formal online education opportunities for adults are offered in higher education, often referred to as post-secondary or tertiary education. Although the term “higher education” is often associated with universities and colleges, it also includes formal programs leading to credentialing at community colleges as well as baccalaureate and graduate degrees granted by private and public universities (Clark, 1983). In higher education, CTE contributes with programs and services designed to help adult students promote their career development and transition into specific occupations or further education. Informal programs are also available in community and corporate settings for technical training and re-training purposes. Teacher preparation programs and opportunities for professional advancement through master’s degrees and doctoral programs are available at universities, while technical preparation and entry-level occupational credentialing are offered at two-year colleges (Hernández-Gantes & Blank, 2009; Johnson & Benson, 2003). Thus, the focus of this article is on reviewing issues relevant to teaching adult learners in online CTE programs in higher education.

CURRENT ISSUES As online education continues to grow, it is important to review online learning trends and

281

The Role of Adult Education in Online Delivery of Career and Technical Education

issues related to adoption in CTE, bridging adult learning developments with curriculum design and instruction, and implications for using instructional technology.

Online Education Growth Beyond a Fad Initially rooted in programmed instruction through correspondence courses, distance education has experienced a booming renewal with the advent of computers and the Internet. Today, while correspondence methods still remain in use, contemporary distance education has shifted to more extensive use of instructional technology to develop and deliver courses and programs in a variety of formats from text to virtual interactive activities (Johnson & Benson, 2003). In the past two decades, the development of related instructional technologies has been dramatic and the demand for distance learning—in particular—has consistently increased during this period as well (Allen & Seaman, 2008; Havice & Havice, 2005; National Center for Education Statistics, 2000). In general, compared to student enrollment in traditional programs, online student enrollments have continued to grow substantially in recent years. The sixth report of the Sloan Consortium on the status of online learning in higher education indicated that about 20 percent of all higher education students were enrolled in at least one online course in the fall of 2006. This figure represents over a 12 percent increase compared to 1.2 percent increase in the overall higher education student population (Allen & Seaman, 2008). This dramatic growth has been well documented also noting the increase in the number of programs offered by postsecondary institutions with growth as high as 70 percent in a single year reported in the 1990s (National Center for Education Statistics, 2000). Overall, the demand for online education is expected to continue growing, though at a less

282

dramatic pace, as current efforts are expanded and new institutions respond to related demand (Allen & Seaman, 2008). Although comprehensive data is not available to gauge the full extent of enrollments in CTE, there is emerging evidence of growth mirroring that of national trends (Flowers, 2005; Johnson & Benson, 2003). Community colleges have shown an increase in enrollments due to the expansion of distance learning programs in various occupational areas (Johnson & Benson, 2003). Similar growth has been reported in the broader field of career and technical education including teacher preparation programs and in graduate education including doctoral level programs (Baltzer, Lazaros, & Flowers, 2007; Flowers, 2005; Flowers & Baltzer, 2006a, 2006b). In general, it has been reported that at the master’s degree level, face-toface enrollments have tended to decrease as new online courses have begun to attract many more students (Blank & Hernandez, 2008; Bruening & Scanlon, 2001; Flowers, 2005). In turn, at the doctoral level, online courses are available and entire programs may become available in the future. About a third of doctoral programs in the field have indicated the possibility of evolving into online models or are already in their way to do so (Baltzer, et al., 2007; Blank & Hernandez, 2008; Flowers & Baltzer, 2006b; Zirkle, 2009). The demand for online education has been fueled by individuals seeking professional advancement who are most likely to be married, have dependents, and are employed full-time. These students are also most likely to seek flexible programs on a part-time basis (National Center for Education Statistics, 2002). For such students the flexibility of online education is the only way to earn a degree as they factor in issues of time, physical location, family, and work demands. These trends are also reported in graduate programs in CTE (Blank & Hernandez, 2008; Flowers, 2005).

The Role of Adult Education in Online Delivery of Career and Technical Education

Lingering Issues As online learning continues to grow at all levels in higher education, CTE included, there are still some lingering issues about overall quality, instructor-related factors, use of technology, and nature of online learning experiences compared to traditional education (Kim & Bonk, 2006). The first issue persistently cited in the literature is the perception that online education, compared to traditional instruction, is of inferior quality. This perception ranges from traditional views on education regarding classroom instruction as the only appropriate setting for teaching and learning, to legitimate questions about the quality of online instructional approaches (Baltzer, et al., 2007; Bower, 2001). In CTE such perceptions have elicited a warning to program graduates about how potential employers may perceive a degree earned primarily online (Flowers & Baltzer, 2006b). In some cases such concerns may be reinforced by the limited evidence of online student performance compared to counterparts in equivalent traditional courses (Ryan, 2000). To be sure, there is positive evidence of impact on higher engagement and motivation, increased collaboration, and extended access to students who may have not otherwise enrolled or completed a program of study. Some reports have indicated that student performance is relatively equivalent when comparing technologymediated and classroom instruction, although the nature of related research has raised questions about the generalizability of findings (Johnson & Benson, 2003; Kim & Bonk, 2006; Phipps & Merisotis, 1999; Ryan, 2000). Albeit the inconclusiveness of available data, emerging evidence appears to suggest that the general quality of online education is really a secondary issue. What matters is the quality of specific instructional strategies and materials, much like in traditional education, pointing to design and development issues (Stilborne & Williams, 1996). In the quest to participate in online education, there has been widespread variability in the quality of

courses and programs available online. The pressure to develop courses and programs in a short period of time regardless of the unique design and development requirements may contribute to the varying quality of online courses as well (Aragon, 2003; Zirkle, 2002). To ensure quality of online courses, participating instructors need sufficient time for design and development of online courses and programs, and sometimes such accommodations are not in place (Lorenzetti, 2003). This, in turn, brings instructor-related factors into the discussion as institutions ask faculty to convert courses online even though they may not be well prepared or—worse yet—may not believe in the value of online education to participate effectively in related efforts (Flowers & Baltzer, 2006a; Li & Akins, 2004). Since every institution is bound to have instructors resisting participation in online education for related reasons, resentment and low morale are often the results of forced participation. This situation has prompted calls to rethink faculty supports and reassess how to consider participation in online instructional efforts for tenure and promotion evaluations given the unique demands of such work (Baltzer, et al., 2007; Bower, 2001; Hernandez, et al., 2004; Flowers, 2005). Another issue stemming perhaps from the push to put courses online, compounded by concerns about appropriate instructors’ preparation, is reliance on design and development strategies building upon sets of documents, lectures, and PowerPoint presentations void of interactive or meaningful connecting activities (Bower, 2001; Stilborne & Williams, 1996). At the other extreme are courses featuring the latest technological products without regard to practical and pedagogical considerations. In both cases, the limited use of technology in the former case and the over-use in the latter case, the facilitation of learning may be hindered in the absence of explicit pedagogical connections and further complicated by technology compatibility issues or distracting technical glitches (Palloff & Pratt, 2001; Partlow & Gibbs, 2003). At the core of this issue is the tendency to

283

The Role of Adult Education in Online Delivery of Career and Technical Education

focus more on the selection and management of resources and use of technology to teach online, rather than the actual design of instructional strategies appropriate for online delivery (Ausburn, 2004; Flowers, 2005). Thus, another lingering issue has been the challenge to facilitate productive interactions among students and between students and instructors. Traditional instructors have argued that such interactions, often taken for granted in the traditional classroom, are difficult to reproduce in an online environment. Critics are also quick to note that students may be left wandering in online courses under the so-called premises of self-paced learning (Kirschner, Sweller, & Clark, 2006; Schmidt & Gallegos, 2001; Rovai, 2001).

Focus on Adult Education Principles In the midst of the steady growth of online education and the lingering issues noted above, available research in CTE has been limited in relation to the general body of knowledge in other fields (Zirkle, 2009). Much of the research focus in CTE contexts has been on descriptive studies of institutional efforts to promote and develop online programs. This includes studies on barriers for placing programs online, instructor-related research looking into issues of participation in design and implementation efforts, and assessments of student satisfaction in higher education programs at both undergraduate and graduate level (Flowers, 2005; Sloan-C, 2009; Zirkle, 2002). As such, some researchers have suggested it is time to shift from an emphasis on institutional factors and online course development and management to the study of pedagogical strategies and student experiences that maximize online learning. As online education continues to grow in CTE, the quality of online pedagogical strategies appropriate to adult learners in higher education is a critical issue that needs to be addressed. While, there is evidence dispelling the perceived lack of interactions in online education as well as questions about self-regulated learning (Kirschner,

284

et al., 2006; Schmidt & Gallegos, 2001; Rovai, 2001), researchers agreed that it is imperative to study new ways of designing learning experiences that are appropriate for online delivery (Flowers 2001; Aragon, 2003; Hirumi, 2002). Another important component of the suggested shift in research focus is the apparent void in the literature bridging adult education principles and online learning. While there is research exploring the connections between adult learning principles and online pedagogical strategies stemming from adult education, related literature and focus has yet to be integrated into parallel lines of research in CTE contexts. The bulk of the literature in online CTE contexts does not make explicit connections to adult education principles, which appears to be taken for granted. For the most part, current literature reflects an emphasis on the management of learning experiences and mediation of delivery through technology (Ausburn, 2004; Flowers, 2001, 2005; Wonacott, 2002; Zirkle, 2009).

BRIDGING ADULT LEARNING AND ONLINE CTE Promising theoretical conceptions of how people learn including transformative learning, contextual teaching and learning principles and holistic views on adult development and learning have emerged over the past decade (Hoare, 2006; Merriam, 2001b, 2008). The challenge for instructors is to bridge emerging theoretical conceptions of adult teaching and learning and online instructional environments. A brief description of recent developments in adult learning is presented in this section along with implications for curriculum design and development, instructional strategies, and use of technology with potential to inform online CTE.

The Role of Adult Education in Online Delivery of Career and Technical Education

Emerging Developments in Adult Learning Theory Historically, adult development and learning have coexisted as separate, albeit complementary, fields of study. The development dimension has been typically treated under the field of psychology, while learning has been usually addressed in educational research (Hoare, 2006). This artificial divide may stem from the traditional view of adult development as progressive age stages, which in turn is associated with the development of experience (i.e., ways of knowing). Under this worldview to understanding how adults develop and learn, andragogy has been a prominent learning theory used in adult education based on the premise of stages of development and noting the unique characteristics of adults compared to children (Knowles, 1980; Merriam, 2001a). Over the past two decades, however, emerging developments in related theoretical and practical teaching and learning conceptions have noted the inclusive interface of adult development and learning (Hoare, 2006; Merriam, 2008). Building upon notions of how people learn, it is becoming clear the relationship between adult development and learning must be understood and taken into consideration when designing teaching and learning strategies. To this end, contextual learning, self-directed learning, and transformational learning have been consistently highlighted in adult education as promising conceptions of teaching and learning with potential to inform online curriculum development and instruction (Partlow & Gibbs, 2003; Roschelle, 1999; Taylor, 2007). Andragogy as an Initial Frame of Reference. Andragogy is a theory of adult education advocating a learner-centered approach to teaching introduced in the 1970s underlined by five major premises. At the core of the andragogy is the idea of adult learners as mature individuals with a clear identity of who they are and capable of self-regulated learning (Knowles, 1980; Merriam, 2001a). The premise is that adults have moved from a younger

stage of development where extrinsic motivation and guided learning were the norm. The challenge for instructors is to promote autonomous learning while recognizing individual differences and stages of development (Cercone, 2008; Cooper & Henschke, 2003; Knowles, 1980). Another important premise is the role of prior knowledge in adult learning suggesting that students learn best when they are provided the opportunity to build on what they know and can do (Fidishun, 2000). Andragogy also relies on the premise that adults are more likely to be goal-oriented and will perform better when content relevancy is high and clearly aligned with personal goals. In this case, the instructor’s goal should be to ensure relevant meaning and connections between new concepts and students’ frame of reference (Cercone, 2008; Merriam, 2001a). Further, andragogy assumes that adult learners will respond better to instruction that is designed to provide practical applications as a means to reinforce the above premises (Fidishun, 2000; Knowles, 1980). Finally, intrinsic motivation to learn is recognized as the driving force in adults who will respond better when they feel their individual needs are met and it is safe to participate in group discourse and collaborate with others (Cercone, 2008; Taylor, King, Pinsent-Johnson, & Lothian, 2003). Although useful in many ways, some researchers argued that the premises underlying andragogy represent a model for teaching adults rather than a theory (Hoare, 2006; Merriam, 2001a). A key limitation of andragogy is that it overlooks the role of the learning context and the interface with background variables such as culture, gender, and experience beyond the mere fact of being classified as an adult. Thus, it does not consider multiple ways of knowing and learning and the important role for critical reflection as part of the adult learning process (Tsao, Takahasi, Olusesu, & Jain, 2006; Taylor, 2007). With all its limitations, andragogy clearly defined what makes adult learners different and served as the root for useful concepts such as student-centered learning, prior

285

The Role of Adult Education in Online Delivery of Career and Technical Education

learning, and content relevancy as factors that matter for adult learners (Cooper & Henschke, 2003; Fidishum, 2000; Merriam, 2001a). In this context, and building upon such concepts, emerging literature in adult development and learning suggests promising implications of constructivist strategies for teaching and learning in online environments. Rethinking Adult Development and Learning. Recognizing the complexity of adult learning, everyone agrees that there is no such thing as a comprehensive adult learning theory that can be applied to all learning situations (Hoare, 2006, Merriam, 2008; Taylor, 2007). Thus, constructivist theoretical conceptions have received greater attention in recent years given their emphasis on both the learners’ characteristics and their worldviews facilitated through contextual and self-regulated instructional strategies. Experiential learning, contextual teaching and learning, self-regulated learning, and transformational learning appear to carry promising implications for online adult learning (Cercone, 2008; Merriam, 2008). For instance, experiential learning suggests that when teaching adults, learning is a product of meaningful connections between new concepts and what the learners already know (i.e., experience) (Itin, 1999). Thus, experiential learning emphasizes clear identification of new knowledge and information, connections to relevant prior knowledge, and critical analysis of learning experiences. In turn, contextual teaching and learning stems from the body of knowledge on the role of context as a meaning-making factor in the learning process. When learners engage in activities featuring realworld situations they can relate to by virtue of their prior knowledge and experience, culture, and other personal and professional variables, expertise is reinforced and further developed (Bransford, Brown, & Cocking, 2000; Itin, 1999; Kolb, 1984). Consequently, contextual teaching and learning emphasizes teaching for understanding through relevant tasks requiring active learning (Bransford,

286

et al., 2000, Perkins, 1993; Hernández-Gantes & Blank, 2009). Self-directed learning has also emerged as another important theoretical concept when teaching adult learners. At the root of this concept is the idea that learning should be intrinsically motivated and as such, adult learners should take responsibility for their own learning although some may require different levels of external assistance (Merriam, 2008; Taylor, 2006). Selfdirected learning is typically associated with goal-oriented strategies which in the past had been mostly relegated to informal learning. Today, the concept of self-regulated learning offers promising applications in online learning environments where independent learning is promoted and expected of adult learners. Self-directed learning is at the core of lifelong learning bridging ways of knowing, experience, and intrinsic motivation to learn in adult development (Taylor, 2006). In turn, transformational learning takes learning one step beyond and promotes change in ways of knowing and doing (Hoare, 2006; Tsao, et al., 2006). In essence, transformational learning allows adult learners to develop deep understandings through critical analysis as the basis for the generation of their own knowledge (Palloff & Pratt, 1999). Critical reflection underlines transformational learning, especially when learners are confronted with learning experiences requiring unique meaning-making relevant only to them based on their individual frame of reference and goals. As such, transformation learning incorporates elements of constructivist conceptions noted above while reinforcing the notion of learning as personal change (Hoare, 2006; Merriam, 2008). Based on the surmised highlights of emerging constructivist theoretical strands it is clear that, given their complementary nature and shared premises, it is not possible to identify a “grand theory” of adult learning. However, emerging theoretical concepts may contribute to our understanding of the adult learning process and can inform curriculum design and development,

The Role of Adult Education in Online Delivery of Career and Technical Education

online learning, and related use of technology (Ausburn, 2004; Cercone, 2008; Hoare, 2006, Merriam, 2008).

Implications for Curriculum Design and Development Considering theoretical conceptions of adult learning, it is clear that instructors should gauge the unique needs and goals of adult learners when designing curriculum and instruction. This is even more relevant for design and development efforts in online education (Ausburn, 2004; Cercone, 2008; Partlow & Gibbs, 2003). To this end, the use of andragogy and more recent developments in adult learning can be integrated when teaching with technology. Online education provides flexible access for adult learners and the opportunity to work on instructional materials in a self-directed mode. At issue is the adaptation and organization of instructional content and resources through interactive designs that are learner-centered, contextually relevant, and most likely to promote independent learning. In this context, three approaches are highlighted to illustrate efforts to connect learning principles and online curriculum design and development including the use of Bloom’s taxonomy, the “backward design” concept, and online blended learning designs. Revisiting the Use of Bloom’s Taxonomy. A model for online curriculum development commonly used in higher education uses Bloom’s Taxonomy as a frame of reference to guide the identification of objectives, content, and learning process. This approach focuses on stages of learning including knowledge, comprehension, application, analysis, synthesis and evaluation. The premise behind the use of Bloom’s Taxonomy is that students learn through the mastery of important content, opportunities to demonstrate what they know; allowances to apply concepts and skills through problem-based activities, and the use of reflective strategies to foster deep understandings. As such, this approach may use a blend of direct

instruction to promote mastery learning complemented with constructivist strategies to engage students in active learning and critical thinking (Anderson & Krathwohl, 2001). Some critics, however, argued that Bloom’s Taxonomy has become outdated and view its contemporary relevance and application as limited. However, recent adaptations have made the use of Bloom’s Taxonomy appealing for today’s applications to curriculum development (Anderson & Krathwohl, 2001; Clark, 2002). Such adaptations are now being used at the college level as well, as a means to promote active learning. For example, Puzziferro & Shelton (2008) reported that all online courses at Colorado State University are developed following an adaptation of Bloom’s work featuring structures for students to check content knowledge, demonstrate what they know and can do through “mastery” activities as well as through application and analytical tasks including reflection components (e.g., discussion forums). Courses also include capstone projects designed to further reinforce individual relevance and reflection. Similar examples are reported at institutions such as Penn State University’s World Campus (Thompson & McGrath, 1999) and Georgia Southern University (Center for Online Learning, 2009) to name a few. The common denominator for using Bloom’s work for curriculum development is the desire to align objectives with teaching and learning, and with assessment outcomes. Backward Design: From Outcomes to Objectives. The “backward design” for curriculum development follows an approach counter to Bloom’s suggested objectives-teaching strategiesoutcomes sequence. In the backward design, instructors identify assessment outcomes first, think about teaching/learning activities second, and then decide on core objectives. This design approach to curriculum development focuses on three stages including the articulation of student competencies, identification of evidence that demonstrates mastery of competencies, and design

287

The Role of Adult Education in Online Delivery of Career and Technical Education

of appropriate instructional activities (McTighe & Wiggins, 1999). Identifying expected student competencies sits at the core of the backward design process and aligns with theoretical principles of adult learning related to making learning relevant (Hoare, 2006; Merriam, 2008). This notion predicates that learners will be more motivated to learn when they know what is expected of them up front. However, rather than emphasizing content coverage through a typical list of expected competencies, backward design requires the identification of essential understandings (or “big ideas) underlying curriculum development. That is, it forces instructors to “chunk” important content into a few identifiable expectations serving as the guide for a course. Stemming from research in cognition and how memory works, the concept of “chunking” has been helpful in explaining how people with different levels of expertise process information (Collins, Brown, & Newman, 1989). Essentially, “chunking” represents a cognitive system comprised of a few “chunks”, each carrying a number of related informational items for easier retrieval and “big-picture” understandings when put together (Conlon, 2002; Gobet, Lane, Croker, Cheng, Jones, Oliver, & Pine, 2001). Chunking has been at the core of information mapping approaches to help instructors organize large amounts of information into a reduced number of blocks (or chunks) to facilitate learning and quick retrieval of needed information In this regard, chunking has been used in a variety of contexts related to human learning and the underlying mechanism can be applied to online curriculum design and development (Ferry, Hedberg, & Harper, 1998; Hirumi, 2002; Janicki & Liegle, 2001). The implications are clear: appropriate curricular chunks need to be developed to promote expertise and understanding in a given domain. For instructional design purposes, the chunking of essential understandings allows for the alignment between assessment outcomes (i.e., goals), content, and instructional strategies. Using

288

this idea as the point of departure, the backward design also builds upon the concept of cognitive apprenticeship for teaching and learning suggesting that novice learners can develop progressive expertise through experiential strategies such as modeling, coaching, and scaffolding (Bransford, et al., 2000; Collins, et al., 1989); and through reflective activities designed to promote understanding and knowledge production (McTighe & Wiggins, 1999; Perkins, 1993). For online curriculum development these ideas can translate into a reduced but optimal number of units or modules, each addressing essential understandings appealing to adult learners. In turn, instructional strategies may emphasize tutorials to model target skills, feedback for scaffolding purposes, and structures for individual and collective analyses. The key emphasis in the backward design is the promotion of understanding through the use of strategies appropriate for the content and the learner (McTighe & Wiggins, 1999). Blending the Best of Both Worlds? Blended education, also referred to as hybrid education, has been used in distance learning for a number of years (Dziuban, Hartman, & Moskal, 2004). The use of the Internet for online delivery has reinforced the notion of blended learning as a viable instructional alternative integrating faceto-face and online activities. In this case, there is a general agreement that blended education typically features 30 to 70 percent of online delivery in single courses, while the rest is complemented with face-to-face instruction. Courses using online instruction at the lower end (less than 30 percent) are often referred to as web-enhanced. Although instructors may opt for a blended design seeking the advantages of traditional and online instruction, such courses are still loosely defined and the optimal balance remains in question (Allen, Seaman, & Garret, 2007; Dziuban, et al., 2004). As a result, the implications for curriculum design and development are also fuzzy. To be sure, blended designs build upon the benefits of traditional instruction drawing from

The Role of Adult Education in Online Delivery of Career and Technical Education

the socialization factors of face-to-face activities. In turn, this approach may also benefit from active learning, asynchronous collaboration, and independent learning made possible by online activities (Ausburn, 2004). Thus, instructors should think of related design development as opportunities to emphasize constructivist strategies (e.g., experiential, contextual, self-regulated, active learning) as part of the entire course independent of the mode of delivery (Aragon, 2003; Partlow & Gibbs, 2003). The design of blended courses should also allow instructors to maximize the opportunities for productive interactions among students and between the students and the instructor. As the face-to-face component is retained, some instructors feel more comfortable embracing the online component and may use blended courses as the springboard for further involvement in online learning. In fact, some reports have indicated high levels of student and instructor satisfaction and student performance surpassing that of counterparts in traditional and fully online instruction (Allen, et al., 2007; Ausburn, 2004;). The advantages of blended designs may be attributed to the combined support and interactions shared through the two instructional channels. To this end, the design features of blended courses often emphasize learner-centered strategies featuring active learning and relevant content facilitated reinforce through discussion groups and other forms of electronic interactions (Aragon, 2003; Ausburn, 2004; Rovai, 2001; Wonacott, 2002). Blended instruction can be appealing for instructors and institutions given the perceived higher level of comfort for student and faculty participation. Thus, it is possible to expect the blended design to be a popular approach to online learning. A national survey of online learning reported a slightly higher percentage of blended designs compared to fully online programs across disciplines. In general, the survey also reported that students in higher education were more likely to experience a blended course than a fully online course (Allen, et al., 2007). This trend suggests that

online education may be undergoing a transformation whereby the divide between face-to-face and online instruction is becoming relatively unimportant. As blended learning continues to evolve, it is clear that, if anything, closer attention must be paid to the use of appropriate curriculum development approaches and delivery mode to ensure the needs of adult learners are met.

Implications for Online Teaching and Learning The instructors’ capacity to teach online is critical for making curriculum design and development work as expected. The starting point is to recognize the unique differences of adult learners compared to traditional college students. For example, adult learners in CTE programs seeking certification or graduate degrees—like in many other higher education programs—have to balance family and full-time work while pursuing further education (Blank & Hernandez, 2008; Flowers & Baltzer, 2006b). As such, this type of adult learners represents a goal-oriented group albeit one requiring special considerations to meet special needs processing information brought about by middle age (Cercone, 2008). In this context, as suggested by adult learning principles, online instructors should make a shift from lecture-driven and teachercentered strategies to constructivist approaches to facilitate, rather than manage learning (Ausburn & Brown, 2006; Fidishun, 2000; Reynolds, 1997). To be sure, pedagogical knowledge is considered the top requirement for effective participation in online education followed by technical expertise. Reports on online teaching and learning strategies have consistently suggested the ability to facilitate learning is emerging as one of the most important pedagogical skills for online learning (Auburn, 2004; Hirumi, 2002; Kim & Bonk, 2006). Further, the shift to constructivist instructional strategies is requiring the capacity to promote online collaboration, independent learning, problem-based learning and case-based

289

The Role of Adult Education in Online Delivery of Career and Technical Education

learning to make instruction relevant, engaging, and meaningful for goal-oriented learners (Kim & Bonk, 2006; Partlow & Gibbs, 2003). This is in direct alignment with student-centered learning rooted in andragogy, experiential learning, contextual instruction, and self-regulated learning (Hoare, 2006; Merriam, 2008). These perspectives have also been called for in career and technical education (Ausburn & Brown, 2006; Doolittle & Camp, 1999; Wonacott, 2002). Project-based learning, problem-based learning, and inquiry-based are concepts often used interchangeable as they share principles rooted in information processing theory and aligned with contextual, experiential, and self-directed learning (Bransford, et al., 2000; Kirschner, et al., 2006; Roschelle, 1999). These instructional approaches have been found helpful in online environments designed to emphasize rich learning experiences. At the core of these strategies is the idea of posing a problem requiring students to produce their own learning (Hmelo-Silver, 2004). For example, problem-based learning (PBL) is an instructional approach that has been used for several decades and stems from project-based learning advocated by Dewey in the early 1900s (Roschelle, 1999). The purpose of PBL is to allow learners to experience and apply knowledge and skills they are learning. Variations of PBL include task-based learning and project-based learning and are sometimes used interchangeable with PBL. What separates PBL from other approaches is the focus on authentic problem situations for which more than one solution can be justified (Ellis, 2003; Hmelo-Silver, Duncan & Chinn, 2007; Ertmer, Lehman, Park, Cramer, & Grove, 2003). Thus, PBL can be designed as an independent or group activity that can be easily used as part of online learning. In turn, project-based learning is typically associated with cooperative investigations as a means to keep teams of students on task requiring them to follow their own procedures and produce their own knowledge (Hmelo-Silver, 2004; Miflin, 2004). On the other hand, inquiry-based learning

290

is usually connected to individual work whereby students follow specific discipline-based methods requiring the application of reasoning skills in the completion of research activities (Hmelo-Silver, et al, 2007). Common to these strategies is the use of driving questions to guide the understanding of a problem and the design and completion of an investigation or a project. Further, a shared assumption is that these strategies can be implemented with limited assistance from the instructor based on selfdirected notions of learning. In this regard, some researchers argued that these strategies are bound to be ineffective if instructors do not account for the role of cognitive processing requiring timely feedback and scaffolding supports (Hmelo-Silver, et al, 2007; Kirschner, et al., 2006; Taylor, et al., 2003). This is particularly relevant given the fact that even though there is a consensus on the importance of constructivist strategies, the extent of use of related pedagogical practices in online education remains limited and uneven in terms of quality (Kim & Bonk, 2006).

Use of Technology Given the underlying use of technology in online education, instructors have to understand and consider the role of technology in adult learning. In this regard, instructors face the challenge of developing expertise in using instructional technology and striking the right balance when using it to facilitate online learning. Specifically, instructors have to consider the role and use of technology in curriculum development, delivery systems, and as instructional tools (Havice & Havice, 2005; Hirumi, 2002). Studies describing online curriculum development efforts have noted that instructors tend to focus initially on the technology tools for online teaching and realize in the process that the primary goal should be related to design factors (Flowers, 2001, 2005). Drawing from constructivist theory advocating the facilitation of active knowledge

The Role of Adult Education in Online Delivery of Career and Technical Education

production, it is then crucial for instructors to think about identifying sets of knowledge structures following an appropriate approach (e.g., backward design). One way to accomplish this is to use technology that allows information mapping (e.g., Inspiration). Information mapping technology does not involve a steep learning curve for instructors and can be used in the selection and development of essential understandings for particular courses (Conlon, 2002; Ferry, et al., 1998). Another consideration is the use of online lesson building technology such as SoftChalk, NTeQ, CAST Universal Design for Learning, and other commercially available programs and services. These online curriculum builders ease the learning curve for instructors as they typically rely on intuitive interfaces involving the use of wordprocessing platforms and curriculum templates. The use of this technology should ease concerns from institutions and instructors about the timeconsuming process for curriculum development and need for technology expertise as a requirement to participate effectively in online education (Hirumi, 2002; Janicki & Liegle, 2001; Thompson & McGrath, 1999). Instructors also need to understand the role and use of specific delivery systems used for online education such as Blackboard, Angel Learning, WebCT, and others. As institutions embrace online education, a course management and delivery system has to be adopted and instructors have to learn the system and work within its constraints and opportunities (Harrington, Staffo, & Wright, 2006; Kraemer, 2003). The most popular systems used in higher education today are WebCT or Blackboard (Carnevale, 2005). The use of a course management system represents an additional layer of technology that may hinder or facilitate faculty participation and, in turn, adult learning. In this regard, instructors are forced to assume additional roles when using course management systems including management, facilitation, and evaluation of learning. Not surprisingly, wide differences are observed between novice and ex-

perienced instructors in the way they interact and use course management technology (Harrington, et al., 2006; Kraemer, 2003). Clearly, as online education continues to grow, the need to evaluate the effectiveness of course management systems from the instructors’ perspective will become more important. The basic premise and appeal of online education is the flexible access to the learners any time, anywhere, at their convenience. In the case of adult learners, it is assumed they are goal-oriented and motivated to learn on their own. Thus, there is false expectation that adult learners will be able to sort out online instructional materials and resources independently (Kirnscher, et al., 2006). However, despite the popularity of online education, participation in such courses or programs may be frustrating for some students leading to higher drop out rates compared to students in traditional courses. Common reasons for dropping out include limited instructor’s assistance, time demands, and difficulty handling the underlying technology (Paloff & Pratt, 2001; Zirkle, 2002). This finding is a reminder that technology should be used as the means to facilitate learning rather than a distraction for learning. This is consistent with reports indicating that in online programs, the way in which technology is used is more important than whether the technology is “cutting edge” or not (Johnson & Benson, 2003; Phipps & Merisotis, 1999). To ensure that adult learners succeed in online programs, instructors should provide opportunities to acquire relevant technological skills, mediate technical support, and recognize differences in self-directed learning (Fidishun, 2000). Used as an instructional tool, technology should facilitate online spaces for collaborative learning, provide access to resources, allow for information processing, and include multiple representations of ideas to address different learning styles. Given the emerging range of choices made possible by the Internet, instructors can tap into videoconferencing, electronic messaging, real-time conferencing,

291

The Role of Adult Education in Online Delivery of Career and Technical Education

and other communication tools for online learning (Stilborne & Williams, 1996). Obviously, this is quite a challenge for instructors who may be limited by their own capacity and commitment to using technology and, in many ways, this is a transformational process for instructors as well (Immel, 1998; Tsao, et al., 2006). Recognizing that instructors are by default asked to bear the responsibility of curriculum design, development, online management and delivery, and selection and use of instructional technology, some institutions are promoting a team approach to ensure the quality of online curriculum and instruction. In such cases, instructors are required to partner with librarians and instructional designers for participation in online education to ensure appropriate support (Aragon, 2003; Care & Scanlan, 2001; Flowers, 2005; Hernandez, et al, 2004). These emerging efforts underscore the need for faculty training and holistic support to help them make a successful shift to online teaching and learning and meet the needs of adult learners effectively (Cercone, 2008; Kim & Bonk, 2009).

EMERGING TRENDS AND NEEDS Based on the review of enrollment trends in online education and issues related to adult teaching and learning in the context of career and technical education, the following trends and needs are emerging. First, online education should continue to grow in higher education and CTE programs need to respond to the demand for flexible teacher re-certification and professional development programs, and for advanced degrees including doctoral preparation (Johnson & Benson, 2003; Flowers & Baltzer, 2006b). At the graduate level, in particular, the growth may be in the conversion of existing programs catering to the increasing number of part-time professionals seeking to continue working full-time while pursuing advanced degrees (Blank & Hernandez, 2008; Flowers & Baltzer, 2006b). Second, as online CTE continues

292

to grow, the issue of quality should become more critical as prospective students empowered by the online premise of “anytime-anywhere” learning become more discerning when choosing a program without regard to geographical location (Flowers, 2001, 2005). The relative advantage of pioneering programs should be leveraged as others join the market, unless program quality is ensured. Third, blended learning appears to be rising in popularity compared to fully online courses and programs supported by a consistent trickle of evidence suggesting an increased preference for this format by both students and instructors (Allen, et al., 2007; Aragon, 2003; Wonacott, 2002). In this context, the issue of faculty participation in online education and related supports will become more prominent given the complex demands embodied in related work compared to traditional teaching assignments (Flowers, 2005; Kim & Bonk, 2009). In turn, the need to rethink the value of participation in online education for tenure and promotion will be more openly discussed as a strategic measure to ensure the quality of future participation (Maguire, 2005; Hernandez et al., 2004). Fourth, given the growth of online learning, understanding teaching and learning in online environments should become a top research priority in higher education, CTE included. Considering the narrow focus of current research, it will be imperative to explore the connections between adult learning developments in online CTE contexts from teaching and learning perspectives (Aragon, 2003; Hoare, 2006; Merriam, 2008; Reynolds, 1997). For example, what constructivist instructional strategies work best with adult learners in CTE and under what conditions? What approaches and technologies facilitate social networking and critical reflection? What are the long-term strategies and supports needed for successful participation in graduate programs? Are there interactions between certain groups of adult learners and particular types of online instructional strategies? These are but a hint of questions that

The Role of Adult Education in Online Delivery of Career and Technical Education

need to be addressed as online education becomes more prominent in CTE in the future. Finally, the continuous evolution of instructional technology will demand closer study of discrete technologies used to facilitate online curriculum development, course management systems, and delivery issues. The use of technology to facilitate social interactions, virtual meetings, and collaborative activities appropriate for adult learning and consistent with adult learning theory should also emerge as an important issue to be researched in online CTE in the future (Ausburn, 2004; Kim & Bonk, 2006; Partlow & Gibbs, 2003; Schmidt & Gallegos, 2001).

CONCLUSION In this article I attempted to make the case for the integration of emerging adult learning principles in the delivery of online education using the context of career and technical education programs. Riding the dramatic rise of online education, online programs are prone to focus too much on the use of technology overlooking the fact that it is only the catalyst for design, delivery, and flexible access to instruction. Instead, principles of adult learning should be at the center of online instruction appropriate to the delivery system in higher education. Yet, in many ways, online education is no different from classroom instruction in this regard. In the classroom faculty tend to lecture, while in online education lecturing is replicated through resources focusing on content delivery. In both instances we fail to realize the different developmental needs of the adult student population in higher education. For example, when the podcasting craze began, I participated in a project lured by the idea of infusing technology in a graduate career and technical program. The goal was to develop instructional content to be podcasted and accessed with iPods. As I developed material, I realized the medium would not work with mature profession-

als enrolled in the program. First of all, none of the graduate students owned an iPod at that time. Second, when telling a story using a combination of visual and text elements, parts of the podcast were fuzzy as text material did not convert well when viewed on a full computer screen, which was the medium commonly used by graduate students. I quickly realized the podcasts would not have been appropriate for graduate students in the program. Although podcasts developed for undergraduate students by other faculty were a success, differences in technology readiness and access rendered this teaching strategy fruitless with older students. As online education continues to grow, it is critical that we bridge emerging developments in adult learning in the context of online teaching and learning in CTE contexts, and any other program context for that matter. Recent developments in adult learning highlighted in this article provide an emerging framework for informing online program delivery as highlighted in the context of career and technical education. Concurrently, it is important to underscore the need to rethink online curriculum design and development as well as complementary student services using strategies based on appropriate adult development and learning considerations. It is clear that online education is an established delivery model that will continue to grow and the time to integrate adult education in the delivery of online programs has come.

REFERENCES Allen, I. E., & Seaman, J. (2008). Staying the course: Online education in the United States, 2008. Needham, MA: The Sloan Consortium. Allen, I. E., Seaman, J., & Garrett, R. (2007). Blending in: The extent and promise of blended education in the United States. Needham, MA: The Sloan Consortium.

293

The Role of Adult Education in Online Delivery of Career and Technical Education

Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy of learning, teaching, and assessment: A revision of Bloom’s taxonomy of educational objectives. New York: Longman. Aragon, S. (Ed.). (2003). Facilitating learning in online environments: New directions for adult and continuing education (Vol. 100). San Francisco: Jossey-Bass. Ausburn, L. J. (2004). Course design elements most valued by adult learners in blended online education environments: An American perspective. Educational Media International, 41(4), 327–337. doi:10.1080/0952398042000314820 Ausburn, L. J., & Brown, D. (2006). Learning strategy patterns and instructional preferences of career and technical education students. Journal of Industrial Teacher Education, 43(4), 6–39. Baltzer, H., Lazaros, E., & Flowers, J. C. (2007). Review of doctoral programs in technical education. Journal of Industrial Teacher Education, 44(2), 37–59. Blank, W., & Hernandez, V. (2008). Preparing CTE leaders online. Techniques, January Issue. Association of Career and Technical Education. ACTE. Bower, B. (2001). Distance education: Facing the faculty challenge. Journal of Distance Learning Administration, IV(II). Retrieved from http:// www.westga.edu/~distance/ ojdla/summer42/ bower42.html. Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Academy Press. Bruening, T. H., & Scanlon, D. C. (2001). The status of career and technical education teacher preparation programs. Columbus, OH: Dissemination Center for Career and Technical Education.

294

Care, W. D., & Scanlan, C. M. (2001). Planning and managing the development of courses for distance delivery: Results from a qualitative study. The Online Journal of Distance Learning Administration, 4(2). Retrived from http://www.westga. edu/~dista nce/ojdla/summer42/care42.html Carnevale, D. (2005). Government’s request for data may delay Blackboard’s purchase WebCT. The Chronicle of Higher Education, 52(16), A29. Retrieved from http://chronicle.com/weekly/ v52/ i16/16a02901.htm. Center for Online Learning. (2009). Online course design: Bloom’s taxonomy. Statesboro, GA: Georgia Southern University. Retrieved from http:// academics.georgiasouthern.edu /col/id/bloom.php Cercone, K. (2008). Characteristics of adult learners with implications for online learning design. Advancement of Computing in Education Journal, 16(2), 137–159. Clark, B. (1983). The higher education system. Berkeley: University of California Press. Clark, B. (2002). Growing up gifted: Developing the potential of children at home and at school. Upper Saddle River, NJ: Merrill Prentice Hall. Collins, A., Brown, J., & Newman, S. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics . In Resnick, L. (Ed.), Knowing, Learning and Instructing: Essays in honor of Robert Glaser. Lawrence Erlbaum. Conlon, T. (2002). Information mapping as support for learning and teaching. Computer Education, Issue 106. Conrad, D. (2008). Online learning . In English, L. M. (Ed.), International encyclopedia of adult education (pp. 442–447). New York: Palgrave Macmillan.

The Role of Adult Education in Online Delivery of Career and Technical Education

Cooper, M. K., & Henschke, J. A. (2003, November). An update on andragogy: The international foundation for its research, theory and practice. Paper presented at the Commission of Professors of Adult Education (CPAE), Conference, Detroit, MI. Doolittle, P. E., & Camp, W. G. (1999). Constructivism: The career and technical education perspective. Journal of Vocational and Technical Education, 16(1). Retrieved from http://scholar. lib.vt.edu/ejournals/ JVTE/v16n1/doolittle.html. Dziuban, C. D., Hartman, J. L., & Moskal, P. D. (2004). Blended learning. EDUCAUSE Center for Applied Research, Research Bulletin, Issue 7. Ellis, R. (2003). Task-based language learning and teaching. Oxford: Oxford University Press. Ertmer, P. A., Lehman, J., Park, S. H., Cramer, J., & Grove, K. (2003). Barriers to teachers’ adoption and use of technology in problem-based learning. Proceedings of the Association for the Advancement of Computing in Education (AACE) Society for information Technology and Teacher Education (SITE) International Conference (1761–1766). Ferry, B., Hedberg, J., & Harper, B. (1998). How do preservice teachers use concept maps to organise their curriculum knowledge? Journal of Interactive Learning Research, 9(1), 83–104. Fidishun, D. (2000). Andragogy and technology: Integrating adult learning theory as we teach with technology. Retrieved from http://frank.mtsu. edu/~itconf/ proceed00/fidishun.htm. Flowers, J. (2001). Online learning in technology education. Journal of Technology Education, 13(1), 17–30. Flowers, J. (2005). The effect of online delivery on graduate enrollment. Journal of Industrial Teacher Education, 42(4), 7–24.

Flowers, J., & Baltzer, H. (2006a). Hiring technical education faculty: Vacancies, criteria, and attitudes toward online doctoral programs. Journal of Industrial Teacher Education, 43(3), 29–44. Flowers, J., & Baltzer, H. (2006b). Perceived demand for online and hybrid doctoral programs in technical education. Journal of Industrial Teacher Education, 43(4), 39–56. Gobet, F., Lane, P. C. R., Croker, S., Cheng, P. C.-H., Jones, G., Oliver, I., & Pine, J. M. (2001). Chunking mechanisms in human learning. Trends in Cognitive Sciences, 5, 236–243. doi:10.1016/ S1364-6613(00)01662-4 Harrington, T., Staffo, M., & Wright, V. H. (2006). Faculty uses of and attitudes toward a Course management system in improving instruction. Journal of Interactive Online Learning, 5(2), 178–190. Havice, W. L., & Havice, P. A. (Eds.). (2005). Distance and distributed learning environments: Perspectives and strategies: 54th yearbook of the Council on Technology Teacher Education. New York. Glencoe: McGraw-Hill. Hernandez, V., Kirby, J., & McGee, S. (2004). Competency assessment in distributed education. Washington, DC: Association of Jesuit Colleges and Universities. Hernández-Gantes, V. M., & Blank, W. (2009). Teaching English language learners in career and technical education programs. New York: Routledge. Hirumi, A. (2002). A framework for analyzing, designing, and sequencing planned e-learning interactions. The Quarterly Review of Distance Education, 3(2), 141–160. Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. doi:10.1023/ B:EDPR.0000034022.16470.f3

295

The Role of Adult Education in Online Delivery of Career and Technical Education

Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: A response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107. Hoare, C. (Ed.). (2006). Handbook of adult development and learning. New York: Oxford. Imel, S. (1998). Technology and adult learning: Current perspectives (ED No. 197). Columbus, OH: ERIC Clearinghouse on Adult, Career and Vocational Education. Itin, C. M. (1999). Reasserting the philosophy of experiential education as a vehicle for change in the 21st Century. Journal of Experiential Education, 22(2), 91–98. Janicki, T., & Liegle, J. O. (2001). Development and evaluation of a framework for creating Web-based learning modules: A pedagogical and systems approach. Journal of Asynchronous Learning Networks, 5(1). Johnson, C. (2006). Degrees of deception: Are consumers and employers being duped by online universities and diploma mills? The Journal of College and University Law, 32(2), 101–180.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. doi:10.1207/s15326985ep4102_1 Knowles, M. S. (1980). The modern practice of adult education: From andragogy to pedagogy. Englewood Cliffs, NJ: Cambridge Adult Education. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Upper Saddle River, NJ: Prentice-Hall. Kraemer, E. W. (2003). Developing the online learning environment: The pros and cons of using WebCT. Information Technologies and Libraries, 22(2), 87–92. Li, Q., & Akins, M. (2004). Sixteen myths about online teaching and learning in higher education: Don’t believe everything you hear. TechTrends, 49(4), 51–60. doi:10.1007/BF02824111 Lorenzetti, J. P. (2003). Thirty-two distance education trends. Distance Education Report, 7(21), 1–6.

Johnson, S. D., & Benson, A. D. (2003). Distance learning in postsecondary career and technical education. St. Paul, MN: National Research Center for Career and Technical Education.

Maguire, L. L. (2005). Faculty participation in online distance education: Barriers and motivators. Online Journal of Distance Learning Administration, 8(1). Retrieved from http://www.westga. edu/~distance/ ojdla/spring81/maguire81.htm.

Kim, K., & Bonk, C. J. (2006). The future of online teaching in higher education: The survey says… EDUCAUSE Quarterly, Issue Number 4.

McTighe, J., & Wiggins, G. (1999). The understanding by design. Alexandria, VA: Association for Supervision and Curriculum Development.

King, K. P. (2008). Distance education. In L. M. English (Ed.), International encyclopedia of adult education (192-199). New York: Palgrave Macmillan.

Merriam, S. B. (2001a). Andragogy and selfdirected learning: Pillars of adult learning theory. New Directions for Adult and Continuing Education, 89, 3–13. doi:10.1002/ace.3 Merriam, S. B. (Ed.). (2001b). The new update on adult learning theory. New directions for adult and continuing education. San Fransisco. Jossey-Bass.

296

The Role of Adult Education in Online Delivery of Career and Technical Education

Merriam, S. B. (Ed.). (2008). Third update on adult learning theory: New directions for adult and continuing education (Vol. 119). San Francisco: Jossey-Bass. Miflin, B. (2004). Adult learning, self-directed learning and problem-based learning: Deconstructing the connections. The entity from which ERIC acquires the content, including journal, organization, and conference names, or by means of online submission from the author. Teaching in Higher Education, 9(1), 43–53. doi:10.1080/1356251032000155821 National Center for Education Statistics. (2000). Distance education at postsecondary education institutions: 1997-1998 (NCES Publication No. 2003-013). Washington, DC: U.S. Government Printing Office. National Center for Education Statistics. (2002). A profile of participation in distance education: 1999-2000 (NCES Publication No. 2003-154). Washington, DC: U.S. Government Printing Office. Paloff, R. M., & Pratt, K. (2001). Lessons from the cyberspace classroom:The realities of online teaching. San Francisco: Jossey-Bass. Partlow, K. M., & Gibbs, W. J. (2003). Indicators of constructivist principles in Internet-based courses. Journal of Computing in Higher Education, 14(2), 68–97. doi:10.1007/BF02940939 Perkins, D. (1993). Teaching for understanding. American Educator, 17(3), 28–35. Phipps, R., & Merisotis, J. (1999). What’s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington, DC: The Institute for Higher Education Policy.

Puzziferro, M., & Shelton, K. (2008). A model for developing high-quality online courses: Integrating a systems approach with learning theory. Journal of Asynchronous Learning Environment Learning Networks, 12(3). Retrieved from http:// sloanconsortium.org/node/1409. Reynolds, K. C. (1997, March). The name assigned to the document by the author. This field may also contain sub-titles, series names, and report numbers.Postsecondary education in cohort groups: Does familiarity breed learning? Additional information about the document that does not fit in any of the other fields; not used after 2004.Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL. Roschelle, J. (1999). Transitioning to professional practice: A Deweyan view of five analyses of problem-based learning. Discourse Processes: A Multidisicplinary Journal, 27(2), 231–240. Rovai, A. P. (2001). Building classroom community at a distance: A case study. Educational Technology Research and Development Journal, 49(4), 33–48. doi:10.1007/BF02504946 Ryan, R. C. (2000). Student assessment comparison of lecture and online construction equipment and methods classes. T.H.E. Journal, 27(6), 76–83. Schmidt, E. K., & Gallegos, A. (2001). Distance learning: Issues and concerns of distance learners. Journal of Information Technology, 17(3). Retrieved from http://nait.org/jit/Articles/ schmidt041801.pdf. Sloan-C. (2009). NASULGC-Sloan National Commission on Online Learning Benchmarking Study: Preliminary findings. Retrieved from http://www.sloan-c.org/publications /survey/ nasulgc_prelim

297

The Role of Adult Education in Online Delivery of Career and Technical Education

Stilborne. L., & Williams, L. (1996). Meeting the needs of adult learners in developing courses for the internet. Retrieved on January 15, 2009 from https://www.isoc.org/inet96/ proceedings/ c4/ca_2.htm

Tsao, J., Takahashi, K., Olusesu, J., & Jain, S. (2006). Transformative Learning. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Retrieved from http://projects.coe.uga.edu/epltt/

Taylor, E. W. (2007). An update of transformative a critical review of the empirical research (1999–2005). International Journal of Lifelong Education, 26(2), 173–191. doi:10.1080/02601370701219475

Washburn, J. (2005). University, Inc.: The Corporate Corruption of Higher Education. New York: Basic Books.

Taylor, K. (2006). Autonomy and Self-directed Learning: A Developmental Journey . In Hoare, C. (Ed.), Handbook of Adult Development and Learning. New York. Oxford.

Wonacott, M. E. (2002). Blending fce-to-face and distance learning methods in adult and careertechnical education. Clearinghouse on Adult, Career and Vocational Education, Application Brief No. 23. Educational Resources Information Center.

Taylor, M., King, J., Pinsent-Johnson, C., & Lothian, T. (2003). Collaborative practices in adult literacy programs. Adult Basic Education, 13(2), 81–99.

Zirkle, C. (2002). Identification of distance education barriers for trade and industrial teacher education. Journal of Industrial Education, 40(1), 20–44.

Thompson, M. M., & McGrath, J. W. (1999). Using LNs to Support a complete educational experience. Journal of Asynchronous Learning Environment Learning Networks, 3(2). Retrieved from http://www.sloan-c.org/publications /jaln/ v3n2/v3n2_thompson.asp.

Zirkle, C. (2009). Distance education: The state of the art in career and technical education . In Mclean, R., & Wilson, D. (Eds.), International Handbook of Education for the Changing World of Work (pp. 2003–2018). The Netherlands: Springer. doi:10.1007/978-1-4020-5281-1_136

298

299

Chapter 17

The Role of Learning Styles and Technology Royce Ann Collins Kansas State University, USA

ABSTRACT Learning style research has informed effective classroom teaching strategies for decades. Technology has allowed faculty and students to move the learning environment from the four-walled classroom to a fluid global virtual space. Knowledge gained through the application of learning style research to online instruction has enhanced practice; however, research demonstrating the alignment of learning styles with current technological resources has been limited. Learning styles and their interrelationship with technology and adult learners is as important today as initial learning style research was in the six decades after its beginnings in the 1940s. Education today must meet the needs of students who are more comfortable in electronic environments, as well as those who need the four-walled classroom. The ability to use learning style research to accomplish both will lead to enhanced student learning and a more productive experience.

INTRODUCTION New technology has changed the way adults receive and solicit information. No longer do adults have to go to a book, journal or newspaper to gain information on a topic; they just “Google it.” To think a few years ago, that phrase was nonexistent. The irony of the situation is that this article is for a book (static) about technology (fluid). DOI: 10.4018/978-1-60960-153-9.ch017

Wireless connections and mobile technologies have changed the flow of information. The new learning spaces on the Internet and online course delivery systems have created a fluid nature to learning. Have these devices and new ways of processing changed our learning styles? What is the impact of technology on the way adults absorb and process information? Online and face-to-face courses can incorporate a variety of technological approaches to education. Some face-to-face courses have

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Role of Learning Styles and Technology

become Web-enhanced, meaning course items are placed in an online environment. These items could include the syllabus, PowerPoint slides, links to Web sites, or group presentations. The hybrid or blended learning format was developed by combining the face-to-face with 30% to 79% of the course time in the online environment (Allen & Seaman, 2007). Entirely online learning is making a significant impact on U.S. colleges and universities with just the number of courses offered in this format. The number of students enrolling in online courses has steadily increased over the past few years according to the Sloan Consortium series on online learning (Allen & Seaman, 2007). In the fall 2007 semester, more than 20% of students were enrolled in an online course (Allen & Seaman, 2008). Technology is here to stay. To offer more convenient, flexible course options to adult students, instructors engage in converting their courses to an electronic environment, examining how they teach, researching the technological capabilities available, implementing the best possible tools for the learning objectives and re-thinking how they approach the educational setting. What is the effectiveness of using CDROM, videotapes, Internet, discussion forums, Web 2.0 technologies in higher educational courses? “The challenge for educators is to utilize this technology in ways that facilitate the highest level of learning outcomes” (Cox, 2008, p. 1). While some institutions may give assistance to the faculty to enhance courses with the aid of an instructional designer, other institutions may not provide such assistance, and it is up to the individual instructor to create the learning situation with more technological opportunities. How does an instructor create an online learning experience that uses technology appropriately and enhances the learning possibilities for students? One way in which education has historically been enhanced is through application of learning style research. This research and the development of assessment inventories have been influencing

300

the entire education system since the 1940s. An online search for “learning styles” using Google Scholar received 1,480,000 hits. Numerous studies concerning learning styles have been conducted on K-12 students as well as undergraduate and graduate students (Butler & Pinto-Zipp, 2006). Kolb (1984) found that students’ learning styles made a significant impact on their learning preferences and choices; however, “individual styles of learning are complex and not easily reducible into simple typologies” (Kolb, 1984, p. 66). This is important to note while reading this article, which includes several different learning style inventories and research. Although researchers may distill their ideas down to a simple model to grasp the complex reality of learning, this phenomenon is multi-faceted. Each learning style author has his or her own lens for examining learning styles and it is too complex to expect that one instrument can assess all aspects. As early as 1991, Verduin and Clark stated that “those designing distance education should, moreover, pay attention to differences among adults—in individual learning styles, preferences for acquiring new knowledge and skills, and levels of maturity or ways of responding to new learning situations” (p. 32). While learning styles complicate the course design process, they must be taken into consideration if an instructor truly desires to create an environment that will enhance the learning for each student (DuCharme-Hansen & Dupin-Bryant, 2004). In this article, we discuss learning styles first to give the reader a brief background of several instruments. The research on learning styles and online courses is aligned with the learning style instruments discussed previously. Finally, the interrelationship of learning styles and technology is discussed, including instructional strategies that coincide with the learning styles described by the Gregorc Style Delineator and the VARK instruments.

The Role of Learning Styles and Technology

LEARNING STYLES What is a learning style? Unfortunately, there is a plethora of definitions to accompany each researcher’s lens from learning preferences to multiple intelligences. Grasha (1996) defined learning style as the participant’s preferred way of learning. Cranton (2005) defines learning styles as “preferences for certain conditions or ways of learning, where learning means the development of meanings, values, skills, and strategies” (p.362). Although researchers cannot agree on one definition of learning styles, most believe that learning style is the way students process, internalize, and remember information (Dunn & Griggs, 2000). Every person has a learning style; however, experience and environment can influence styles. Most people have a learning style preference, but even within a single preference, there is great diversity among learners, “The researcher or practitioner entering the areas of learning style may well do so with some sense of trepidation given the volume, diversity, and apparent dissociation of writing, theory, and empiricism in the field” (Cassidy, 2004, p. 440). Authors often use learning style and cognitive style interchangeably, while some define the terms distinctly. The term “cognitive style” came from cognitive psychologists and usually limits its discussion to the processing of information (Cranton, 2005). Some researchers made a distinction between learning styles and learning modalities. They defined learning modalities as sensory (i.e., visual, auditory, kinesthetic) ways to take in information. To keep the confusion to a minimum, this article will just use the term learning style and limit the scope to those authors using this term. On the first day of a course, the instructor encounters extraverts, introverts, visual learners, auditory learners, concrete learners and abstract learners, just to name a few. The diversity alone can be overwhelming. When working with an array of adults, knowledge of learning styles can foster effective teaching techniques.

For years, educational specialists have identified that students in a face-to-face classroom learn more if the learning activities are directed at their different learning styles (Dunn, Honigsfeld, & Doolan, 2009; Merriam, Caffarella, & Baumgartner, 2007). Building on adult education literature, Cranton (2005) lists six approaches to addressing learning styles: “1) experiential, 2) social interaction, 3) personality, 4) multiple intelligences and emotional intelligence, 5) perceptions, and 6) conditions or needs” (p. 362). Because of the diverse learning style typologies, we use Cranton’s framework to organize and focus this discussion of learning styles. The instruments described here will be used in the following discussion of research on learning styles and online courses. The first category, experiential approaches, encompasses learning styles that incorporate making meaning from the learner’s experiences. David Kolb (1984) developed the most popular and most researched experiential learning style inventory. His model has been adapted to classroom instruction where students are taken through the four stages of a learning cycle (concrete experience, reflective observation, abstract conceptualization, and active experimentation) in order to touch on the strengths of each student. Kolb’s Learning Style Inventory (LSI) rates learners on a bipolar scale, which indicates the learner’s preference for active experimentation (doing) versus reflective observation (reflecting) and concrete experience (experiencing) versus abstract conceptualization (thinking). Learners fall into one of four quadrants: Diverger, Converger, Assimilator or Accommodator. Each of these learning styles appreciates a different learning experience. Convergers need action that is driven by their understanding of the abstract concepts. They use logic and a scientific approach with the preference to actively experiment with the information and need to apply the material immediately to a practical situation. They are unemotional in their approach to learning and prefer to work alone. Converger and Assimilator types share a preference for abstract conceptual-

301

The Role of Learning Styles and Technology

ization. Assimilators combine their strength for abstract concepts with reflective reasoning. They can distill information down to a more logical form and are more interested in abstract thoughts than people. Assimilators like to spend time refining theories. Diverger and Accommodators learn through the concrete experience (hands-on activity) instead of abstract conceptualization. Accommodators combine concrete experiences with a preference for active experimentation, which means they dive in and learn by trial and error. Divergers prefer a concrete experience with time for reflections and observation. They look at the information from many different angles and can become overwhelmed with the volume of information. Divergers are creative learners who consider multiple potential strategies for learning and problem-solving. The LSI was the predominant instrument utilized in studies reviewed later in this article. In the experiential category, another popular learning style indicator with adult students is Gregorc Style Delineator (Gregorc, 1982). This instrument measures a person’s perceptual and ordering abilities. Perception is the means by which a learner grasps information on a continuum of abstractness and concreteness. The abstractness qualities enable the learner to grasp information using intuition and feelings. The concreteness qualities enable the learner to grasp the information via the five senses. Ordering abilities are ways that learners organize, arrange, and reference information on continuum from sequential to random. The learner with a sequential preference will organize information in a step-by-step fashion, logically, and methodically. Those with a random preference will organize information nonlinearly, in leaps or large chunks at a time. These qualities are grouped together in four distinct patterns: concrete sequential, abstract sequential, abstract random and concrete random. A critical difference between Kolb’s LSI and the Gregorc Style Delineator is the ordering dimension, which notes whether a student likes a sequential approach to the learning

302

or a random approach to topics (Miller, 2005). This is an important consideration in selecting a learning style instrument for research. Cranton’s (2005) second category, the social interaction approach, focuses on the engagement of students with others during the learning process. With the emphasis in most adult education classrooms on collaboration and discussion, this approach might not be as neutral as some of the other assessments. Grasha-Riechmann Student Learning Style Scale (Grasha, 1996) measures the social interaction preferences of a learner. Although developed for college age students, this instrument has adult norms available and has been rated with strong reliability (James & Blank, 1993). The Grasha-Riechmann Student Learning Style Scale addresses six dimensions: 1) competitive, where students try to outperform others, 2) collaborative, where students like to share ideas and discuss, 3) avoidant, where students do not like to participate in class activities or attend class, 4) participative, where students take responsibility and like to be active in the learning environment, 5) dependent, where students rely on the instructor for information and requirements, and 6) independent, where students are self-directed and learn on their own. All learners possess all six of these categories to a certain extent; however, most learners will show a stronger preference toward one or two categories. The third learning style category described by Cranton (2005) was the personality models, which give a much broader description of the person than just a learning style inventory. One of the popular instruments, Myers-Briggs Type Indicator (MBTI), builds on Carl Jung’s theories (Myers, 1993). Personality is a much broader concept and gives a more comprehensive picture of the student. Learning characteristics are derived from the psychological type preference. It places a significant role in what grabs a learner’s attention. The theory is that if the instructor can teach in a manner that is in harmony with the student, then that student will attend to the lesson and the pos-

The Role of Learning Styles and Technology

sibility of learning increases. The Myers Briggs is based on the fact that there is a logical reason for the differences among people. “Psychological type theory is based on two attitudes towards the world and four functions of living” (Cranton, 2005, p. 364). MBTI delineates these differences down to how a person perceives (the process of becoming aware) and judges (the conclusions made about these perceptions) each encounter. The introvert gains energy within, focusing on self, while the extravert gains energy from and focuses on the external world. Persons approaching the topic logically and analytically demonstrate the thinking function. The feeling function is demonstrated when people take others and values into consideration. The sensing function is demonstrated when people take in information from the world through their five senses. When persons perceive the world through intuition, possibilities, and imagination, they are using the intuitive function determined by the MBTI. These elements are combined to create 16 different personality types. Examples of the learning characteristics derived from personality type are persons using introverted thinking are reflective and critical as they approach the topic, while extraverted thinkers learn through organized planned experiences (Myers, 1993). The fourth category encompasses multiple intelligences and emotional intelligence. While Cranton (2005) states that these are not learning styles, it is her perspective that they inform adult educators understanding of learning styles. Howard Gardner (1999) brought the idea of multiple intelligences to the education community. He argued for the existence of relatively autonomous human intellectual competencies: linguistic, logicalmathematical, musical, spatial, bodily-kinesthetic, interpersonal, intrapersonal, naturalist, spiritual, and existential. Linguistic and logical mathematical have traditionally been the most recognized intelligences in the educational systems. Those people with linguistic intelligence are sensitive to the written or spoken word. People whose strength is the logical mathematical intelligence analyze

information logically and scientifically. According to Gardner, people with musical intelligence excel at musical performance and composition. Those who possess spatial intelligence exhibit the potential to see and manipulate patterns, have depth perception, and work in three-dimensional space, such as artists or surgeons. The intelligence demonstrated by dancers and athletes is bodilykinesthetic, which involves the potential to use the entire body to create.. Individuals who work effectively with others and understand their desires and motivations are expressing the interpersonal intelligence. Intrapersonal intelligence involves understanding oneself and regulating ones performance and emotions. Persons who display the naturalist intelligence understand living things (plants and animal). The gift for mysticism, religion, or spiritual feeling is associated with spiritual intelligence. Persons who have an aptitude for transcendence and understanding the meaning of life and death reveal existential intelligence. Daniel Goleman (1998) popularized the theory of emotional intelligence, which includes understanding, knowing and managing one’s emotions and handling relationships with others. Emotional intelligence closely aligns with intrapersonal and interpersonal intelligences. Perception models, the fifth category listed by Cranton, primarily deal with the observable traits or instructional preferences of visual, auditory, tactile or kinesthetic. Physiological styles are sensory-based. Some researchers refer to these as learning modalities. A simple example is when people ask for directions to a new location. Would they rather have the person draw a map (visual) or just listen to the directions (auditory)? Perhaps, they prefer to have the person tell them the directions while they draw the map (tactile). Do they listen to the person and physically move their body to make the turns as indicated (kinesthetic)? A popular physiological style inventory is the VARK. VARK is an acronym for visual, auditory, read/write, and kinesthetic (Fleming, n.d.). Visual learners prefer information presented using mind

303

The Role of Learning Styles and Technology

maps, concept maps, models, patterns, or graphs. Auditory learners prefer to hear the information, so lectures, podcasts, chat rooms, mobile phones, and discussing the material are all ways to tap into their strengths. The read/write learners prefer information displayed in print, thus, textbooks, PowerPoint, and Web sites work well. Kinesthetic learners prefer information demonstrated and like to interact with the topic, write notes, highlight, and touch it. An instructor could use simulations, videos, and documentary films with these learners. Most learners possess all these modalities and mix them as the context deems appropriate. Cranton’s sixth category described was conditions and needs. These include the environmental condition and physical needs for students to learn. Environmental conditions include such elements as amount of light, background sound, temperature of the room, and location of learning space. Physical needs takes into consideration the time of day, extent of mobility and quantity and type of foodstuff. The most popular model in this category is Dunn and Dunn Learning Style Model. This sociological approach takes into consideration the environment (sound, light, temperature, learning space), emotions (motivation, persistence, responsibility, structure), sociological (working alone, in pairs, with peers, with a team, with an instructor, or varied), physiological (perceptual, intake, time, mobility), and psychological (global, analytic, impulsive, reflective) processing (Dunn & Griggs, 2000). The learner can use these simultaneously or successively. As demonstrated above, “the construct of learning style is a complicated issue and cannot be defined in simple terms” (James & Maher, 2004, p. 123). Many of the learning styles discussed are based on Western culture, which tends to emphasize individuality and competition. A more holistic, collaborative environment may be learning style strength for persons from other cultures. While knowledge of learning styles can facilitate guiding the activities for learning experiences, instructors cannot focus on just one. An understanding of the

304

diverse learning style research is a good foundation for designing learning experiences in any format (face-to-face, hybrid, or online). The diversity of learning style research also significantly impacts the information gleaned from researching online course experiences.

LEARNING STYLES AND ONLINE COURSE STUDIES As online learning gained momentum, research studies followed suit. There have been numerous studies conducted concerning online learning and learning styles on K-12 learners and undergraduate students. Fewer studies have focused on graduate students and adult students. Even fewer studies have looked at the impact of learning styles, online learning and adult students. These particular research studies were chosen because their population included what has been classified as adult students (25 years or older) and they addressed one of the instruments described in the experiential, social interaction and perception categories. The personality and multiple intelligences categories were excluded because as described earlier they do not include learning style inventories, but learning characteristics were derived from their models. The condition and need category was excluded because no research was found investigating online learning or online instructional strategies. Diaz and Cartnal (1999) questioned if a difference existed between the learning styles of students who choose a face-to-face format and those who choose to take the course in the online format. Their research compared student learning styles in a face-to-face and an online health education course at a community college. There were students over the age of 26 in both formats. Thirty-six percent of the online students were over the age of 26 compared to only 6% of the students in the face-to-face format. Diaz and Cartnal (1999) observed the lack of social interaction in the online format during their investigation

The Role of Learning Styles and Technology

and chose to use the Grasha-Reichmann Student Learning Style Scales (GRSLSS). The researchers based their decision on the fact the GRSLSS was created for use with college students and it focuses on interactions between students, instructor and learning in general. As described earlier, the GRSLSS measures learning styles across six categories: independent learners, dependent learners, competitive learners, collaborative learners, avoidant learners, and participant learners. Using correlation analysis, their findings indicated that the online learners showed a negative relationship between the independent learning style and the collaborative and dependent styles. This means they preferred independent study, working alone on assignments, and a self-paced approach to instruction. Students in the face-to-face environment had a significant positive correlation between collaborative and competitive and participant learning styles. This group demonstrated a preference for working collaboratively with students and instructor, a drive to perform better than their classmates, and a need for direction from the instructor. While some may see collaboration and competition as direct opposites, these students were working on group projects (collaborative), but wanted their group project to be better than other groups in the course (competitive). There was also a positive correlation between competitive and participant, which means they were willing to do what the instructor wanted them to do. The conclusion that Diaz and Cartnal (1999) generated from their research was that online learning must emphasize the independent nature of the learning and limit group work. By giving students choices over their learning projects, instructors can tap into the independent nature of these learners. From this research, instructors can glean the learning style type (independent and self-regulating) that may self select the online course environment. Terrell and Dringus (1999) studied the effect of learning styles on student performance in an online master’s level course. Using Kolb’s Learning Style Inventory (LSI), they found out of 98

graduate students, 75% fell into the Converger and Assimilator categories. Kolb’s (1984) studies demonstrated there were “reasonable indications of the learning style orientations that characterize the different professions” (p. 88). The Converger and Assimilator indicated an association with technical, information processing, and scientific careers. The learning style that had the lowest completion rate was the Accommodator category. Accommodators value hands-on concrete experiences and people. Terrell and Dringus (1999) hypothesized that the Accommodators need for working with people, relying on people to gather information, needing to affect change or do something, and drawing on intuition that caused them to be unsuccessful in the online course environment. Because they like to immerse themselves in the learning situation and collaborate with others, Accommodators may find the distance between instructor and other learners a determent to their ability to maximize their learning. This research leads to the question as to whether the online course environment is suited for all types of learners. Once again, the implication is that certain learning styles will self-select online courses because they are better suited to succeed with the technology and remoteness of the instructor. In another study that used Kolb’s Learning Style Inventory, Simpson and Du (2004) looked at the relationship between learning style and enjoyment level in an online course for graduate students. Their findings revealed that Convergers liked the online experience the most, while Assimilators liked the online experience the least. Simpson and Du (2004) classified participation as “hits,” “reads,” and “posts.” A “hit” was when a student accessed an online course page or course tool. A “read” was when a student accessed a posting in the mail or discussion area of the course. A “post” was when a student composed a message either in the mail or discussion area. Divergers made the most “hits” and “reads,” and Assimilators made the least “posts” even though students knew that participation counted toward their final

305

The Role of Learning Styles and Technology

grade. As courses are designed, instructors need to look at ways to incorporate electronic activities that appeal to the observing and doing strength of one student and the reflecting and theorizing strength of another student. Simpson and Du (2004) concluded it was “good practice for online instructors to incorporate students’ learning styles into the pedagogical design of their courses to maximize their students’ success” (p. 133). It also demonstrates research that documents which learning style has a more positive attitude toward online learning. Butler and Pinto-Zipp (2006) was the one study found that broke down the online experience into instructional strategies used in the online environment with a population of adult students. They used the Gregorc Learning Styles Delineator to assess the learning styles of 96 graduate students with an age range of 23 to 83. Approximately 72% of the population was female, and 83% stated that they had taken at least three online courses. Fifty-six percent of the respondents exhibited a dual learning style rather than a single style, with the 25% reporting a combination of concrete random and abstract random and 18% a combination of concrete sequential and abstract sequential. The percentage of single learning styles reported was concrete sequential (14%), concrete random (14%), abstract random (9%), and abstract sequential (5%). They also had students rank a variety of instructional methods on a scale of most helpful to least helpful in learning the material. Several positive correlations were found between learning styles and online instructional method. The concrete sequential style and e-mail had a positive correlation (r = .562, p < .05). A strong positive correlation (r = 994, p < .01) was reported between abstract sequential type and computer simulations. The abstract random learning style was positively correlated with mandated number of assignments (r = .787, p < .05) and e-mail ((r = .787, p < .05). Although these may not seem to correlate according to the learning style descriptors for an abstract random learner, these strategies

306

assisted the learners in staying on track with the course. Negative correlations were found between concrete random and online exams (r = -.743, p < .01) and abstract sequential with e-journals (r = -.918, p < .05), use of multimedia (r = -.984, p < .01), and video clips (r = -.976, p < .01). There were four positive correlations between the combination concrete sequential and abstract sequential with self-assessment quizzes (r = .712, p < .01), video clips (r = .596, p < .05), chat rooms (r = .556, p < .05), and group activities (r = .485, p < .05). Butler and Pinto-Zipp (2006) caution the reader about making cause and effect relations based on these correlations. Another point to keep in mind is that adult population in the Butler and Pinto-Zipp (2006) study was very experienced with online learning and very satisfied with their current experiences, “The instructional methods that emphasized interactions and convenience were rated highly by the subjects as most beneficial to online learning” (p. 213). With working adults, convenience and flexibility are hallmarks whether the course is delivered face-to-face or online. A good mix of discussion, sharing ideas, debating, and fostering a learning community are important to adult students in any forum (Collins & Zacharakis, 2009). However, it does demonstrate the variety of learning elements needed in an online course and that learners with different learning styles prefer different forms of electronic learning. In a classroom setting, instructors should make the same accommodations to the different learning styles. This knowledge can now be transferred to the electronic tools available. While Gaytan and McEwen (2007) studied effective online instructional strategies, their research only included one statement concerning learning styles. Out of 332 students, 67% of the students surveyed were over the age of 23. They compared the perceptions of faculty and students in online courses. One of the quality indicators of online instruction was “a variety of instructional strategies (e.g., visual, audio, kinesthetic) are being used to address various learning styles of students”

The Role of Learning Styles and Technology

(Gaytan & McEwen, 2007, p. 124). Seventy-two percent of the faculty agreed or strongly agreed with this statement. Interestingly, only 42% of the entire student population agreed or strongly agreed with it. While Gaytan and McEwen (2007) recommend that instructors review the literature on learning style preferences and develop a variety of teaching strategies, there is not much data in their research study to support it. These are just a few of the rich studies that are published researching learning styles and online learning. Most of the studies as represented above are concerning learning style preferences and students’ choice for online instruction or face-to-face instruction. The researchers all chose their learning style instrument deliberately for its measure of certain learning characteristics or traits with a majority choosing Kolb’s Learning Style Indicator. While this type of research informs the questions of which learning styles seem to assist the learner in having a more positive experience in an online environment, they do not assist the instructor in developing teaching strategies to address multiple learning styles. One study examined the technological instructional strategies and learning style with adult students. Ultimately, knowledge of learning styles should impact the teaching strategies used in the course.

USING TECHNOLOGY INFORMED BY LEARNING STYLES From the research discussed in this article, we know that learning styles are important for instructors to understand and that just as certain learning styles prefer certain approaches in a face-to-face classroom, similarly certain learning styles will prefer certain technological approaches to learning. The question for the instructor is how to design a course using the technology appropriately informed by the learning style research. Much of the literature focuses on online learning and technology; however, technology can equally

be incorporated into a face-to-face environment as well. Further, from the research, instructors could be led to believe that students with a certain learning style will self-select to enroll in online courses, but instructors can never take for granted the student population’s learning styles. Therefore, instructors need to design learning experiences that touch on the variety of learning styles. Kolb (1984) even stated that exposing learners to different approaches to the learning material increased the students’ adaptability and strengthened their non-dominant learning styles. The learning style researchers consistently state that learners possess all the traits measured by the instrument, but that learners prefer or are dominate in one or two traits over the others. When instructors create a course and develop the myriad of approaches to the content, a mix of all the styles can be incorporated into the learning activities. The goal is to use the technology appropriately for the learning style. What electronic tools are available to assist instructors in meeting the learning style preferences of all learners? Because the information about learning styles is incredibly diverse, as well as the descriptions of learners, and to demonstrate the application of technology with learning styles, this section will narrow the focus on Web 2.0 tools that can enhance learning and the electronic tools aligned with the VARK approach (visual, auditory, read/write, and kinesthetic) and the experiential category represented by the Gregorc Style Delineator (concrete sequential, abstract sequential, abstract random and concrete random). This section is informed by the research studies as well as information gathered from discussions with adult students in higher education courses concerning their learning styles according to the VARK approach and the Gregorc Style Delineator. The experience of these adult learners with electronic mediums varied; some only had experience with a few of the electronic tools in one course, while others had experience with several in up to 50 courses.

307

The Role of Learning Styles and Technology

IMPACT OF WEB 2.0 While practitioners have incorporated many of these tools into educating and training the adult population, researchers are just now beginning to consider some of the Web 2.0 functions currently available. The new technologies include weblogs, wikis, podcasting and video casting, photo galleries, such as Flickr, and virtual multiplayer games (e.g., Second Life). These are innovative technologies for all educators to grapple with and come to some understanding of how they can be used to improve the learning of students (Richardson, 2009). While this section will not describe how to create some of these, it will link the technologies with learning style research. Weblogs, commonly known by the shortened name of blogs, have become very popular. They are simply Web sites that individuals easily update and contain conversations or reflections (Richardson, 2009). Blogs are dynamic learning sites that allow readers to exchange ideas, links, and questions. In addition, blogs can include graphics, photos, audio and video files. The learner, who needs interaction with other people and active products, would find blogging a great technique to enhance their learning. For instance, one use with adult students would be assigning a blog instead of a typewritten or handwritten reflective journal. Blogs can be open to fellow students or closed to just a few people. Blogs can be public on the Internet or limited to course participants or a small group within the course. Students can explore other blogs on the Web and link to contradictory and supporting opinions, “Posting to a Weblog can take many forms. Students can write about personal reactions to topics covered in class, post links, write reflectively, and summarize and annotate reading” (Richardson, 2009, p. 28). Blogs can be combined with a research activity like Web site evaluations. Students would link to the sites, analyze and critic each site within the blog format.

308

Another use of blogs is to structure a student portfolio. Portfolios have been used in programs to demonstrate student learning throughout a degree program. These allow students to collect and present the best work to demonstrate their learning aligning with program outcomes or rubrics created by the faculty of the program. Traditionally, students have submitted massive notebooks or the institution may have specialized software they purchased to allow for electronic submissions. Unfortunately, at this time, special software may be too expensive for an institution. An alternative submission format, using the electronic medium, is to create a blog electronic portfolio. Students just upload or link to their work, write their reflections on the learning experience and examine their own progress through the degree program. Instructors have permissions to view student blogs and evaluate them online, allowing for feedback to be given expediently. Wikis are another electronic tool that supports fluid interaction. From the constructivist mindset, knowledge is not created in isolation, and a wiki provides a great collaborative site for knowledge to be shared. Wikipedia is an example of a group created and edited encyclopedia (Richardson, 2009). In a course, students could be assigned to find information on Wikipedia that conflicted with information the students had learned through their own research and update the Wikipedia site. Wikis are a great way for students to create an online text for a course. Students learn to evaluate and analyze the work of others as they are responsible for the content collected on the Wiki. If students are reviewing separate books on a subject, instead of just writing a book critique for the instructor, these could be placed on a wiki and available to all the students in the course. The learning community is enlarged from one-to-one to oneto-many. From year-to-year, the wikis become increasingly more dynamic as each section of the course access the book’s wiki page and add to the site. Now the learning community is expanded from just the students enrolled this semester or

The Role of Learning Styles and Technology

for this course to students from year to year. The collaborative world of wikis really “demonstrates how knowledge and information is becoming more and more a group effort” (Richardson, 2009, p. 69). Wikis definitely appeal to learning styles that enjoy collaborating with others and generating a creative product. Podcasting or audio streaming is already being used by instructors to record lectures and make available to students with great success (Evans, 2008; Richardson, 2009). Podcasts are audio material that can be downloaded to a mobile listening device (e.g., iPOD, iPhone, Blackberry) or to a computer. Students listen at a time that is convenient for them. In reverse flow, the students could also digitally record material, such as an interview and upload the file for everyone to hear. Digital cameras are very popular, providing a wonderful electronic tool for the educational environment. They enable instructors and learners to create a video and upload to the course management system. It also gives students the means to complete an assignment creatively. For example, in a course on group dynamics, the instructor could give students different scenarios and record the small group interactions. The digital recordings could then be played back, so all students review and analyze the group dynamics displayed. Digitally recording a graduate of the program and playing it the first night of a class or making it available for students to download and view at their convenience, allows students to see and hear a testimonial without having to be physically present with the graduate. Smartphones or cell phones are other digital recording devices used to capture digital photos. On the Web there are numerous places to publish these photographs and videos. Flickr is one such place that educators have been using in their classrooms (Richardson, 2009). Flickr allows annotations to be created and comments to be posted, allowing for conversations to develop. Multiuser virtual environment was once isolated to the digital gaming community. However,

Second Life has moved into the education and corporate environment (Vossen & Hagemann, 2007). Second Life provides a three-dimensional virtual world where participants own a place or an island. Several institutions have islands where prospective students can take a tour of the campus. Through the use of an avatar, students are able to virtually walk across campus. Classrooms are constructed and instructors can lecture in a virtual world. Second Life is also being used by instructors to create real life professional scenarios students will encounter in the world. Instead of just reading a case study, an instructor could create a hotel and conference center. In groups, students have to market and host an event at the center with all the aspects of catering, signage, and audiovisual equipment at a fraction of the cost to experience such an event as at a real world hotel or conference center. K-12 teachers are using Web 2.0 features, and these features are quickly being integrated into adult and higher education. While more research needs to be conducted as to how these support different learning styles, the alignment of electronic educational tools with learning styles in the following section is informed by adult student experiences.

LEARNING STYLES AND INSTRUCTIONAL STRATEGIES “I learn best by hands on and interaction with peers,” an adult student responded when asked if he or she preferred face-to-face or online learning. To this student, the only way to experience learning, in this manner, was to have it presented to him or her in a face-to-face format. The challenge for educators is to create a hands-on and interactive learning experience even if the format is not face-to-face. Creating a learning experience with learning styles in mind is one way to approach this student’s needs. What learning style aligns with different electronic mediums at the

309

The Role of Learning Styles and Technology

disposal of the instructor? We will look first at the physiological model as described by VARK learning styles (visual, auditory, read/write, and kinesthetic), which was explained earlier. According to VARK, the visual learners need images (Fleming, n.d.). The best learning strategies to incorporate into a course include graphics, pictures, flow charts, and graphs. Video streaming a lecture where students can see the instructor’s facial expressions and gestures is a wonderful way to enhance the learning with electronic medium. Many instructors may get stage fright as they are being recorded. It is important to be as animated on the video as in the classroom. To appeal to this learning style, instructors need to use color and lots of it. Examples include highlighting portions of the announcements or e-mails and writing messages in different colors. Another excellent tool to use with these learners is to create a mind map of the course structure and assignment due dates. Instructors can begin linking with this learning style by brainstorming all the ways a course can be enhanced with color and visual representations. Auditory learners need to listen to the message and verbally process it with another person. This learner will attend face-to-face classes, because they need to hear and discuss with others the ideas presented. To enhance these learners’ experience using electronic medium the course format will include downloadable audio versions of lectures and PowerPoint slides. These learners enjoy the experience of hearing authors read their own book or present their own concepts. With many course management systems, it is possible to make an audio recording of announcements and any lectures created through PowerPoint. Instructors can describe the graphs and upload the recording along with the PowerPoint slide. This is a great way to enhance the learning experience for auditory learners. The facilitator can create Podcasts of interviews or lectures with authors or link to podcasts already created on the Internet. To appeal to the auditory learner, podcasts and audio streaming are great electronic tools to incorporate into

310

any course. Many instructors are already digitally recording lectures and placing them on Web sites for students to download to their iPod, computer, or other listening device. This allows the auditory learner to review a lecture in the learning format that is their strength. It also allows for students who are at distance or unable to attend to have access to the information in a verbal format instead of just reading an instructor’s or classmates notes. These learners would also benefit from a synchronous session where they connect with the instructor using visual software, such as Skype. For instance, Skype users make telephone and video connections through the Internet using their computer and Skype software. This gives the learner and instructor the opportunity to see and hear each other in real time. Another possibility is the use of Webinar (Web-based seminar) software where again the students and instructor can connect using their telephone and computer. Participants can all hear each other as they view the same document on their computer screens; however, most software does not allow them to see each other. This is a tool to deliver a lecture, presentation, or seminar. It is very interactive with the participants able to discuss and engage each other. The third learning style documented by VARK is read/write. The read/write learner has a strong preference for reading and writing as a way to learn. Textbook assignments, readings, lecture notes, and manuals are important learning tools for these students (Fleming, n.d.). These learners like to turn graphs and flow charts into words. Links to e-journals and electronic databases align with this learners need to read. The message board or discussion board also assists these students in learning the material. Assignments that tap into the read/write learners’ strengths include writing and posting papers, and peer evaluation of assignments. These students often enjoy blogging and wikis. As described earlier, blogging could be in the form of an electronic reflective journaling activity that allows other students to make

The Role of Learning Styles and Technology

comments, whereas wikis are platforms for the creation of group papers and online collaboration. The kinesthetic learner needs to incorporate all their senses into the learning situation. They need hands-on experiences, field trips, and laboratory experiences where they can see, touch, smell, hear and taste the concepts. Even distance learners can be sent out into their community to experience a concept and then share that experience in a pictorial and written format in an electronic format. Digital cameras are one option to capture the experience, but another is just a cell phone with a camera or a smartphone. Instructors can create videos of real life experiences (i.e., capturing a video of a face-to-face adult learning experience), upload the videos and have students work in groups to evaluate the example. Flickr is a tool that allows instructors to upload photos and annotate parts of the picture. Group discussions can result as students add their comments and questions under the picture. These tools address the kinesthetic learner need to “do” things to learn. Virtual gaming technology is another electronic tool to be used with the kinesthetic learner. In a community like Second Life, the kinesthetic learner could immerse themselves into a learning situation, such as planning a conference as illustrated earlier. While physiological category is important to consider, the experiential approaches inform instructors of the ways adults make meaning of the information. The next learning styles types, which will be discussed in alignment with suggested technological tools to enhance their learning, are the Gregorc’s concrete sequential, abstract sequential, abstract random, and concrete random. The concrete sequential learner has a preference for step-by-step directions, concrete examples, and specificity (Gregorc, 1982). Learning tools appealing to this style which can be incorporated into a face-to-face environment or an online environment include: checklists, mandated number of assignments, mandated number of posts on the message board, self-assessment quizzes, textbook readings, CD-ROM tutorials, video clips with

step-by-step instructions or explanation, threaded discussion about current trends with application to their workplace or life, and online examinations. The abstract sequential learner has a preference to analyze, compare, contrast, and evaluate (Gregorc, 1982). A person with this learning style prefers to work alone and needs recognition of their personal effort. Learning tools appealing to this style which can be incorporated into a face-to-face environment or an online environment include: individual assignments, textbook readings, webquest (read, analyze, and synthesize material contained on the Web), threaded debate, blogs, case studies, problem-based assignments, online tutorials, and computer simulations. The abstract random learner has a preference for subjective, abstract material (Gregorc, 1982). This learner likes to collaborate with others and demonstrate learning through creative artifacts (e.g., art, music, prose, film). Learning tools appealing to this style that can be incorporated into a face-to-face environment or an online environment include: wikis, blogs, student lounge on the message board, synchronous discussions, post bios and pictures, collaborative opportunities, group projects, audio conferencing, video conferencing, video clips, movies/films, using emoticons, and express emotions in posts. A possible assignment is to have the students create a Web page introducing themselves to the group. If a Web page is not an option, the course management systems may have the capability for learners to post their bios and pictures. In the online environment, many students, and especially those who are abstract random (Gregorc), find it difficult because their strength is reading body language and they feel disconnected from the learning environment without the physical presence of classmates and the instructor. To build a learning community, it is important to give students time to become acquainted; it does not matter whether the environment is face-to-face or online. The concrete random learner prefers to create new ideas, products, or approaches (Gregorc,

311

The Role of Learning Styles and Technology

1982). This learner begins with the big picture, is naturally curious, competitive, inventive, and explores. Learning tools appealing to this style which can be incorporated into a face-to-face environment or an online environment include: individual assignments with creative products, video clips, multimedia, computer simulations, virtual multi-player games (e.g., Second Life), threaded discussions, chat rooms, graphics, audio and video lectures, self-assessment quizzes, online examinations, and CD-ROM or online tutorials. Technology has provided the opportunity for instructors to include multiple learning experiences into their courses. Manner (2005) recommended that instructors incorporate redundancy and reciprocity into their online course design and delivery. Redundancy involves giving multiple ways for students to access information in navigation opportunities, formats (audio and visual files), and descriptions of material. There is not one way to access information online which aligns with the multiple learning preferences discussed earlier. Instructors need to take this into consideration when designing a course and provide links to the same material in multiple locations. In its early generations, online learning relied heavily on print to instruct. It seemed instructors took correspondence courses and merely transferred them to a different type of technology. Today, there are numerous alternatives from audio files (i.e., podcasts) of instructor lectures, audio and video files of others, and Web sites that convey the same information found in a textbook. Just as instructors vary examples in a face-to-face classroom, the online environment needs numerous examples. Reciprocity can be achieved by keeping in mind that some students need the forest (the big picture) and others need the trees (the details and steps). Instructors need to approach the learning from all directions in order to create a learning environment for all learning types. By providing a summary of information, instructors provide for students who need to start with the big picture and then move to the details and as

312

well as providing for students who start with the details a way to capture the overall picture at the end. For instance, in addition to the narrative discussion which appeals to abstract random, instructors can create templates with assignments for the concrete sequential. Synchronous learning options are necessary for some learning styles, as described earlier. One student responded, “The instant response to my questions and the information from fellow students is useful in my learning effectiveness”. Real time chats and video conferencing can assist these students in achieving their learning goals. These are just a few examples on how to align technological enhancements in the learning environment with learning styles for adult students. More research needs to be conducted with an adult student population concerning learning styles and online instructional strategies.

FUTURE RESEARCH RECOMMENDATIONS Where do we go from here? Many of the studies have been reviewing learning styles and online learning. They have noted which learning styles are successful in the electronic environment. Few studies have analyzed the instructional devices or Web 2.0 features aligning them with learning styles with adult learners. In addition to adult learners in the Western culture, researchers need to explore the link between learning styles and adult students from different cultures. With online courses, the possibility of students from different cultures and regions of the world enrolling in a course anywhere is very high. The holistic approach to learning found in more collaborative cultures may affect how the learning styles and electronic tools align. Students have commented that their analysis of learning in an online environment was tainted by whether they value their online course experiences as good or bad. If the experience was bad, then no

The Role of Learning Styles and Technology

electronic instructional strategies appeal to them or seem to be effective. If students perceived the experience in a positive light, then many of the learning approaches were perceived to be very effective. However, the real reason some students may have perceived the experience as “bad” was because the instructor did not give them enough feedback. This issue has nothing to do with learning styles and effective learning techniques. First, conduct a course created to include technologyenhanced learning experiences for all learning types. Then study the students’ perception of the learning and the effectiveness of the electronic instructional tools. Research with learning styles and technology needs to also take into consideration whether the adult learner is a digital native (born with technology and very familiar with the electronic world) or digital immigrant (relearning how to do things with technology). How familiar a person is with the medium will impact how easy it is to navigate and accomplish tasks. How does learning style affect the advanced user in contrast to the inexperienced user of technology?

CONCLUSION With the current economic situation of rising gas prices and laying off more workers, Allen and Seaman (2008) predict adults will be seeking viable ways to increase their knowledge base and diversify their skills in order to find employment opportunities. Historically, in economic down turns adult students have been a major source for increased enrollments. According to Allen and Seaman (2008), there is widespread conviction that adults will opt for the online course. For example, adults may need to save money on fuel and need the flexible time schedule in order to complete their education anytime and anywhere. Instructors of online courses must improve their understanding of their students, as well as how the medium influences learning.

There is a range of offerings that different institutions classify as online learning. Online courses began as text-only using just PowerPoint slides and instructor notes. Most courses may still be at this point as instructors new to using technology join the ranks of experienced online facilitators. There are more tools available now for online courses, from blogs to wikis to webquests, which have the potential to enhance the learning and engage the learner in new and different ways. Some institutions may also offer online courses using an avatar and the third dimensional world, such as Second Life. Instructors need not limit the incorporation of technology to just online course formats. These tools can greatly enhance the learning in a face-to-face environment as well. While instructors cannot be all things to all learners, the knowledge of learning styles can assist instructors in making deliberate decisions about what technologies to incorporate in courses. Web 2.0 features should be given serious consideration. Multitasking is moving to a new level. Learning is fluid and students move easily from synchronous events to asynchronous explorations. There are new learning spaces, such as blogs, wikis, and Flickr, which appeal to multiple learning preferences. Students and faculty can post a comment while walking to lunch with the mobile wireless devices available. Learning styles can still inform instructors and learners as they move from the walled learning environment to dynamic, fluid, mobile, and global knowledge exploration.

REFERENCES Allen, I., & Seaman, J. (2007). Online nation: Five years of growth in online learning. Needham, MA: Sloan Consortium. Retrieved April 22, 2009, from http://www.sloan-c.org/public ations/survey /pdf/online_nation.pdf

313

The Role of Learning Styles and Technology

Allen, I., & Seaman, J. (2008). Staying the course. Needham, MA: Sloan Consortium. Retrieved April 22, 2009, from http://www.sloanconsortium.org/ publicat ions/survey/pdf/staying_the_course.pdf Butler, T., & Pinto-Zipp, G. (2006). Students’ learning styles and their preferences for online instructional methods. Journal of Educational Technology Systems, 34(2), 199–221. doi:10.2190/8UD2-BHFU-4PXV-7ALW Cassidy, S. (2004). Learning studies: An overview of theories, models, and measures. Educational Psychology, 24(4), 419–444. doi:10.1080/0144341042000228834 Collins, R. A., & Zacharakis, J. (2009). Impact of e-learning on adult education: A changing postmodern approach. In V. Wang (Ed.), Handbook of research on E-learning applications for career and technical education: Technologies for vocational training (pp. 286-296). Hershey, PA: IGI Global. Cox, T. (2008). Learning styles and students’ attitudes toward the use of technology in higher and adult education classes. Institute for Learning Styles Journal, 1, 1-13. Retrieved February 13, 2009, from http://www.auburn.edu/~wittej e/ ilsrj/latestissue.htm Cranton, P. (2005). Learning styles. In L. English (Ed.), International encyclopedia of adult education (pp. 362-366). New York: Palgrave McMillan. Diaz, D., & Cartnal, R. (1999). Students’ learning styles in two classes: Online distance learning and equivalent on-campus. College Teaching, 47(4), 130–135. DuCharme-Hansen, B. A., & Dupin-Bryant, P. A. (2004). Web-based distance education for adults. Malabar, FL: Krieger Publishing. Dunn, R., & Griggs, S. A. (Eds.). (2000). Practical approaches to using learning styles in higher education. Westport, CT: Bergin & Garvey.

314

Dunn, R., Honingsfeld, A., & Doolan, L. (2009). Impact of learning-style instructional strategies on students’achievement and attitudes: Perceptions of educators in diverse institutions. Clearing House (Menasha, Wis.), 82(3), 135–140. doi:10.3200/ TCHS.82.3.135-140 Evans, C. (2008). The effectiveness of m-learning in the form of podcast revision lectures in higher education. Computers & Education, 50(2), 491– 498. doi:10.1016/j.compedu.2007.09.016 Fleming, N. (n.d.). VARK: A guide to learning styles. Retrieved March 16, 2009, from http://www. vark-learn.com/englis h/page.asp?p=categories Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic Books. Gaytan, J., & McEwen, B. (2007). Effective online instructional and assessment strategies. American Journal of Distance Education, 21(3), 117–132. doi:10.1080/08923640701341653 Goleman, D. (1998). Working with emotional intelligence. New York: Bantam Books. Grasha, A. (1996). Teaching with style: A practical guide to enhancing learning by understanding teaching and learning styles. Pittsburgh, PA: International Alliance of Teaching Scholars. Gregorc, A. F. (1982). An adult’s guide to style. Columbia, CT: Gregorc Associates. James, W., & Blank, W. (1993). Review and critique of available learning style instruments for adults. New Directions for adult and Ccontinuing education, 1993(59), 47-57. James, W., & Maher, P. (2004). Understanding and using learning styles. In M. Galbraith (Ed.), Adult learning methods: A guide for effective instruction (3rd ed.) (pp. 119-139). Malabar, FL: Krieger Publishing.

The Role of Learning Styles and Technology

Kolb, D. A. (1984). Experiential learning. Englewood Cliffs, NJ: Prentice Hall. Manner, J. (2005). Accommodating diverse learning styles with online course enhancements. Journal of Interactive instruction . Development, 17(4), 19–21. Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in adulthood: A comprehensive guide (3rd ed.). San Francisco: Jossey Bass. Miller, L. (2005). Using learning styles to evaluate computer-based instruction. Computers in Human Behavior, 21(2), 287–306. doi:10.1016/j. chb.2004.02.011 Myers, I. B. (1993). Gifts differing: Understanding personality type. Palo Alto, CA: CPP Books.

Simpson, C., & Du, Y. (2004). Effects of learning styles and class participation on students’ enjoyments level in distributed learning environments. Journal of Education for Library and Information Science, 45(2), 123–136. Terrell, S., & Dringus, L. (1999). An investigation of the effect of learning style on student success in an online learning environment. Journal of Educational Technology Systems, 28(3), 231–236. Verduin, J. R., & Clark, T. (1991). Distance education: The foundations of effective practice. San Francisco: Jossey-Bass. Vossen, G., & Hagemann, S. (2007). Unleashing Web 2.0 from concepts to creativity. Burlington, MA: Morgan Kaufmann.

Richardson, W. (2009). Blogs, wikis, podcasts, and other powerful web tools for classrooms. Thousand Oaks, CA: Corwin Press. This work was previously published in International. Journal of Web-Based Learning and Teaching Technologies, edited by Nikos Karacapilidis, Eugenia M. W. Ng, Mahesh S. Raisinghani pp. 50-65, copyright 2009 by Information Science Reference (an imprint of IGI Global)

315

316

Chapter 18

Towards an Effective ICTBased University Learning:

The Tacit and the Interaction Dimensions Manuel Ahedo University Rovira i Virgili, Spain

ABSTRACT The principles and practices of university learning are being subject to critical reconsideration from new approaches to adult teaching and a growing use of information and communication technologies (ICTs). ICTs in adult learning have an ambivalent effect. On the one hand, they offer potential improvement in on-line communicative activities and the transmission of codified or explicit knowledge. On the other hand, they can reduce socially- and interactive-mediated tacit teaching and learning. Thus, the crucial criterion for effective and complementary use of ICTs in adult andragogy is whether they enable time and interactive social space for the tacit dimension of teaching and learning. This chapter analyzes these issues by comparing how two young universities in Spain have dealt with these effects of ICTs in relation to the tacit and interaction challenging dimensions of learning and teaching.

INTRODUCTION Until recently adult learning has been rather marginalized in most countries. For many decades, higher education systems were entrusted with providing industrial societies with the qualified professionals they needed. During the second half of the 20th century, increasing numbers of adults attended an expanding offer of tertiary education programs. In this context, then, it became necesDOI: 10.4018/978-1-60960-153-9.ch018

sary to discuss and analyze the teaching techniques for both young and mature adult learners. With this purpose, in 1980 Knowles proposed the concept and principles of andragogy, targeted at discovering the specificities of the pedagogy of adult learning. Since then Knowles’s principles have been revised and developed within a substantial process of social and educational change. Particularly since the 1990s, in many Western societies continuing adult education began to get both public and academic attention, and emphasis was increasingly placed on skills, training, and

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Towards an Effective ICT-Based University Learning

competences. In the same period, other structural changes have occurred: for example, increasing use is made of the information and communication technologies (ICTs), and there are new forms of social relations and networks (Webster, 1995; Castells, 1997). In these last two decades or so, learning, lifelong learning and the learning society have served as umbrella concepts in most discussions on adults and learning in the emerging knowledge or learning society and economy (Stehr, 1994). These concepts have become a new analytical framework for educational studies (Young, 1998). The notions of lifelong learning and learning society, however, have also been subject to critical analysis and discussions (Barry, 1999; Coffield, 2000). For Fischer (2001) lifelong learning is broader than adult education or training, as it includes such new dimensions as self-directed learning, learning on demand, informal learning, and organizational learning. Jarvis (2000) advocates that the concept of learning society allows for a more comprehensive comparative educational approach, because in the context of globalization, expanding use of ICTs, and new forms of industrialism and post-industrialism, learning takes place in more than educational institutions. As technology and innovation have gained momentum, knowledge and learning have also received more attention from the social and human sciences. International organizations such as the World Bank (2003) and the OECD (2005) have also highlighted the challenges posed to tertiary and university education in the current era of social and technological change. The European Union has undergone a process of harmonization of national higher education during which, the tacit dimension of teaching and learning clearly emerged in the discussions on competences and skills as will be shown below. Traditional teaching pedagogy was designed to transmit codified or written knowledge to young generations within the paradigm of general standardized industrial production and mass

consumption known as Fordism. This codified or formalized knowledge consisted of lists of technical information and facts, the purpose of which was to ensure stable use over time. The aim of teaching and learning was to acquire it. When the Fordism model entered into crisis in the 1980s, alternative proposals for teaching different age groups began to be made. Constructivist and pragmatist pedagogy, inspired by Dewey (1933) and others, became more widespread as qualitative and micro social sciences became more prominent, as can be seen by the evolution of the theory of practices (Bourdieu, 1977; Schatzki, Knor-Cetina, & VonSavigny, 2001; Schön, 1983; Searle, 1995). The educational and pedagogical literature began to go beyond the formal teaching of codified knowledge and started considering the more tacit, reflective and informal dimensions of learning (Burbules, 2008). Learning to learn became one of the key competencies by which students can go beyond the individual and collective skill-bases (Jarvis & Parker, 2005; Schön, 1987; Sternberg & Horvath, 1999). In Spain, as in many other European countries, the discussion on educational methodologies and pedagogies took place as a side-debate on the issues of competencies and skills. The ICTs have been a driving force behind the change in national adult learning systems. Generally, technology, science and knowledge and the corresponding technological determinism have been strongly criticized, and it is now widely argued that society shapes technology (MacKenzie & Wacjman, 1985). Concerned about the use of technology in education, educational organizations began to use ICTs as both the content to be taught and the means by which this content was taught. At first, the focus was on ICTs as content so that the new generations could acquire technological skills and those already active in the labor market could upgrade their existing skills. Subsequently, ICTs were gradually used in education as instruments for teaching and learning. This second phase has been subject to considerable critical discussion and research. The main problem is that

317

Towards an Effective ICT-Based University Learning

teaching and learning involve a certain amount of tacit practice. And because tacit teaching and learning is highly socially-mediated, it depends mainly on face-to-face interaction. This is even more critical in adult teaching, since adults have already completed their basic process of cognitive and relational socialization, and their face-to-face communication is already highly patterned. Adults can always undergo a process of re-socialization, but they have considerable difficulties in doing so. It can be argued, then, that whereas ICTs have so far been generally practical and appropriate tools for education, they also have important limitations for substantial teaching and learning, especially regarding the tacit dimension. This chapter aims to discuss these issues by comparing how ICTs have been used by two universities in Spain in their attempts to provide high quality university education. The section below presents the background in three parts. In the first of these parts, the principles of adult learning and traditional pedagogy are discussed and reviewed from the perspective of tacit learning. In the second, the need for new teaching roles in the emerging information and learning society is discussed, again in connection with the idea of tacit teaching. In the third, the relation between ICTs and tacit learning and teaching is analyzed. The next section provides the main arguments and foci of this chapter and, once again, is divided into three sub-sections. The first sub-section contextualizes the recent changes brought about by the standardization of higher education in the

European Union, under the so-called Bologna process. The second summarizes the most important features of higher education and the use of ICTs in Spain. The third analyzes the attempts made by two Spanish Universities to use ICTs effectively. The two universities studied were the University Rovira i Virgili (URV), a conventional university in the province of Tarragona, and the Open University of Catalonia (Universitat Oberta de Catalunya – UOC), a public distance and elearning university. The third major section also suggests future research directions. A final section summarizes the main arguments and conclusions.

BACKGROUND Adult Learning and Pedagogy Principles With Regard To The Use Of Icts And The TacitInteractive Dimensions ICTs in adult and university education need to be put to more effective use for a variety of reasons (Figure 1). First, there is a need to develop new andragogical principles that are more relevant to the requirements of adults. Second, university teachers and teachers of adults need to design and adopt new teaching roles for transmitting information and knowledge. And finally, the tacit dimension in learning and teaching needs to be operationalized through social face-to-face interactive mediation as a key complementary

Figure 1. The relational triangle of the tacit and interaction dimensions in university teaching and learning with regard to the use of ICTs

318

Towards an Effective ICT-Based University Learning

mechanism for the effective use of ICTs in adult and university education.

Principles of Adult Learning: Towards A New Andragogy Learning is a complex activity. Learning something new and using it is by no means straightforward, and the complexity of the process can only be grasped by resorting to such traditions as cybernetics, experimentalism and pragmatism. Cybernetics has provided a series of tools for understanding cognitive and information processes (Von Forrester, 1984; Varela, Thompson, & Rosch, 1993). Experimentalism and pragmatism have emphasized reflection and activity. According to Horyp (2006), Dewey regarded reflective thought as an active, persistent and careful consideration of any beliefs or supposed forms of knowledge in the light of the grounds on which they were based and the consequences that they would have. Dewey viewed the process of learning as being similar to the process of scientific knowledge and discovery. Reflection, then, is conceived as the outcome of three main steps: separation, initiation and return. Separation involves inhibiting action, habits and routines first, and then postponing immediate action by controlling impulses, a process that is somewhat similar to un-learning and doubting. Initiation has two sub-steps: learners must first try to define what is wrong, and then formulate an idea to guide the action they take (that’s to say, a kind of working hypothesis). Return also involves two sub-activities: firstly, learners must understand what ideas mean in relation to each other (in other words, they test their working hypothesis on their thought process mainly by using memory), and secondly, they must put the idea into action, and observe the feedback. In sum, pragmatism-inspired perspectives regard learning as being similar to discovering scientific knowledge: they aim to ground learning on a firm basis of evidence and rationality, a view that is not far from accounts of the current knowledge-based

reflexive society and social actors (Stehr, 1994), inspired in ethnomethodology’s argument that lay actors think, learn and act as highly knowledgeable actors (Garfinkel, 1967) Adult learning has specific aspects and features that differentiate it from other types of learning. Knowles (1980) pointed out that adults are autonomous and self-directed individuals, and, therefore, accustomed to participating in equal and mutually respectful adult relationships. They also have life experiences, which are their main source of knowledge. They are goal-oriented, as they know clear objectives are important for saving resources and time, and they are also oriented by relevance and practical application. Adult experience is like a repository of information, consisting of direct experimentation and realities. Although most of these features can be seen as positive assets for learning, this may not to be the case in all respects. Adults’ established routines and habits can sometimes hinder reflection. Adults can have difficulty accepting that they lack understanding as they think they have sound knowledge based on life and experience. One of the most critical aspects of adults as learners is motivation. Many adults, already established and safe in family and social routines, need stimulation and incentives. From the above and the recent literature on learning, adult learning and andragogy (Antonocopoulou et al., 2006; Boud, 2000; Boud, Keogh, & Walker, 1985; Merriam & Cafarella, 1999; Yang, 2003), it is deemed necessary to take a holistic and comprehensive approach to learning in higher education. This holistic process involves three steps: reflection, re-conceptualization and action. First, the initial reflection obliges students to separate themselves from their experiences, and existing knowledge. Second, interactive reconceptualization enables students to embody and apprehend the new knowledge so that they can overcome the doubts and uncertainties that have arisen in the first step. Third, action allows students to experience how the new knowledge is used or can be used. In fact, in higher education

319

Towards an Effective ICT-Based University Learning

there has been growing interest in applying new knowledge so that it can be seen how it works in reality. To enact all these steps, learners need to undergo a deep and substantial process of questioning, doubting, listening, communicating, interacting and, finally, doing. Each of these three steps has something to do with tacit learning. In particular, two aspects can be highlighted: the tacit and the interaction dimensions, which will be dealt with bellow. In sum, it has been argued that adult learning in our changing societies is a complex process, which has an important tacit dimension. This process involves developing an updated andragogy, and experimenting with new teaching roles and techniques. In other words, a systematic reflection on tacit teaching is needed. This reflection will be made in the next section.

Pedagogical Teaching: Towards New Teaching Roles Traditional pedagogy has long focused on faceto-face guided teaching activities which transmit both information and knowledge. The teaching capacities required for face-to-face communication (both verbal and non-verbal) have been thoroughly discussed. In universities there is a wide range of teaching techniques and options, most of which depend on the instructional form of education (face–to-face, correspondence or distance): for example, seminars (small group teaching), tutorials, research seminars, exercise classes or courses, workshops (classroom-based practical classes), problem-solving sessions, laboratory teaching, demonstrations, placement (internship/traineeship), work-based practice, fieldwork, online / distance or e-learning (which may be paper-based or ICT-based). University teachers need to adopt all these techniques in their classes, taking into account the subject they are teaching, the age of the students and the size of the group. They should also bear in mind that in democratic societies, adults are increasingly criti-

320

cal and willing to participate actively in learning activities. Teaching is also better conceived as a process now. Reyes and Zarama (1998) propose a model for learning and teaching that consists of a context with four pre-conditions, and a four-step teaching process. The pre-conditions of the context are: a) the declaration of ignorance (we must accept naturally that we do not know something and that we want to learn it); b) the acceptance of possible cognitive blindness (we must accept that we do not know what we do not know, which brings constructive skepticism and doubt), c) a declaration of trust and authority in the status of the teacher, and d) research into the factors that might hinder learning, so that any self-constraints can be identified, and potentialities and capacities can be exploited. The stages for learning include: a) a break; b) knowing: drawing a distinction by the tools of reflection and language; c) understanding: grounding and embedding the distinction by putting in contexts and historical evolution; and d) learning: embodying the distinction, by practicing and incorporating it. The authority of teachers in our current societies is controversial because it is not taken for granted but needs to be earned. Therefore, current social, cultural and political changes are challenging the traditional pedagogical principles of teaching adults. In the emerging information and consumption society, adults have increasing access to experience, information and relational networking, which can be a useful tool for learning. Information-oriented technologies stimulate new roles for teachers, such as facilitators, tutors, supervisors, collaborators, guides, etc. They are adopting a role that is more that of assistant and guide, while maintaining the role of knowledge-related authority. Many interesting contributions have been made to the advancement of pedagogy in general (Cochran-Smith, FeimanNemser, & McIntyre, 2008), and adult teaching in particular (Apps, 1988; Biggs, 2003; Hillier, 2005; Pratt, 1998; Rogers, 2002). However, the tacit dimension in teaching is still underdeveloped.

Towards an Effective ICT-Based University Learning

As Burbules (2008) states,“Tacit teaching refers to the many forms of informal instruction—some intentional, some unintentional, and some difficult to categorize simply as one or the other—by which skills, capacities, and dispositions are passed along within a domain of practice” (p. 668). In sum, in order to follow the steps of the learning process described above, processes and mechanisms of information and communication are very important, and it is here that the benefits of ICTs are a clear challenge to traditional pedagogy. In higher education, however, they are limited by their inability to provide the tacit dimension of teaching, which emerges after many face-to-face teaching and communicative situations. Teaching adults in our society today means that teachers must adopt the new roles of facilitators, guides, supervisors, tutors, etc. This should be kept in mind if ICTs are to be effectively used for appropriate educational purposes.

The Challenge of Integrating ICTs with Tacit-Interactive Teaching to Adults The use of technology for educational purposes is not linear: it depends on the social structures in which it is used by individuals and groups (Gorard & Selwyn, 1999). Laurillard (1993) and Pelgrum and Anderson (1999) advocated that technology was a potential means of improving university teaching. Tait and Mills (1999) argue that ICTs and other technologies are important mechanisms through which conventional and distance education can converge. ICTs have been used for educational purposes (Goodman, 2002), and especially for adult and university education, which is a growing field (Howard, Schenk, & Discenza, 2003; Qvotrup, 2006; Sangrá & GonzálezSanmmaned, 2004a, 2004b). Other authors, such as Watson (2001), who focus mainly on primary school education, remain skeptical about the pedagogical potential of ICTs.

The effective use of ICTs for teaching and learning purposes has already been subject to thorough debate. By the end of the 1990s, Katz (1999) had summarized many of the important issues involving ICTs and the challenge they presented to higher education. Higher-education institutions, most of which are public, tend to change slowly in comparison with private organizations. It is necessary to take into account the role that ICT-based codified knowledge plays in the new emerging learning and teaching spaces and processes in higher and adult education. ICTs in adult/higher education have two main functions: a) they are a means by which information can be delivered both before and after face-to-face teaching activity; b) they make communication possible at various levels (teacher with all students, among students, and teacher with one student). However, how effective can ICTs be for the actual purpose of adult learning in higher education? This is a difficult question. Lundberg, Castillo, and Dahmani (2008), after reviewing a wide range of literature, point out that there is very little to support to the idea that online students perform better than faceto-face students. They also indicate that there is considerable disparity in the results of the studies, partly because different methodologies make it difficult for them to be compared. A particularly important issue is which ICTs are the most appropriate for effective learning and how they should be used for maximum effect. One debate has focused on the advantages of private versus open software resources. The Open Educational Resources (OER) initiatives are a relatively new phenomenon in tertiary education. The open sharing of educational resources means that knowledge is made freely available on non-commercial terms, sometimes in the framework of users and doers communities. In such communities the impact of innovation is greater when it is shared: users freely reveal their knowledge and thus work cooperatively. The financial sustainability of OER initiatives is a key issue. Many initiatives are sponsored by private

321

Towards an Effective ICT-Based University Learning

foundations, public funding or paid for by the institutions themselves. In general, the social value of knowledge and information tools increases to the extent that they can be shared with and used by others. Technically, there are two main software products for secondary and tertiary education: Moodle and Sakai. Both are open software and well tested and developed instruments. The differences between the two have more to do with the logic behind how they function and how they can be improved. It seems that Sakai is more robust technically, as it incorporates several safety and technical criteria of computer science. Moodle, on the contrary, is more pedagogical, as it is more user friendly, and therefore allows more user-based experimentation. In fact, Moodle is most used in secondary education. In many languages, Moodle has user communities that meet regularly and encourage ongoing communication. This system of user communities and communication stimulates interaction between multiple users who strive for intensive experimentation and improvement. In sum, ICTs have the potential to transform learning and teaching processes, and to provide novel ways of educating and training in conjunction with more traditional teaching. Effective use of ICTs can enable teachers to develop new teaching techniques such as learner-centered guidance, group work and inquiry projects which can result in good skills and competencies. Likewise, interactive forms of e-learning can lead to reflective, deeper and participative learning, learningby doing, inquiry learning, problem solving and creativity. ICTs provide the means to support personalization, where learners are also regarded as being knowledge builders and creators. Thus, innovative pedagogical and didactic approaches are needed to provide the changing skills and competencies necessary for employment, selfdevelopment and participation in a knowledgebased, digital society.

322

The Tacit and Interaction Dimensions in University Learning The tacit dimension is very important for the learning process. Tacit learning, as opposed to explicit and codified learning, is an uncertain and undetermined process of learning sophisticated know-how. It can also refer to practical intelligence (Sternberg & Wagner, 1986). After analyzing Wittengstein’s experiences of teaching philosophy, Burbules points out: “Tacit knowledge is often related to practical intelligence, ‘know-how’, common sense, ‘street smarts’, or what Bourdieu calls habitus—the experientially grounded capacities that allow us to navigate the choices and activities of everyday life” (Burbules, 2008, p. 669). This points to the importance of organizing inputs and mechanisms to stimulate the learning process, especially in the case of the tacit dimension. After reflecting on some practical and exemplary instances of tacit knowledge, such as how groupware can help to make tacit knowledge more explicit, Durrance (1998) suggests four principles for cultivating the sharing of tacit knowledge among people in an organization: a) watch: observe what your people do and how they do it; b) create an environment of trust, respect, and commitment, beginning with yourself; c) let people learn by doing; and d) in any training exercise, allow time for reflection and interpersonal exchange. In sum, tacit learning is the result a complex process of personal and socially interactive activities. The importance of the interaction dimension for learning was initially emphasized among others by the Deweynian pragmatist pedagogy. In this perspective, social interaction is the means by which the crucial and natural interdependence of individuals and society takes place, and it is also the main way to enact a sense of collective or community of learners collaboratively inquiring and searching on their shared space of interests and ignorance. In the last three of four decades, social interaction has become a crucial element

Towards an Effective ICT-Based University Learning

in social theory, and especially in the more micro and mezzo-oriented sociology, being a constitutive part of the above-mentioned practice turn in the social and human sciences. Interaction is conceived as a source of shared beliefs, which in turn are the main sources of social identification and behavior. As human learning implies certain improvement of beliefs, interaction renders to be one of the pre-requisite for the learning process.

E-Learning in Higher Education Higher education is meant to provide the higher level of learning and knowledge. Universities are the institutions in charge of ensuring that professionals and researchers are equipped with the highest knowledge and most advanced skills and competences for the benefit of the whole society. In this sense, the application of ICTs in university teaching receives a special strategic perspective, in order to enhance the promised heightened learning. Within a growing literature on general e-learning (Naidu, 2003), increasing attention has been given to the special features and characteristics of the application of ICTs for higher learning purposes (Ashwin, 2006; Fry, Ketteridge & Marshall, 2009; Garrison & Anderson, 2006; Laurillard, 2002; Light & Cox, 2001). The status of e-learning in higher education debate is still low, as can be observed in the only chapter on the topic in the third edition of Light & Cox original 1999 book. ICTs can be very important tools for improving teaching and learning, although it should be borne in mind that they can by no means cover all the depth and complexity of teaching and learning, especially their tacit dimension. Garrisson and Anderson (2006), inspired in a Dewenyan pedagogic pragmatism, emphasize the importance of interaction as a critical element to unfold the potentials of e-learning in higher education. They argue that ICTs can provide tools and mechanisms for interaction and collaboration, moving beyond facilitating access to information

and ideas. In their view, the positive potentials of ICT in higher education resides in promoting the emergence and development of communities of learners collaboratively inquiring and searching for advanced knowledge and beliefs. Higher education institutions are experimenting with the use of ICTs, and at the same time responding to the challenge of integrating them effectively and discovering the importance of the tacit dimension of learning and teaching.

THE MAIN FOCUS OF THE CHAPTER This major section will look at how the two Universities selected (URV and UOC) have used and experimented with ICTs, and how they have tried to solve the challenge of the tacit and interactive challenges, within the context of latest developments of higher education in the European Union and Spain.

ICTs in University Education in Spain In the European Union (EU), ICTs in higher education are quite widespread. For information on the latest harmonization process of EU’s higher education (the so-called Bologna Process), see Ahedo (2009). The European Commission’s report (2008) shows that practically all universities had websites and 9 out of 10 had intranets. By 2004, 3 out of 4 EU universities were experiencing high or very high rates of increase in the use of ICT for teaching. By 2005, individual modules, and in some cases whole programs, were being offered online, with a slow shift to more collaborative, problem-based and project-based learning methods. This has changed the role of both students and teachers. One question, however, must be asked: how are ICTs used for adult learning in Europe?. The European Commission’s report (2008) provides evidence that 1 out of 8 adults outside formal education uses the internet for formal learning activities, such as research and

323

Towards an Effective ICT-Based University Learning

downloading learning content. Online availability certainly meets the needs of some learners who require formal training, and nearly half of the adult learners consider it to be a necessary condition. What is more, results seem to be encouraging, because 2 out of 3 users are satisfied and 5 out of 6 say they would take online courses again. This may reflect the user-focus of ICT-based adult education, which allows individuals to choose appropriate learning paths. Interactive forms of e-learning can lead to more reflective, “deeper” learning and more empowered discussion, better suited to and more motivating for adult learners. E-learning may offer ways of attracting social groups that do not traditionally engage in formal training, such as the 80 million low-skilled workers. Nevertheless, two-thirds of the participants see adult learning as the chance to meet people with similar interests. Home-based e-learning does not satisfy this social need. Moreover, more than half the participants prefer guided learning to self-direction. In sum, there is still considerable ambivalence surrounding e-learning. In Spain, historically its educational system has been underdeveloped. In the second half of the twentieth century, however, it underwent a rapid and unbalanced growth and in the last two decades it has been modernized and balance has been restored. In university education in Spain, ICT-based technologies have been used for only a short time because Spain embarked rather late on the development of the information society. The European Commission’s report (2008) indicates a low level in the use of ICTs for educational and learning purposes. For example, whereas the average percentage of households with access to Internet in 2006 in EU-15 was 54% and in EU-25 51%, in Spain this percentage was only 39%. In EU-25 there were 12.1 computers per 100 pupils in 2006 in the whole of compulsory education (including upper-secondary and vocational levels), whereas in Spain there were 9.5 (the difference was larger in vocational levels: 16.8 in EU-25 and 11 in Spain). Finally, in EU-25 41% of internet

324

users between 17 and 74 years old used Internet for learning purposes whereas in Spain this figure was 37%. For the population of 16 and 17 year olds, the figures were 25% and 20%, respectively. In university education the picture is rather diverse. Because of complex organizational obstacles and constraints in collective decision-making, large universities tend to work slowly in incorporating ICTs. Medium and small-sized universities, on the other hand, have been more proactive in adopting ICTs, sometimes through experiments in departments and faculties, which are subsequently extended throughout the university. There are two main e-learning universities: the UNED at the national level and the UOC in the large region of Catalonia. At the national level, the UNED (National University of Distance Education) was created in 1972. By 2007, the number of students enrolling every year in UNED had reached about 180,000. It has 9 faculties and 2 graduate technical schools. It offers 33 official degrees, and more than 50 programs in continuing education. It has a teaching staff of about 1,400 university teachers, and close to 7,000 tutors. It has about 60 associated centers, 80 extension centers, and a number of supporting classrooms throughout Spain. Internationally, it has supportive centers in 11 countries, attending more than 2,100 students. Its main objective has been to offer professional opportunities and university education to those who did not have the opportunity in their time (women, for example). In fact, in 1982 UNED elected the first female university dean in Spain. In the 1990s, UNED began to incorporate technologies such as TV, radio, ICTs and multimedia. UNED, then, integrates different technologies and cannot be regarded as a fully internet-based e-learning university. At the regional level, the Open University of Catalonia (Universitat Oberta de Catalunya – UOC) is a younger university, created in 1995, with full commitment to ICTs. By 2005 it had over 20,000 students and offered 16 official degrees. In 2009, the UOC is offering more than 250 continu-

Towards an Effective ICT-Based University Learning

ing education courses. The UOC does not offer degrees in technical and experimental sciences, as it is almost impossible to organize the practical dimension in labs and similar infrastructures on line. So, the UOC focuses on human, management, social, law and related sciences, and its format is flexible enough to capture newly emerging niches in the educational and professional market, especially in second and master degrees, and in continuing education. In the region of Catalonia, information society indicators have evolved more rapidly than in the other regions of Spain, because of its advanced industrial and socio-economic structure. In 2008, these indicators were similar to the current EU-25 average, and were particularly high as far as connection to Internet was concerned.

Comparing How Two Universities Cope With the Tacit & Interaction Dimensions in Their Use of ICTs This section compares the use of ICTs in two Spanish universities: the UOC, a new e-learningoriented higher education institution; and the URV, a young, conventional university that has experimented with the use of ICTs for teaching purposes.

University Rovira i Virgili (URV) The URV is a young university, created in the mid-1990s, and it has been proactive in the introduction of ICTs. The use of ICTs for teaching in the URV has undergone a rapid evolution. The Unit for educational resources was created in 2001 for two main reasons. In the pedagogical field, its goal was to help teachers in teaching innovation projects. In the technological field, its goal was to help teachers use the new technologies. Initially, this mainly involved developing specific web-pages for courses, and instructing the teaching staff in basic ICTs, such as e-mail and other software programs. In 2002, the Unit bought some private educational software, the

Java Learning Environment (JLE), and began to collaborate with a handful of teachers keen on using ICTs in their teaching. Despite the general interest in using JLE, it had two problems that limited its use. Technically, its interface was rather difficult even for advanced ICT-users. This problem was not eased with a new product, Edustance. Generally speaking, JLE and Edustance were private products so any further development and improvement depended on the company’s interest in working with the University. In the academic year 2004-2005, and although Edustance was still the official ICT resource, the Unit decided to experiment with the Moodle program. Moodle, explained above, is a course management system, a free open source software package designed to help educators create online learning communities. Moodle was initially developed by a computer scientist in Australia. Its pedagogical principles are based on constructivist learning and, in this sense, electronic communication between teacher and students and between students is one of the main objectives of the software. The trial year in the URV included a visit to a university in Spain (University of Las Palmas in the Canary Islands) that had already adopted Moodle, and several meetings and discussions, especially with one of the URV’s engineering departments that had already used Moodle. The fact that several engineering departments were quick to promote the use of Moodle in their teaching is an indicator of their long pedagogical experience, dating back to the new teaching and andragogical model adopted in the mid-1990s as can be seen below. In the academic year 2005-2006 Moodle was thus set up officially in the URV and the Unit began a process of diffusion and adaptation of Moodle to the needs and practices of the URV. By the academic year 2008-2009, about 60% of teachers and about 70% of students regularly used Moodle, showing that it has been well accepted and largely adopted. The URV is one of the first three universities in Spain to adopt Moodle, together with the previously cited University of Las Palmas

325

Towards an Effective ICT-Based University Learning

in the Canary Islands and Jaume I University in Castellón. The three Universities are mediumsized with between 10,000 and 15,000 students, which may explain why Moodle was so quickly adopted and implemented. Technicians in the Unit have seen how useful Moodle user communities are for sorting out problems and suggesting improvements. The URV Unit has already identified three challenges for the near future. First, Moodle must be developed and improved, and teachers encouraged to put it to greater use. Second, it must be adapted to the European Higher Educational Area (EEES), which, through the Bologna Process of harmonization of higher education, also involves significant changes in methodology and andragogy. Two examples of this are: a) all course programs now need to be set up in a new software tool, Docnet, the aim of which is to harmonize competences; b) individual tutorials and supervision are central to this European Union process, as is planning courses according to the system of credits (ECTS). Third, the URV needs to integrate new ICT products for video-conference activities and software to identify copying practices by students. The Unit for educational resources is aware that one of the most effective ways of using ICTs in higher education is as information and knowledge depositories, and for teacher-student instructional communication. This use would make high-value time available for more substantial face-to-face teaching and learning activities, thus catering for the tacit dimension of learning. Experimentation with the tacit dimension in the URV can be observed in the cases of the School of Chemical Engineering and the Faculty of Law. The leading case of combining ICTs and faceto-face interactive teaching and learning can be found in the School of Chemical Engineering (ETSEQ). As stated above, the ETSEQ departments were among the first to use and implement Moodle in their teaching activities. Its current andragogy of chemical engineering was inspired by the methodology of the Harvard School (USA), which was based on practical application of

326

knowledge through teamwork and PBL (problembased-learning). This methodology was adopted by the ETSEQ in the mid 1990s. After more than 10 years, and despite initial complaints by students because of its demanding nature, this methodology has increasingly been evaluated in positive terms by both students and firms. The American Institute of Chemical Engineers (AICHE), in Ziemlewski (2009), appraised the pedagogical development of URV- ETSEQ in its February bulletin. AICHE is the world’s leading organization for chemical engineering professionals, with more than 40,000 members from 93 countries. In this bulletin, URV teachers point out that “Universities have to teach science as well as art, figuring out ways to engage students, and teaching them how to use principles not just apply a procedure to reach a solution” (p. 6). As one of the URV teachers interviewed states, “In addition to technical knowledge and management competence, chemical engineers need to possess social skills. These skills need to include teamwork, cooperation, creativity, innovation, communication, cultural diversity, leadership, decision-making and organizational development” (p. 6). More interestingly, most of this is achieved through team-based problem-based learning and projects. As the teacher says, “Student teams grow from leader-directed teams in the first academic year to self-directed or empowered teams in the fifth year. Fourth-year students play a key role by acting as facilitative leaders of the first-year and second-year project teams” (p. 8). Students are encouraged to become client-oriented, and to adjust their capacities and skills towards clients’ needs. The concept of “integrated project” is important, as it involves both project-based learning and cooperative learning, as a stimulus to learn how to learn, integrating and dispersing knowledge, and developing social skills. The open-ended questions and lack of information force students to understand the principles of different unit operations, to be active in determining the information that is needed to solve a problem and to seek it out. The URV teacher concludes, “Students remember 20%

Towards an Effective ICT-Based University Learning

of what we explain, 50% of what they do in the lab, and 100% of the soft skills” (p. 9). Soft skills include know-how and tacit capacities, acquired in face-to-face interaction between teachers and students, and between students. The Faculty of Law, which also includes several social sciences, has experimented more modestly with ICTs and Moodle. In 2004, a group for pedagogical innovation (Grupo de Innovación Docente - GID) was formally set up to integrate a variety of individual initiatives, one of the aims of which was to apply ICTs to teaching. Since the early 2000s, faculty staff had been investigating various aspects of ICTs (Barrat, et al., 2007; Giménez-Costa, & González-Bondia, 2007). Considering the specificities of the discipline and its particular tacit dimension, these examples in the Law Sciences are very interesting. Law education has traditionally distinguished three main bodies of knowledge—doctrine, legislation and jurisprudence—each of which has its own rationale of documentation and information. Usually, managing all this information and its sources has been an important part of the teaching of many law subjects. In this respect, several teachers have attempted to use ICTs as repositories and for other information-oriented purposes, such as the creation of wikis, etc., thus making time available to teach the more complex nuances between the three bodies of knowledge. The results have been very interesting. The use of ICTs has meant that information is provided in a more effective way, thus saving time for other more substantial teaching and learning activities. Likewise, teachers have been made more aware of the importance of face-to-face communication for providing instruments and tools to master the three legal rationales in each subject. In sum, the tacit dimension of the teaching and learning of the rationales of law is transmitted best by face-to-face communicative interaction in the classroom. The tacit dimension is gradually coming to the fore, and there is an increasing awareness that it should be made more

explicit, as it has been in the new degrees that are to come into effect in autumn 2009. Several conclusions can be drawn from the URV case. First, the URV has rapidly and substantially incorporated ICTs, and the choice of Moodle seems to have been an effective strategy, especially since it has allowed on-going experimentation and improvement through interactive user communities both inside and outside the URV. Second, university subjects organize teaching and learning in very different ways, so the use of ICTs needs to be adapted to the subject specificities. Third, it was only after a process of experimentation that URV teachers and ICT managers managed to develop appropriate ways of using ICTs and discover the importance of the tacit dimension of learning and teaching, with the subsequent need to incorporate this tacit dimension into teaching practices through more explicit terms.

Universitat Oberta de Catalunya (UOC) As an innovative university, UOC tries to offer a new way of experiencing education (Sangrá, 2002). Building on an intensive use of ICTs, UOC has tried to break through the barriers of space and time by offering an educational model of distance education based on the use of the Internet. From the start, UOC was designed to be an example of a new generation of distance education providers capable of creating cooperative interaction not only between students and professors, students and learning materials, but also among students themselves. To support this goal, the UOC grounds its model on flexibility, co-operation, personalization and interactivity. The UOC has opened out to the world by maintaining contacts with the principal international knowledge networks. Its new strategy is to make students the centre of a completely personalized educational process during which they receive guidance from an accredited teaching team. As a public university in Europe, the UOC has also been involved in changing and organizing

327

Towards an Effective ICT-Based University Learning

competence-based university programs. This has been a critical challenge, since the more social and interactive skills (particularly know how to be and know how to act) seem to be especially difficult to acquire in e-learning processes. One of the main problems faced by distance universities, and explicitly recognized by the UOC, is the high rate of drop-out among students, mainly because of the difficulties of following a distance teaching system and of maintaining a high level of self-discipline. The high drop-out rate may also be due to a low level of tacit teaching, by which a teacher can better guide a student and learner towards the meaning and purpose of the knowledge taught. In order to solve these problems, the UOC has reorganized the tasks and roles of the various members of the teaching staff. There are a variety of teacher profiles for each course: consultants, supervisors, teachers and teachers in charge. They all play their own role in helping students to complete the course, and in helping them operate within the e-learning system. Recently, two supervisory roles have been experimented with: the initial and follow-up supervisors or tutors. The initial steps have been identified as one of the most critical points in e-learning training. The initial tutor, then, is responsible for assisting students to adapt to the e-learning system. In order to do so, the tutor must establish some sort of personal relationship with the students, and then help them to design a learning and teaching profile that is compatible with their private and professional life. After completing the initial stage, the follow-up tutor is responsible for assisting students during the course. Students have the right to one face-to-face meeting with each of the two tutors. The problem of the high drop-out suggests that the UOC needs to personalize and foster more proximate and interactive communication with new students. In other words, teachers, tutors and students should have a more face-to-face interactive relation, so that different forms of tacit teaching and learning can be practiced.

328

To conclude, the UOC was born as an e-learning university, so one of its main goals and one of the main driving forces behind its activity is to make effective use of ICTs. After about 10 years of experience, however, it has opted to improve the personal relations with students through personalized tutors and, in particular, through initial tutors who help students prepare for the e-learning system. This is an example of how face-to-face interaction is needed in communication, teaching and learning, and indirectly to encourage tacit teaching and learning activities. To sum up, the following conclusions can be drawn about the use of ICTs at the URV and the UOC. First, there is a gradual trend towards convergence in the use of ICTs in the two types of university, the conventional URV and the elearning UOC. Second, the individual subjects and disciplines affect how ICTs are used: the UOC does not offer some subjects because of clear technological and infrastructure limitations, and at the URV ICTs are being used in different ways in engineering and law studies. Third, in both the universities analyzed, ICTs are used mainly to deliver information and codified knowledge, whereas personal and group interaction has been given the important role of providing more substantial learning, teaching and personal relations, thus ensuring the tacit dimension of the process.

FUTURE RESEARCH DIRECTIONS In line with the above arguments, four areas are suggested for future research. First, as far as new andragogical principles are concerned, research should be made into how adults’ life experiences can be effectively used as a base for the acquisition of different kinds of knowledge (codified, tacit, communicative), and the tacit dimension of learning. Second, if ICTs are to be used effectively to teach university learning adults, teachers need to adopt new teaching roles (e.g. facilitators, guides, supervisors, etc.). Research should also be carried

Towards an Effective ICT-Based University Learning

out on how information and communication is managed and delivered, and how these new teaching roles can be combined with the traditional role of knowledge provider. Third, another field for future research is how the effective use of ICTs depends on subjects and disciplines, because the mastery of the essential knowledge of each discipline is tacit rather than explicit, undetermined not planned. Finally, universities, as the main higher education organizations in an increasing period of individuality and distance human communication, need to reflect upon the importance of the socially-based interactive human relations as strategic elements for the growing complexities in the transfer and diffusion of advanced knowledge.

CONCLUSION Generally, the chapter has shown the potentials and the limitations of using ICTs in university adult teaching. On the basis of an analysis of two young universities in Spain, a conventional public University (URV) and an e-learning distance University (UOC), it has been argued that face-to-face interaction and communication is still a very important dimension for adult learning, particularly for the tacit dimension of learning and teaching. The use of ICTs for university adult education is in its first stages of development. However as more adult and university educators are experimenting with ICTs, more and more positive complementarities are being found and they are gradually becoming integrated into teaching processes. The following specific conclusions have been drawn. First, the chapter has argued that the current technological changes pose important challenges to adult learning principles. In this respect, good management of information and codified knowledge by appropriate ICTs can improve the learning abilities of adults in two main ways: a) the time saved can be used for face-to face interaction in which adults can show their full capacity

for learning; and b) input can be provided to help them reflect upon their life experiences. Second, the chapter has highlighted various factors that should be taken into account if ICTs are to be strategically used for university adult learning (for example, university subjects, distinctions between codified knowledge and tacit knowledge, open versus private educational software). Beyond the general distinction between technical and non-technical sciences, greater efforts should be made to adapt ICTs to specific subjects and disciplines. Third, the increasing use of ICTs by universities has had the positive side-effect of helping to differentiate between information and knowledge. In this respect, it has facilitated the process of making the tacit dimensions of learning and teaching more evident, and thus revealed the need to take the tacit and interactive dimension into account in the organization of adult teaching and learning.

REFERENCES Ahedo, M. (2009). Comparing the Principles of Adult Learning with Traditional Pedagogical Teaching in Relation to the Use of Technology: The Tacit Dimension of ICT-based University Teaching. International Journal of Web-Based Learning and Teaching Technologies, 4(4), 66–81. Antonocopoulou, E., Jarvis, P., Andersen, V., Elkjaer, B., & Hoyrup, S. (Eds.). (2006). Learning, working and living. London: Palgrave Macmillan. Apps, J. W. (1988). Higher education in a learning society. Meeting new demands for education and training. San Francisco: Jossey-Bass. Ashwin, P. (2006). Changing higher education: the development of learning and teaching. London: Routledge.

329

Towards an Effective ICT-Based University Learning

Barrat-Esteve, J., Franquet-Sugrañes, T., Giménez-Costa, A., González-Bondia, A., Jaria i Manzano, J., Marquès i Banqué, M., & Martí-Baiget, M. (2007). “El diseño de una comunidad virtual como estrategia de adaptación del profesorado a los postulados docentes del EEES” (The design of a virtual community as strategy to adopt teachers to the objectives of the European Higher Educational Space). In D. García-San José (Ed.), Innovación docente y calidad en la enseñanza de ciencias jurídicas en el espacio europeo de educación superior (Pedagogy innovation and quality of Law Science teaching in the European Higher Educational Space) (pp.171-200). España: Ediciones Laborum. Barry, J. H. (1999). Lifelong learning in late modernity: The challenges to society, organizations, and individuals. Adult Education Quarterly, 49(2), 79–90. doi:10.1177/074171369904900201 Biggs, J. B. (2003). Teaching for quality learning at university: what the student does (2nd ed.). Buckingham: Society for Research into Higher Education. Boud, D. (2000). Sustainable assessment: rethinking assessment for the learning society. Studies in Continuing Education, 22(2), 151–167. doi:10.1080/713695728 Boud, D., Keogh, R., & Walker, D. (Eds.). (1985). Reflection: Turning experience into learning. London: Kogan Page. Bourdieu, P. (1977). Outline of a theory of practice. New York: Cambridge University Press. Burbules, N. C. (2008). Tacit teaching. Educational Philosophy and Theory, 40(5), 666–677. doi:10.1111/j.1469-5812.2008.00453.x Castells, M. (1997). The rise of the network society. London: Routledge.

330

Cochran-Smith, P. M., Feiman-Nemser, S., & McIntyre, D. J. (Eds.). (2008). Handbook of research on teacher education: enduring questions in changing contexts. London: Routledge. Coffield, F. (2000). Differing visions of a learning society. Research findings (Vol. 1). London: The Policy Press. Dewey, J. (1933). How we think: a restatement of the relation of reflective thinking to the educative process. In J. A. Boydston (Ed.), (1986) The latter works (pp. 105-325). Southern Illinois University Press. Durrance, B. (1998). Some explicit thoughts on tacit learning. Training & Development, 52(12), 24–29. European Commission. (2008). The use of ICT to support innovation and lifelong learning for all - A report on progress. Brussels: Commission of the European Communities. Fischer, G. (2001). Lifelong learning and its support with new media. In Smelser, N. J., & Baltes, P. B. (Eds.), International encyclopedia of social and behavioral sciences (pp. 8836–8840). New York: Elsevier. Fry, H., Ketteridge, S., & Marshall, S. (Eds.). (2009). A handbook for teaching and learning in higher education: enhancing academic practice (3rd ed.). London: Taylor & Francis. Garfinkel, H. (1967). Studies in Ethnomethodology. Englewod Cliffs. Prentice Hall. Garrison, D. R., & Anderson, T. (2003). Elearning in the 21st century: a framework for research and practice. London: Routledge. doi:10.4324/9780203166093 Giménez-Costa, A., & González-Bondia, A. (2007). Design of a wiki-based collaborative working strategy within the context of legal sciences. European Journal of Legal Education, 4(1), 105–114.

Towards an Effective ICT-Based University Learning

Goodman, P. S. (2002). Technology enhanced learning: opportunities for change. Mahwah, NJ: Lawrence Erlbaum Associates.

Light, G., & Cox, R. (Eds.). (2001). Learning and teaching in higher education: the reflective professional. London: Routledge.

Gorard, S., & Selwyn, N. (1999). Switching on the learning society? - questioning the role of technology in widening participation in lifelong learning. Journal of Education Policy, 14(5), 523–534. doi:10.1080/026809399286198

Lundberg, J., Castillo, D., & Dahmani, M. (2008). “Do online students perform better than face-toface students? Reflections and a short review of some empirical findings”. In “The Economics of E-learning” - Revista de Universidad y Sociedad del Conocimiento (RUSC).1 (5) UOC. Retrieved May 27, 2009, from http://www.uoc.edu/rusc/5/1/ dt /eng/lundberg_castillo_dahmani.pdf

Hillier, Y. (2005). Reflective teaching in further and adult education (2nd ed.). London: Continuum. Horyp, S. (2006). Reflection in learning at work. In Antonocopoulou, E., Jarvis, P., Andersen, V., Elkjaer, B., & Hoyrup, S. (Eds.), Learning, working and living (pp. 85–100). London: Palgrave Macmillan. Howard, C., Schenk, K., & Discenza, R. (2003). Distance Learning and university effectiveness: changing educational paradigms for online learning. Long Beach, USA: IGI Global. Jarvis, P. (2000). Globalisation, the learning society and comparative education. Comparative Education, 36(23), 343–355. doi:10.1080/713656613 Jarvis, P., & Parker, S. (Eds.). (2005). Human learning: a holistic approach. London: Routledge. doi:10.4324/9780203463321 Katz, R. N. (Ed.). (1999). Dancing with the devil: information technology and the new competition in higher education. San Francisco: Jossey-Bass Higher and Adult Education Series. Knowles, M. S. (1980). The modern practice of adult education: From pedagogy to andragogy (2nd ed.). New York: Cambridge Books. Laurillard, P. D. (1993). Rethinking university teaching. A framework for the effective use of educational technology. London: Routledge.

MacKenzie, D., & Wacjman, J. (Eds.). (1985). The social shaping of technology. London: Open University Press. Merriam, S. B., & Cafarella, R. S. (1999). Learning in adulthood: a comprehensive guide (2nd ed.). San Francisco: Jossey-Bass. Naidu, S. (Ed.). (2003). Learning & Teaching with Technology: Principles and Practices. Open and Distance Learning Series. London: Routledge. OECD. (2005). E-learning in tertiary education. Where do we stand?Paris: OECD Publications. Pelgrum, W. J., & Anderson, R. E. (Eds.). (1999). ICT and the emerging paradigm for lifelong learning. Amsterdam: IEA. Pratt, D. D. (1998). Five perspectives on teaching in adult and higher education. Melbourne: Krieger Publishing. Qvotrup, L. (2006). Knowledge, education and learning. E-learning in the knowledge society. Frederiksberg, Denmark: Samfudsliteratur Roskilde Universitets Forlag. Reyes, A., & Zarama, A. (1998). The process of embodying distinctions. A re-construction of the process of learning. Cybernetics & Human Knowing, 5(3), 19–33. Rogers, A. (2002). Teaching adults (3rd ed.). London: Open University Press.

331

Towards an Effective ICT-Based University Learning

Sangrá, A. (2002). A new learning model for the information and knowledge society: The case of the Universitat Oberta de Catalunya (UOC). The International Review of Research in Open and Distance Learning, 2(2). Retrieved March 31, 2009, from http://www.irrodl.org/index .php/irrodl/article/view/55/114 Sangrá, A., & González-Sanmamed, M. (Eds.). (2004a). La transformación de las universidades a través de las TIC: discursos y prácticas (University changes through ICTs: discourses and practices). Barcelona: UOC. Sangrá, A., & González-Sanmamed, M. (2004b). “El profesorado universitario y las TIC: redefinir roles y competencias” (University teachers and the ICTs: redefining roles and competences). In Sangrá, A., & González-Sanmamed, M. (Eds.), La transformación de las universidades a través de las TIC: discursos y practices (University changes through ICTs: discourses and practices (pp. 79–80). Barcelona: UOC. Schatzki, T. R., Knorr-Cetina, K., & Von Savigny, E. (Eds.). (2001). The practice turn in contemporary theory. London: Routledge. Schön, D. A. (1983). The reflective practitioner. How professionals think in action. New York: Basic Books. Schön, D. A. (1987). Educating the reflective practitioner. Toward a new design for teaching and learning of professions. San Francisco: Jossey-Bass. Searle, J. (1995). The construction of social reality. New York: Penguin Books. Stehr, N. (1994). Knowledge societies. The Transformation of labor, property and knowledge in contemporary society. London: Sage.

332

Sternberg, R. J., & Horvath, J. (Eds.). (1999). Tacit knowledge in professional practice: Researcher and practitioner perspectives. Mahwah, NJ: Erlbaum. Sternberg, R. J., & Wagner, R. K. (Eds.). (1986). Practical intelligence. Cambridge: Cambridge University Press. Tait, A., & Mills, R. (1999). The convergence between conventional and distance education. London: Routledge. Varela, F., Thompson, E., & Rosch, E. (Eds.). (1993). The embodied mind. Cambridge: the MIT Press. Von Forrester, H. (1984). Observing systems. Salinas: Intersystems Publications. Watson, D. (2001). Pedagogy before technology: re-thinking the relationship between ICT and teaching. Education and Information Technologies, 6(4), 266–266. Webster, F. (1995). Theories of the information society. London: Routledge. World Bank. (2003). Constructing knowledge societies: new challenges for tertiary education. Washington, D.C.: The Word Bank. Yang, B. (2003). Toward a holistic theory of knowledge and adult learning. Human Resource Development Review, 2(2), 106–129. doi:10.1177/1534484303002002002 Young, M. F. D. (1998). The curriculum of the future. From the “new sociology of education” to a critical theory of learning. London: Falmer Press. Ziemlewski, J. (2009, February). Chemical engineering progress. In Bulletin of the American Institute of Chemical Engineers (AiCHE).

333

Chapter 19

What Can We Learn from the Past about Future Technological Trends in Adult Education? John K. Hope University of Auckland, New Zealand

ABSTRACT The purpose of this chapter is to examine the past two decades of technology use in adult education with the intention of providing a critical lens with which to view future technological trends in adult education. The article begins with a brief summary of technological trends, such as the introduction of the Internet and the World Wide Web, that have influenced adult education over the past two decades. Political, economic, social, and pedagogical issues that have influenced the use of technology in adult education are also discussed and possible solutions to these issues are outlined. The article concludes with an attempt to extrapolate future technological trends that could influence the direction of adult education in the decade to come.

INTRODUCTION Knowles 1970s prediction that adult education would be delivered electronically in the 21st century has proved spectacularly accurate. Thirty years later potential adult learners have a bewildering plethora of electronic delivery options available at the touch of a keyboard. Almost all adult educators use distance technology in one form or another and most are either involved with electronic delivery systems, or are contemplating such. Yet traditional

face-to-face delivery methods survive alongside the new technological innovations and are likely to continue in the foreseeable future. Just as the invention of the computer and, more latterly, the widespread availability of the Internet, changed the face of the adult education at the end of the 20th century, recent dramatic changes in the political, social, educational and economic systems of the world could stimulate new trends in adult education that will once again change its visible face in directions that as yet, we know not. This article attempts to analyse the past and extrapolate

DOI: 10.4018/978-1-60960-153-9.ch019 Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

What Can We Learn from the Past about Future Technological Trends in Adult Education?

technological trends that will help us plan for an exciting but, uncertain, future in adult education.

BACKGROUND At the time of completing this chapter in early 2010, the last two decades encompassed the period from the late 1980s until the present. What significant technological developments influenced adult education during that that time? Most readers of this book will have been involved with education in some form during the last two decades of the twentieth century, as either student or teacher. It is likely that most adult educators would recall that use of educational technology in the form of a computer was minimal, being confined to a small group of “early adopters” (Jones, Kirkup, & Kirkwood, 1993) who had access to mainframe computers, or very early purchasers of desktop personal computers mainly used for word processing. In the late 1980s most adult education was hard copy print based (Bates, 1993). Some institutions were experimenting with live audio and video technology (Isenberg, 2007), television (Bates, 1993) and institutions such as Jutland Open University in Denmark investing hugely in teleconferencing (Jones et al., 1993), but these institutions were the exception rather than the rule (Moore, 1995). Over the last one hundred and seventy years since the recorded inception of adult education, technological innovation was generally limited to print innovations. In 1981 the IBM PC arrived (Olle, 2004), allowing the decentralisation of computer terminals linked to mainframe computers to stand-alone desktop devices. The widespread and extremely rapid of uptake of personal computers in the 1980s and 1990s (Kodama, 2008) was one of the most significant technological developments of that period. Most adult learners, being by definition more mature learners rather than younger computer whiz kids, were not the earliest adopters of the new computer

334

technological aids but the convenience of word processing with it’s simplified editing of written text on a personal computer, available in the home, led to rapid growth in computer use by both adult learners and their teachers. The enhanced convenience of a less significant but, still important technological leap, the invention and mass marketing of the laptop computer, was not lost on adult educators and students either. First developed for the space shuttle programme in 1979 but not mass marketed until Compaq launched their laptop in 1988 and Apple launched the first Mac laptop in 1989 (Roseberry, n.d.), the laptop was, until 2009, the computing tool of first choice for most people on the move. By its portable nature, the laptop computer helped bring home, workplace and tertiary institution together rather than having students limited to using computer laboratories in tertiary institutions. Writing associated with an adult learning programme could continue regardless of location, a major incentive for busy adult learners to trying to pursue their education while working and running a family. Intensive expansion and innovation in adult education e-learning through the late 1980s and 1990s was the result of the PC and later laptop introduction, leading to a subtle but profound paradigm shift in not only the design and delivery of education, but also in the very nature of learning (Harasim, 2006). The most significant new technological development in adult education during the years of the review period must surely be the move from purely experimental use of the Internet up to the late 1980s to its public launch in 1989, use by learning organisations in the early 1990s (Leiner, Cerf, Clark, Kahn, Kleinrock, Lynch, et al., 2003) and its widespread adoption for educative purposes during the past decade. The electronic campus became the virtual campus; geographic proximity no longer limiting the linking of electronic devices. Physical distance barriers to adult education were instantly removed, equity of access to adult education enhanced and the widespread

What Can We Learn from the Past about Future Technological Trends in Adult Education?

availability of the World Wide Web from its inception in 1990 (Berners-Lee & Mark, 1999) meant that the knowledge of the world became available to any who could purchase and connect to the technology. Such was the impact of this technological leap that use of information and communication technology (ICT) and the more contemporary term e-learning were seen by adult educators in many developed countries as the “technological fix” for adult education (Selwyn, Gorard, & Furlong, 2006). Electronic campuses, meaning electronically linked departments via ethernets within one physical institution, were in vogue in the late 1980s and 1990s (Gardner, 1989), but of more significance to this article was the launch of the first totally on-line adult education course in 1981, followed by the launch of the first large scale, on-line learning institution in 1989, the Open University in the United Kingdom (Harasim, 2006). As is often the case with very new technology, the first on-line courses were disasters. There were no pedagogical models to follow and the technical problems associated with using ancient 48K Apple II computers and the first generations of Powerbooks linked to early, slow modems deterred all but the most enthusiastic (Feenberg, 1993). Explosive growth in the provision of distance education for adult learners (Johnson, 2003) was a predictable outcome from the moment that widespread, cheap and efficient electronic communication via the Internet became available. Rather than having the immediate, geographical area as a catchment for recruitment of potential adult learners, or expensive and slow, paper-based mail-out recruitment to more distant areas, educational institutions could inexpensively advertise their programmes almost anywhere on the globe, and they did. The English Open University, one of the “early adopter” universities to offer distance education to adults grew from 70,000 paper-based distance students in the 1980s to more than 180,000 electronically linked students in 2008 (Open University, 2009). The percentage

of U.S.-based institutions using Internet-based learning technologies tripled between 1994–5 and 1997–8 (NCES, 2000) and other developed countries rapidly followed suit. Growth of electronic learning is such that in 2009 it would be difficult to find an educational institution in a developed country that did not include at least some Internetbased courses within its adult education offerings. The ultimate expression of the influence of the Internet and World Wide Web in 2010 can be seen by the growing list of virtual universities in first and, more recently, particularly in previously less developed countries such as India, many catering for adult students; all distinguishable in that they have no physical campus because all courses are offered on-line. Explosive growth does not occur without reason. Internet-based technological innovations have been widely adopted within adult education because ICT offers a number of potential advantages for adult educators. Frequently touted advantages include broadening the provision of adult education into new fields, extending participation to more marginalised learners and improving educational outcomes. But these potential benefits have been mitigated by wider issues. These issues will be the focus of the next section of this chapter.

TECHNOLOGICAL TRENDS IN THE FUTURE AND THEIR IMPLICATIONS FOR ADULT EDUCATION Any academic able to accurately predict technological trends in the future would be unlikely to waste their time writing book chapters, they would be far better employed investing their own money in lucrative technological innovations or, at the least, being first to implement the innovation within their own institution. Future prediction is known to be an inexact science, well demonstrated by the inaccuracy of some future predictions, particularly when new technological

335

What Can We Learn from the Past about Future Technological Trends in Adult Education?

inventions are the subject. One example of many that are available from the public school system will suffice. Between 1950 and 1959, television ownership in the United States soared from 10% to 90% (Putnam, 1995), leading to confident 1950s predictions that educational television would be the dominant form of technology used in education. With 50 million dollar backing from the Ford Foundation and Congress, a plane was commissioned to circle above the Midwest beaming educational television to six states. Finding that classroom uptake was only 2– 4%, the plane was grounded (Tyack & Cuban, 1995). There was and, still is, some use of educational television, but the domination of educational television that was so confidently predicted and expensively funded, did not happen. The same can be said for use of radio, film and video in education, limited uptake and no golden bullet solution to educational problems. Unlike its television predecessor, the personal computer, and particularly the almost universal availability of the Internet, has fulfilled the touted potential of changing the face of adult education, but their implementation has introduced other problems. Widespread implementation of the Internet has introduced issues such as hacking that were unheard of when earlier educational technology was in use. Examination of the technologically based issues confronting adult educators today may offer glimpses of potential solutions for the future. A selection of political, economic, social and pedagogical issues that some see as having an influence on adult education will be presented in the next section, followed by an attempt to confront the inexact science of predicting the near future, that of the next decade.

Issues, Controversies, Problems It is said that optimists see opportunities where pessimists see problems. The next section of this chapter discusses current technologically based

336

issues for adult education but in so doing, also notes the future opportunities that may accompany the issue.

Political Issues Internal, regional and international political issues all have potential to impact on the technological provision of adult education. Western democracies traditionally lurch between left and right over time, often with consequent change to funding and direction for adult education. Examples include national provision of new technology such as high end broadband capability to educational institutions, and policy directives regarding use of technology to address the ‘digital divide’ (limitations of access to technology-based education for disadvantaged groups). International examples of governmental policy shifts for adult education oriented technological progress include tax incentives for ICT purchases in Hungary, government funding for the provision of ICT based adult education to targeted groups in Italy, provision of virtual schools in Finland (Pont & Sweet, 2006) and installation of broadband capability for educational institutions in New Zealand. Evidence of the internationalisation of education can be seen in countries such as China, India and Malaysia that were previously exporters of adult students now becoming or, about to become, net importers of international students. New political forces have emerged, such as the BRIC axis (Brazil, Russia, India, China), where major investment in technological development, often supported by adult education programmes, has generated a new force in world politics. Politically motivated international and domestic terrorism by individuals and groups in countries as diverse as Afghanistan, Iraq and the United States has resulted in reluctance by some to physically attend public educational institutions or to travel to providers of adult education in countries deemed unsafe. Politically inspired visa restrictions have also begun to limit physical movement between

What Can We Learn from the Past about Future Technological Trends in Adult Education?

some countries. The recent emergence of politically or morally inspired censorship of access to the Internet in countries such as China and the United States has limited access for some adult students to Web sites deemed a threat to moral standards or the ruling authority and, in turn, has become a threat to wider uptake of electronically mediated adult education. Economic issues will be discussed in the next section, but protectionism and ultra-nationalism are political issues often arising from economic downturns, as may occur when the global economy confronted a major economic downturn in 2009. Malaysia, for many years a provider of thousands of government scholarships for Malaysian students to study abroad, has recently re-allocated all but a few of these scholarships to local universities, the remaining transnational scholarships being limited to students gaining entry to the very highest ranked universities such as Harvard and Oxford. Some international markets for adult education by distance may be closed to external providers in such circumstances, but that correspondingly provides an opportunity for domestic providers of adult education to pick up where international providers have been excluded.

Economic Issues Economic issues have had a major impact on adult education in the past ten years and are likely to have even greater impact in the future. Widespread utilisation of ICT’s has increased the rate of globalisation with consequent economic impact, both positive and negative, on many domestic economies. Competition from other countries drives the need for better skilled workers who can compete on a global scale, in turn creating a need for more commercially and internationally oriented adult education programmes. This trend is seen as a potential narrowing of adult education (Selwyn et al., 2006) to vocationally oriented skill training with a consequent reduction in broader adult education provision.

Rapid escalation in oil-based fuel costs has resulted in sky rocketing international fuel surcharges being imposed that can limit the ability of adult international students to travel to other countries to further their education, but also provides a consequent rise in demand for electronic delivery of coursework. Adult educators are not spared either, rising fuel costs encouraging more use of electronic communication for conferences and meetings, in place of face to face gatherings. Of greater concern for adult education is the so-called credit squeeze that, at the time of writing, has the potential to have a greater economic impact than any other issue in the era being addressed in this chapter. As has occurred in several European countries during 2010, serious budget deficits stop growth, reduce spending, increase unemployment and have the potential to increase protectionism and sharing of economically sensitive information. Adult education, being traditionally seen by some as of lower priority than compulsory schooling, can suffer massive budget cuts or be directed toward outcomes that have immediate commercial application rather than wider educational merit. A positivist view of the outcome of the global credit squeeze is that it provides an added incentive for the provision of electronically mediated adult education, a view addressed in a later section of this chapter.

Social Issues Economic issues often create social issues that, in turn, impact on adult education. Social issues that have emerged in the last ten years include increasing limitations on the time available for adult education students to address their continuing education needs. Longer working hours, working spouses and partners, and an increasing emphasis on leisure are social changes that have the potential to limit participation in adult education, but also create an opportunity for electronic delivery methodology to supplant face to face delivery that involves time consuming travel. Those who live

337

What Can We Learn from the Past about Future Technological Trends in Adult Education?

within large cities increasingly experience traffic deadlock that can limit their ability to travel relatively short distances to an educational institution in a timely manner. In contrast, longer life spans in many countries create a larger pool of retired workers who have free time and want to continue learning for health, leisure, or social reasons, but also to fulfil life dreams of an education that was thwarted in earlier years for cultural, economic or family reasons. Growth in electronic communication forums dedicated to those more senior in years, such as SeniorNet, have introduced a new generation of learners to electronic communication and, in turn, generated opportunities for Internet-based adult education provision to a group not previously targetted (O’Day, Ito, Adler, Linde, & Mynatt, 2006). Unemployment can limit the financial capacity of those so affected to enrol in adult education but unemployment, or employment insecurity, can also generate the motivation to obtain better education qualifications that may improve the chance of further employment. Future unemployed workers may look to electronic delivery of courses as a more cost-efficient alternative delivery method and governments may look toward funding targeted adult education programmes to provide a form of work for the unemployed by enhancing workplace skills. Other rapidly emerging trends within adult education include issues related to the conservation movement, sometimes termed “the greening of the adult education academy” (Taylor, 2006). Eco-sensitive adults are more aware of their carbon footprints and may be less inclined to travel overseas to further education, or may want to limit use of paper-based print technologies to save forests, so they turn to electronic delivery mechanisms that are seen as more eco-friendly. In countries emerging from the third world, a new wave of upwardly mobile adults who are ICT literate and have been denied chosen educational opportunities earlier in their lives may also turn to electronic adult education to meet their

338

adult learning needs. Some developed countries, such as Italy, must confront declining birth rates generated by lifestyle choices and economic circumstances. Japan is facing a predicted decline of up to 100,000 tertiary students during the next decade, with consequent closure, or merger, of tertiary institutions. Many of those institutions deliver adult education, so may turn to electronic, distance-based education to replace their declining domestic student enrolments.

Pedagogical Issues Pedagogical issues that have, or are likely to impact on adult education in the near future include the emergence of Mandarin to challenge the domination of English as the chosen Internet language of choice in the world. Internet traffic in Mandarin is likely to surpass Internet traffic in English in the near future (Riley, 2008) yet almost all of the adult education research literature is written in English. Electronic translation methodologies offer adult educators possible solutions to this issue, and to the likely emergence of other languages becoming better represented in net traffic, but translation technology is still in its infancy and is often subject to questionable accuracy of interpretation (Hung, Chen, & Wong, 2006). In addition to languages other than English having a greater presence in electronic communication, the era under discussion has seen greater awareness of Islamic educational methodologies. On-line adult education is tightly regulated but does exist in Islamic countries, particularly in the moderate Islamic countries such as Malaysia (McCarty, Ibrahim, Sedunov, & Sharma, 2006). Immigration, refugee flows and economic drivers of international mobility have created new pools of potential Islamic adult learners in non-Islamic countries and, in doing so, raised awareness in destination countries of religiously sourced pedagogies different from indigenous pedagogies. Similarly, greater movement of people from countries with varying Asian pedagogies has

What Can We Learn from the Past about Future Technological Trends in Adult Education?

created more awareness in destination countries of differing perceptions of appropriate learning styles. Adult students who have received their childhood education using transmitive pedagogies focussed more on direct instruction, and whose only experience of assessment has been examinations with a focus on memorisation and recall, may struggle to adapt to contemporary Western pedagogies that are often more focussed on critique, synthesis, and formative assessment. A student raised in some Eastern countries may be taught never to challenge their teacher as this would be a mark of disrespect. The same student in a Western educational environment will have difficulty when asked to critique a work by an academic “superior” because it would be a mark of disrespect to criticise. The challenge for adult educators is to bridge this pedagogical gap, with ICT having an important role in providing personal tutorial support to bridge pedagogical differences. Computer skills are now a critical necessity for students pursuing adult education programmes in most countries, particularly where net-based distance methodologies are utilised. Adult students were most likely to have had some experience with computers if they attended compulsory education in childhood within the last thirty years, so the generations of adult learners who lack computer skills, because they engaged in their compulsory education in pre-computer years, are becoming smaller every year. Many of those that did not obtain computer skills during their compulsory schooling have gained computer skills through their employment, or from pursuing recreational and personal interests, so the number of adult students who need basic computer skills is reducing every year. Of more pertinence to this discussion is the nature and quality of their computer skills. Many adult students have missing skill sets, searching academic databases being one skill set and learning to discriminate between the qualities of different sources of data being another.

Technical Issues All users of modern technology know that technical issues can be a problem, often unexpectedly. An example of a serendipitous technical issue was found when a New Zealand university set up a distance education, adult learning programme in remote farming areas of New Zealand. Adult students studying in their homes in one area were experiencing unexplained, random network crashes that the technical support staff could not solve. The solution was found to be voltage drops caused by sheep farmers turning on electric fences in a remote area where mains power supply was tenuous at best. Technical problems such as these can be accentuated in less developed countries with non-existent or uncertain electricity supplies, where technical support is often unavailable and the technology in use is of earlier vintage. A technical issue that annoys most adult learners is unsolicited electronic spam, that can even elude state of the art anti-spam programmes. The spam that gets through is a minor irritant only requiring use of the delete button, but the more insidious unsolicited and unwanted arrival is the electronic virus. Discontented student hackers can sometimes infiltrate adult learning programme computer servers with the consequence that adult learners wherever in the world become infected too. An adult learner who is completing their studies part-time while maintaining a busy lifestyle, but is not a confident user of ICT and is removed from immediate technical expertise support, may lack the technical knowledge to protect their computer system so can lose data and, at the least, lose their motivation to continue when these technical issues strike. Electronic plagiarism is a recent and unwelcome visitor to adult education programmes. When adult education was paper-based, copying of unacknowledged material was laborious, relatively simple to detect and consequently infrequent. The availability of the world’s net-sourced literature in the home at the touch of a keystroke increases

339

What Can We Learn from the Past about Future Technological Trends in Adult Education?

the temptation to plagiarise. The convenience of technology assisted searching followed by “copy and paste” also simplifies the process. Some adult learners remain unaware of the importance of acknowledging sources and will plagiarise innocently, others come from an education background where plagiarism is not considered as much of an issue as in most developed countries. In pre-computer years, cheating was limited to unlawful strategies such as paying someone to write essays or copying essays from students studying in previous years, all dangerous and difficult to attempt. The net-based adult learner of today will receive unsolicited e-mail offering to provide bogus degrees, ready written essays for popular courses, and offers to provide customwritten assignments for a fee. Cheating has become easier and the pressure to acquire qualifications in contemporary society provides the motivation for some to cheat.

Lessons from the Past and Future Trends Past and present issues are relatively simple to list, future solutions are less so. Some issues as yet have no solutions, others have partial solutions; some have potential solutions that have yet to be tested, others have been solved. This section will address a selection of the issues raised in the previous section and introduce some newer forms of technology that are beginning to be used, or have potential for future use, in adult education.

Political Solutions Political issues cannot usually be solved by adult educators. War, terrorism, protectionism and ultra-nationalism all pose threats to adult education, but also provide opportunities for more electronic delivery to those most affected by these issues. Potential students in countries vulnerable to such problems are not usually able to travel to other countries for their education so will seek

340

options at home. International concerns are such that the United Nations General Assembly held a special session in 2009 to debate the crucial role of education in national emergencies and post-crisis situations. Home based education, whether for security, or nationalistic reasons, is an opportunity for domestic distance providers, or, where approved, international distance education providers, to establish programmes within the political environment of countries in crisis. Web censorship is a threat more difficult to counter but it is the much maligned hackers who sometimes find unofficial electronic fixes for state censorship of the Web, that ultimately lead to easing of difficult to police Web restrictions. In the longer term, hunger for knowledge is a powerful motivator such that popular opinion can influence unpopular political policy. Adult educators would be advised to constantly look to take advantage of government policy shifts in broader technical areas that could have application in their own industry. Examples of policy shifts likely to increasingly occur in the future are economically inspired adult education courses provided to upgrade the employment-related skills of the recently unemployed and technical measures to address digital divides of various kinds such as poverty, gender, race and class discrimination.. Adult education workforce skill upgrade opportunities are likely outcomes from the global economic difficulties of 2009, either to keep those unemployed in constructive activity, or to develop new skills more appropriate to the more competitive business environment generated by the economic downturn. The good news for adult educators working internationally when the global economy recovery begins is that the internationalisation of education, technology and trade is an economically generated political force likely to continue in the longer term, and this political force should be seen as an opportunity by all providers of adult education. An example of this trend in the midst of the economic downturn is a major move by UNESCO, initiated by China, to promote

What Can We Learn from the Past about Future Technological Trends in Adult Education?

multilinguism by developing an international cyber network for learning languages (UNESCO Institute for Statistics, 2009).

Economic Solutions Transnational education is rapidly growing where economic drivers are encouraging technologically advanced countries such as Denmark to request tertiary students to include an international component within their tertiary education. Tertiary enrolments of students from less developed countries seeking education in middle income countries have increased by 77% in the past decade (UNESCO Institute for Statistics, 2005), many of those enrolling being adult learners. Globalisation will require more workers to have international experience, forcing adult learners to go off-shore using electronic technology to meet the employment requirements of the global order. Adult learners paying for their education themselves will be increasingly likely to Google the world in their efforts to source the cheapest and highest quality provider of distance education to meet their learning requirements. Boom and bust economies can have a marked influence on adult education take up. The recent credit squeeze knocked trillions of dollars off the stock exchange and left old age pensioners bereft of their life savings. Dire predictions of declining numbers of tertiary students, particularly international students, were frequently heard in the latter part of 2008. However, the positivists were proved correct. Both international and domestic student applications increased rather than declined, with many applicants being adult students wanting academic qualifications to enhance their employment opportunities or provide qualifications for entry into occupations that were perceived to more secure, such as teaching. The dotcom crash of the year 2000 and the more recent credit squeeze have eroded public confidence in business. Some confidence has been lost by revelations of illegal activity by

greedy entrepreneurs, and other by distrust of the “smoke and mirrors” technology systems that can mask signs of economic woe from the sight of investors. Many people have become suspicious of Web site promotional material, such as bogus qualifications, due to bitter experience, lack of user friendliness and lack of transparency. This applies as much to adult education as to business. Australia is confronting a major drop in international student enrolments driven by perceived, race-inspired attacks on international students, the result being closures of some tertiary institutions that provided lower level academic qualifications, often to adult learners. Urban (2008) sees Web 2.0 technologies helping to improve consumer trust by facilitating user control and ownership of data. Adult educators can provide a friendly Web presence and authentication of their material via provision of transparent and authentic information sharing, thereby developing a trusting relationship that will endure over time (Dennis & Wisely, 2008). Fisher and McKee (2008), commenting on reports indicating that since 1995, 25% of United States economic growth is the result of electronic network and information technologies at a cost of only 3% of GDP, suggest that cost benefits such as these are likely to continue in the future. When tertiary budgets are squeezed, cost effectiveness drives change. Despite the social and pedagogical advantages of electronic delivery of adult education that are evident to many academics, the economics of delivering more education to more students at what is perceived to be less cost, is attractive to those in politics. Electronic delivery may also be perceived as good preparation for the ‘real’ world of work and hence become a desirable economic goal. OECD surveys have established the importance of adult education for improved living standards and productivity. A 2005 report found that an equitable distribution of skills across the workforce had such a strong, positive impact on economic performance that it justified policies to address educational disadvantage for disadvan-

341

What Can We Learn from the Past about Future Technological Trends in Adult Education?

taged groups such as older adult learners. The pedagogical section below will address these solutions further.

Pedagogical Solutions The UNESCO statistical report noted above states that much of the improvement in education participation across the globe can be attributed to increased participation in adult education. For example, in the countries surveyed, the proportion of 35–44 year olds with less than primary education has decreased from 75% to 50% in eight years (UNESCO Institute for Statistics, 2005). Adult education via situated e-learning in the workplace is driven by economic factors but provides opportunities for adult educators to develop on-line pedagogies tailored to workplace needs and delivered in a manner sensitive to time and location constraints. Examples include greater use of formative assessment to increase feedback to learners struggling with new concepts and pedagogies or lacking in confidence. Continuous on-line assessment utilising electronic portfolios provides flexibility for students, limits the constraints of assessment fixed in time and place and assuages known issues for more mature learners such as exam anxiety. Generation X and Y adult learners can be encouraged into adult education by utilising their social networking skills and dispositions honed on Facebook, Twitter and the like. The developing cyberpedagogy or cybergogy will be based around collaborative learning models where learners construct their own learning in collaboration with other learners via various discussions, role playing and problem solving strategies (Luke, 2006) delivered on new and more creative software platforms such as Moodle. Most adult learners who have access to the Internet are unlikely to use it purely for educative purposes. The Internet has become the entertainment forum for many. Witness the phenomenal growth of the social interaction sites already described, such as Facebook and Twitter. Futur-

342

ists see the distinction between education and entertainment become increasingly difficult to define (Pauling, 2006), as in the virtual reality developments discussed later in this chapter. Facial recognition technological developments (Mitchener, 2008) are likely to make on-line communication more personal and allow, for better or for worse, interpretation of emotions during discussions. More importantly, facial recognition would help solve cheating problem that blight many on-line programmes by answering the question: who is it that is responding to these questions? One concern the has already surfaced is that facial recognition has the potential to be misused by cyber stalkers looking for attractive targets in chat groups but, equally, facial recognition has the potential to make it more difficult for cyber stalkers to make out they are someone other than in real life. Face to face synchronous communication, such as freely downloadable with Skype, offers cheap communication for those with a computer and screen mounted camera. Little used by adult educators, technologies such as Skype improve interactivity, student confidence and help educators tailor the content they are delivering to the needs of their students. Recent moves away from the hypertext language HTML that was used to develop the Web hold promise for adult educators. The semantic Web may not be fully developed until the end of the next decade (Warren, Davies, & Brown, 2008) but is a potential solution to some problems that adult educators experience, particularly when working across different cultures, languages and pedagogies. Differing interpretations of words and concepts can lead to misunderstandings that discriminate against learners working across cultures and languages. The previously quoted United Nations cyber linguistic initiative is one strategy that may assist in alleviating this problem. It took 75 years for fixed line phones to reach 50% of consumers but only twenty years for most people in western countries to own a cellular phone. Internet uptake in the United Kingdom

What Can We Learn from the Past about Future Technological Trends in Adult Education?

soared from 14% to 61% between 1999 and 2005 (Warren et al., 2008). New technologies, such as intuitive and collaborative Web 2.0 knowledge articulation processes, are showing even faster uptakes, at a pace never seen before (Warren et al., 2008). One particularly significant trend that can be expected to accelerate in the future is that of Web users increasingly designing their own content (Anderson & Stoneman, 2008), obvious examples being content sharing via blogs, shared knowledge creation on wikis or Wikipedia and the burgeoning plethora of social communication Web sites like Twitter, Facebook, MySpace, BeBo, Flickr, YouTube and the like. Asynchronous electronic social communication networks have great potential for use in adult education. In a personal communication a colleague at another university explained that she had set up an alternative Web presence on Facebook and now gets more hits on Facebook than on the official university Web site. An adult learner in an ICT foundation class (preparation programme for entry to university for adults who did not attain university entrance qualifications while in compulsory schooling) that I was teaching responded to my suggestion that she e-mail to herself some work she had written in my class. Her response was: it is much easier to copy and paste to my BeBo page. For many adult learners, Web-based social networks have become the repository for their tacit knowledge, personal knowledge they are willing to share (Marwick, 2001). When such knowledge becomes explicit via the Web site, it can be a rich, but as yet often little exploited, data source for learning communities within adult education programmes. Wikis, blogs and the like can exploit for educational purposes the Web networking and knowledge sharing characteristics of many of today’s adult learners. Kings, Davies, Verril, Aral, Bryniolfsson, and Alstyne (2008) suggests that future knowledge management systems will build on Web 2.0 type knowledge articulation processes such as those mentioned above because

they create a link between Web-based social recreational activity and shared learning. Wikis became available on the Internet in 1994 but widespread uptake only began in the new millennium. The best known wiki is Wikipedia, now one of the most often quoted sources of information by students. Wikipedia’s success comes from its open and interactive environment; anyone who has access to a Web browser can read it and add to it. The great attraction of wikis for adult educators is their use in collaborative learning models. Just as collaborative writing has made Wikipedia arguably the most used encyclopaedia of knowledge in the world, adult educators can create student groups where subtasks are delegated and the resultant work assembled electronically on the wiki. The resultant collaborative information resource is private to those who have access to the wiki allowing all those who take part to benefit from the collective research and expertise of the group. Blogs differ from wikis as the information contained therein is available to any who can access the appropriate Web site. Blog authors document in reverse chronological order their musings in an informal manner and the blog so created, being public, can encourage input from others. Adult educators have been slow to grasp the potential of blogs because blogs have tended to be the domain of the young, particularly those in secondary schools. More recently, blogging has also becoming the domain of the not so young and this trend can be expected to continue as the younger generations enter adult education. The potential of the personal narrative contained in many blogs is an opportunity deserving of more attention in adult education. Adult educator hesitancy in using blogs relates to their open nature, others can input and move the blog away from the educational objective, or it can degenerate when interpersonal issues are introduced. Despite these disadvantages, blogs are very popular with many students and can provide rich chronological data in much the way that diaries once did, so should

343

What Can We Learn from the Past about Future Technological Trends in Adult Education?

be considered by adult educators as another technological tool to improve learning. Portfolios of student work are now popular at tertiary level and the e-portfolio has particular relevance for adult education. E-portfolios are compilations of student work assembled electronically, so they can include videos, graphic work and creative art genre as well as traditional text information. An e-portfolio is usually private to the student and their tutor, but could include blogs as a valid information source contributing to the e-portfolio. Some futurists see a combination of the pedagogical and technological solutions briefly outlined above with the the traditional pedagogies of adult education being called blended learning. Inoue (2010) sees blended learning as an appropriate response to the increasing diversity of adult learners and web 2.0 developments facing the educators of today, and also as an interim step to the totally on-line environment of the future. Those who have participated in online discussion groups will appreciate that accommodating the diversity of study strategies, termed universalists, butterflies, changelings and minimalists in one study (Cornelius & Gordon, 2009), that current and future adult learners are likely to bring to blended adult education programmes, will require a flexibility of structure not commonly found in most contemporary adult education programmes. This implies that the adult educator of the future will be developing new, more flexible, and more individualised programmes, to meet changing learning needs.

Technological Solutions Most of us eventually buy the latest technological device. Apple says it sold three million iPads in the first 80 days of sales in the United States. Are there any adult educators left who do not have a cellular phone, use a computer or access the Web? Only the computer existed two decades ago and for many of us, a PC was still too expensive and

344

a laptop a dream. What is in store for us during the next decade? Mitchener (2008) sees more seamless, automatic, synchronous and numerous network connections, developments we would all applaud. Specific technological developments likely to occur include improved voice recognition as is now available in exotic cars, wider use of improved touch screens as on the Apple iPhone and even technology that could include physical movement as a learning tool. Physical movement capable software is already available in interactive gaming systems such as the physical swings of golf clubs or baseball bats on the popular computer game Wii. Rapid increases in memory storage capacity utilising physically smaller componentry, particularly through use of nanotechnology, is likely to increase the physical portability of technological devices and hence access for distance learners. Handheld mobile technology such as PDAs and mobile phones are increasingly merging into smartphones, always-connected Blackberrys and iPhones with their ready access to e-mail and Web on a handheld phone anywhere, anytime. Intelligent mobile devices allow lecturers and students to communicate asynchronously and cheaply by text or e-mail or synchronously by phone. Student to student and student to tutor text messaging (the correct term for text messaging is Short Messaging Service abbreviated on phones as SMS) to ask questions about coursework and share ideas, instant data recording while at work and recreation, capturing video clips for use in learning portfolios and using the in-built planner to keep track of assignment timelines are all examples of the technological applications currently in use by some adult educators (Dawson, 2007). 3G phones are common now, 4G phones with more seamless connectivity and roaming are most likely to be available within the next ten years (Dennis & Wisely, 2008). Improvements to batteries and greater use of intelligent alternative sources of electricity from sunlight, movement, sound and pressure changes are likely to create

What Can We Learn from the Past about Future Technological Trends in Adult Education?

opportunities for adult education by improving access to information and communication in less developed countries and isolated areas. Utilising these technological innovations, use of mobile technology in adult education, (termed m-learning), is likely to be one of the most promising developments for adult education in the next ten years. Student centred, anywhere, anytime adult education will increasingly be possible as sales of mobile smartphones, (Blackberries, iPhones and the like), overtake sales of computers across the globe (Cochran & Bateman, 2010). Top of the line smartphones now have many of the capabilities of multimedia computers so can link into web 2.0 social software and pedagogical affordances. Innovations such as the front mounted camera on the 2010 iPhone create opportunities for more personal learning conversation interactions. The frustration, shared by teaching staff members and students, arising from slow downloads is a major barrier to the uptake of distance education. More information sharing is required, more documents include graphic material and Web sites that increasingly incorporate video clips all slow downloads. The touted answer to this problem has been increased bandwidth. In many countries broadband has become the rule rather than the exception and in this case Asian countries are outstripping their Western counterparts (Payne, 2008). Increased bandwidth capacity is quickly soaked up driving demand for even more bandwidth that exceeds the capacity of copper wire technology to deliver. Fibre optic networks are now common on many campuses but any component of the network in use that is not an optical network will slow downloads. Similarly, information entering and leaving network nodes is slowed. New intelligent network technology that bypasses unnecessary nodes can also be expected to increase speed (Payne, 2008). Adult educators can expect to see more complete optical systems installed in the next ten years, including interconnectivity across regional and national boundaries (Wittgreffe, Dames, Clark, & McDonald, 2008)

that will, in turn, increase capacity to deliver more graphics-based and video based adult education programmes to more students. Storage technology has increased incrementally in the last five years. Most of us now use a $10 memory stick that can store everything that we have written in our lifetime. Memory sticks may soon have wireless capacity to enable them to talk to each other, allowing transfer of information anywhere, anytime from a small object around the neck, on a key ring or in a pocket, without being plugged into a computer (Pearson, 2008). With time pressures and transport problems driving increasing situated e-learning in the workplace instead of going to dedicated learning institutions, memory sticks that could communicate with each other would allow information transfer to occur over lunch or while working, without the need for a larger computer or smartphone. Replacement of expensive, technically demanding, distance delivery software packages such as WebCT and Blackboard with cheap and easy to use technologies such as Moodle will further simplify and facilitate delivery of adult education. Many potential students avoid on-line courses because they consider themselves technologically illiterate or sign up with trepidation only when there is no other option available to them. Tertiary educators who teach their courses on-line have come to expect calls asking whether IT qualifications are required to join the course, or “I have not done this before” comments indicating lack of confidence. Easy to use software packages give new distance learners confidence, are less likely to crash at critical moments and are designed to increase student to student, teacher to student and student to teacher communication. They are also easier for adult educators to use for the first time. Obtaining approval to purchase a new paperbased journal has become problematic in the author’s university; new journals must be electronic journals. Variously described as E-libraries or digital libraries, virtual libraries are reality, or

345

What Can We Learn from the Past about Future Technological Trends in Adult Education?

a partial reality, in many universities now. They provide an electronic interface between repositories of knowledge and learners individual needs that is more than the traditional index cards or electronic catalogues. Their unique feature is their ability to be searched using increasingly complex and inductive search engines to suit a learner’s individual needs. In doing so they support the newer pedagogies where learners construct their own learning, the remaining limitations being the learner’s technological literacy and the sophistication of the library search access (Brophy, 2006). Initially adopted to save expensive space needed for paper-based technology, virtual libraries are a boon for busy adult learners as they can completely obviate the need to attend a library in person. Journal and database searching is simplified and available from any keyboard, anywhere, anytime. Although electronic books are still not in vogue with many in adult education because they find reading a book on a screen odious, the increasing availability of electronic books combined with declining paper availability and cheapness, will force adoption. New electronic readers are becoming available that come closer to replicating the paper book. They still do not duplicate the physical page turning of a book, but can be read in bed or on the bus and are a great deal easier to transport in quantity. Solutions to the cheating and plagiarism issues have centred around use of products such as Turnitin and MyDropBox, effectively large databases of written works that allow comparison of student text with that written previously. New pedagogical strategies such as portfolio assessment raise new issues for the detection of illegal activity that are beyond the scope of existing electronic detection methods. As always, a technological problem breeds a technological solution and new open architecture systems are being developed that can detect plagiarism in other media such as graphics and even the audio component of podcasts (Butakov & Scherbinin, 2009).

346

Cyberspace was a term coined by a science fiction author in 1984, but it soon become reality and was being discussed as a potential medium for adult education in the early 1990s (Boyd, 1993). Virtual games are now commonplace, but their use in adult education less so. Technology enabled virtual worlds formed by the merger of Google Earth and virtual reality programmes like Second Life offer the ability to inhabit a virtual world via avatars “that will be at best a virtual representation of planet earth and at worst, the frighteningly deep and dark spaces of collective human consciousness without the shackles of convention surrounding an evolved society!” (Dennis & Wisely, 2008, p. 139). Virtual reality provides unique opportunities for adult education based on personal choice and decision-making. Its potential advantages are that it happens in no fixed physical place and involves communities of learners interacting and collaborating to solve problems in ways not possible within the real world (Burbules, 2006). Boyd (1993) saw application of virtual reality in adult education such as “gateways to other organisations’ cyberspace worlds to provide observations of people at work, and apprenticeship-internship situations” (p. 245). Fifteen years on that prediction is already reality. One early example is use of virtual reality adapted to teach humanistic subjects such as history. Virtual Harlem is a collaborative learning environment where students can learn about the history of Harlem via virtual reality, giving the impression of being there (Sosnoski, Jones, Carter, McAllister, Moeller, & Mir, 2006). In 2009, virtual reality must still be regarded as experimental, expensive and of limited availability, so its current use in adult education is still limited. Future use of virtual reality is likely to increase. Several universities have purchased ‘islands’ in Second Life and are experimenting with their use for adult education. Cautions have been expressed about the dark side of virtual reality mentioned by Dennis and Wisely above. Boon and Sinclair (2009) noted in their case study that unexpected

What Can We Learn from the Past about Future Technological Trends in Adult Education?

emotional and psychological effects to both students and lecturers were apparent when participating in Second Life virtual reality programmes, and also with social networking such as Facebook. To date, the research base addressing these issues is limited. Wider debate is urgently needed. This chapter began with a look at the technological past in adult education and there was mention of technology such as educational television that did not ever become mainstream. In contrast, strewn throughout the sections above are many examples of extremely rapid uptake of newer technology such as the Internet and its slightly slower, but nevertheless pervasive adaption for use in adult education. What of the future? Will we all be working as avatars in virtual reality scenarios?

FUTURE RESEARCH DIRECTIONS This essay has highlighted many examples of the ever increasing speed of technical change, change that generates the most persistent and pervasive technological issue within adult education. The world’s total knowledge doubles in ever shorter time frames and new products that have potential for application in adult education arrive regularly. How to keep up? Should we keep up? These questions beggar the real question, where is the research-based evidence in favour of improved pedagogy for each new technological tool? Two major research themes demand consideration, technological change and changes to the learning needs of adult learners. Technological change can happen much more quickly than the time required to develop a research base rigorous enough to analyse the applicability of new technologies for improved educational outcomes. Good research takes time and it often takes even longer to become available in published form. By the time research into the veracity of a new technology is readily available, there is a newer technology. This places the adult educator in a difficult position. Students are often early

adopters of new technology so look for courses utilising the latest technology, while lecturers tend to favour more conservative approaches. The moral high ground for the educator is to focus research on the pedagogy involved by posing the question, will it improve learning? Until that question is answered by sound, evidence-based research the adult educator is at risk of promoting a 90 day wonder that will go the way of educational television. The role of the teacher is clearly changing in the increasingly cyber oriented world of adult education. Zao, Lei, and Conway (2006) see the traditional teachers’ role as that of gatekeeper to knowledge, but the e-learning teachers’ role as more akin to that of a designer of technological strategies and a learning facilitator rather than an instructor. But what will the adult educator working on a virtual reality learning model need to know and be able to do? The technical scientists are often generously funded to complete the technical research needed to make new technologies commercially viable because there is a potential economic return. Funding for pedagogically-based research into the application of new technology in adult education is often less readily available, as is adult educator’s time to pursue the necessary research. In the course of writing this article, it has become clear that that there are a plethora of books devoted to the more abstract and theoretical issues within adult education but less devoted to applied research around the application of new technologies. Timely technological support when applying new technology can be difficult to come by. Does this new, technically oriented environment require the e-learning adult educator to acquire new technological skills, should adult educators work collaboratively with technical experts, or can they depend on on-line support services to solve pedagogical and technical issues? Current experience with new technologies suggests that immediate support for the baby boomer generation adult educator is never on-site when required, and

347

What Can We Learn from the Past about Future Technological Trends in Adult Education?

when the immediate problem is resolved another becomes apparent just after the technician has left the room, hung up the phone or terminated the link. The hope on the horizon is that the younger generation of more technologically savvy adult educators who have grown up with the internet and social networking will fare better. Pauling (2006) notes that Japanese researchers are working on hyper-reality models of learning, where reality and virtual reality blend at the whim of the learner and it becomes increasingly difficult to distinguish between what is real and what is virtual, such that it would be difficult to know if people are real or not, or even if they have human or artificial intelligence (Tiffen & Terashima, 2001). The new generations X, Y and Z adapt much more quickly, but how much more difficult will it be for all generations when they have to work with a completely new technical environment beyond their immediate experience, particularly if it becomes adopted as quickly as the Internet did? Future oriented research that attempts to define the knowledge, skills and dispositions required to link the pedagogical and technical requirements of future adult educators is not abundant but urgently needed. Issues such as how to manage the cognitive load generated by the increasingly multimedia web 2.0 technologies will require new research. Dissonance between learner task-specific expertise and instructional guidance occurs where experienced learners coming into adult education with advanced expertise about how to electronically access the available knowledge of the world meet an instructional environment more suited to the novice learner, termed the expertise reversal effect (Kalyuga, 2009). These learners will need a more flexible form of instructional guidance to ensure their continued engagement with learning than in the past. The generation X, Y and Z students of yesterday are the adult learners of tomorrow. These students will increasingly demand interactive, socially co-constructed knowledge development with which they have become accustomed in the web

348

2.0 environment in which they increasingly live, both socially and in their education (McLoughlin & Lee, 2010). Greenhow, Robelia and Hughes (2009) see these changes in student learning needs also requiring changes in academic scholarship. They outline an environment where participatory social scholarship utilising web 2.0 affordances facilitate connections between academics transnationally and across disparate disciplines. Dede (2009) takes this scenario even further, predicting newer forms of scholarly wisdom generated via the social networking capabilites of web 2.0. Technological and adult learner changes clearly demand changes in adult educator approaches. Early adopters tend to be enthusiasts, but it takes more than enthusiasm to attract many adult educators to newer forms of learning. Lecturers need to be given the information and opportunity to make new technological choices (Samarawickrema, Benson & Brack, 2010). This requires additional time for educators to probe the capabilities of new technologies and develop innovative learning programmes the better cater for the new demands of adult learners (Cochran and Bateman, 2010). Solutions and recommendations as outlined above are the personal views of the author. They are neither comprehensive nor inviolate but are intended to stimulate thought about an adult education future that becomes increasingly difficult to predict as the pace of technological change quickens. The overwhelming impression gained from the literature reviewed is that demand for adult education will continue to grow and the role of the adult educator and their students will continue to change with ever increasing momentum, due to societal changes and technological advances. For that we must be prepared as best we can.

CONCLUSION The audience laughed when Maxwell Smart used a shoe phone in the 1970s television comedy series Get Smart. Does any reader of this article not have

What Can We Learn from the Past about Future Technological Trends in Adult Education?

a mobile phone thirty years later? Kubrick and Clarke’s epic 1968 film, 2001: A Space Odyssey, showed astronauts using iPad like devices. History tells us that many technological developments that were initially in the realm of film and the experimental laboratory have become pervasive. It also tells us that some have not. Eastmond questions whether the experiences of the past, “can accurately navigate us through the future” (Eastmond, 2010, p. 304). It remains to be seen whether the newer technologies described above are adopted as mainstream tools for adult education, whether those that are adopted last very long, and whether other technologies not envisaged above, arrive within the next ten years. What does not remain to be seen is that new technologies will arrive, and that some will become mainstream in adult education. It seems likely that the trend of the last two decades to move away from paper-based provision of adult education to electronic provision will continue, as will the increasing prevalence of distance education delivery. History has shown us that predictions of the demise of the classroom teacher face to face with students, to be replaced with intelligent computers, did not happen in schools (Cuban, 2001), nor is it likely to happen in adult education. Some face to face delivery will continue, particularly in blended form. What did change in schools, and in adult education, was the mode of electronic delivery, the technical developments associated with electronic delivery and the pedagogy utilised via electronic delivery. History is our best predictive resource. Two decades of incredibly rapid technological change in adult education suggests that the future will be rapid technological change, but the change will occur at an ever increasing rate.

REFERENCES Anderson, B., & Stoneman, P. (2008). Predicting the socio-technical future (and other myths) . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 3–16). Chichester, UK: John Wiley & Sons. Augar, N., Raitman, R., & Zhou, W. (2006). Wikis: Collaborative virtual learning environments . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1251– 1270). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_52 Bates, T. (1993). Theory and practice in the use of technology in distance education . In Keegan, D. (Ed.), Theoretical principles of distance education (pp. 213–233). New York: Routledge. Berners-Lee, T., & Mark, F. (1999). Weaving the web: Origins and future of the world wide web. Stamford, UK: Orion Business. Boon, S., & Sinclair, C. (2009). A world I don’t inhabit: disquiet and identity in Second Life and Facebook. Educational Media International, 46(2), 99–110. doi:10.1080/09523980902933565 Boyd, G. (1993). A theory of distance education for the cyberspace era . In Keegan, D. (Ed.), Theoretical principles of distance education (pp. 213–233). New York: Routledge. Brophy, P. (2006). The eLibrary and learning . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 895–914). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_33

349

What Can We Learn from the Past about Future Technological Trends in Adult Education?

Burbules, N. C. (2006). Rethinking the virtual . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 37–58). Dordrecht, The Netherlands: Springer. doi:10.1007/9781-4020-3803-7_1

Feenberg, A. (1993). Building a global network: The WBSI executive education experience . In Harasim, L. (Ed.), Global networks: Computers and international communication (pp. 185–197). Cambridge, MA: MIT Press.

Butakov, S., & Scherbinin, V. (2009). The toolbox for local and global plagiarism. Computers & Education, 52, 781–788. doi:10.1016/j. compedu.2008.12.001

Fisher, M., & McKee, P. (2008). Flexible ICT infrastructure . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, realtime and secure service (pp. 67–78). Chichester, UK: John Wiley & Sons.

Cochrane, T., & Bateman, R. (2010). Smartphones give you wings: Pedagogical affordances of mobile Web 2.0. Autsralasian Journal of Educational Technology, 26(1), 1–14.

Gardner, N. (1989). The electronic campus: The first decade. Higher Education Quarterly, 43, 332–350. doi:10.1111/j.1468-2273.1989. tb01518.x

Cornelius, C., & Gordon, G. (2009). Adult learners’ use of flexible online resources in a belnded programme. Educational Media International, 46(3), 239–253. doi:10.1080/09523980903135392

Greenhow, C., Robelia, B., & Hughes, E. (2009). Learning, teaching, and scholarship in a digital age. Educational Researcher, 38(4), 246–259. doi:10.3102/0013189X09336671

Cuban, L. (2001). Oversold and underused: Computers in the classroom. Cambridge, MA: Harvard University Press.

Halavais, A. C. (2006). Weblogs and collaborative web publishing as learning spaces . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1215–1236). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_50

Dawson, D. (2007). Handheld technologies for mobile learning. London: Latimer Trend. Dede, C. (2009). Technologies that facilitate generating knowledge and possible wisdom. Educational Researcher, 38(4), 260–263. doi:10.3102/0013189X09336672 Dennis, R., & Wisely, D. (2008). Mobility and ICT . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 129–142). Chichester, UK: John Wiley & Sons. Eastmond, D. (2010). Book reviews. Adult Education Quarterly, 60(3), 303–309. doi:10.1177/0741713609350486

350

Harasim, L. (2006). A history of e-learning: Shift happened . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 59–94). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_2 Hung, D., Chen, D. T., & Wong, A. F. L. (2006). An overview of virtual learning environments in the Asia-Pacific: Provisos, issues, and tensions . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 699–722). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_27

What Can We Learn from the Past about Future Technological Trends in Adult Education?

Inoue, Y. (2010). Cases on online and blended learning technologies in higher education: Concepts and practices. New York: Hershey. Isenberg, S. (2007). Applying andragogical principles to internet learning. New York: Cambria Press. Johnson, J. (2003). Distance education: The complete guide to design, delivery and improvements. New York: Teachers College Press. Jones, A., Kirkup, G., & Kirkwood, A. (1993). Personal computers for distance education. New York: St. Martin’s Press. Kalyuga, S. (2009). Managing cognitive load in adaptive multimedia learning. New York: Hershey. Kings, N. J., Davies, J., Verrill, D., Aral, S., Bryniolfsson, E., & Alstyne, M. V. (2008). Social networks, social computing and knowledge management . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, realtime and secure service (pp. 17–26). Chichester, UK: John Wiley & Sons. Kodama, M. (2008). New knowledge creation through ICT dynamic capability. Charlotte, NC: Information Age Publishing. Leiner, B., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., et al. (2003). A brief history of the internet. Retrieved March 11, 2009, from http://www.isoc.org/internet /history/ brief.shtml Luke, C. (2006). Cyberpedagogy . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 269–278). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_10 Marwick, A. D. (2001). Knowledge management technology. IBM Systems Journal, 40(4), 814-830. Retrieved October 2, 2007, from http://www. research.ibm.com /journal/sj/404/marwik.html

McCarty, S., Ibrahim, B., Sedunov, B., & Sharma, R. (2006). Global online education . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 723–788). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_28 McLoughlin, C., & Lee, M. J. W. (2010). Personalised and self regulated learning in the Web 2.0 era: International exemplars of innovative pedagogy using social software. Australasian Journal of Educational Technology, 26(1), 28–43. Mitchener, J. (2008). Device Futures . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 27–38). Chichester, UK: John Wiley & Sons. Moore, M. G. (1995). American distance education . In Lockwood, F. (Ed.), Open and distance learning today (pp. 32–41). London: Routledge. O’Day, V. L., Ito, M., Adler, A., Linde, C., & Mynatt, E. D. (2006). Cemeteries, oak trees, and black and white cows: Newcomers’ understandings of the networked world . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 873–894). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_32 OECD. (2005). Promoting adult learning. Retrieved March 14, 2009, from http://www.oecd. org/document/57/0,334 3,en_2649_39263238_3 6675769_1_1_1_1,00.html Olle, T. W. (2004). Eight significant events in the 50 year history of computing . In Impagliazzo, J., & Lee, J. A. N. (Eds.), History of computing in education (pp. 47–56). Dordrecht, The Netherlands: Kluwer. doi:10.1007/1-4020-8136-7_5 Open University. (2009). About the OU. Retrieved March 11, 2009, from http://www.open.ac.uk/ about/ou/p3.shtml

351

What Can We Learn from the Past about Future Technological Trends in Adult Education?

Pauling, B. (2006). Virtual learning environments in higher education “down under” . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 609–652). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_24 Paulson, K. (2002). Reconfiguring faculty roles for virtual settings. The Journal of Higher Education, 73, 123–141. doi:10.1353/jhe.2002.0010 Payne, D. (2008). The future all optical network— why we need it and how we get there . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 93–114). Chichester, UK: John Wiley & Sons. Pearson, I. (2008). Over the horizon . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 215–226). Chichester, UK: John Wiley & Sons. Pont, B., & Sweet, R. (2006). ICT and learning: Supporting out-of-school youth and adults. Paris: Organisation for Economic Cooperation and Development. Putnam, R. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6, 65–78. doi:10.1353/jod.1995.0002 Riley, D. (2008). China to become world’s largest internet market by users. Retrieved March 25, 2009, from http://www.techcrunch. com/2008/01/17/ china-close-to-becomingworlds-largest-internet-market-by-users Roseberry, C. (n.d.). What is the history of laptops? Retrieved March 24, 2009, from http:// mobileoffice.about.com/od/ laptopstabletpcs/f/ laptophistory.htm

352

Samarawickrema, G., Benson, R., & Brack, C. (2010). Different spaces: Staff development for Web 2.0. Australian Journal of Educational Technology, 26(1), 44–49. Selwyn, N., Gorard, S., & Furlong, J. (2006). Adult learning in the digital age. Milton Park, UK: Routledge. Sosnoski, J., Jones, S., Carter, B., McAllister, K., Moeller, R., & Mir, R. (2006). Virtual Harlem as a collaborative learning environment: A project of the University of Illinois at Chicago’s electronic visualization Lab . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1289–1320). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_54 Taylor, E. W. (2006). The greening of the adult education academy . In Merriam, S. B., Courtenay, B. C., & Cervero, R. M. (Eds.), Global issues and adult education: Perspectives from Latin America, Southern Africa, and the United States (pp. 254–264). San Francisco: Jossey-Bass. Tiffin, J., & Terashima, N. (2001). Hyper-reality: Paradigm for the third millennium. London: Routledge. Tyack, D., & Cuban, L. (1995). Tinkering towards utopia: A century of school reform. Cambridge, MA: Harvard University Press. UNESCO Institute for Statistics. (2005). Educational trends in perspective. Retrieved March 21, 2009, from http://www.uis.unesco.org/ TEMPLATE/pdf/wei/WEI2005.pdf UNESCO Institute for Statistics. (2009). Expert meeting on cyber network for learning languages. Retrieved March 21, 2009, from http://portal. unesco.org/en/ev.php-URL_ID=44836& URL_ DO=DO_TOPIC&URL_SECTION=201.html

What Can We Learn from the Past about Future Technological Trends in Adult Education?

Urban, G. L. (2008). Online trust and customer power: The emergence of customer advocacy . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 39–54). Chichester, UK: John Wiley & Sons.

Wittgreffe, J., Dames, M., Clark, J., & McDonald, J. (2008). End-to-end service level agreements for complex ICT solutions . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 115–128). Chichester, UK: John Wiley & Sons.

Warren, P., Davies, J., & Brown, D. (Eds.). (2008). ICT futures: Delivering pervasive, real-time and secure service. Chichester, UK: John Wiley & Sons.

Zhao, Y., Lei, J., & Conway, P. F. (2006). A global perspective on political definitions of e-learning: Commonalities and differences in national educational technology strategy discourses . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 673–698). Dordrecht, The Netherlands: Springer. doi:10.1007/978-14020-3803-7_26

353

354

Compilation of References

Abdul-Hamid, H., & Lewis, C. (2005). Identifying effective online instructional practices in undergraduate and graduate level courses. In G. Richards (Ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2005 (pp. 1864-1868). Chesapeake, VA: AACE.

Ahedo, M. (2009). Comparing the Principles of Adult Learning with Traditional Pedagogical Teaching in Relation to the Use of Technology: The Tacit Dimension of ICT-based University Teaching. International Journal of Web-Based Learning and Teaching Technologies, 4(4), 66–81.

Abels, S., Haak, L., & Hahn, A. (2005). Identification of common methods used for ontology integration tasks. In the Proceedings of the first international workshop on Interoperability of heterogeneous information systems IHIS ’05 Publisher: ACM Press

Aivazidis, C., Lazaridou, M., & Hellden, G. F. (2006). A comparison between a traditional and an online environmental educational program. The Journal of Environmental Education, 37, 45–54. doi:10.3200/JOEE.37.4.45-54

Adaktilou, N., & Cartalis, C. (2007). A Learning Platform for the Introduction of Remote Sensing Principles and Applications: A pilot Phase. In Proceedings of the 6th European Conference on e-Learning, Copenhagen, Denmark. Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24, 665–694. doi:10.2307/3250951 Aggarwal, A. K. (2003). A Guide to eCourse Management: Stakeholders’ Perspective. Chapter in Web-Based Education: Learning from Experiences. Hershey, PA: Idea Group Pub. Aggarwal, A. K., & Adlakha, V. G. (2006). Quality Management Applied to Web-Based Courses. Total Quality Management & Business Excellence, 17(1). Aggarwal, A. K., & Bento, R. (2000). Web-based Learning and Teaching Technologies: Opportunities and Challenges. ed., A. K. Aggarwal, Hershey, PA: Idea Group Publishing.

Akscyn, R. M., McCracken, D. L., & Yoder, E. A. (1988). Kms: a distributed hypermedia system for managing knowledge in organizations. Communications of the ACM, 31(7), 820–835. doi:10.1145/48511.48513 ALEKS Corporation. (2008). ALEKS teacher’s menu for K-12 (Version 3.8). Retrieved August 20, 2009, from http://www.aleks.com/k12/user_guides ALEKS Corporation. (2009). ALEKS Corporation Web site. Retrieved August 20, 2009, http://www.aleks.com Alfonseca, E., Carro, R. M., Martin, E., Ortigosa, A., & Paredes, P. (2006). The impact of learning styles on student grouping for collaborative learning: A case study. User Modeling and User-Adapted Interaction, 16(3-4), 377–401. doi:10.1007/s11257-006-9012-7 Allen, I. E., & Seaman, J. (2008). Staying the course: Online education in the United States, 2008. Needham, MA: The Sloan Consortium. Allen, I. E., Seaman, J., & Garrett, R. (2007). Blending in: The extent and promise of blended education in the United States. Needham, MA: The Sloan Consortium.

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Compilation of References

Allen, I. E., & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States. Needham, MA: Sloan & Sloan Center for Online Education (SCOLE). Allen, I., & Seaman, J. (2007). Online nation: Five years of growth in online learning. Needham, MA: Sloan Consortium. Retrieved April 22, 2009, from http://www. sloan-c.org/public ations/survey /pdf/online_nation.pdf American Psychological Association. (1997). Learnercentered psychological principles: A framework for school redesign and reform. Retrieved April 20, 2009, http://www.apa.org/ed/lcp.html Anastasiades, P., & Retalis, S. (2001, June 25-30). The educational process in the emerging information society: Conditions for the reversal of the linear model of education and the development of an open type hybrid leaning environment. [Tampere, Finland.]. Proceedings of ED-MEDIA, 2001, 43–50. Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1–17. Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy of learning, teaching, and assessment: A revision of Bloom’s taxonomy of educational objectives. New York: Longman. Anderson, B., & Stoneman, P. (2008). Predicting the socio-technical future (and other myths) . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 3–16). Chichester, UK: John Wiley & Sons.

Antonocopoulou, E., Jarvis, P., Andersen, V., Elkjaer, B., & Hoyrup, S. (Eds.). (2006). Learning, working and living. London: Palgrave Macmillan. Apps, J. W. (1988). Higher education in a learning society. Meeting new demands for education and training. San Francisco: Jossey-Bass. Aragon, S. (Ed.). (2003). Facilitating learning in online environments: New directions for adult and continuing education (Vol. 100). San Francisco: Jossey-Bass. Ardissono, L., Goy, A., Petrone, G., & Segnan, M. (2005). A multi-agent infrastructure for developing personalized Web-based systems. ACM Transactions on Internet Technology, 5(1), 47–69. doi:10.1145/1052934.1052936 Ashwin, P. (2006). Changing higher education: the development of learning and teaching. London: Routledge. Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94(2), 416–427. doi:10.1037/00220663.94.2.416 Atkinson, R. C. (1976). Adaptive instructional systems: some attempts to optimize the learning process . In Klahr, D. (Ed.), Cognition and instruction. New York: Wiley. Augar, N., Raitman, R., & Zhou, W. (2006). Wikis: Collaborative virtual learning environments . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1251–1270). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_52 Ausbel, D. (1963). The psychology of meaningful learning. New York: Grune & Stratton.

André, E., Rist, T., & Müller, J. (1999). Employing AI methods to control the behaviour of animated interface agents. Applied Artificial Intelligence, 13, 415–448. doi:10.1080/088395199117333

Ausburn, L. J. (2004). Course design elements most valued by adult learners in blended online education environments: An American perspective. Educational Media International, 41(4), 327–337. doi:10.1080/0952398042000314820

Angers, J., & Machtmes, K. (2005). An EthnographicCase Study of Beliefs, Context Factors, and Practices of Teachers Integrating Technology. Qualitative Report, 10(4), 771–794.

Ausburn, L. J., & Brown, D. (2006). Learning strategy patterns and instructional preferences of career and technical education students. Journal of Industrial Teacher Education, 43(4), 6–39.

355

Compilation of References

Ayres, P., & van Gog, T. (2009). State of the art research into Cognitive Load Theory. Computers in Human Behavior, 25(2), 253–257. doi:10.1016/j.chb.2008.12.007 Bajraktarevic, N., Hall, W., & Fullick, P. (2003). Incorporating learning styles in hypermedia environment: Empirical evaluation. In Proc. Fourteenth Conference on Hypertext and Hypermedia, pages 41–52. Balan, C. (2009). Teaching security concepts using handson and open source products. Journal of Computing Sciences in Colleges, 24(6), 144–145. Baldoni, M., Baroglio, C., Brunkhorst, I., Marengo, E., & Patti, V. (2007). A service-oriented approach for curriculum planning and validation. In Proc. of Int. Workshop on Agents, Web-Services, and Ontologies - Integrated Methodologies, pages 108–123. Baldoni, M., Baroglio, C., Patti, V., & Torasso, L. (2004). Reasoning about learning object metadata for adapting SCORM courseware. In Proc. of International Workshop on Engineering the Adaptive Web: Methods and Technologies for personalization and Adaptation (EAW’04). Baltzer, H., Lazaros, E., & Flowers, J. C. (2007). Review of doctoral programs in technical education. Journal of Industrial Teacher Education, 44(2), 37–59. Bar, V., & Travis, A. S. (1991). Children’s views concerning phase changes. Journal of Research in Science Education, 18, 363–382. Barab, S. A., & Luehmann, A. L. (2002). Building sustainable science curriculum: Acknowledging and accommodating local adaptation. Science Education, 87, 454–467. doi:10.1002/sce.10083 Barak, M., & Dori, Y. J. (2004). Enhancing undergraduate students’ chemistry understanding through project-based learning in an IT environment. Science Education, 89, 117–149. doi:10.1002/sce.20027 Barr, R. B., & Tagg, J. (1995). From teaching to learning— a new paradigm for undergraduate education. Change, 27(6), 12–25.

356

Barrat-Esteve, J., Franquet-Sugrañes, T., Giménez-Costa, A., González-Bondia, A., Jaria i Manzano, J., Marquès i Banqué, M., & Martí-Baiget, M. (2007). “El diseño de una comunidad virtual como estrategia de adaptación del profesorado a los postulados docentes del EEES” (The design of a virtual community as strategy to adopt teachers to the objectives of the European Higher Educational Space). In D. García-San José (Ed.), Innovación docente y calidad en la enseñanza de ciencias jurídicas en el espacio europeo de educación superior (Pedagogy innovation and quality of Law Science teaching in the European Higher Educational Space) (pp.171-200). España: Ediciones Laborum. Barresi, S., Rezgui, Y., Lima, C., & Meziane, F. (2005). Architecture to support semantic resources interoperability. In the Proceedings of the first international workshop on Interoperability of heterogeneous information systems, pp 79 - 82, ACM 2005 Barrett, H. C. (2007). Researching electronic portfolios and learner engagement: The REFLECT initiative. Journal of Adolescent & Adult Literacy, 50(6), 436–449. doi:10.1598/JAAL.50.6.2 Barry, J. H. (1999). Lifelong learning in late modernity: The challenges to society, organizations, and individuals. Adult Education Quarterly, 49(2), 79–90. doi:10.1177/074171369904900201 Bash, L. (2003). Adult learners in the academy. Bolton, MA: Anker Publishing. Bastable, S. B. (2003). Nurse as educator: Principles of teaching and learning for nursing practice (2nd ed.). Sudbury, MA: Jones & Bartlett. Bates, A. W. (1997). The impact of technological change on open and distance learning. Distance Education, 18(1), 93–109. doi:10.1080/0158791970180108 Bates, A. W. (2000). Managing technological change. Strategies for College and University Leaders. San Francisco: Jossey – Bass.

Compilation of References

Bates, T. (1993). Theory and practice in the use of technology in distance education . In Keegan, D. (Ed.), Theoretical principles of distance education (pp. 213–233). New York: Routledge. Bates, A. W., & Poole, G. (2003). teaching with technology in higher education: Foundations for success. San Francisco: Jossey-Bass. Baylor, A. L., & Ryu, J. (2003). The effects of image and animation in enhancing pedagogical agent persona. Journal of Educational Computing Research, 28(4), 373–394. doi:10.2190/V0WQ-NWGN-JB54-FAT4 Beaumie, K. (2001). Social constructivism. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Retrieved: 1/2008, from http://www.coe.uga. edu/e pltt /SocialConstructivism.htm Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D. L., Patel-Schneider, P. F., & Stein, L. A. (2004), OWL Web Ontology Language Reference [Online]. Available: http://www.w3.org/TR/owl-ref/ Beetham, H. (2001). The evaluation Cycle, Embedding Learning Technologies. Retrieved from http://www.elt. ac.uk/ Beetham, H. (2005). Evaluating an e-tools project: some guidelines. http://www.jisc.ac.uk/uploaded _documents/ Guidelines.doc Bellotti, J., Vogel, C., Burwick, A., Nagatoshi, C., Ford, C., Schiff, B., et al. (2003, October). Dedicated to dads: Lessons from the Early Head Start Fatherhood Demonstration. Report to the Head Start Bureau, Administration on Children, Youth and Families. Princeton, NJ: Mathematica Policy Research. Benard, C. (2006). Fixing What’s Wrong - and Building on What’s Right - With Middle East Education (pp. 29–46). SAIS Review. Bender, B. (2003). Student-Centered Learning: A Personal Journal. ECAR Research Bulletin, Vol. 2003, No. 11. Retrieved from http://www.educause.edu/ir/ library/p df/ERB0311.pdf

Benke, M., Bishop, T., Scarafiottiet, C., SchWeber, C., & Thompons, M. (2004). Promoting student support and satisfaction in online learning, Sloan-C series, 5. (1995). InBerge, Z., & Collins, M. P. (Eds.). Computermediated communications and the online classroom: Vol. III. Distance Learning. Cresskill, New Jersey: Hampton Press. Berners-Lee, T., & Mark, F. (1999). Weaving the web: Origins and future of the world wide web. Stamford, UK: Orion Business. Biggs, J. B. (2003). Teaching for quality learning at university: what the student does (2nd ed.). Buckingham: Society for Research into Higher Education. Billings, D. M., & Halstead, J. A. (2005). Teaching in nursing: A guide for instructors (2nd ed.). St. Louis, MO: Elsevier Saunders. Blank, W., & Hernandez, V. (2008). Preparing CTE leaders online. Techniques, January Issue. Association of Career and Technical Education. ACTE. Bleek, W. G., & Jackewitz, I. (2004). Providing an ELearning Platform in a University Context – Balancing the Organisational Frame for Application Service Providing. In Proceedings of the 37th Hawaii International Conference on System Sciences - 2004 Bloom, B. S. (1964). Taxonomy of Educational Objectives. David McKay Comp. Inc. Bollen, J. (2000, August 28-30). Group user models for personalized hyperlink recommendations. In Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Trento, Italy, (pp. 38-50). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Bonk, C. J. (2004). The Perfect E-Storm emerging technology, enormous learner demand, enhanced pedagogy, and erased budgets. Retrieved 8/2006, from http://www. publicationshar e.com/part1.pdf

357

Compilation of References

Bonk, C. J., Wisher, R. A., & Lee, J. Y. (2004). Moderating learner-centered e-learning: Problems and solutions, benefits and implications. In T. S. Roberts (Ed.), Online collaborative learning: Theory and practice (pp. 54-85). Hershey, PA: IGI Global. Boon, S., & Sinclair, C. (2009). A world I don’t inhabit: disquiet and identity in Second Life and Facebook. Educational Media International, 46(2), 99–110. doi:10.1080/09523980902933565 Borko, H. (2004). Professional Development and Teacher Learning: Mapping the terrain. Educational Researcher, 33(8), 3–15. doi:10.3102/0013189X033008003 Botafogo, R. A., Rivlin, E., & Shneiderman, B. (1992). Structural analysis of hypertexts: identifying hierarchies and useful metrics. ACM Transactions on Information Systems, 10(2), 142–180. doi:10.1145/146802.146826

Boyd, G. (1993). A theory of distance education for the cyberspace era . In Keegan, D. (Ed.), Theoretical principles of distance education (pp. 213–233). New York: Routledge. Boyer, E. (1990). Scholarship reconsidered: Priorities for the professoriate. Princeton, NJ: The Carnegie Foundation for the Advancement of Teaching. Brabeck, M. M. (1983). Critical thinking skills and reflective judgment development: Redefining the aims of higher education. Journal of Applied Developmental, 4, 23–34. doi:10.1016/0193-3973(83)90056-4 Bransford, J., Brown, A., & Cocking, R. (2000). How people learn: Brain, mind, experience and school. Committee on development in the science of learning, National Research Council. National Academy Press.

Boud, D. (2000). Sustainable assessment: rethinking assessment for the learning society. Studies in Continuing Education, 22(2), 151–167. doi:10.1080/713695728

Breen, R., Jenkins, A., Lindsay, R., & Smith, P. (1998). Insights through riangulation . In Oliver, M. (Ed.), Innovation in the Evaluation of Learning Technology (pp. 151–168). London: University of North London.

Boud, D., Keogh, R., & Walker, D. (Eds.). (1985). Reflection: Turning experience into learning. London: Kogan Page.

Brookfield, S. D. (2006). The skillful teacher: On techniques, trust, and responsiveness in the classroom (2nd ed.). San Francisco: Jossey-Bass.

Bouhnik, D., & Marcus, T. (2006). Interaction in distancelearning courses. Journal of the American Society for Information Science and Technology, 57(3), 299–305. doi:10.1002/asi.20277

Brophy, P. (2006). The eLibrary and learning . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 895–914). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_33

Bourdieu, P. (1977). Outline of a theory of practice. New York: Cambridge University Press. Bourne, J., & Moore, J. (2004). Elements of quality online education: Into the mainstream. Needham, MA: Sloan Consortium. Bower, B. (2001). Distance education: Facing the faculty challenge. Journal of Distance Learning Administration, IV(II). Retrieved from http://www.westga.edu/~distance/ ojdla/summer42/bower42.html.

358

Brown, J., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Research, 18, 32–42. Brown, E., Fisher, T., & Brailsford, T. (2007). Real users, real results: examining the limitations of learning styles within AEH. In Proc. of the eighteenth conference on Hypertext and hypermedia, pages 57–66. Brown, M. (2005). Learning Theory. Retrieved: 1/2008, from http://www.dartmouth.ed u/comp/ about/pubs/2005spaces/theory.html.

Compilation of References

Bruce, A., Feng, F., Nishizawaumiko, S., Palulis, P., Russel, B. D., & Worthing, C. (2003). Provoking signs: Un/ canny moments as curriculum theorizing. Educational Insights, 8(2), 1–20. Bruening, T. H., & Scanlon, D. C. (2001). The status of career and technical education teacher preparation programs. Columbus, OH: Dissemination Center for Career and Technical Education. Brunetta, G. P. (1993). Storia Del Cinema Italiano - dal Neorealismo al Miracolo Economico: 1945-1959 (Vol. III). Rome, Italy: Editori Riuniti. Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(2-3), 87–129. doi:10.1007/BF00143964 Brusilovsky, P. (1994). The construction and application of student models in intelligent tutoring systems. Journal of Computer and Systems Sciences International, 32(1), 70–89. Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-Adapted Interaction, 11(1-2), 87–110. doi:10.1023/A:1011143116306 Brusilovsky, P., Karagiannidis, C., & Sampson, D. (2004). Layered evaluation of adaptive learning systems. International Journal of Continuing Engineering Education and Lifelong Learning, 14(4/5), 402–421. doi:10.1504/ IJCEELL.2004.005729 Brusilovsky, P., & Maybury, M. T. (2002). From adaptive hypermedia to the adaptive web. Communications of the ACM, 45(5), 30–33. doi:10.1145/506218.506239 Brusilovsky, P., & Millan, E. (2007). User models for adaptive hypermedia and adaptive educational systems . In Brusilovsky, P., Kobsa, A., & Nejdl, W. (Eds.), The Adaptive Web: Methods and Strategies of Web Personalization, LNCS 4321 (pp. 3–53). Berlin, Heidelberg, New York: Springer-Verlag.

Brusilovsky, P. (2003). Developing adaptive educational hypermedia systems: from design models to authoring tools . In Murray, T., Blessing, S., & Ainsworth, S. (Eds.), Authoring Tools for Advanced Technology Learning Environment (pp. 377–410). Amsterdam: Kluwer Academic Publishers. Brusilovsky, P. (2007). Adaptive navigation support. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The Adaptive Web, Methods and Strategies of Web Personalization, vol. 4321 of Lecture Notes in Computer Science (pp. 263–290). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Brusilovsky, P., & Millan, E. (2007). User models for adaptive hypermedia and adaptive educational systems. In P. Brusilovsky, A. Kobsa, & W. Nejdl (Eds.), The Adaptive Web, Methods and Strategies of Web Personalization, vol. 4321 of Lecture Notes in Computer Science (pp. 3-53). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Brusilovsky, P., Eklund, J., & Schwarz, E. (1998). Webbased education for all: A tool for developing adaptive courseware. In Computer Networks and ISDN Systems (Proceedings of Seventh International World Wide Web Conference). Brusilovsky, P., Schwarz, E., & Weber, G. (1996). ELMART: An intelligent tutoring system on world wide web. In Proc. of Third Int. Conf. on Intelligent Tutoring Systems (ITS96), pages 261–269. Brusilowsky, P., & Vassileva, J. (2003). Course sequencing techniques for large-scale web-based education. International Journal of Continuing Engineering Education and Lifelong Learning, 13, 75–94. Burbules, N. C. (2008). Tacit teaching. Educational Philosophy and Theory, 40(5), 666–677. doi:10.1111/j.14695812.2008.00453.x Burbules, N. C. (2006). Rethinking the virtual . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 37–58). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_1

359

Compilation of References

Burge, E. J. (2000). Editor’s notes . In Burge, E. J. (Ed.), The strategic use of learning technologies: New directions for adult continuing education, no. 88 (pp. 1–5). San Francisco: Jossey-Bass.

Carrol, J., & Chappell, G. (1996). An Intelligent Universal Advisor. in The 1996 ACM symposium on Applied Computing, Philadelphia, Pennsylvania, United States, 1996, pp. 105-109.

Burrell, G., & Morgan, G. (1979). Sociological Paradigms and Organizational Analysis. Brookfield: Ashgate Publishing Company.

Carswell, A., & Fleming, E. (2003, January/February). Graduate school faculty evaluation study. DE Oracle@ UMUC. Retrieved 10, 2008, from http://info.umuc.edu /de/ezine/f eatures /jan_feb_2003/fac_eval_study.htm

Butakov, S., & Scherbinin, V. (2009). The toolbox for local and global plagiarism. Computers & Education, 52, 781–788. doi:10.1016/j.compedu.2008.12.001 Butler, T., & Pinto-Zipp, G. (2006). Students’ learning styles and their preferences for online instructional methods. Journal of Educational Technology Systems, 34(2), 199–221. doi:10.2190/8UD2-BHFU-4PXV-7ALW Bylander, T. (1994). The computational complexity of propositional strips planning. Artificial Intelligence, 69(1-2), 165–204. doi:10.1016/0004-3702(94)90081-7 Cahoon, B. (1998). New directions for adult and continuing education, Summer, No. 78. Adult Learning and the Internet. San Francisco: Jossey-Bass. Calabrese, N. M. (2006). Video technology: A vehicle for educators to enhance relationships with families. Education, 127(1), 155–160. Calder, J. (1994). Programme Evaluation and Quality. London: Kogan Page. Care, W. D., & Scanlan, C. M. (2001). Planning and managing the development of courses for distance delivery: Results from a qualitative study. The Online Journal of Distance Learning Administration, 4(2). Retrived from http://www.westga.edu/~dista nce/ojdla/summer42/ care42.html Carnevale, D. (2005). Government’s request for data may delay Blackboard’s purchase WebCT. The Chronicle of Higher Education, 52(16), A29. Retrieved from http:// chronicle.com/weekly/ v52/i16/16a02901.htm.

360

Carver, C. A., Howard, R. A., & Lane, W. D. (1999). Enhancing student learning through hypermedia courseware and incorporation of student learning styles. IEEE Transactions on Education, 42(1), 33–38. doi:10.1109/13.746332 Cassell, J., & Thórisson, K. R. (1999). The power of a nod and a glance: Envelope vs. emotional feedback in animated conversational agents. Applied Artificial Intelligence, 13, 519–538. doi:10.1080/088395199117360 Cassidy, S. (2004). Learning studies: An overview of theories, models, and measures. Educational Psychology, 24(4), 419–444. doi:10.1080/0144341042000228834 Castells, M. (2004). The Network Society: A Cross-cultural Perspective. Edward Elgar. Castells, M. (1997). The rise of the network society. London: Routledge. Center for Online Learning. (2009). Online course design: Bloom’s taxonomy. Statesboro, GA: Georgia Southern University. Retrieved from http://academics. georgiasouthern.edu /col/id/bloom.php Cercone, K. (2008). Characteristics of adult learners with implications for online learning design. Advancement of Computing in Education Journal, 16(2), 137–159. Ceri, S., Dolog, P., Matera, M., & Nejdl, W. (2005). Adding client-side adaptation to the conceptual design of e-learning Web applications. Journal of Web Engineering, 4(1), 21–37. Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies, and why do we need them? IEEE Intelligent Systems and Their Applications, 14, 20–26. doi:10.1109/5254.747902

Compilation of References

Chang, C. (1997). A study on the concepts of evaporation, condensation and boiling by senior students in elementary schools. Chinese Journal of Science Education, 5(3), 321–346.

Chen, C.-M., Lee, H.-M., & Chen, Y.-H. (2005). Personalized e-learning system using item response theory. Computers & Education, 44(3), 237–255. doi:10.1016/j. compedu.2004.01.006

Chang, W., Hsu, H., Smith, T. K., & Wang, C. (2004). Enhancing SCORM metadata for assessment authoring in e-Learning. Journal of Computer Assisted Learning, 20, 305–316. doi:10.1111/j.1365-2729.2004.00091.x

Chen, H., Wigand, R. T., & Nilan, M. (1998, May 17-19). Optimal flow experience in Web navigation. In Effective utilization and management of emerging information technologies: Proceedings of the 9th Information Resources Management Association International Conference, Boston (pp. 633-636). Hershey, PA: Idea Group Publishing.

Chang, K., & Lim, J. (2006). The role of Interface Elements in Web-Mediated Interaction and Group Learning: Theoretical and Empirical Analysis. International Journal of Web-Based Learning and Teaching Technologies, 1(Issue 1), Chang, K. (2003). A research on the concepts of states of water. Master thesis, National Pingtung Teachers College, Pingtung, Taiwan. Chang, S. L. (2005). Applying characteristics described system to diagnosis of e-learning. Master thesis, Department of Information and Computer Engineering, Chung Yuan Christian University, Chung-Li, Taiwan. Chao-Min, C., Meng-Hsiang, H., Szu-Yuan, S., TungChing, L., & Pei-Chen, S. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45, 399–416. doi:10.1016/j.compedu.2004.06.001 Charney, D. (1987, November 13-15). Comprehending non-linear text: the role of discourse cues and reading strategies. In HYPERTEXT ’87: Proceedings of the ACM conference on Hypertext, Chapel Hill, NC, USA, (pp. 109–120). New York, NY, USA: ACM. Checkland, P., & Holwell, S. (1998). Action Research: Its Nature and Validity. Systemic Practice and Action Research, 11(1), 9–21. doi:10.1023/A:1022908820784 Chen, C. M., Liu, C. Y., & Chang, M. H. (2006). Personalized curriculum sequencing utilizing modified item response theory for web-based instruction. Expert Systems with Applications, 30(2), 378–396. doi:10.1016/j. eswa.2005.07.029

Chen, J., & Mizoguchi, R. (1999). Communication Content Ontology for Learner Model Agent in Multi-Agent Architecture. in AIED99 Workshop on Ontologies for Intelligent Educational Systems, 1999. Cheung, B., Hui, L., Zhang, J., & Yiu, S. M. (2003). SmartTutor: An intelligent tutoring system in Web-based adult education. Journal of Systems and Software, 68(1), 11–25. doi:10.1016/S0164-1212(02)00133-4 Cheverst, K., Davies, N., Mitchell, K., & Smith, P. (2000, August 28-30). Providing tailored (context-aware) information to city visitors. In Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Trento, Italy, (pp. 73-85). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag Chi, Y.-L., & Lee, H.-M. (2006). Building conceptual knowledge for managing learning paths in e-learning. Lecture Notes in Artificial Intelligence, 4092, 66–77. Chin, D. N. (2001). Empirical evaluation of user models and user-adapted systems. User Modeling and User-Adapted Interaction, 11(1), 181–194. doi:10.1023/A:1011127315884 Choi, D. H., Jeoungkun, K., & Soung, H. K. (2007). ERP training with a Web-based electronic learning system: The flow theory perspective. International Journal of Human-Computer Studies, 65, 223–243. doi:10.1016/j. ijhcs.2006.10.002

361

Compilation of References

Choi, Y. K., Miracle, G., & Biocca, F. (2001). The effects of anthropomorphic agents on advertising effectiveness and the mediating role of presence. Journal of Interactive Advertising, 2(Fall), available online: http://wwwjiad.org

Cochrane, T., & Bateman, R. (2010). Smartphones give you wings: Pedagogical affordances of mobile Web 2.0. Autsralasian Journal of Educational Technology, 26(1), 1–14.

Cialdea Mayer, M., Limongelli, C., Orlandini, A., & Poggioni, V. (2007). Linear temporal logic as an executable semantics for planning languages. Journal of Logic Language and Information, 1(16), 63–89.

Cochran-Smith, P. M., Feiman-Nemser, S., & McIntyre, D. J. (Eds.). (2008). Handbook of research on teacher education: enduring questions in changing contexts. London: Routledge.

Clarebout, C., Elan, J., & Johnson, W. L. (2002). Animated Pedagogical Agents: An opportunity to be grasped? Journal of Educational Multimedia and Hypermedia, 11(3), 267–286.

Coffey, A., & Atkinson, P. (1996). Making Sense of Qualitative Data. USA: Sage.

Clark, K. F., & Graves, M. F. (2005). Scaffolding students’ comprehension of text. The Reading Teacher, 58(6), 570–580. doi:10.1598/RT.58.6.6 Clark, R. E., & Choi, S. (2005). Five design principles for experiments on the effects of animated pedagogical agents. Journal of Educational Computing Research, 32(3), 209–225. doi:10.2190/7LRM-3BR2-44GW-9QQY Clark, V. L., & Creswell, J. (2008). The mixed methods reader. Thousand Oaks, CA: Sage. Clark, B. (1983). The higher education system. Berkeley: University of California Press. Clark, B. (2002). Growing up gifted: Developing the potential of children at home and at school. Upper Saddle River, NJ: Merrill Prentice Hall. Clegg, V. L., & Cashin, W. E. (1986). Improving MultipleChoice Tests. Idea Paper No. 16. Center for Faculty Evaluation and Development, Kansas State University. Clyde, L. A. (2005). Wikis. Teacher Librarian, 32(4), 54–57. Coats, H., James, R., & Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11, 19–36. doi:10.1080/13583883.20 05.9967137

362

Coffield, F. (2000). Differing visions of a learning society. Research findings (Vol. 1). London: The Policy Press. Cohen, D. K., & Ball, D. L. (1999). Instruction, capacity, and improvement. (CPRE Research Report No. RR-043). Philadelphia: University of Pennsylvania, Consortium for Policy Research in Education. Colace, F., De Santo, M., & Pietrosanto, A. (2006). Evaluation for E-Learning Platform: an APH approach. In Proceedings of the 36th ASEE?IEEE Frontiers in Education Conference. Colace, F., De Santo, M., & Vento, M. (2003). Evaluating On-line Learning Platforms:a case study. In Proceedings of the 36th Hawaii International Conference on System Sciences. Collins, A., Brown, J., & Newman, S. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics . In Resnick, L. (Ed.), Knowing, Learning and Instructing: Essays in honor of Robert Glaser. Lawrence Erlbaum. Collins, R. A., & Zacharakis, J. (2009). Impact of elearning on adult education: A changing postmodern approach. In V. Wang (Ed.), Handbook of research on E-learning applications for career and technical education: Technologies for vocational training (pp. 286-296). Hershey, PA: IGI Global. Collis, B. (1996). Tele-learning in digital world: The future of distance learning. New York: International Thomson Computer Press.

Compilation of References

Conklin, J., & Begeman, M. (1989). gIBIS: A tool for all reasons. Journal of the American Society for Information Science American Society for Information Science, 40(3), 200–213. doi:10.1002/(SICI)10974571(198905)40:33.0.CO;2-U

Cox, T. (2008). Learning styles and students’ attitudes toward the use of technology in higher and adult education classes. Institute for Learning Styles Journal, 1, 1-13. Retrieved February 13, 2009, from http://www.auburn. edu/~wittej e/ilsrj/latestissue.htm

Conklin, J., Selvin, A. M., Buckingham Shum, S., & Sierhuis, M. (2001). Facilitated hypertext for collective sense-making: 15 years on from gIBIS. In Proceedings of the 12th ACM Conference on Hypertext and Hypermedia, ACM Press, pp. 123-124.

Craig, S. D., Driscoll, D. M., & Gholson, B. (2004). Constructing knowledge from dialog in an intelligent tutoring system: Interactive learning, vicarious learning, and pedagogical agents. Journal of Educational Multimedia and Hypermedia, 13(2), 163–183.

Conlon, T. (2002). Information mapping as support for learning and teaching. Computer Education, Issue 106.

Craig, S. D., Gholson, B., & Driscoll, D. M. (2002). Animated pedagogical agents in multimedia educational environments: Effects of agent properties, picture features, and redundancy. Journal of Educational Psychology, 94(2), 428–434. doi:10.1037/0022-0663.94.2.428

Conner, M. L. (1997-2004). Andragogy and Pedagogy. Ageless Learner. Retrieved: 1/2008, from http://agelesslearner.com/intros/ andragogy.html. Conrad, R. M., & Donaldson, J. A. (2004). Engaging the online learner: Activities and resources for creative instruction. San Francisco: Jossey-Bass. Conrad, D. (2008). Online learning . In English, L. M. (Ed.), International encyclopedia of adult education (pp. 442–447). New York: Palgrave Macmillan. Cooper, C., Taft, L. B., & Thelen, M. (2004). Examining the role of technology in learning: An evaluation of online clinical conferencing. Journal of Professional Nursing, 20(3), 160–166. doi:10.1016/j.profnurs.2004.04.003 Cooper, M. K., & Henschke, J. A. (2003, November). An update on andragogy: The international foundation for its research, theory and practice. Paper presented at the Commission of Professors of Adult Education (CPAE), Conference, Detroit, MI. Cornelius, C., & Gordon, G. (2009). Adult learners’ use of flexible online resources in a belnded programme. Educational Media International, 46(3), 239–253. doi:10.1080/09523980903135392 Cornelius-White, J. (2007). Learner-centered instructors-student relationships are effective: A metaanalysis. Review of Educational Research, 77(1), 113. doi:10.3102/003465430298563

Cranton, P. (1994). Understanding and promoting transformative learning. San Francisco: Jossey-Bass. Cranton, P. (2010). Working toward self-evaluation . In Wang, V. C. X. (Ed.), Assessing and evaluating adult learning in career and technical education (pp. 1–11). Cranton, P. (2005). Learning styles. In L. English (Ed.), International encyclopedia of adult education (pp. 362366). New York: Palgrave McMillan. Creswell, J. W. (1998). Qualitative Inquiry and Research Design - Choosing Among Five Traditions. Sage Publications Inc. Creswell, J. W. (2008). Educational research: planning, conducting and evaluating quantitative and qualitative research (3rd ed.). Pearson. Creswell, J. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage. Cristea, A., & Calvi, L. (2003). The three layers of adaptation granularity. In Proc. of UM 2003, LNAI 2702, pages 4–14. Cristea, A., & De Mooij, A. (2003a). Adaptive course authoring: My Online Teacher. In Proc. of ICT’03, vol. 2, pages 1762–1769.

363

Compilation of References

Cristea, A., & De Mooij, A. (2003b). LAOS: Layered WWW AHS authoring model and its corresponding algebraic operators. In Proc. of WWW’03. Csikszentmihalyi, M. (1977). Beyond boredom and anxiety (2nd ed.). San Francisco: Jossey-Bass. Csikszentmihalyi, M. (1982). Towards a psychology of optimal experience. In L. Wheeler (Ed.), Annual review of personality and social psychology (Vol. 3, pp. 13-36). Beverly Hills, CA: Sage. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper and Row. Csikszentmihalyi, M., & Csikszentmihalyi, I. (Eds.). (1988). Optimal experience: Psychological studies of flow in consciousness. Cambridge, UK: Cambridge University Press. Cuban, L. (2001). Oversold and underused: Computers in the classroom. Cambridge, MA: Harvard University Press. Dabbagh, N. (2004). Distance learning: Emerging pedagogical issues and learning designs. Quarterly Review of Distance Education, 5(5), 37–40. Dailey, L. (2004). Navigational Web atmospherics: Explaining the influence of restrictive navigation cues. Journal of Business Research, 57, 795–803. doi:10.1016/ S0148-2963(02)00364-8 Daniel, J. S. (1996). Mega Universities and Knowledge Media. Technology Strategies for Higher Education. London: Kogan Page. Datta, A., Dutta, K., VanderMeer, D., Ramamritham, K., & Navathe, S. B. (2001). An architecture to support scalable online personalization on the Web. The International Journal on Very Large Data Bases, 10(1), 104–117. Dawson, D. (2007). Handheld technologies for mobile learning. London: Latimer Trend. De Bra, P., Smits, D., & Stash, N. (2006). Creating and delivering adaptive courses with AHA! (pp. 21–33). EC-TEL.

364

de Bra, P., Smits, D., & Stash, N. (2006, August 22-25). The design of AHA! In U. K. Wiil, P. J. Nurnberg, and J. Rubart (Eds.), In HYPERTEXT 2006, Proceedings of the 17th ACM Conference on Hypertext and Hypermedia, Odense, Denmark, (pp. 171–195). New York, NY, USA: ACM. De Laat, M. (2006). Networked Learning. Utrecht: Unpublished PhD, University of Utrecht. de Moor, A., & Aakhus, M. (2006). Argumentation support: from technologies to tools. Communications of the ACM, 49(3), 93–98. Dede, C. (2005). Planning for Neomillennial Learning Styles. EDUCAUSE Quarterly, 28(1). Dede, C. (2009). Technologies that facilitate generating knowledge and possible wisdom. Educational Researcher, 38(4), 260–263. doi:10.3102/0013189X09336672 Dee Fink, L. (2003). Creating Significant Learning Experiences. Jossey-Bass, Dewey, J. (1982). How we think (rev. ed.). Lexington, Mass: Heath. Dehn, D. M., & van Mulken, S. (2000). The impact of animated interface agents: A review of the empirical literature. International Journal of Human-Computer Studies, 52, 1–22. doi:10.1006/ijhc.1999.0325 Deline, G., Lin, F., Wen, D., & Gasevic, D. Kinshuk. (2007). Ontology-Driven Development of Intelligent Educational Systems. Presented at the 2007 IEEE Pacific-Rim Conference on Communications, Computers and Signal Processing (PACRIM07), Victoria, BC, Canada, 2007. Demirkan, H., Goul, M., & Gros, M. (2010). A Reference Model for Sustainable E-Learning Service Systems: Experiences with the Joint University/Teradata Consortium . Decision Sciences Journal of Innovative Education, 8(1), 151–189. doi:10.1111/j.1540-4609.2009.00250.x Dennis, R., & Wisely, D. (2008). Mobility and ICT . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 129–142). Chichester, UK: John Wiley & Sons.

Compilation of References

Derntl, M., & Motschnig-Pitrik, R. (2004, March 14-17). Patterns for blended, person-centered learning: Strategy, concepts, experiences, and evaluation. In Proceedings of the 2004 ACM Symposium on Applied Computing, Nicosia, Cyprus (pp. 916-923). ACM Publishing. Dewey, J. (1933). How we think: a restatement of the relation of reflective thinking to the educative process. In J. A. Boydston (Ed.), (1986) The latter works (pp. 105-325). Southern Illinois University Press. Diaz, D., & Cartnal, R. (1999). Students’ learning styles in two classes: Online distance learning and equivalent on-campus. College Teaching, 47(4), 130–135. Diekelmann, N., Schuster, R., & Nosek, C. (1998). Creating new pedagogies at the millennium: The common experiences of University of Wisconsin-Madison instructors using distance education technologies (commissioned final report to University System of Wisconsin no. 1). Madison, WI: University of Wisconsin.

Dodds, P. (2001b). Sharable Content Object Reference Model (SCORM) Version 1.2 Technical Report. The SCORM Run-Time Environment, Advanced Distributed Learning Initiative, URL: http://www.adlnet.org/ index. cfm?fuseaction=SCOR-Down [last accessed 20 November 2003] Doolittle, P. E., & Camp, W. G. (1999). Constructivism: The career and technical education perspective. Journal of Vocational and Technical Education, 16(1). Retrieved from http://scholar.lib.vt.edu/ejournals/ JVTE/v16n1/ doolittle.html. Dougiamas, M., & Taylor, P. (2003). MOODLE: Using learning communities to create an open source course management system. In Proceedings of the EDMEDIA Conference, Honolulu, Hawaii. Downes, S. (n.d.). E-learning 2.0. Retrieved: 1/2008, from http://www.elearnmag.org/s ubpage. cfm?section= articles&article=29-1

Dimitrova, M., Mimirinis, M., & Murphy, A. (2004). Evaluating the Flexibility of a Pedagogical Framework for e-Learning. In Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT).

Draper, S., Brown, M. I., Henderson, F. P., & McAteer, E. (1996). Integrative Evaluation: An Emerging Role for Classroom Studies of CAL. Computers & Education, 26(1-3), 17–32. doi:10.1016/0360-1315(95)00068-2

Dirkin, K. H., Mishra, P., & Altermatt, E. (2005). All or nothing: Levels of sociability of a pedagogical software agent and its impact on student perceptions and learning. Journal of Educational Multimedia and Hypermedia, 14(2), 113–128.

Du, H., & Wagner, C. (2005). Learning with weblogs: An empirical investigation. In Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS’05), Big Island, Hawaii (pp. 7). IEEE.

Dobrovolny, J. (2002). Learning strategies. Retrieved from http://www.learningcircuits.org /200 3/oct2003/ dobrovolny.htm Dodds, P. (2001a). Sharable Content Object Reference Model (SCORM) Version 1.2 Technical Report. The SCORM content aggregation Model, Advanced Distributed Learning Initiative, URL: http://www.adlnet.org/ index.cfm ?fuseaction=SCOR-Down [last accessed 20 November 2003]

DuCharme-Hansen, B. A., & Dupin-Bryant, P. A. (2004). Web-based distance education for adults. Malabar, FL: Krieger Publishing. Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction . In Jonassen, D. H. (Ed.), Handbook of research for educational communications and technology. New York: Simon & Schuster Macmillan. Duffy, T. M., & Knuth, R. A. (1990). Hypermedia and instruction: where is the match? Designing hypermedia for learning, 199–226.

365

Compilation of References

Dunn, R., Honingsfeld, A., & Doolan, L. (2009). Impact of learning-style instructional strategies on students’ achievement and attitudes: Perceptions of educators in diverse institutions. Clearing House (Menasha, Wis.), 82(3), 135–140. doi:10.3200/TCHS.82.3.135-140 Dunn, R., & Griggs, S. A. (Eds.). (2000). Practical approaches to using learning styles in higher education. Westport, CT: Bergin & Garvey. Durrance, B. (1998). Some explicit thoughts on tacit learning. Training & Development, 52(12), 24–29. Dziuban, C. D., Hartman, J. L., & Moskal, P. D. (2004). Blended learning. EDUCAUSE Center for Applied Research, Research Bulletin, Issue 7. Eastmond, D. (2010). Book reviews. Adult Education Quarterly, 60(3), 303–309. doi:10.1177/0741713609350486 Ebart, C. (2008). Open source software in industry. IEEE Software, 25(3), 52–53. doi:10.1109/MS.2008.67 Ebel, R. L., & Frisbie, D. A. (1991). Essential of Educational Measurement. Englewood Cliffs, NJ: Prentice-Hall. Elder, J. H. (2002). Current treatments in autism: Examining the scientific evidence and clinical implications. The Journal of Neuroscience Nursing, 34, 67–73. Elder, J. H., Valcante, G., Won, D., & Zylis, R. (2003). Effects of in-home training for culturally diverse fathers of children with autism. Issues in Mental Health Nursing, 24(3), 273–295. doi:10.1080/01612840305276 Elias, J. L., & Merriam, S. B. (1995). Philosophical foundations of adult education. Malabar, FL: Krieger Publishing Company. Elias, J. L., & Merriam, S. B. (2005). Philosophical foundations of adult education (3rd ed.). Malabar, FL: Krieger Publishing Company. Ellis, R. (2003). Task-based language learning and teaching. Oxford: Oxford University Press.

Entwistle, N. (2003). Enhancing teaching learning environments to encourage deep learning. In E. De Corte (Ed.), Excellence in higher education. Wenner-Gren international series, 82, 83-96. London: Portland Press. Ertmer, P., Ottenbreti-Leftwich, A., & York, C. (2006-07). Exemplary Technology - using Teachers: Perceptions of Factors Influencing Success. Journal of Computing Education, 23(2), 55–61. Ertmer, P. A., Lehman, J., Park, S. H., Cramer, J., & Grove, K. (2003). Barriers to teachers’ adoption and use of technology in problem-based learning. Proceedings of the Association for the Advancement of Computing in Education (AACE) Society for information Technology and Teacher Education (SITE) International Conference (1761–1766). Escobedo del Cid, J. P., de la Fuente Valentín, L., Gutiérrez, S., Pardo, A., & Kloos, C. D. (2007). Implementation of a learning design run-time environment for the. LRN learning management system. Journal of Interactive Media in Education. Retrieved August 20, 2009, from http://jime.open.ac.uk/2007/07 Esmahi, L. (2007). An agent-based framework for personalized e-learning services. International Journal of WebBased Learning and Teaching Technologies, 2(4), 1–11. European Agency for Vocational Training, (2002). Quality and e-Learning in Europe. Survey report. European Commission. (2008). The use of ICT to support innovation and lifelong learning for all - A report on progress. Brussels: Commission of the European Communities. Euzenat, J., & Shvaiko, P. (2007). Ontology Matching. Berlin Heidelberg, Germany: Springer-Verlag. Evaluating eLearning (n.d.). Why evaluate? Warwick University. Retrieved from http://www2.warwick.ac.uk/ services/ cap/resources/egui des/evaluation/eLearning Evaluation of Learning Management System Software, Part II of LMS Evaluation. (2004). Open source eLearning Environment and Community Platform Project.

366

Compilation of References

Evans, C. (2008). The effectiveness of m-learning in the form of podcast revision lectures in higher education. Computers & Education, 50(2), 491–498. doi:10.1016/j. compedu.2007.09.016 Facione, P. A. (2007). Critical thinking: What it is and why it counts. Retrieved: 12/2008, from http://www. insightassessm ent.com /pdf_files/what&why2006.pdf Falmagne, J. C., Koppen, M., Villano, M., Doignon, J. P., & Johannesen, L. (1990). Introduction to Knowledge Spaces: How to Build, Test, and Search Them. Psychological Review, 97(2), 201–224. doi:10.1037/0033-295X.97.2.201 Farrell, G. M. (2001). The changing faces of virtual education. London: Commonwealth of Learning. Feenberg, A. (1993). Building a global network: The WBSI executive education experience . In Harasim, L. (Ed.), Global networks: Computers and international communication (pp. 185–197). Cambridge, MA: MIT Press. Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. English Education, 78(7), 674. Felder, R. M., & Spurlin, J. (2005). Application, reliability and validity of the index of learning styles. International Journal of Engineering Education, 21(1), 103–112. Felder, R. M., Felder, G. M., & Dietz, E. J. (1995). A longitudinal study of Engineering student performance and retention vs comparisons with traditional taught students. Journal of Engineering Education, 87(4), 469–480. Ferdig, R. E. (2006). Assessing technologies for teaching and learning: Understanding the importance of technological-pedagogical content knowledge. British Journal of Educational Technology, 37(5), 749–760. doi:10.1111/j.1467-8535.2006.00559.x Ferdig, R. E., Roehler, L., & Pearson, P. D. (2002). Scaffolding preservice teacher learning through web-based discussion forums: An examination of online conversations in the Reading Classroom Explorer. Journal of Computing in Teacher Education, 18(3), 87–94.

Ferdig, R. E., Roehler, L. R., & Pearson, P. D. (2006). Video and database-driven web environments for pre-service literacy teaching and learning. In M. C. McKenna, L. D. Labbo, R. D. Kieffer, & D. Reinking (Eds.), International handbook of literacy and technology (Vol. 2, pp. 235-256). Mahwah, NJ: Lawrence Erlbaum Associates. Ferry, B., Hedberg, J., & Harper, B. (1998). How do preservice teachers use concept maps to organise their curriculum knowledge? Journal of Interactive Learning Research, 9(1), 83–104. Fichter, D. (2005). The Many Forms of E-Collaboration: Blogs, Wikis, Portals, Groupware, Discussion Boards, and Instant Messaging. Online, 29(4), 48–50. Fidishun, D. (2000). Andragogy and technology: Integrating adult learning theory as we teach with technology. Retrieved from http://frank.mtsu.edu/~itconf/ proceed00/ fidishun.htm. Fink, J., A. K., & Nill, A. (1998). Adaptable and adaptive information provision for all users, including disabled and elderly people. New Review of Hypermedia and Multimedia, 4, 163–188. doi:10.1080/13614569808914700 Fink, J., Kobsa, A., & Nill, A. (1998). Adaptable and adaptive information provision for all users, including disabled and elderly people. New Review of Hypermedia and Multimedia, 4, 163–188. doi:10.1080/13614569808914700 Fischer, G., Lemke, A. C., McCall, R., & Morch, A. (1991). Making Argumentation Serve Design. HumanComputer Interaction, 6(3-4), 393–419. doi:10.1207/ s15327051hci0603&4_7 Fischer, G. (2001). Lifelong learning and its support with new media . In Smelser, N. J., & Baltes, P. B. (Eds.), International encyclopedia of social and behavioral sciences (pp. 8836–8840). New York: Elsevier. Fisher, M., & McKee, P. (2008). Flexible ICT infrastructure . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 67–78). Chichester, UK: John Wiley & Sons.

367

Compilation of References

Fleming, N. (n.d.). VARK: A guide to learning styles. Retrieved March 16, 2009, from http://www.vark-learn. com/englis h/page.asp?p=categories Flores, F. (1998). Information technology and the institution of identity. Information Technology & People, 11(4), 351–372. doi:10.1108/09593849810246156 Flowers, J. (2001). Online learning in technology education. Journal of Technology Education, 13(1), 17–30. Flowers, J. (2005). The effect of online delivery on graduate enrollment. Journal of Industrial Teacher Education, 42(4), 7–24. Flowers, J., & Baltzer, H. (2006a). Hiring technical education faculty: Vacancies, criteria, and attitudes toward online doctoral programs. Journal of Industrial Teacher Education, 43(3), 29–44. Flowers, J., & Baltzer, H. (2006b). Perceived demand for online and hybrid doctoral programs in technical education. Journal of Industrial Teacher Education, 43(4), 39–56. Fontana, D. (1981). Psychology for teachers. London: Macmillan/British Psychological Society. Freire, P. (1970). Pedagogy of the oppressed. New York: Seabury Press. Friedrich, J., & Karslioglou, M. O. (2003). A Remote Sensing computer assisted learning tool developed using the unified modelling language. Journal of Photogrammetry & Remote Sensing, 58, 265–274. doi:10.1016/ S0924-2716(03)00022-4 Fry, H., Ketteridge, S., & Marshall, S. (Eds.). (2009). A handbook for teaching and learning in higher education: enhancing academic practice (3rd ed.). London: Taylor & Francis. Funk, P., & Conlan, O. (2002, September 4). Using casebased reasoning to support authors of adaptive hypermedia systems. In Proceedings of Workshop on Case-Based Reasoning for Education and Training, CBRET’2002, Aberdeen, Scotland, (pp. 15–23). Aberdeen, UK: Robert Gordon University.

368

Furnas, G. W. (1986). Generalized fisheye views. SIGCHI Bulletin, 17(4), 16–23. doi:10.1145/22339.22342 Gagne, R. M. (1985). The conditions of learning and theory of instruction. New York: Holt, Rinehart, & Winston. Gallagher, S. (2003). The New Landscape for Course Management Systems. ECAR Research Bulletin, Vol. 2003, No. 11. Gardner, N. (1989). The electronic campus: The first decade. Higher Education Quarterly, 43, 332–350. doi:10.1111/j.1468-2273.1989.tb01518.x Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic Books. Garfinkel, H. (1967). Studies in Ethnomethodology. Englewod Cliffs. Prentice Hall. Gargiulo, T. L. (2009). The top ten strategies for managers of mobile workers. Retrieved April 10, 2009, from http:// makingstories.net Garrison, D. R., Anderson, T., & Archer, W. (2000, Spring). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2), 87–105. doi:10.1016/S10967516(00)00016-6 Garrison, D. R., & Anderson, T. (2003). [st Century: A framework for research and practice. London: RoutledgerFalmer.]. E-learning, 21. Garrison, R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(3), 87–105. doi:10.1016/S1096-7516(00)00016-6 Garrison, D. R., & Anderson, T. (2003). E-learning in the 21st century: a framework for research and practice. London: Routledge. doi:10.4324/9780203166093 Garrison, D. R. (2003). Cognitive presence for effective asynchronous online learning: The role of reflective inquiry, self-direction and metacognition. In J. Bourne & J. C. Moore (Eds.), Elements of quality online education: Practice and direction. Volume 4 in the Sloan C Series, Needham, MA: The Sloan Consortium.

Compilation of References

Garrison, D. R., & Anderson, T. (2003). e-Learning in the 21 st century: A framework for research and practice. Routledge, London.

Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Chicago: Aldine.

Garrison, D.R., & Clevelan-Innes, M. (2004). Critical factor in student satisfactions and success: Facilitating student role adjustment in online communities of Inquiry, Slocan-C series, CD-ROM 5.

Glatthorn, A. A., Boschee, F., & Whitehead, B. M. (2006). Curriculum leadership: Development and implementation. Thousand Oaks, CA: SAGE Publications.

Garzotto, F., Paolini, P., & Schwabe, D. (1993). Hdm—a model-based approach to hypertext application design. ACM Transactions on Information Systems, 11(1), 1–26. doi:10.1145/151480.151483 Gaytan, J., & McEwen, B. (2007). Effective online instructional and assessment strategies. American Journal of Distance Education, 21(3), 117–132. doi:10.1080/08923640701341653 Gena, C. (2005). Methods and techniques for the evaluation of user-adaptive systems. The Knowledge Engineering Review, 20(1), 1–37. doi:10.1017/S0269888905000299 Ghani, J. A., Supnick, R., & Rooney, P. (1991, December 16-18). The experience of flow in computer-mediated and in face-to-face groups. In J. I. DeGross, I. Benbasat, G. DeSanctis, & C. M. Beath (Eds.), Proceedings of the Twelfth International Conference on Information Systems, New York (pp. 229-237). ACM Publishing. Gillespie, M. (2005). Student-instructors connection: A place of possibility. Journal of Advanced Nursing, 52(2), 211–219. doi:10.1111/j.1365-2648.2005.03581.x Gillette, Y., & MacDonald, J. D. (1989). ECO resources. San Antonio, TX: Special Press. Giménez-Costa, A., & González-Bondia, A. (2007). Design of a wiki-based collaborative working strategy within the context of legal sciences. European Journal of Legal Education, 4(1), 105–114. Ginsburg, L. (1998). Integrating technology into adult learning. In C. Hopey (Ed.), Technology, basic skills, and adult education: Getting ready and moving forward (Information Series No. 372, pp. 37-45). Columbus, OH: Center on Education and Training for Employment. (ERIC Document Reproduction Service No. ED 423 420)

Glushko, R. J., Tenenbaum, J. M., & Meltzer, B. (1999). An XML framework for agent-based e-commerce. Communications of the ACM, 42(3), 106–114. doi:10.1145/295685.295720 Glynn, S. M., & Druit, R. (1995). Learning science in the schools: Research reforming practice. Mahwah, NJ: Elbaum. Gobet, F., Lane, P. C. R., Croker, S., Cheng, P. C.-H., Jones, G., Oliver, I., & Pine, J. M. (2001). Chunking mechanisms in human learning. Trends in Cognitive Sciences, 5, 236–243. doi:10.1016/S1364-6613(00)01662-4 Godwin-Jones, R. (2003). Emerging technologies: blogs and wikis: environments for on-line collaboration. Language Learning & Technology, 7(2), 12–16. Goleman, D. (1998). Working with emotional intelligence. New York: Bantam Books. Gonzalez, E. E., Garcia, F. B., & Jorge, H. A. (2007). Using a quality framework to evaluate e-Learning based Experiences. 6th European Conference on e-learning, Copenhagen. Goodman, P. S. (2002). Technology enhanced learning: opportunities for change. Mahwah, NJ: Lawrence Erlbaum Associates. Gorard, S., & Selwyn, N. (1999). Switching on the learning society? - questioning the role of technology in widening participation in lifelong learning. Journal of Education Policy, 14(5), 523–534. doi:10.1080/026809399286198 Gordon, S. (2006). Rise of the blog. IEE Review, 52(3), 32–35. doi:10.1049/ir:20060301

369

Compilation of References

Gori, M., Maggini, M., Martinelli, E., & Scarselli, F. (2000). Learning user profiles in nautilus. In AH ’00: Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, London, UK, (pp. 323–326). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag Goriparthi, T., Das, M. L., & Saxena, A. (2009). An improved bilinear pairing based remote user authentication scheme . Computer Standards & Interfaces, 31(1), 181–185. doi:10.1016/j.csi.2007.11.016 Gow, L., & Kember, D. (1993). Conceptions of teaching and their relationship to student learning. The British Journal of Educational Psychology, 63, 20–33. Graesser Graesser, A.C., Moreno, K., Marineau, J., Adcock, A., Olney, A., & Person, N. (2003). AutoTutor improves deep learning of computer literacy: Is it the dialog or the talking head? Proceedings of Artificial Intelligence in Education Graf, S., & Kinshuk (2007). Providing adaptive courses in learning management systems with respect to learning styles. In World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (eLearn 2007), pages 2576–2583. Grasha, A. (1996). Teaching with style: A practical guide to enhancing learning by understanding teaching and learning styles. Pittsburgh, PA: International Alliance of Teaching Scholars. Greenfield, P. M., & Cocking, R. (1996). Interacting with video. Norwood, NJ: Ablex. Greenhow, C., Robelia, B., & Hughes, E. (2009). Learning, teaching, and scholarship in a digital age. Educational Researcher, 38(4), 246–259. doi:10.3102/0013189X09336671 Gregorc, A. F. (1982). An adult’s guide to style. Columbia, CT: Gregorc Associates. Guba, E., & Lincoln, Y. (1989). Fourth Generation Evaluation. London: Sage.

370

Guller, J., Durndell, A., & Ross, A. (2007). Peer Interaction and crtictical thinking: Face-to-face or online discussion, 18(2), 187-200. Gulz, A., & Haake, M. (2006). Design of Animated pedagogical agents: A look at their look. International Journal of Human-Computer Studies, 64(4), 322–339. doi:10.1016/j.ijhcs.2005.08.006 Guyon, J., Moreau, P.-E., & Reilles, A. (2004). An integrated development environment for pattern matching programming. Electronic Notes in Theoretical Computer Science, 107, 33–49. doi:10.1016/j.entcs.2004.02.045 Haag, S., Cummings, M., & Philips, A. (2007). Management Information Systems for the Information Age. New York, NY: McGraw-Hill. Habermas, J. (1971). Knowledge and human interests. Boston: Beacon Press. Hadwin, F. H., Winne, P. H., & Nesbit, J. C. (2005). Roles for software technologies in advancing research and theory in educational psychology. The British Journal of Educational Psychology, 75, 1–24. doi:10.1348/000709904x19263 Halasz, F. (1988). Reflections on NoteCards: Seven Issues for the Next Generation of Hypermedia Systems. Communications of the ACM, 31(7), 836–852. doi:10.1145/48511.48514 Halavais, A. C. (2006). Weblogs and collaborative web publishing as learning spaces . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1215–1236). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_50 Hall, J. (2003). Assessing Learning Management Systems. Chief Learning Officer. Retrieved from http://www. clomedia.com/conten t/ templates/clo_feature.asp?articl eid=91&zoneid=29 Hammersley, M. (1993). Educational Research: current issues. London: Paul Chapman in association with the Open University.

Compilation of References

Hangzhou, China; Hershey, PA: ZUP and Information Science Reference. Harasim, L. (2006). A history of e-learning: Shift happened . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 59–94). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_2 Harrington, T., Staffo, M., & Wright, V. H. (2006). Faculty uses of and attitudes toward a Course management system in improving instruction. Journal of Interactive Online Learning, 5(2), 178–190. Harris, D., & Holmes, J. (1976). Open-ness and control in higher education: towards a critique of the Open University . In Dale, R., Esland, G., & MacDonald, M. (Eds.), Schooling and Capitalism: A sociological reader. London: Routledge and Kogan Page. Harris, S. L. (1994). Siblings of children with autism: A guide for families. Bethesda, MD: Woodbine House. Harris, S. L., & Glasberg, B. A. (2003). Siblings of children with autism: A guide for families (2nd ed.). Bethesda, MD: Woodbine House. Harrison, D. (2009). Engaging students in virtual learning. Retrieved April 23, 2009, from http://campustechnology. com/Articles/2009/04 /22/Engaging-Students-in-VirtualLearning Hartley, K., & Bendixen, L. D. (2001). Educational research in the Internet age: Examining the role of individual characteristics. Educational Researcher, 30(9), 22. doi:10.3102/0013189X030009022 Hartshorne, R., & Ferdig, R. E. (2006). Hypermedia applications in web-based teaching and learning environments: The role of databases as intermediaries. Electronic Journal for the Integration of Technology in Education, 5, 63–76. Harvard, B., Du, J., & Olinzock, A. (2005). Deep Learning: The knowledge, methods, and cognition process in instructor-led online discussion. Quarterly Review of Distance Education, 6(2), 125–135.

Hassanien, A. (2006). Using Webquest to Support Learning with Technology in Higher Education . Journal of Hospitality, Leisure, Sport and Tourism Education, 5(1), 41–49. doi:10.3794/johlste.51.96 Havice, W. L., & Havice, P. A. (Eds.). (2005). Distance and distributed learning environments: Perspectives and strategies: 54th yearbook of the Council on Technology Teacher Education. New York. Glencoe: McGraw-Hill. Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behaviour. Trends in Cognitive Sciences, 9(4), 188–194. doi:10.1016/j.tics.2005.02.009 Haykin, S. (1999). Neural Networks: A Comprehensive Introduction. Prentice Hall. Heller, R. B., & Procter, M. (2007). Conversational Agents and Learning Outcomes: An Experimental Investigation. Proceedings of the World Conference on Multimedia, Hypermedia, and Telecommunications. Heller, R. B., Procter, M., Mah, D., Jewell, L., & Cheung, B. (2005). Freudbot: An Investigation of Chatbot Technology in Distance Education. Proceedings of the World Conference on Multimedia, Hypermedia, and Telecommunications. Henderson, J. M., & Hollingworth, A. (1999). High-level scene perception. Annual Review of Psychology, 50, 243–271. doi:10.1146/annurev.psych.50.1.243 Henessy, S., Twigger, D., Driver, R., O’Malley, C. E., Byard, M., & Draper, S. (1995). Design of a computer-augmented curriculum for mechanics. International Journal of Science Education, 17(1), 75–92. doi:10.1080/0950069950170106 Henze, N., & Nejdl, W. (2001). Adaptation in open corpus hypermedia. International Journal of Artificial Intelligence in Education, 12(4), 325–350. Heo, H. (2004). Story telling and retelling as narrative inquiry in cyber learning environments. In R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds), Beyond the comfort zone: Proceedings of the 21st ASCILITE Conference

371

Compilation of References

Hernandez, V., Kirby, J., & McGee, S. (2004). Competency assessment in distributed education. Washington, DC: Association of Jesuit Colleges and Universities. Hernández-Gantes, V. M., & Blank, W. (2009). Teaching English language learners in career and technical education programs. New York: Routledge. Herrington, A., Herrington, J., Kervin, L., & Ferry, B. (2006). The design of an online community of practice for beginning teachers. Contemporary Issues in Teacher Education, 6(1). http://www.citejournal.org/ vol6/ iss1/ general/aricle1.cfm Hillier, Y. (2005). Reflective teaching in further and adult education (2nd ed.). London: Continuum. Hirumi, A. (2002). A framework for analyzing, designing, and sequencing planned e-learning interactions. The Quarterly Review of Distance Education, 3(2), 141–160. Hislop, G. W., & Ellis, H. J. C. (2004). A study of faculty effort in online teaching. The Internet and higher education. The Internet and Higher Education, 7(1), 15–31. doi:10.1016/j.iheduc.2003.10.001 Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. doi:10.1023/ B:EDPR.0000034022.16470.f3 Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: A response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107. Hoare, C. (Ed.). (2006). Handbook of adult development and learning. New York: Oxford. Hodges, J., & Lehmann, E. (1956). The efficiency of some non parametric competitors of the t-test. Annals of Mathematical Statistics, 35, 324–335. doi:10.1214/ aoms/1177728261 Hodges, J., & Lehmann, E. (1963). Estimates of location based on rank tests. Annals of Mathematical Statistics, 34, 598–611. doi:10.1214/aoms/1177704172

372

Hodgins, W., & Conner, M. (2000). Everything you ever wanted to know about learning standards but were afraid to ask. LiNE Zine, URL: http://www.adlnet.or g/index. cfm [last accessed on 20 November 2003], http://www.adl net.org/index.cfm [last accessed on 20 November 2003], and http://www.linezine.com/2.1/fea tures/wheyewtkls. htm [last accessed on 9 Feb. 2004]. Hofer, B., & Pintrich, P. (1997). The development of epistemological theories: Beliefs about knowledge and knowing and their relation to learning. Review of Educational Research, 67(1), 88–140. Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60, 50–68. doi:10.2307/1251841 Holcomb, J. B., Dumire, R. D., Crommett, J. W., Stamateris, C. E., Fagert, M. A., & Cleveland, J. A. (2002). Evaluation of trauma team performance using an advanced human patient simulator for resuscitation training. The Journal of Trauma Injury Infection and Critical Care, 52(6), 1078. doi:10.1097/00005373-200206000-00009 Hollan, J., Hutchins, E., & Kirsh, D. (2000). Distributed Cognition: Toward a New Foundation for HumanComputer Interaction Research. ACM Transactions on Computer-Human Interaction, 7(2), 174–196. doi:10.1145/353485.353487 Horyp, S. (2006). Reflection in learning at work . In Antonocopoulou, E., Jarvis, P., Andersen, V., Elkjaer, B., & Hoyrup, S. (Eds.), Learning, working and living (pp. 85–100). London: Palgrave Macmillan. Howard, C., Schenk, K., & Discenza, R. (2003). Distance Learning and university effectiveness: changing educational paradigms for online learning. Long Beach, USA: IGI Global. Hsu, C.-L., & Lu, H.-P. (2003). Why do people play online games? An extended TAM with social influences and flow experience. Information & Management, 41, 853–868. doi:10.1016/j.im.2003.08.014

Compilation of References

Huang, U. (2002). Toward constructivism for adult learners in online learning environments. British Journal of Educational Technology, 33(1), 27–37. doi:10.1111/14678535.00236

James, W., & Maher, P. (2004). Understanding and using learning styles. In M. Galbraith (Ed.), Adult learning methods: A guide for effective instruction (3rd ed.) (pp. 119-139). Malabar, FL: Krieger Publishing.

Hudson, B. (2002). Critical dialogue online: Personas, covenants, and candlepower. In K.E. Rudestam, & J. Schoenholt – Read (Eds.), Handbook of online learning: innovations in higher education and corporate training (pp. 53-90), London, Sage.

Janicki, T., & Liegle, J. O. (2001). Development and evaluation of a framework for creating Web-based learning modules: A pedagogical and systems approach. Journal of Asynchronous Learning Networks, 5(1).

Hung, D., Chen, D. T., & Wong, A. F. L. (2006). An overview of virtual learning environments in the AsiaPacific: Provisos, issues, and tensions . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 699–722). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_27 Imel, S. (1998). Technology and adult learning: Current perspectives (ED No. 197). Columbus, OH: ERIC Clearinghouse on Adult, Career and Vocational Education. Imel, S. (1990). Collaborative Learning in Adult Education. ERIC Digest, 113. Imel, S. (2001). Learning technologies in adult education. Myths and realities. ERIC Clearinghouse on Adult, Career, and Vocational Education, No. 17. Retrieved: 12/2008, from http://eric.ed.gov/ER ICDocs/data/ericdocs2sql/ content_storage_01/ 0000019b/80/19/83/bf.pdf Inoue, Y. (2010). Cases on online and blended learning technologies in higher education: Concepts and practices. New York: Hershey. Isenberg, S. (2007). Applying andragogical principles to internet learning. New York: Cambria Press. Itin, C. M. (1999). Reasserting the philosophy of experiential education as a vehicle for change in the 21st Century. Journal of Experiential Education, 22(2), 91–98. James, W., & Blank, W. (1993). Review and critique of available learning style instruments for adults. New Directions for adult and Ccontinuing education, 1993(59), 47-57.

Jarvis, P. (2000). Globalisation, the learning society and comparative education. Comparative Education, 36(23), 343–355. doi:10.1080/713656613 Jarvis, P., & Parker, S. (Eds.). (2005). Human learning: a holistic approach. London: Routledge. doi:10.4324/9780203463321 Jennings, D. (2005). E-learning 2.0, whatever that is. Retrieved: 12/2008, from http://alchemi.co.uk/archives/ ele/elearning_20_wh.html Jensen, J. R. (1996). Introductory Digital Image Processing: A Remote Sensing Perspective (2nd ed.). Upper Saddle River, NJ: Prentice Hall. Jensen, J. R., & Jackson, M. The Remote Sensing Process. Retrieved from http://www.cas.sc.edu/geog/r slab/Rscc/ fmod1.html JISC eLearning Programme (2003). Designing for eLearning, an overview of the eLearning and Pedagogy Strand. Johnson, W. L., Rickel, J. W., & Lester, J. C. (2000). Animated pedagogical agents: Face-to-face interaction in interactive learning environments. International Journal of Artificial Intelligence in Education, 11, 47–78. Johnson, S. A., & Romanello, M. L. (2005). Generational diversity: Teaching and learning approaches. Nurse Educator, 30(5), 212–216. doi:10.1097/00006223-20050900000009 Johnson, C. (2006). Degrees of deception: Are consumers and employers being duped by online universities and diploma mills? The Journal of College and University Law, 32(2), 101–180.

373

Compilation of References

Johnson, S. D., & Benson, A. D. (2003). Distance learning in postsecondary career and technical education. St. Paul, MN: National Research Center for Career and Technical Education. Johnson, J. (2003). Distance education: The complete guide to design, delivery and improvements. New York: Teachers College Press. Joia, L. (2001). Evaluation of a Hybrid Socio-Constructivist Model for Teacher Training. [Norfolk, VA: AACE.]. Journal of Technology and Teacher Education, 9(4), 519–549. Jonansen, D., Mayers, T., & McAleese, R. (1993). A manifesto for a constructivist approach to technology in higher education . In Duy, T., Jonassen, D., & Lowyck, J. (Eds.), Designing Constructivist Learning Environments (pp. 231–247). Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Jones, A., Kirkup, G., & Kirkwood, A. (1993). Personal computers for distance education. New York: St. Martin’s Press. Kadobayashi, R., Nishimoto, K., Sumi, Y., & Mase, K. (1998). Personalizing museum exhibition by mediating agents. In IEA/AIE ’98: Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, London, UK, (pp. 648–657), Berlin, Heidelberg, Germany/ New York, NY: Springer-Verlag.

Kandies, J., & Stern, M. B. (1999). Weaving the Web into the classroom: An evolution of Web enhanced instruction. Paper presented at the Teacher Education International Conference, San Antonio, TX. (ERIC Document Reproduction Service No. ED 432270). Kanuka, H., & Garrison, D. R. (2004). Cognitive Presence in Online Learning. Journal of Computing in Higher Education, 15(2), 30–49. doi:10.1007/BF02940928 Karacapilidis, N., & Papadias, D. (2001). Computer supported argumentation and collaborative decision making: The HERMES System. Information Systems, 26(4), 259–277. doi:10.1016/S0306-4379(01)00020-5 Karacapilidis, N., & Tzagarakis, M. (2009). Supporting Argumentative Collaboration in Communities of Practice: The CoPe_it! approach . In Karacapilidis, N. (Ed.), Solutions and Innovations in Web-Based Technologies for Augmented Learning: Improved Platforms, Tools and Applications (pp. 245–257). Hershey, PA: IGI Global. Karampiperis, P., & Sampson, D. (2005a). Adaptive learning resources sequencing in educational hypermedia systems. Journal of Educational Technology & Society, 8(4), 128–147. Karampiperis, P., & Sampson, D. (2005b). Automatic learning object selection and sequencing in web-based intelligent learning systems . In Ma, Z. (Ed.), Web-Based Intelligent e-Learning Systems: Technologies and Applications (pp. 56–71). Information Science Publishing.

Kalyuga, S. (2009). Instructional designs for the development of transferable knowledge and skills: A cognitive load perspective. Computers in Human Behavior, 25(2), 332–338. doi:10.1016/j.chb.2008.12.019

Katz, R. (2003). Balancing Technology and Tradition: The Example of Course Management Systems. EDUCAUSE Review, 38(4). Retrieved from http://www.educause.edu/ lr/lib rary/pdf/erm0343.pdf.

Kalyuga, S. (2009). Managing cognitive load in adaptive multimedia learning. New York: Hershey.

Katz, R. N. (Ed.). (1999). Dancing with the devil: information technology and the new competition in higher education. San Francisco: Jossey-Bass Higher and Adult Education Series.

Kamba, T., Sakagami, H., & Koseki, Y. (1997). ANATAGONOMY: A personalized newspaper on the World Wide Web. International Journal of Human-Computer Studies, 46(6), 789–803. doi:10.1006/ijhc.1996.0113

374

Kavcic, A. (2004). Fuzzy user modeling for adaptation in educational hypermedia. IEEE Transactions on Systems, Man, and Cybernetics, 34(4), 439–449. doi:10.1109/ TSMCC.2004.833294

Compilation of References

Kay, J. (1999) Ontologies for reusable and scrutable student model. in Proceedings of AIED99 Workshop on Ontologies for Intelligent Educational Systems, 1999. Kayler, M., & Weller, K. (2007). Pedagogy, self-assessment, and online discussion groups. Journal of Educational Technology & Society, 10(1), 136. Kemery, E. (2000). Developing On-Line Collaboration, Chapter . In Aggarwal, A. K. (Ed.), Web-Based Learning and Teaching Technologies: Opportunities and Challenges. Hershey, PA: Idea Group Publishing. Kennedy, G. E., Judd, T. S., Churchward, A., Gray, K., & Krause, K. L. (2008). First year students’ experiences with technology: Are they really digital natives. Australasian Journal of Educational Technology, 24(1), 108–122. Kenny, G., Pontin, D., & Moore, L. (2004). Negotiating socialisation: The journey of novice nurse academics into higher education. Nurse Education Today, 24(8), 629–637. Kim, K., & Bonk, C. J. (2006). The future of online teaching in higher education: The survey says… EDUCAUSE Quarterly, Issue Number 4. King, K. P. (2005). Bringing transformative learning to life. Malabar, FL: Krieger Publishing Company. King, K. P. (2008). Distance education. In L. M. English (Ed.), International encyclopedia of adult education (192199). New York: Palgrave Macmillan. Kings, N. J., Davies, J., Verrill, D., Aral, S., Bryniolfsson, E., & Alstyne, M. V. (2008). Social networks, social computing and knowledge management . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 17–26). Chichester, UK: John Wiley & Sons. Kirkwood, A., & Price, L. (2006). Adaptation for a Changing Environment: Developing learning and teaching with information and communication technologies. International Review of Research in Open and Distance Learning, 7(2).

Kirschner, F., Paas, F., & Kirschner, P. A. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25(2), 306–314. doi:10.1016/j. chb.2008.12.008 Kirschner, P., Buckingham Shum, S., & Carr, C. (2003). Visualizing Argumentation: Software Tools for Collaborative and Educational Sense-Making. New York: Springer. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. doi:10.1207/ s15326985ep4102_1 Knowles, M. S. (1970). The modern practice of adult education: Andragogy vs. pedagogy. New York: Association Press. Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press. Knowles, M. S., Holton, E., & Swanson, A. (2005). The adult learner (6th ed.). Boston: Elsevier Butterworth Heinemann. Knowles, M. S. (1980). The modern practice of adult education: From andragogy to pedagogy. Englewood Cliffs, NJ: Cambridge Adult Education. Knowles, M. S. (1980). The modern practice of adult education: From pedagogy to andragogy (2nd ed.). New York: Cambridge Books. Knowles, M. (1984). The Adult Learner: A Neglected Species. 3rd Ed edn, Gulf Publishing, Houston. Knowles, M. S. (1990). The modern practice of adult education: From pedagogy to andragogy. New York: Cambridge. Knublauch, H. (2003). An AI tool for the real world Knowledge modeling with Protégé. In Java World, June 20, 2003

375

Compilation of References

Knublauch, H. (2006). Ontology-Driven Software Development in the Context of the Semantic Web: An Example Scenario with Protégé/OWL. Presented at the International Workshop on the Model-Driven Semantic Web, Monterey, CA (2004) Knublauch, H., Fergerson, R. W., Noy, N. F., & Musen, M. A. (2004)The Protégé OWL Plugin: An Open Development Environment for Semantic Web Applications. Presented at the Third International Semantic Web Conference, Hiroshima, Japan (2004) Knublauch, H., Musen, M. A., & Rector, A. L. (2004). Editing Description Logic Ontologies with the Protégé OWL Plugin. Presented at the International Workshop on Description Logics, Whistler, BC, Canada (2004)

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Upper Saddle River, NJ: Prentice-Hall. Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall. Kolb, D. A. (1984). Experiential learning. Englewood Cliffs, NJ: Prentice Hall. Koohang, A., & Harmon, K. (2005). Open source: A metaphor for e-learning. Informing Science Journal, 8, 76–86. Koohang, A. (2004). Creating learning objects in collaborative e-learning settings. Issues in Information Systems, 5(2), 584–590.

Kobsa, A., Koenemann, J., & Pohl, W. (2001). Personalised hypermedia presentation techniques for improving online customer relationships. The Knowledge Engineering Review, 16(2), 111–155. doi:10.1017/S0269888901000108

Kools, S., McCarthy, M., Durham, R., & Robrecht, L. (1996). Dimensional Analysis: Broadening the conception of grounded theory. Qualitative Health Research, 6(3), 312–330. doi:10.1177/104973239600600302

Koda, T., & Maes, P. (1996). Agents with faces: The effect of personification. Proceedings of the 5th IEEE International Workshop on Robot and Human Communication.

Koper, R. (2004). Use of the semantic web to solve some basic problems in education. Journal of Interactive Media in Education, 6, 1–23.

Kodama, M. (2008). New knowledge creation through ICT dynamic capability. Charlotte, NC: Information Age Publishing.

Koper, R., & Olivier, B. (2004). Representing the learning design of units of learning. Journal of Educational Technology & Society, 7, 97–111.

Koehler, M. J., & Mishra, P. (2005a). Instructors learning technology by design. Journal of Computing in Instructors Education, 21(3), 94–102.

Koper, R., & Tattersall, C. (2004). New directions for lifelong learning using network technologies. British Journal of Educational Technology, 35(6), 689–700. doi:10.1111/j.1467-8535.2004.00427.x

Koehler, M. J., & Mishra, P. (2005b). What happens when instructors design educational technology? The development of technological pedagogical content knowledge. Journal of Educational Computing Research, 32(2), 131–152. doi:10.2190/0EW7-01WB-BKHL-QDYV Koenig, G., & Weser, Th. A (n.d.). Servlet based training course for Remote Sensing. Commission VI, WG VI/2-4-1. Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Upper Saddle River, NJ: Prentice-Hall.

376

Koppenhaver, G., Blackburn, V., Palan, K., Ravenscroft, S., & Shrader, C. B. (2007). Student/Faculty connections in the development of teaching. Decision Sciences Journal of Innovative Education, 5(2), 373–378. doi:10.1111/j.15404609.2007.00146.x Kosba, E., Dimitrova, V., & Boyle, R. (2004). Using fuzzy techniques to model students in web-based learning environments. Int. J. Artif. Intell. Tools Special Issue on AI Techniques in Web-Based Educational Systems, 13(2), 279–297.

Compilation of References

Kosba, E., Dimitrova, V., & Boyle, R. (2007). Adaptive feedback generation to support teachers in web-based distance education. User Modeling and User-Adapted Interaction, 17(4), 379–413. doi:10.1007/s11257-0079031-z Koschmann, T. D. (1994). Towards a theory of computer support for collaborative learning. Journal of the Learning Sciences, 3, 219–226. doi:10.1207/s15327809jls0303_1 Kothari, D. P., Jain, S. K., Khurana, A., & Saxena, A. (2001). Developing a Marketing Strategy for Global Online Customers . International Journal of E-Business Strategy Management, 2(4), 301–305. Kotrlik, J., & Redmann, D. (2005). Extent of technology integration in instruction by adult basic education teachers. Adult Education Quarterly, 55(3), 200–219. doi:10.1177/0741713605274630 Kozleski, E. (2004, August). Technology Transfer and the Field of Education. Comparative Technology Transfer and Society, 2(2), 176–194. doi:10.1353/ctt.2004.0017 Kraemer, E. W. (2003). Developing the online learning environment: The pros and cons of using WebCT. Information Technologies and Libraries, 22(2), 87–92. Kreijns, K., Kirschner, P. A., Jochems, W., & Van Buuren, H. (2004). Determining sociability, social space, and social presence in (a) synchronous collaborative groups. Cyber-psychology & Behavior: The Impact of the Internet . Multimedia and Virtual Reality on Behavior and Society, 7(2), 155–172. Krentler, K. A., Willis-Flurry, L. A., & Washington, J. (2005). Does Technology Enhance Actual Student Learning? The Case of Online Discussion Boards. Journal of Education for Business, 80(6), 316–322. doi:10.3200/ JOEB.80.6.316-321 Krichen, J. P. (2004). Online university administration: Impacts on instructors’ management and course delivery. Retrieved from http://www.decadeconsulting.com/ decade/images/Jkrichen.pdf

Kunz, W., & Rittel, H. (1970). Issues as Elements of Information Systems. Technical Report 0131, Universität Stuttgart, Institut für Grundlagen der Planning. Lacity, C. M., & Janson, A. M. (1994). Understanding qualitative data: A framework of text analysis methods. Journal of Management Information Systems, 11(2), 137–155. Lai, H. C. (1994). Children’s concepts of water cycle and the forms of substances. Master thesis, National Taiwan Normal University, Taipei, Taiwan. Lamb, B. (2004). The Standard Wiki Overview. EDUCASEUSE Review, 39(5), 36–48. Lamb, M. E. (1987). The father’s role: Cross-cultural perspectives. Hillsdale, NJ: Erlbaum. Lane, L. (2009). Insidious pedagogy: How course management systems affect teaching. First Monday, 14(10). Laudon, K., & Laudon, J. (2010). Management Information Systems – Managing Digital Firm (11th ed.). Upper Saddle River, NJ: Prentice Hall. Laurillard, D. (1993). Rethinking University Teaching a Framework for the Effective Use of Educational Technology. London: Routledge. Laurillard, D. (1993). Rethinking university teaching: A framework for the effective use of educational technology. London: Routledge. Laurillard, P. D. (1993). Rethinking university teaching. A framework for the effective use of educational technology. London: Routledge. Lee, G., & Su, S. Y. W. (2006). Learning object models and an e-learning service infrastructure. International Journal of Distance Education Technologies, 4(1), 1–16. Leiner, B., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., et al. (2003). A brief history of the internet. Retrieved March 11, 2009, from http://www. isoc.org/internet /history/brief.shtml

377

Compilation of References

Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A., & Bhogal, R. S. (1997). The persona effect: Affective impact of animated pedagogical agents. In S. Pemberton (Ed.), Human Factors in Computing Systems: CHI’97Conference Proceedings. New York: ACM Press. Lester, J. C., Converse, S. A., Stone, B. A., Kahler, S. E., & Barlow, S. T. (1997). Animated pedagogical agents and problem solving effectiveness: A large-scale empirical evaluation. In Proceedings of the Eighth World Conference on Artificial Intelligence in Education. Leuf, B., & Cunningham, W. (2001). The WIKI WAY. Quick Collaboration of the Web. Addison-Wesley. Leutner, D., Leopold, C., & Sumfleth, E. (2009). Cognitive load and science text comprehension: Effects of drawing and mentally imagining text content. Computers in Human Behavior, 25(2), 284–289. doi:10.1016/j.chb.2008.12.010 Levy, S., Kim, A., & Olive, M. L. (2006). Interventions for young children with autism: A synthesis of the literature. Focus on Autism and Other Developmental Disabilities, 21(1), 55–62. doi:10.1177/10883576060210010701 Lewis, J. R. (1995). IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use. International Journal of Human-Computer Interaction, 7(1), 57–78. Li, P., Santhanam, R., & Carswell, C. M. (2009). Effects of Animations in Learning—A Cognitive Fit Perspective. Decision Sciences Journal of Innovative Education, 7(2), 377–410. doi:10.1111/j.1540-4609.2009.00227.x Li, L., Shi, H., Shang, Y., & Chen, S.-S. (2003). Open learning objects for data structure course. Journal of Computing Sciences in Colleges, 18(4), 56–64. Li, Q., & Akins, M. (2004). Sixteen myths about online teaching and learning in higher education: Don’t believe everything you hear. TechTrends, 49(4), 51–60. doi:10.1007/BF02824111 Light, G., & Cox, R. (Eds.). (2001). Learning and teaching in higher education: the reflective professional. London: Routledge.

378

Limongelli, C., Sciarrone, F., & Vaste, G. (2009). An Application of the LS-Plan System to an Educational Hypermedia. International Journal of Web-Based Learning and Teaching Technologies, 4(1), 16–34. Limongelli, C., Sciarrone, F., Temperini, M., & Vaste, G. (2008a). Lecomps5: a framework for the automatic building of personalized learning sequences. In Proc. of Word summit on the Knowledge Society WSKS 2008, LNCS 5288, pages 296-303. Springer Berlin/Heidelberg. Limongelli, C., Sciarrone, F., Temperini, M., & Vaste, G. (2008b). Lecomps5: a web-based learning system for course personalization and adaptation. In Proceedings of the IADIS Multi Conference on Computer Science and Information Systems, e-Learning 2008, pages 325–332. Limongelli, C., Sciarrone, F., Temperini, M., & Vaste, G. (2009). Adaptive learning with the LS-Plan system: a field evaluation. In IEEE Transactions on Learning Technologies, 2(3), 203-215. Limongelli, C., Sciarrone, F., & Vaste, G. (2008). Ls-plan: An effective combination of dynamic courseware generation and learning styles in web-based education. In Proc. of 5-th Int. Conf. on Adaptive Hypermedia and Adaptive Web-Based Systems AH 2008, LNCS 5149, pages 133-142. Lin, C. H. (1998). The study of individual differences and automated learning strategies in hypertext learning environment. Journal of National Hsinchu Teachers College, 11, 1–14. Lin, S. (1995). A study on students’ concepts of evaporation and condensation in elementary schools. Technical report. Taipei, Taiwan: National Science Council. Lin, F., Holt, P., Leung, S., & Li, Q. (2006). A Multiagent and Service-Oriented Architecture for Developing Adaptive e-learning Systems. International Journal of Continuing Engineering Education and Lifelong Learning, 16, 70–91. doi:10.1504/IJCEELL.2006.008919

Compilation of References

Lin, C. S., & Kuo, M. S. (2005, July 5-8). Adaptive networked learning environments using learning objects, learner profiles and inhabited virtual learning worlds. The 5th IEEE International Conference on Advanced Learning Technologies, Kaohsiung, Taiwan. Lindquist, E. F. (Ed.). (1996). Educational Measurement. Washington, DC: American Council on Education. Litzinger, T. A., Lee, S. H., Wise, J. C., & Felder, R. M. (2005). A Study of the Reliability and Validity of the Felder-Soloman Index of Learning Styles. In Proc. of the 2005 American Society for Engineering Education Annual Conference and Exposition. Long, P. D., & Ehrmann, S. C. (2005). Future of the Learning Space: Breaking Out of the Box. EDUCAUSE Review, 40(4), 42–58. Lopez, A. K., & Willis, G. D. (2004). Descriptive versus Interpretive phenomenology: Their contribution to nursing knowledge. Qualitative Health Research, 14(5), 726–735. doi:10.1177/1049732304263638 Lorenzetti, J. P. (2003). Thirty-two distance education trends. Distance Education Report, 7(21), 1–6. Louwerse, M. M., Graesser, A. C., Lu, S., & Mitchell, H. H. (2005). Social cues in animated conversational agents. Applied Cognitive Psychology, 19, 693–704. doi:10.1002/acp.1117 Lu, H., Jia, L., Gong, S., & Clark, B. (2007). The relationship of Kolb Learning Styles, online learning behaviors, and learning outcomes. Educational Technology & Society, 10(4), 187–196. Luke, C. (2006). Cyberpedagogy . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 269–278). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_10

Lundberg, J., Castillo, D., & Dahmani, M. (2008). “Do online students perform better than face-to-face students? Reflections and a short review of some empirical findings”. In “The Economics of E-learning” - Revista de Universidad y Sociedad del Conocimiento (RUSC).1 (5) UOC. Retrieved May 27, 2009, from http://www.uoc.edu/ rusc/5/1/dt /eng/lundberg_castillo_dahmani.pdf MacIntosh, J. (2003). Reworking professional nursing identity. Western Journal of Nursing Research, 25(6), 725–741. doi:10.1177/0193945903252419 MacKenzie, D., & Wacjman, J. (Eds.). (1985). The social shaping of technology. London: Open University Press. Madhuri, L., & Nair, T. R. Goplakrishnana, (2010). Authentication and Authorization in Server Systems for Bio-Informatics, International Conference, Teamteach, Bangalore. Magjuka, R. J., Shi, M., & Bonk, C. J. (2005). Critical design and administrative issues in online education. Online Journal of Distance Learning Administration, 8(4), Article 4. Retrieved April 28, 2009, from http://www. westga.edu/~distance/ojdla /winter84/magjuka84.htm Maguire, L. L. (2005). Faculty participation in online distance education: Barriers and motivators. Online Journal of Distance Learning Administration, 8(1). Retrieved from http://www.westga.edu/~distance/ ojdla/spring81/ maguire81.htm. Manen, M. (1990). Researching Lived Experience. USA: The State University of New York. Manner, J. (2005). Accommodating diverse learning styles with online course enhancements. Journal of Interactive instruction . Development, 17(4), 19–21. Marshall, C., & Shipman, F. M. (1995). Spatial hypertext: designing for change. Communications of the ACM, 38(8), 88–97. doi:10.1145/208344.208350 Marshall, C., & Shipman, F. M. (1997). Spatial Hypertext and the Practice of Information Triage. In Proceedings of the 8th ACM Conference on Hypertext, pp. 124-133.

379

Compilation of References

Martin, K., Quigley, M. A., & Rogers, S. (2005). Implementing a learning management system globally: An innovative change management approach. IBM Systems Journal, 44(1), 125–143. doi:10.1147/sj.441.0125

McCrory, R., Putnam, R., & Jansen, A. (2008). Interaction in Online Courses for Teacher Education: Subject Matter and Pedagogy. [Chesapeake, VA: AACE.]. Journal of Technology and Teacher Education, 16(2), 155–180.

Marucci, L., & Paterno, F. (2000). Designing an adaptive virtual guide for web applications. In Proc. of 6th ERCIM Workshop User Interfaces for Al l, Firenze, Italy, (pp. 57-67).

McGarr, O. (2009). A review of podcasting in higher education: Its influence on the traditional lecture. Australasian Journal of Educational Technology, 25(3), 309–321.

Marwick, A. D. (2001). Knowledge management technology. IBM Systems Journal, 40(4), 814-830. Retrieved October 2, 2007, from http://www.research.ibm.com / journal/sj/404/marwik.html Masthoff, J. (2003). The evaluation of adaptive systems . In Patel, N. V. (Ed.), Adaptive evolutionary information systems (pp. 329–347). Idea Group publishing. Mather, P. (1999). Computer processing of remotely sensed images, An introduction. New York: Wiley. Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds. Journal of Educational Psychology, 95(4), 806–813. doi:10.1037/0022-0663.95.4.806 Mayer, R. E., Sobko, K., & Mautone, P. D. (2003).. . Journal of Educational Psychology, 95(2), 419–425. doi:10.1037/0022-0663.95.2.419 McCarty, S., Ibrahim, B., Sedunov, B., & Sharma, R. (2006). Global online education . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 723–788). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_28 McCombs, B. L., & Lauer, P. A. (1997). Development and validation of the learner-centered battery: Self-assessment tools for teacher reflection and professional development. Professional Educator, 20(1), 1–21. McCombs, B. L., & Vakili, D. (2005). A learnercentered framework for e-learning. Teachers College Record, 107(8), 1582–1600. doi:10.1111/j.14679620.2005.00534.x

380

McGovern, G. (2000). Clutter versus clicking in web design, The ClickZ Network. Retrieved from http://www. clickz.com/sh ow Page.html?page=826531 McLoughlin, C., & Lee, M. J. W. (2010). Personalised and self regulated learning in the Web 2.0 era: International exemplars of innovative pedagogy using social software. Australasian Journal of Educational Technology, 26(1), 28–43. McTighe, J., & Wiggins, G. (1999). The understanding by design. Alexandria, VA: Association for Supervision and Curriculum Development. Merriam, S. B., & Brockett, R. G. (2007). The profession and practice of adult education: An introduction. San Francisco: Jossey-Bass. Merriam, S. B. (2001a). Andragogy and self-directed learning: Pillars of adult learning theory. New Directions for Adult and Continuing Education, 89, 3–13. doi:10.1002/ace.3 Merriam, S. B. (Ed.). (2001b). The new update on adult learning theory. New directions for adult and continuing education. San Fransisco. Jossey-Bass. Merriam, S. B. (Ed.). (2008). Third update on adult learning theory: New directions for adult and continuing education (Vol. 119). San Francisco: Jossey-Bass. Merriam, S. B., & Cafarella, R. S. (1999). Learning in adulthood: a comprehensive guide (2nd ed.). San Francisco: Jossey-Bass. Merriam, S. B., Caffarella, R. S., & Baumgartner, L. M. (2007). Learning in adulthood: A comprehensive guide (3rd ed.). San Francisco: Jossey Bass.

Compilation of References

Merriam, S., Caffarella, R., & Baumgartner, L. (2007). Learning in adulthood: A comprehensive guide (3rd ed.). San Francisco: Jossey-Bass.

Mizoguchi, R., & Bourdeau, J. (2000). Using ontological engineering to overcome AI-ED problems. International Jounal of Engineering Education, 11, 107–121.

Mezirow, J. (1990). Fostering critical reflection in adulthood: A guide to transformative and emancipatory learning. San Francisco: Jossey-Bass.

Moneta, G. B., & Csikszentmihalyi, M. (1996). The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality, 64(2), 275–310. doi:10.1111/j.1467-6494.1996.tb00512.x

Mezirow, J. (1991). Transformative dimensions of adult learning. San Francisco: Jossey-Bass. Mezirow, J. (Ed.). (2000). Learning as transformation: Critical perspectives on a theory in progress. San Francisco: Jossey-Bass. Mezirow, J. (1985). A critical theory of self-directed learning . In Brookfield, S. (Ed.), Self-directed learning: From theory to practice: New directions for continuing education, no. 25. San Francisco: Jossey-Bass. Miflin, B. (2004). Adult learning, self-directed learning and problem-based learning: Deconstructing the connections. The entity from which ERIC acquires the content, including journal, organization, and conference names, or by means of online submission from the author. Teaching in Higher Education, 9(1), 43–53. doi:10.1080/1356251032000155821 Mikropoulos, T. A., & Strouboulis, V. (2004). Factors that influence presence in educational virtual environments. Cyberpsychology & Behavior, 7(5), 582–591. Miles, M., & Huberman, A. M. (2004). Qualitative Data Analysis. Thousand Oaks, CA: Sage Publications. Miller, L. (2005). Using learning styles to evaluate computer-based instruction. Computers in Human Behavior, 21(2), 287–306. doi:10.1016/j.chb.2004.02.011

Moore, M. G. (1995). American distance education . In Lockwood, F. (Ed.), Open and distance learning today (pp. 32–41). London: Routledge. Moreno, R., & Mayer, R. E. (2000). Engaging students in active learning: the case for personalized multimedia messages. Journal of Educational Psychology, 92(4), 724–733. doi:10.1037/0022-0663.92.4.724 Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610. doi:10.1037/0022-0663.94.3.598 Moreno, R., & Mayer, R. E. (2004). Personalized messages that promote science learning in virtual environments. Journal of Educational Psychology, 96(1), 165–173. doi:10.1037/0022-0663.96.1.165 Moreno, R., & Mayer, R. E. (2005). Role of guidance, reflection, and interactivity in an agent-based multimedia game. Journal of Educational Psychology, 97(1), 117–128. doi:10.1037/0022-0663.97.1.117 Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177–213. doi:10.1207/S1532690XCI1902_02

Mitchener, J. (2008). Device Futures . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 27–38). Chichester, UK: John Wiley & Sons.

Morgan, G. (2003). Faculty Use of Course management Systems. ECAR, Educause Center for Applied Research, May.

Mitrovic, A. (2003). An intelligent SQL tutor on the Web. International Journal of Artificial Intelligence in Education, 13, 173–197.

Morris, P., & Jamieson, A. (2004). Translating Corporate Strategy into Project Strategy: Realizing Corporate Strategy Through Project Management. Project Management Institute.

381

Compilation of References

Mott, V. W. (2004). Book review: Learner-centered teaching: Five key changes to practice. Adult Education Quarterly, 54(3), 244–245. doi:10.1177/0741713604263058 Mott, V. W. (2008). Learner-derived curriculum development. In V. C. X. Wang (Ed.), Curriculum development for adult learners in the global community volume I: Strategic approaches (pp. 58-78). Malabar, FL: Krieger Publishing Company. Mott, V. W. (2009). Evolution of adult education: Is our future in e-learning? In V. C. X. Wang (Ed.), Handbook of research on e-learning applications for career and technical education: Technologies for technical training (pp. 778-791). Hershey, PA: IGI Global. Moundridou, M., & Virvou, M. (2002). Evaluating the persona effect of an interface agent in a tutoring system. Journal of Computer Assisted Learning, 18, 253–261. doi:10.1046/j.0266-4909.2001.00237.x Muilenburg, L., & Berge, Z. L. (2000). A Framework for Designing Questions for Online Learning. Retrieved from http://emoderato rs.com/mode rators/muilenburg.html Muniz-Solaris, O. A., & Coats, C. (2009). Integrated networks: National and international online experiences. The International Review of Research in Open and Distance Learning, 10(1). Retrieved August 20, 2009, from http:// www.irrodl.org/index.php /irrodl/issue/view/33 Murphy, E. (2004). An instrument to support thinking critically about critical thinking in online asynchronous discussions. Australasian Journal of Educational Technology, 20(3), 295–315. Murray, W. S., & Le Blanc, L. (1995). A Decision Support System for Academic Advising, in 1995 ACM Symposium on Applied Computing, Nashville, TN, USA, 1995. Myers, I. B. (1993). Gifts differing: Understanding personality type. Palo Alto, CA: CPP Books. Naidu, S. (Ed.). (2003). Learning & Teaching with Technology: Principles and Practices. Open and Distance Learning Series. London: Routledge.

382

National Center for Education Statistics. (2000). Distance education at postsecondary education institutions: 19971998 (NCES Publication No. 2003-013). Washington, DC: U.S. Government Printing Office. National Center for Education Statistics. (2002). A profile of participation in distance education: 1999-2000 (NCES Publication No. 2003-154). Washington, DC: U.S. Government Printing Office. Neal, A., & Winnipeg, M. (1995). Group apraxia: The phenomenology of acculturalism. The Canadian Journal of Native Studies, 10(2), 219–242. Newman, M. (2006). Teaching defiance. San Francisco: Jossey-Bass. Nielsen, J., & Loranger, H. (2006). Prioritizing Web Usability. Thousand Oaks, CA, USA: New Riders Publishing. Nilssen, A., & Greenberg, A. (July 2006). The vital role of web conferencing in small and medium enterprises. Live Oak, FL: Wainwright Research. Nonaka, I. (2005). Knowledge management: critical perspectives on business and management. Boca Raton, FL: Taylor & Francis. Northedge, A. (1976). Examining our implicit analogies for learning processes. Programmed Learning and Educational Technology, 13(4), 67–78. Novak, J. D. (1988). Learning science and the science of learning. Studies in Science Education, 15, 77–101. doi:10.1080/03057268808559949 Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–44. doi:10.1287/mksc.19.1.22.15184 Novak, J. D. (2003). The promise of new ideas and new technology for improving teaching and learning. Life Sciences Education, 2(2), 122–132. Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13(1,2), 3-16.

Compilation of References

Novak, T. P., Hoffman, D. L., & Yung, Y. F. (1998). Modeling the structure of the flow experience. Paper presented at the INFORMS Marketing Science and the Internet Mini-Conference, Boston, MA. O’Day, V. L., Ito, M., Adler, A., Linde, C., & Mynatt, E. D. (2006). Cemeteries, oak trees, and black and white cows: Newcomers’ understandings of the networked world . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 873–894). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_32 O’Lawrence, H. (2007). An overview of the influences of distance learning on adult learners. Journal of Education and Human Development, 1(1), 7. Retrieved March 12, 2009, from http://www.scientificjournals.org /journals2007/articles/1041.htm O’Reilly, T. (2005). What Is Web 2.0. Retrieved: 1/2008, from http://www.oreillynet.co m/pub/a/oreilly/tim/ news/2005/09/30/wha t-is-web-20.html Oblinger, D., & Oblinger, J. (2005). Educating the net generation (1st ed.). Retrieved from http://www.educause. edu /educatingthenetgen OECD. (2005). E-learning in tertiary education. Where do we stand?Paris: OECD Publications. OECD. (2005). Promoting adult learning. Retrieved March 14, 2009, from http://www.oecd.org/document/57/0,334 3,en_2649_39263238_36675769_1_1_ 1_1,00.html Office of Technology Assessment. U.S. Congress. (1995). Teachers and technology: Making the connection. OTA report summary. Washington, DC: Government Printing Office. (ERIC Document Reproduction Service No. ED 386 154) Olgren, C. H. (2000). Learning strategies for learning technologies . In Burge, E. J. (Ed.), The strategic use of learning technologies: New directions for adult continuing education, no. 88 (pp. 7–16). San Francisco: Jossey-Bass.

Oliver, M. (1998). Innovation in the Evaluation of Learning Technology. London: University of North London press. Olle, T. W. (2004). Eight significant events in the 50 year history of computing . In Impagliazzo, J., & Lee, J. A. N. (Eds.), History of computing in education (pp. 47–56). Dordrecht, The Netherlands: Kluwer. doi:10.1007/14020-8136-7_5 OMG MDA. (2008). Object Management Group: Model Driven Architecture, http://www.omg.org/mda Open University. (2009). About the OU. Retrieved March 11, 2009, from http://www.open.ac.uk/ about/ou/p3.shtml Osbome, R. J., & Cosgrove, M. M. (1983). Children’s conception of changes of state of water. Journal of Research in Science Teaching, 27, 825–838. Ozonoff, S., & Cathcart, K. (1998). Effectiveness of a home program intervention for young children with autism. Journal of Autism and Developmental Disorders, 28, 25–32. doi:10.1023/A:1026006818310 Pace, S. (2003). A grounded theory of the flow experiences of Web users. International Journal of Human-Computer Studies, 60, 327–363. doi:10.1016/j.ijhcs.2003.08.005 Pal, S. K., Aha, D. W., & Gupta, K. M. (2006). Case-Based Reasoning in Knowledge Discovery and Data Mining. New York, NY, USA: John Wiley & Sons. Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace. San Francisco: Jossey-Bass. Palloff, R. M., & Pratt, K. (2003). The virtual student: A profile and guide to working with online learners. San Francisco: Jossey-Bass. Paloff, R. M., & Pratt, K. (2001). Lessons from the cyberspace classroom:The realities of online teaching. San Francisco: Jossey-Bass. Papanikolaou, K., Grigoriadou, M., Magoulas, G. D., & Kornilakis, H. (2002). Towards new forms of knowledge communication: the adaptive dimension of a web-based learning environment. Computers & Education, 39, 333–360. doi:10.1016/S0360-1315(02)00067-2

383

Compilation of References

Partlow, K. M., & Gibbs, W. J. (2003). Indicators of constructivist principles in Internet-based courses. Journal of Computing in Higher Education, 14(2), 68–97. doi:10.1007/BF02940939

Pelgrum, W. J., & Anderson, R. E. (Eds.). (1999). ICT and the emerging paradigm for lifelong learning. Amsterdam: IEA.

Pascarella, E., & Terenzini, P. (1991). How college affects students: Findings and insights from twenty years of research. San Francisco, CA: Jossey Bas.

Perkins, C., & Murphy, E. (2006). Indentifying and measuring individual engagement in critical think in online discussions: an exploratory case study. Journal of Educational Technology & Society, 9(1), 298–307.

Pask, G. (1976). Styles and Strategies of Learning. The British Journal of Educational Psychology, 46, 128–148.

Perkins, D. (1993). Teaching for understanding. American Educator, 17(3), 28–35.

Patrinos, H. A. (1995). The Private Origins of Public Higher Education in Greece. Journal of Modern Greek Studies, 13, 179–200.

Perry, B., & Edwards, M. (2005). Exemplary online educators: Creating a community of Inquiry. Turkish online . Journal of Distance Education, 6(2), 1–8.

Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Newbury Park, CA: Sage Publications, Inc.

Pettitt, J. M. (2002). Power relationships in two web-based courses. Raleigh, NC: North Carolina State University. (ERIC Document Reproduction Service No. ED471832)

Pauling, B. (2006). Virtual learning environments in higher education “down under” . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 609–652). Dordrecht, The Netherlands: Springer. doi:10.1007/9781-4020-3803-7_24

Phillips, B., & Lee, W. (2005). Interactive Animation: Exploring spokes-characters on the Internet. Journal of Current Issues and Research in Advertising, 27.

Paulson, K. (2002). Reconfiguring faculty roles for virtual settings. The Journal of Higher Education, 73, 123–141. doi:10.1353/jhe.2002.0010 Paulson, K. (2002). Reconfiguring Faculty Role for Virtual Settings, The Journal of Higher Education. Retrieved from http://muse.jhu.edu/demo/journ al_of_higher_education/ v073/73.1paulson.pdf Payne, D. (2008). The future all optical network—why we need it and how we get there . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 93–114). Chichester, UK: John Wiley & Sons. Pearson, I. (2008). Over the horizon . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 215–226). Chichester, UK: John Wiley & Sons.

384

Phipps, R., & Merisotis, J. (1999). What’s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington, DC: The Institute for Higher Education Policy. Pinto, H., & Martins, J. (2003). A methodology for ontology integration. In the Proceedings of the 1st international conference on Knowledge capture, pp 131 – 138, ACM 2001 Piskurich, G. M. (Ed.). (2003). Preparing learners for e-learning. San Francisco: Jossey-Bass. Pont, B., & Sweet, R. (2006). ICT and learning: Supporting out-of-school youth and adults. Paris: Organisation for Economic Cooperation and Development. Popolov, D., Casllaghan, M., & Luker, P. (2002). Tying models of learning to desing of collaborativelearning software tools. Journal of Computer Assisted Learning, 18(1), 46–47. doi:10.1046/j.0266-4909.2001.00207.x Porter, L. R. (1997). Creating the virtual classroom: Distance learning with the Internet. New York: John Wiley.

Compilation of References

Pratt, D. D. (1998). Five perspectives on teaching in adult and higher education. Melbourne: Krieger Publishing. Putnam, R. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6, 65–78. doi:10.1353/jod.1995.0002 Puzziferro, M., & Shelton, K. (2008). A model for developing high-quality online courses: Integrating a systems approach with learning theory. Journal of Asynchronous Learning Environment Learning Networks, 12(3). Retrieved from http://sloanconsortium.org/node/1409. Qi, J., & Vandersall, K. (2007). Facilitating reflective practice for pre-service teachers through electronic portfolio development. In C. Crawford et al. (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference 2007 (pp. 2609-2616). Chesapeake, VA: AACE. Quinsee, S., & Hurst, J. (2005). Blurring the boundaries? Supporting students and staff within an online learning environment (ERIC Document Reproduction Service No. ED494786). Retrieved on April 28, 2009, from http://www.eric.ed.gov/ERICWebPortal/Home.portal?_ nfpb=true&_pageLabel=basic&Clearme=true Quitadamo, J., & Kurtz, M. J. (2007). Learning to Improve: Using Writing to Increase Critical Thinking Performance in General Education Biology. CBE Life Sciences Education, 6(2), 140–154. doi:10.1187/cbe.06-11-0203 Qvotrup, L. (2006). Knowledge, education and learning. E-learning in the knowledge society. Frederiksberg, Denmark: Samfudsliteratur Roskilde Universitets Forlag. Rapin, I. (2002). The autistic-spectrum disorders. The New England Journal of Medicine, 347(5), 302–303. doi:10.1056/NEJMp020062 Razmerita, L., Angehrn, A., & Maedche, A. Ontology based user modeling for Knowledge Management Systems. In the User Modeling Conference, Pittsburgh, USA, 2003, pp. 213-217.

Rector, A. (2003) Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In the Proceedings of the 2nd international conference on Knowledge capture, pp 121 – 128, ACM (2003) Rector, A., Drummond, D., Horridge, M., Rogers, J., Knublauch, H., Stevens, R., et al. (2004). OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns. Presented at the 14th International Conference on Knowledge Engineering and Knowledge Management (EKAW), Whittlebury Hall, Northamptonshire, UK (2004) Reed, C. A., & Rowe, G. W. A. (2004). Araucaria: Software for Argument Analysis, Diagramming and Representation. International Journal of AI Tools, 14(3-4), 961–980. doi:10.1142/S0218213004001922 Reeves, B., & Nass, C. I. (1996). The media equation: How people treat computers, television, and new medialike real people and places. Cambridge, UK: Cambridge University Press. Resnick, L. (1987). Education and learning to think. Washington, DC: National Academy Press. Reyes, A., & Zarama, A. (1998). The process of embodying distinctions. A re-construction of the process of learning. Cybernetics & Human Knowing, 5(3), 19–33. Reynard, R. (2009). Can we gauge technology’s impact on learning outcomes? Retrieved April 23, 2009, from http://campustechnology.com/Articles/ 2009/03/25/DoesTechnology-Improve-Learning Reynolds, K. C. (1997, March). The name assigned to the document by the author. This field may also contain sub-titles, series names, and report numbers.Postsecondary education in cohort groups: Does familiarity breed learning? Additional information about the document that does not fit in any of the other fields; not used after 2004. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL. Richard, P. (2005). The state of critical thinking today. New Directions for Community Colleges, 130, 27–38.

385

Compilation of References

Richardson, W. (2009). Blogs, wikis, podcasts, and other powerful web tools for classrooms. Thousand Oaks, CA: Corwin Press. Riddell, T. (2007). Critical Assumptions: Thinking Critically About Critical Thinking. The Journal of Nursing Education, 46(3). Riley, D. (2008). China to become world’s largest internet market by users. Retrieved March 25, 2009, from http://www.techcrunch.com/2008/01/17/ china-close-tobecoming-worlds-largest-internet-market-by-users Rivlin, E., Botafogo, R., & Shneiderman, B. (1994). Navigating in hyperspace: designing a structure-based toolbox. Communications of the ACM, 37(2), 87–96. doi:10.1145/175235.175242 Rogers, A. (2002). Teaching adults (3rd ed.). London: Open University Press. Roschelle, J. (1999). Transitioning to professional practice: A Deweyan view of five analyses of problem-based learning. Discourse Processes: A Multidisicplinary Journal, 27(2), 231–240. Roseberry, C. (n.d.). What is the history of laptops? Retrieved March 24, 2009, from http://mobileoffice.about. com/od/ laptopstabletpcs/f/laptophistory.htm Rouke, L., Anderson, T., Garrison, D. R., & Archer, W. (2001). Assessing Social Presence in Asynchronous Text-based Computer Conferencing. Journal of Distance Education, http://cade.athabascau.ca/vol14.2 /rouke_et_ al.html. Retreived 6/28/08. Rourke, L. T., Anderson, T., Garrison, D. R., & Archer, W. (2001). Assessing social presence in asynchronous text-based computer conferencing. Journal of Distance Education, 14(2), 50–71. Rovai, A. P. (2001). Building classroom community at a distance: A case study. Educational Technology Research and Development Journal, 49(4), 33–48. doi:10.1007/ BF02504946

386

Russo, T., & Benson, S. (2005). Learning with invisible others: Perceptions of online presence and their relationship to cognitive and affective learning. Educational Technology & Society, 8(1), 54–62. Ryan, R. C. (2000). Student assessment comparison of lecture and online construction equipment and methods classes. T.H.E. Journal, 27(6), 76–83. Saba, V. K. (2001). Nursing informatics: Yesterday, today and tomorrow. International Nursing Review, 48(3), 177–187. doi:10.1046/j.1466-7657.2001.00064.x Samarawickrema, G., Benson, R., & Brack, C. (2010). Different spaces: Staff development for Web 2.0. Australian Journal of Educational Technology, 26(1), 44–49. Sanders, D. W., & Morrison-Shetlar, A. I. (2002). Student attitudes toward web-enhanced instruction in an introductory biology course. Journal of Research on Computing in Education, 33(3), 251–262. Sandvig, J. C. (2004). ASPEN—a Web-based application for managing student server accounts. Campus-Wide Information Systems, 21(4), 157–162. doi:10.1108/10650740410555034 Sangineto, E., Capuano, N., Gaeta, M., & Micarelli, A. (2008). Adaptive course generation through learning styles representation. Universal Access in the Information Society, 7(1-2), 1–23. doi:10.1007/s10209-007-0101-0 Sangrá, A., & González-Sanmamed, M. (Eds.). (2004a). La transformación de las universidades a través de las TIC: discursos y prácticas (University changes through ICTs: discourses and practices). Barcelona: UOC. Sangrá, A., & González-Sanmamed, M. (2004b). “El profesorado universitario y las TIC: redefinir roles y competencias” (University teachers and the ICTs: redefining roles and competences) . In Sangrá, A., & González-Sanmamed, M. (Eds.), La transformación de las universidades a través de las TIC: discursos y practices (University changes through ICTs: discourses and practices (pp. 79–80). Barcelona: UOC.

Compilation of References

Sangrá, A. (2002). A new learning model for the information and knowledge society: The case of the Universitat Oberta de Catalunya (UOC). The International Review of Research in Open and Distance Learning, 2(2). Retrieved March 31, 2009, from http://www.irrodl.org/index .php/ irrodl/article/view/55/114

Schiffman, S., Vignare, K., & Geith, C. (2007). Why Do Higher-Education Institutions Pursue Online Education? Journal of Asynchronous Learning, 11(2), Taylor, L., & Clark, S. (2010). Educational design of short, audio-only podcasts: The teacher and student experience . Australian Journal of Educational Technology, 26(3), 386–399.

Saulnier, B. M., Landry, J. P., Longenecker, H. E. Jr, & Wagner, T. A.From Teaching to Learning: Learner-Centered Teaching and Assessment in Information Systems Education. Journal of Information Systems Education, 19(2), 169–175.

Schmidt, E. K., & Gallegos, A. (2001). Distance learning: Issues and concerns of distance learners. Journal of Information Technology, 17(3). Retrieved from http:// nait.org/jit/Articles/schmidt041801.pdf.

Saxena, A., Kothari, D. P., Jain, S. K., & Khurana, A. (2003). Development of a “flow process scale” to measure flow among Web users. Journal of Internet Commerce, 2(4), 55–86. doi:10.1300/J179v02n04_04

Schmitz, V., & Leukel, J. (2005). Findings and recommendations from a Pan-European research project: Comparative analysis of e-catalog standards. International Journal of IT Standards and Standardization Research, 3(2), 51–65.

Saxena, A., Kothari, D. P., Jain, S. K., & Khurana, A. (2002). Analyzing the business models on the Web for internet commerce. International Journal of e-Business Strategy Management, 3(3), 229-241.

Schoech, D., & Helton, D. (2002). Qualitative and quantitative analysis of a course taught via classroom and internet chatroom. Qualitative Social Work, 1(1), 111–124. doi:10.1177/1473325002001001748

Schaffert, S., Bischof, D., Bürger, T., Gruber, A., Hilzensauer, W., & Schaffert, S. (2006, June 11-14). Learning with semantic wikis. Paper presented at the 1st Workshop on From Wiki to Semantics, 3rd Annual European Semantic Web Conference (ESWC), Budva, Montenegro. Retrieved April 29, 2009, from http://www.salzburgresearch.at/res earch/gfx/semantic_wiki_elearning.pdf

Schön, D. A. (1983). The reflective practitioner. How professionals think in action. New York: Basic Books.

Schatzki, T. R., Knorr-Cetina, K., & Von Savigny, E. (Eds.). (2001). The practice turn in contemporary theory. London: Routledge. Schatzman, L. (1991). Dimensional Analysis: Notes on alternative approach to the grounding of theory in qualitative research . In Maines, D. R. (Ed.), Social Organization and Social Work - Essays in Honor of Anselm Strauss (pp. 303–314). New York: Walter de Gruyter. Schellens, T. (2004). Collaborative learning in asynchronous discussion groups: What about the impact on cognitive processing? Computers in Human Behavior, 21(6), 957–975. doi:10.1016/j.chb.2004.02.025

Schön, D. A. (1987). Educating the reflective practitioner. Toward a new design for teaching and learning of professions. San Francisco: Jossey-Bass. Seale, J., & Rius-Riu, M. (2001) An introduction to learning technology within tertiary education in the UK: A Handbook for Learning Technologist [online]. Oxford: ALT. Retrieved from http://www.alt.ac.uk/alt_lt _handbook.asp Searle, J. (1995). The construction of social reality. New York: Penguin Books. Seeberg, C., Reichenberger, K., Fischer, S., Steinmetz, R., & Steinacker, A. (1999, June 19-24). Dynamically generated tables of contents as guided tours in adaptive hypermedia systems. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications, Seattle, WA, USA, (pp. 640-645), Charlottesville, VA, USA:AACE.

387

Compilation of References

Seidenberg, J., & Rector, A. (2006). Web ontology segmentation: analysis, classification and use. In the Proceedings of the 15th international conference on World Wide Web, pp 13 - 22, ACM 2006 Selwyn, N., Gorard, S., & Furlong, J. (2006). Adult learning in the digital age. Milton Park, UK: Routledge. Seung, H. K., Ashwell, S., Elder, J. H., & Valcante, G. (2006). Verbal communication outcomes of children with autism after in-home father training. Journal of Intellectual Disability Research, 50, 139–150. doi:10.1111/j.13652788.2005.00767.x Shank, R. C. (1995). Tell me a story: Narrative and Intelligence. Northwestern University Press. Shank, R., & Neaman, A. (2001). Motivation and Failure in Educational Systems Design, Smart Machines in Education (Forbus, K., & Feltovich, P., Eds.). Cambridge, MA: AAAI Press/ The MIT Press. Shaw, M., & Corazzi, S. (2000). Avoiding holes in holistic evaluation . Journal of Educational Technology & Society, 3(4). Shipman, F. M., & Marshall, C. C. (1994). Formality Considered Harmful: Issues, Experiences, Emerging Themes, and Directions. Technical Report ISTL-CSA-94-08-02, Xerox Palo Alto Research Center. Shipman, F. M., & McCall, R. (1994). Supporting knowledge-base evolution with incremental formalization. In Proceedings of the CHI ’94 Conference, pp. 285-291. Sicilia, M., Ruiz, S., & Munuera, J. L. (2005). Effects of interactivity in a Web Site. Journal of Advertising, 34, 31–45. Simpson, T. L. (2002). Dare I oppose constructivist theory. The Educational Forum, 347–354. doi:10.1080/00131720208984854 Simpson, C., & Du, Y. (2004). Effects of learning styles and class participation on students’ enjoyments level in distributed learning environments. Journal of Education for Library and Information Science, 45(2), 123–136.

388

Skinner, B. F. (1968). The technology of teaching. New York: Appleton-Century-Crofts. Sloan-C. (2009). NASULGC-Sloan National Commission on Online Learning Benchmarking Study: Preliminary findings. Retrieved from http://www.sloan-c.org/publications /survey/nasulgc_prelim Sloane, A. M., & Waite, W. M. (2005). Eclipse support for using Eli and teaching programming languages. Electronic Notes in Theoretical Computer Science, 141(4), 189–194. doi:10.1016/j.entcs.2005.02.058 Smith, D. N., & Sivakumar, K. (2004). Flow and Internet shopping behavior: A conceptual model and research propositions. Journal of Business Research, 57, 1199–1208. doi:10.1016/S0148-2963(02)00330-2 Smith, H., & Poulter, P. (1999). Share the ontology in XML-based trading architectures. Communications of the ACM, 42(3), 110–111. doi:10.1145/295685.295891 Smith, G. G., Ferguson, D., & Caris, M. (2001). Teaching college courses online vs. face-to-face. THE Journal ONLINE. Retrieved from http://www.thejournal.com/ magazine/vault/A3407.cfm Smith, M. K. (2002). Malcolm Knowles, informal adult education, self-direction and anadragogy the encyclopedia of informal education. Retrived from www.infed.org/ thinkers/et-knowl.htm. Snaprud, M., & Kaindl, H. (1994). Types and inheritance in hypertext. International Journal of Human-Computer Studies, 41(1-2), 223–241. doi:10.1006/ijhc.1994.1057 Sosnoski, J., Jones, S., Carter, B., McAllister, K., Moeller, R., & Mir, R. (2006). Virtual Harlem as a collaborative learning environment: A project of the University of Illinois at Chicago’s electronic visualization Lab . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 2) (pp. 1289–1320). Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3803-7_54

Compilation of References

Sproull, L., Subramani, M., Keisler, S., Walker, J. H., & Waters, K. (1996). When the interface is a face. Human-Computer Interaction, 11, 97–124. doi:10.1207/ s15327051hci1102_1

Stilborne. L., & Williams, L. (1996). Meeting the needs of adult learners in developing courses for the internet. Retrieved on January 15, 2009 from https://www.isoc. org/inet96/ proceedings/c4/ca_2.htm

Squires, D., Conole, G., & Jacobs, G. (2000). The Changing Face of Learning Technologies. Cardiff: University of Wales Press.

Su, J. M., Tseng, S. S., Lin, H. Y., & Lu, C. Y. (2005, May 6-7). The development of an object-oriented learning activities system. Taiwan e-Learning Forum 2005, Taipei, Taiwan.

Stanton, N., & Baber, C. (1992). An investigation of styles and strategies in self directed learning. Journal of Educational Multimedia and Hypermedia, 1(2), 147–167. Stegmann, K., Weinberger, A., & Fischer, F. (2007). Facilitating argumentative knowledge construction with computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning, 2(4), 421–447. doi:10.1007/s11412-007-9028-y Stehr, N. (1994). Knowledge societies. The Transformation of labor, property and knowledge in contemporary society. London: Sage. Steinbronn, P., & Merideth, E. (2008, March). Perceived Utility of Methods and Instructional Strategies Used in Online and Face-to-face Teaching Environments. Innovative Higher Education, 265(14). Stephenson, J. (Ed.). (2002). Teaching & Learning Online: Pedagogies for new technologies. VA: Stylus Publishing. Stephenson, D. (2006). Futures in e-learning. CampusWide Information Systems, 23(2), 102–103. Sterbini, A., & Temperini, M. (2003). A logical framework for course configuration in elearning. In Proc. of ITHET03. Sternberg, R. J., & Horvath, J. (Eds.). (1999). Tacit knowledge in professional practice: Researcher and practitioner perspectives. Mahwah, NJ: Erlbaum. Sternberg, R. J., & Wagner, R. K. (Eds.). (1986). Practical intelligence. Cambridge: Cambridge University Press. Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. The Journal of Communication, 42, 73–93. doi:10.1111/j.1460-2466.1992.tb00812.x

Sun, C., Ching, Y., & Lin, F. (1995). Modeling hypermedia navigation: An AI approach. In Proceedings of the 4th International Conference on Artificial Intelligence in Education (AI-ED), Washington, DC, (pp. 365-372), Charlottesville, VA, USA:AACE. Suthers, D., Johnson, S., & Tillinghast, B. (2002). Learning object meta-data for a database of elementary and secondary school resources. Interactive Learning Environments, 9, 273–289. doi:10.1076/ilee.9.3.273.3572 Suthers, D., Weiner, A., Connelly, J., & Paolucci, M. (1995). Belvedere: Engaging students in critical discussion of science and public policy issues. In Proceedings of the 7th World Conference on Artificial Intelligence in Education, pp. 266-273. Swan, K., & Shih, L. F. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115–136. Swan, K. (2004). Relationships Between Interactions and Learning . In Online Environments. The Sloan Consortium, Sloan-C. Tait, A., & Mills, R. (1999). The convergence between conventional and distance education. London: Routledge. Takeuchi, A., & Naito, T. (1995). Situated facial displays: Towards social interaction . In Katz, I., Mack, R., Mack, L., Rosson, M. B., & Nielsen, J. (Eds.), Human Factors in Computing Systems (pp. 450–455). New York: ACM Press. doi:10.1145/223904.223965 Takeuchi, A., & Nagao, K. (1993). Communicative facial displays as a new conversational modality. Proceedings of the Conference on Human Factors in Computing Systems.

389

Compilation of References

Talbert, J. E., & McLaughlin, M. W. (1993). Understanding teaching in context . In Cohen, D. K., McLaughlin, M. W., & Talbert, J. E. (Eds.), Teaching for understanding: Challenges for policy and practice. San Francisco: Jossey-Bass Publishers.

Terrasse, M., Savonnet, M., Leclercq, E., Grison, T., & Becker, T. (2006). Do we need metamodels AND ontologies for engineering platforms? In the Proceedings of the 2006 international workshop on Global integrated model management, pp 21 – 28, ACM 2006

Tallent-Runnells, M., Thompsons, J., Lan, Y., & Cooper, S. (2006, Spring). Teaching courses online: A review of the research. Review of Educational Research, 76, 93–135. doi:10.3102/00346543076001093

Terrell, S., & Dringus, L. (1999). An investigation of the effect of learning style on student success in an online learning environment. Journal of Educational Technology Systems, 28(3), 231–236.

Task Force on Distance Education and Training in Professional Psychology American Psychological Association. (2002). Principals of good practice in distance education and their application to professional education and training in psychology. Washington, DC: American Psychological Association, Task Force on Distance Education.

The eLearning Developers Journal, (2003). Learning Measurement: It is not how much you train, but how well. Retrieved from http://www.eLearningGuild.com

Taylor, J., Sumner, T., & Tosunoglu, C. (2000). Peering Through a Glass Darkly: Integrative evaluation of an on-line course . Journal of Educational Technology & Society, 3(4). Taylor, E. W. (2007). An update of transformative a critical review of the empirical research (1999–2005). International Journal of Lifelong Education, 26(2), 173–191. doi:10.1080/02601370701219475 Taylor, M., King, J., Pinsent-Johnson, C., & Lothian, T. (2003). Collaborative practices in adult literacy programs. Adult Basic Education, 13(2), 81–99. Taylor, K. (2006). Autonomy and Self-directed Learning: A Developmental Journey . In Hoare, C. (Ed.), Handbook of Adult Development and Learning. New York. Oxford. Taylor, E. W. (2006). The greening of the adult education academy . In Merriam, S. B., Courtenay, B. C., & Cervero, R. M. (Eds.), Global issues and adult education: Perspectives from Latin America, Southern Africa, and the United States (pp. 254–264). San Francisco: Jossey-Bass. Temperini, M., & Vitti, U. (2007). A web application for automated course configuration. In Proc. of ITHET 2007, pages 536–540.

390

The World Bank. (2008). The Road Not Traveled: Education Reform in the Middle East and North Africa. Retrieved: 10/2008 http://go.worldbank.org/JLMVU0I6R0 Thomas, L., & Knezek, D. (1995). Technology literacy for the nation and for its citizens. Retrieved April 28, 2009, from http://www.iste.org/AM/PrinterTemplate. cfm?Section=Technology_Literacy Thompson, K. (2001). Constructivist curriculum design for professional development: A review of the literature. Australian Journal of Adult Learning, 41(1), 94–109. Thompson, M. M., & McGrath, J. W. (1999). Using LNs to Support a complete educational experience. Journal of Asynchronous Learning Environment Learning Networks, 3(2). Retrieved from http://www.sloan-c.org/publications /jaln/v3n2/v3n2_thompson.asp. Thorndyke, P. (1977). Cognitive structures in comprehension and memory of narrative discourse. Cognitive Psychology, 9, 77–110. doi:10.1016/0010-0285(77)90005-6 Tibi, B. (1981). The Crisis of Modern Islam. Munich: Beck. Tiedge, L. B., & Darling-Fisher, C. (1996). Fatherhood reconsidered: A critical review. Research in Nursing & Health, 19(4), 471–484. Tiffin, J., & Terashima, N. (2001). Hyper-reality: Paradigm for the third millennium. London: Routledge.

Compilation of References

Tough, A. (1967). Learning without a teacher. Educational research series, no. 3. Toronto, Ontario, Canada: Ontario Institute for Studies in Education. Tough, A. (1971). The adult’s learning project. Toronto, Ontario, Canada: Ontario Institute for Studies in Education. Trevino, L. K., & Webster, J. (1992). Flow in computermediated communication. Communication Research, 19(5), 539–573. doi:10.1177/009365092019005001 Tsai, C., & Chou, C. (2002). Diagnosing students’ alternative conceptions in science through a networked two-tier test system. International Journal of Computer Assisted Learning, 18(2), 157–165. doi:10.1046/j.02664909.2002.00223.x Tsao, J., Takahashi, K., Olusesu, J., & Jain, S. (2006). Transformative Learning. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Retrieved from http://projects.coe.uga.edu/epltt/ Turban, E., Fisher, J. C., & Altman, S. (1988, March). Decision Support Systems in Academic Administration. Journal of Educational Administration, 26, 97–113. doi:10.1108/eb009943 Turoff, M., & Aggarwal, A. Legon, R., & Hackbarth, G. (2004). Panel: Web-Based Education: Diffusion And Issues --The Next Stage, AMCIS, New York, NYC. Tyack, D., & Cuban, L. (1995). Tinkering towards utopia: A century of school reform. Cambridge, MA: Harvard University Press.

UNDP (United Nationas Developmnet Projgramme). (2005). Regional Bureau for Arab States, Quality assessment of computer science and business administration education in arab universities. Retrieved: 1/2008, from: http://www.undp.org/ar abstates/site_ docs/HE%20Overvie w%20Report.pdf UNESCO Institute for Statistics. (2005). Educational trends in perspective. Retrieved March 21, 2009, from http://www.uis.unesco.org/ TEMPLATE/pdf/wei/ WEI2005.pdf UNESCO Institute for Statistics. (2009). Expert meeting on cyber network for learning languages. Retrieved March 21, 2009, from http://portal.unesco.org/en/ev.phpURL_ID=44836& URL_DO=DO_TOPIC&URL_SECTION=201.html Urban, G. L. (2008). Online trust and customer power: The emergence of customer advocacy . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 39–54). Chichester, UK: John Wiley & Sons. Valenti, S. Panti, M., & Leo, T. (2003). Relevant Issues for the Design of a Successful Web-Based Instructional System: MODASPECTRA. Web-Based Education: Learning from Experience, book edited by A.K.Aggarwal, Info Science pub. Van de Pol, J. (2001). A Look at the Course management Systems. IT Times May/June, online: Retrieved from http:// ittimes.ucdavis.edu / june2001/cms/html

Tyler, R. W. (1950). Basic principles of curriculum and instruction. Chicago: University of Chicago Press.

van Gelder, T.J. (2002). Argument mapping with Reason!Able. The American Philosophical Association Newsletter on Philosophy and Computers, 85-90.

Ullman, C., & Rabinowitz, M. (2004). Course Management Systems and the Reinvention of Instruction. Retrieved from http://thejournal.com /magazine/ vault/articleprin tversion.cfm?aid=5070.

Van Mulken, S., André, E., & Müller, J. (1998). The persona effect: How substantial is it? In H. Johnson, L. Nigay, & C. Roast Eds. People and Computers XIII [Berlin: Springer.]. Proceedings of, HCI98, 53–66. Varela, F., Thompson, E., & Rosch, E. (Eds.). (1993). The embodied mind. Cambridge: the MIT Press.

391

Compilation of References

Vaughan, N. (2007). Perspective on Blended Learning in Higher Education. International Journal on E-Learning, 6(1), 81–94.

Wakefield, J. (1996). Educational Psychology: Learning to be a problem-solver. Boston: Houghton Mifflin.

Verduin, J. R., & Clark, T. (1991). Distance education: The foundations of effective practice. San Francisco: Jossey-Bass.

Wang, H.-C., & Hsu, C.-W. (2006). Teaching-material design center: An ontology-based system for customizing reusable e-materials. Computers & Education, 46(3), 458–470. doi:10.1016/j.compedu.2005.09.005

Verheij, B. (2003). Artificial argument assistants for defeasible argumentation. Artificial Intelligence, 150(1-2), 291–324. doi:10.1016/S0004-3702(03)00107-3

Wang, M. (2003). Teaching Web-driven database application with templates. Information Systems Education Journal, 1(11), 1–8.

Vinga, S. (2006). Analysis and prediction of user behaviour in a museum environment. PhD thesis, University of Melbourne.

Wang, V. C. X. (2007-2008). Chinese knowledge transmitters or western learning facilitators adult teaching methods compared. Perspectives: The New York Journal of Adult Learning, 6(2), 15–40.

Von Forrester, H. (1984). Observing systems. Salinas: Intersystems Publications. Vossen, G., & Hagemann, S. (2007). Unleashing Web 2.0 from concepts to creativity. Burlington, MA: Morgan Kaufmann. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, Massachusetts: Harvard University Press. Vygotsky, L. S. (1978). Mind in Society. Cambridge, MA: Harvard University Press. W3C ODA (2006). Ontology Driven Architectures and Potential Uses of the Semantic Web in Systems and Software Engineering, http://www.w3.org/2001/sw/ BestPractices/SE/ODA/ W3C. (2004a). OWL Web ontology language reference. Retrieved August 20, 2009, from http://www.w3.org/ TR/2004/R EC-owl-ref-20040210/. W3C. (2004b). SWRL: A semantic Web rule language combining OWL and RuleML. Retrieved August 20, 2009, from http://www.w3.org/Submission/SWRL. Wagner, C. (2004). WIKI: A Technology for Conversational Knowledge Management and Group Collaboration. Communications of the Association for Information Systems, 13, 265–289.

392

Wang, V. C. X. (2008). Facilitating adult learning: A comprehensive guide for successful instruction. Boston: Pearson Education. Wang, V. C. X. (Ed.). (2010). Integrating adult learning and technologies for effective education: Strategic approaches. Hershey, PA: Information Science Reference. Wang, V. C. X., & King, K. P. (2006). Understanding Mezirow’s theory of reflectivity from Confucian perspectives: A model and perspective. Radical Pedagogy, 8(1), 1–17. Wang, V. C. X. (2007). Chinese knowledge transmitters or western learning facilitators adult teaching methods compared . In King, K. P., & Wang, V. C. X. (Eds.), Comparative adult education around the globe (pp. 113–1370). Hangzhou, China: Zhejiang University Press. Wang, V. C. X., & King, K. P. (2007). Confucius and Mezirow—understanding Mezirow’s theory of reflectivity from Confucian perspectives: A model and perspective . In King, K. P., & Wang, V. C. X. (Eds.), Comparative adult education around the globe (pp. 253–275). Hangzhou, China: Zhejiang University Press. Warren, P., Davies, J., & Brown, D. (Eds.). (2008). ICT futures: Delivering pervasive, real-time and secure service. Chichester, UK: John Wiley & Sons.

Compilation of References

Washburn, J. (2005). University, Inc.: The Corporate Corruption of Higher Education. New York: Basic Books. Watson, G. (1960-1961). What do we know about learning? Teachers College Record, 253–257. Watson, D. (2001). Pedagogy before technology: rethinking the relationship between ICT and teaching. Education and Information Technologies, 6(4), 266–266. Watson, G. (Ed.). (1967). Concepts for social change. Washington, DC: National Training Laboratories Institute for Applied Behavioral Science, NEA. Weber, G., & Brusilovsky, P. (2001). ELM-ART: An adaptive versatile system for web-based instruction. International Journal of Artificial Intelligence in Education, 12, 351–384. Weber, G., & Brusilovsky, P. (2001). Elm-art: An adaptive versatile system for web-based instruction. International Journal of AI in Education, 12(4), 351–384. Weber, G., Kuhl, H. C., & Weibelzahl, S. (2001). Developing adaptive internet based courses with the authoring system NetCoach. In Proc. of Third workshop on Adaptive Hypertext and Hypermedia, pages 35–48. Webster, J., Trevino, L. K., & Ryan, L. (1993). The dimensionality and correlates of flow in human computer interactions. Computers in Human Behavior, 9(4), 411–426. doi:10.1016/0747-5632(93)90032-N Webster, F. (1995). Theories of the information society. London: Routledge. Weimer, M. (2002). Learner centered teaching (1st ed.). San Francisco: Jossey-Bass. Wenger, E. (1999). Communities of Practice: Learning, Meaning and Identity. Cambridge, UK: Cambridge University Press. West, R. (1997). Review of Higher Education Financing an Policy. (Report of the West Review). Canberra: Department of Education, Training and Youth Affairs.

White, D. (2007). Results of the ‘Online Tool Use Survey’ undertaken by the JISC funded SPIRE project. Oxford, UK: Author. Whittington, D. (2000). Evaluating three years’ use of virtual university. Quality Assurance in Education, 8(1), 48–52. doi:10.1108/09684880010313153 Wilcoxon, F. (1947). Probability tables for individual comparisons by ranking methods. Biometrics, 3, 119–122. doi:10.2307/3001946 Wilkinson, R., Lu, S., Paradis, F., Paris, C., Wan, S., & Wu, M. (2000). Generating personal travel guides from discourse plans. In AH’00: Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, London, UK, (pp. 392-395), Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag. Willis, J. (2000). The maturing of constructivist instructional design: Some basic principles that can guide practice. Educational Technology, 40(1), 5–16. Witten, I. H., & Frank, E. (2005). Data mining: Practical machine learning tools and techniques (2nd ed.). San Francisco: Elsevier. Wittgreffe, J., Dames, M., Clark, J., & McDonald, J. (2008). End-to-end service level agreements for complex ICT solutions . In Warren, P., Davies, J., & Brown, D. (Eds.), ICT futures: Delivering pervasive, real-time and secure service (pp. 115–128). Chichester, UK: John Wiley & Sons. Wolper, P. (1985). The tableau method for temporal logic: an overview. Journal of Logique et Analyse, 28, 119–152. Wonacott, M. E. (2002). Blending fce-to-face and distance learning methods in adult and career-technical education. Clearinghouse on Adult, Career and Vocational Education, Application Brief No. 23. Educational Resources Information Center. World Bank. (2003). Constructing knowledge societies: new challenges for tertiary education. Washington, D.C.: The Word Bank.

393

Compilation of References

Wu, H. (2002). A Reference Architecture for Adaptive Hypermedia Applications. PhD thesis, Eindhoven University of Technology. Wubbels, T. (1992). Taking account of student teachers’ preconceptions. Teaching and Teacher Education, 8, 137–149. doi:10.1016/0742-051X(92)90004-M Wurm, K. B. (2005). Andragogy in Survey Education. Surveying and Land Information Science, 65(3), 159–163. Yang, J. T., Yu, P. T., Chen, N. S., Tsai, C. Y., Lee, C. C., & Shih, T. K. (2005). Using ontology as scaffolding for authoring teaching materials. International Journal of Distance Education Technologies, 3(1), 81–96. Yang, B. (2003). Toward a holistic theory of knowledge and adult learning. Human Resource Development Review, 2(2), 106–129. doi:10.1177/1534484303002002002 Yin, R. (1984). Case Study Research: design and methods. Beverly Hills, CA: Sage Publications. Young, M. F. D. (1998). The curriculum of the future. From the “new sociology of education” to a critical theory of learning. London: Falmer Press. Zachary, J. (1994, March). Tutorial-based teaching of introductory programming classes. In Proceedings of the 25th SIGCSE Symposium on Computer Science Education,Phoenix, AZ (pp. 136-140). ACM Publishing. Zancanaro, M., Kuflik, T., Boger, Z., Goren-Bar, D., & Goldwasser, D. (2007, June 25-29). Analyzing museum visitors’ behavior patterns. In User Modeling 2007, 11th International Conference, UM 2007, Corfu, Greece, (pp. 238-246), Berlin, Heidelberg, Germany/New York, NY: Springer-Verlag.

394

Zhang, D., Zhao, J. L., Zhou, L., & Nunamaker, J. F. (2004). Can e-learning replace classroom learning? Communications of the ACM, 47(5), 75–79. doi:10.1145/986213.986216 Zhao, Y., Lei, J., & Conway, P. F. (2006). A global perspective on political definitions of e-learning: Commonalities and differences in national educational technology strategy discourses . In Weiss, J., Nolan, J., Hunsinger, J., & Trifonas, P. (Eds.), The international handbook of virtual learning environments (pt. 1) (pp. 673–698). Dordrecht, The Netherlands: Springer. doi:10.1007/9781-4020-3803-7_26 Zhao, J., & Kanji, A. (2001, July 4-6). Web based Collaborative learning methods and strategies in higher education. International Conference on Information Based Higher Education and Training, Kumamoto, Japan Ziemlewski, J. (2009, February). Chemical engineering progress. In Bulletin of the American Institute of Chemical Engineers (AiCHE). Zirkle, C. (2002). Identification of distance education barriers for trade and industrial teacher education. Journal of Industrial Education, 40(1), 20–44. Zirkle, C. (2009). Distance education: The state of the art in career and technical education . In Mclean, R., & Wilson, D. (Eds.), International Handbook of Education for the Changing World of Work (pp. 2003–2018). The Netherlands: Springer. doi:10.1007/978-1-4020-5281-1_136 Zywno, M. S., & Waalen, J. K. (2001). The effect of hypermedia instruction on achievement and attitudes of students with different learning styles. In Annual ASEE Conf.

395

About the Contributors

Eugenia M. W. Ng is an associate professor in Department of Mathematics and Information Technology and Associate Dean of Graduate School at the Hong Kong Institute of Education. She has been a research investigator of various internal and external funded projects. Her publications have appeared in Issues in Informing Science and Information Technology, Journal of Interactive Instruction Development, of Information Systems Education, Journal of Quality School Education and Annals of Cases on Information Technology. Her book chapters have appeared in Subject Teaching and Teacher Education in the New Century: Research and Innovation, and Improving student learning: Learning-oriented assessment in action, Encyclopaedia of Information Technology Curriculum Integration, Encyclopaedia of Information Communications and Technology and Encyclopaedia of Networked and Virtual Organizations. She is the editor of Comparative blended learning practices and environments, Co-editor-in-Chief of International Journal of Web-based Learning and Teaching Technologies, a member of the editorial board of Annals of Cases on Information Technology, and reviewers for Journal of Computers in Human Behavior, Journal of Interactive Learning Research and Journal of Technology and Teacher Education. Nikos Karacapilidis holds a Professor position at the University of Patras (field: Management Information Systems). His research interests lie in the areas of Technology-Enhanced Learning, Intelligent Web-Based Information Systems, e-Collaboration, Knowledge Management Systems, Group Decision Support Systems, Computer-Supported Argumentation, Enterprise Information Systems and Semantic Web. He has been appointed as Editor-in-Chief of the Advances in Web-based Learning (AWBL) Book Series, as well as co-Editor-in-Chief of the International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), both published by IGI Global. More detailed information about his publications list, research projects involved and professional activities can be found at http://www.mech.upatras. gr/~nikos/. Mahesh S. Raisinghani is an associate professor in the Executive MBA program at the TWU School of Management. He is a Certified E-Commerce Consultant (CEC), a Certified Information Security Manager (CISM) and a Project Management Professional (PMP). Dr. Raisinghani was awarded the 2008 Excellence in Research & Scholarship award and the 2007 G. Ann Uhlir Endowed Fellowship in Higher Education Administration. He was also the recipient of TWU School of Management's 2005 Best Professor Award for the Most Innovative Teaching Methods; 2002 research award; 2001 King/Haggar Award for excellence in teaching, research and service; and a 1999 UD-GSM Presidential Award. His research has been published in several academic journals such as IEEE Transactions on Engineering Management, Information & Management, Information Resources Management Journal, Journal of E-

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

About the Contributors

Commerce Research, International Journal of Distance Education Technologies, International Journal of Innovation and Learning, Journal of IT Review, Journal of Global IT Management, and Journal of IT Cases and Applications Research among others and international/national conferences. Dr. Raisinghani is included in the millennium edition of Who's Who in the World, Who's Who among Professionals, Who's Who among America's Teachers and Who's Who in Information Technology. *** Salam Abdallah is an IS&T academic and practitioner. Dr. Abdallah has a PhD in Information Systems from Curtin University of Technology, Australia. He has worked for several years with UN Relief and Works Agency (UNRWA) overseeing ICT facilities and curriculum development at schools and vocational training centers in UNRWA’s entire field of operations. He is an active participant on the Global Text Project, and a founder member of Special Interest Group of the Association of Information Systems: ICT and Global Development. Dr. Abdallah is also an active researcher in the field of Information Systems and has published articles in local and international conferences and journals. Currently he is the Coordinator for the College of Business and Administration at Abu Dhabi University, Al Ain, UAE. Nektaria Adaktilou holds a BSc in Physics and a MSc in Environmental Physics both from the University of Athens. She is a PhD Candidate working as a Research Assistant at the Remote Sensing and Image Processing Group of the Physics Faculty at the University of Athens. She has considerable experience in the area of Remote Sensing applications and is currently working on the design, development, application and evaluation of an electronic tool-learning platform, to support remote sensing instruction at a University level. Blended learning approaches and collaborative practices consist main elements of the research. She has participated in several scientific projects in the fields of remote sensing and environmental science, both research as well as education oriented. Veena Adlakha is a professor of Production Management at the Merrick School of Business in the University of Baltimore, Maryland. She received her M.S. degree in Mathematics from Stanford University and the Ph.D. in Operations Research from the University of North Carolina at Chapel Hill. Her research on discrete event simulation, and fixed-charge transportation problem, web-based education has appeared in several journals including Networks, EJOR, Management Science, Operations Research, OMEGA, JORS, Total Quality Management, and e-Service Journal. Dr. Adlakha served on the Southeast Asia Fulbright Peer Review Committee of the Council for International Exchange of Scholars and the State Department for 2002-2004 and served as the Executive Director of the Production and Operations Management Society (POMS) for 1990-95. She served as the managing editor of the POM journal for 1991-95. Her current research interests include fixed-charge transportation problem, total quality management and web-based education. Anil Aggarwal is a professor of Management Information Systems in the Merrick School of Business in the University of Baltimore, Maryland. He has published in many national international journals including Computers and Operations Research, Decision Sciences, Information and Management, eService, Production and Operation Management, Journal of EUC and Total Quality Management and Business Excellence. In addition, he has edited two book on web-based education. his current research interests include web-based teaching, model-based systems, decision support systems and educational issues in MIS. 396

About the Contributors

Manuel Ahedo, since 2006 he has been Associate Professor in Sociology in the University Rovira i Virgili (Catalonia – Spain), where he is a member of the Research Group in Social and Organizational Analysis, and a member of the GID (Group of Pedagogical Innovation) of the Faculty of Law Sciences of the same University. He is Bachelor (5 year- Licenciatura) in History in 1988 by the University of Deusto in Spain; Bachelor (5 year- Licenciatura) in Sociology in 1997 by the UNED (Spain’s National Distance University). He made an MSc in Science and Technology Studies by the University of Edinburg (Scotland, United Kingdom) in 1998. In 2002 he obtained his PhD degree in Sociology in the University of the Basque Country (Spain). His main areas of interest are comparative social sciences, with a major focus on comparative economic and educational sociology, mainly at the European Union level. Currently he is interested in the organizational and institutional factors in comparative socio-learning systems. Hilary Amberg is a graduate student in the University of Florida’s College of Education, focusing on Counselor Education. Anshu Arora is an Assistant Professor (Marketing) at College of Business Administration, Savannah State University, Savannah, Georgia, USA. She is a certified Project Management Professional (PMP) from Project Management Institute (PMI), USA. She has been awarded PhD in the area of Hypermedia CMEs from the Indian Institute of Technology, Delhi. She has written about 20 papers in National and International journals of repute, presented about 15 papers in National and International Conferences. She has about a decade of industrial and academic experience. She has been actively involved in major projects with Lufthansa German Airlines, Hyundai Motor India Limited, and Siemens India. Her book – “Hypermedia – From Multimedia to Virtual Reality” was published by Prentice Hall of India in April 2004. She has also contributed a chapter on “Creativity and Innovations in Organizations” in the book: “International Encyclopaedia of Organizational Behavior” by Pentagon Press, UK. Roxanna Bendixen has a Ph.D. in Rehabilitation Science and serves as a Research Assistant Professor in the College of Public Health and Health Professions. Her doctoral work focused on qualitative and quantitative assessment of healthcare services for individuals with chronic illnesses following an OT intervention. Dr. Bendixen has more than 10 years of clinical experience specializing in assessment and treatment of children with chronic illnesses and disabilities. Her research focuses on participation and quality of life in children with Duchenne muscular dystrophy and in-home training for parents of children with autism. She teaches OT theory, therapeutic skills, and adult and pediatric assessment and intervention. Costas Cartalis has completed his undergraduate studies at the University of Athens (B.S. In Physics) and pursued his graduate studies (University of Michigan, Ann Arbor) completing Masters Degree in Aerospace Engineering, Masters Degree in Atmospheric Physics and PhD in Remote Sensing (1989). He has also followed a post graduate course on Strategic Information Systems at the Heriot Watt University. C. Cartalis is an Associate Professor at the Department of Applied Physics of the University of Athens and visiting Professor at the University of Thessaloniki. He is responsible for the operation of the Remote Sensing and Image Processing Research Unit within the Division of Applied Physics of the Department of Physics. He has participated in several research projects funded by either national or EU funding (mostly from DG Research).. He is member of the Scientific Committee of the European Environment Agency and of the Management Board of the International Olympic Academy.

397

About the Contributors

Mei-Yu Chang is a professor in National Hsinchu University of Education, Taiwan, where she teaches the instructional design, assessment and research methods. She holds her Ph.D. in Instructional Design, Development and Evaluation in Syracuse University, and her master degree in Instructional Systems Technology in Indiana University, Bloomington. Her research interests include science teaching and learning, e-Learning and assessment. Yu-Liang Chi is an Associate Professor and Chair of Information Management in the Business College at Chung Yuan Christian University, Taiwan. He received his Master degree in Computer Science Engineering and Ph.D. degree in Industry Engineering from the Arizona State University. His current teaching and research interests focus on distributed systems integration, intelligent system design, and knowledge engineering. His research has been published in leading academic journals such as The Electronic Library, Expert Systems with Applications, and International Journal of Services and Standards. Spyros Christodoulou is a computer engineer and member of Research Academic Computer Technology Institute in Patras, Greece since 2004. He is a graduate of Computer Engineering and Informatics Department, Patras, Greece (2001) and received his master degree in Signal Processing and Telecommunications from the same department (2003). Since 2000, he has been with CTI, published papers in a number of conferences and participated in national and European research projects. Robert Davis is an Associate Dean and Director of Graduate Programs in the McCoy College of Business. He is also a professor in the Department of Computer Information Systems. He earned his MBA and Ph.D. degrees from the University of South Carolina and his undergraduate degree from the University of North Carolina-Pembroke. He is the co-author of Operations Management: Concepts in Manufacturing and Services. His research has been published in leading academic journals such as Decision Support Systems, Management Science, Journal of Marketing, Journal of Organizational Computing and Electronic Commerce, International Journal of Production Research, and Journal of Business Research. Gordon Deline is a Senior Project Manager, Project and Risk Management, at CBC/Radio-Canada. Gordon has over twenty years of experience in software systems research and development in North America, Asia, and Europe, designing and implementing virtual reality, telerobotic/supervisory control, object database, supply chain, reverse logistics, and business intelligence systems. Current research interests include systems development in the context of alignment and integration with strategy and business knowledge, and distributed heterogeneous implementation teams with client/vendor/competitor membership. Susan Donaldson is the Project Director for Dr. Jennifer Elder’s R01 grant: Fathers as in-home trainers of autistic children. She has her BSN and MSN from the University of Florida and is also a Nationally Board Certified Psychiatric-Mental Health Nurse Practitioner. Jennifer Elder has spent the last 27 years studying autism and related child neuropsychiatric disorders. She has developed and tested a variety of in-home parent training components, evaluated the effects of a gluten-free, casein-free diet on children with autism, and participated in several interdisciplinary autism projects. She is currently the Principal Investigator on a four-year R01 grant from the National

398

About the Contributors

Institute of Nursing Research at NIH ($1.1 million) to continue evaluating the effects of father-directed training for children with autism. This includes a newly developed web-enhanced component. Richard Ferdig is the RCET Research Professor and Professor of Instructional Technology at Kent State University. He works within the Research Center for Educational Technology and also the School Lifespan Development & Educational Sciences. He earned his PhD in educational psychology from Michigan State University. At Kent State University, his research, teaching, and service focus on combining cutting-edge technologies with current pedagogic theory to create innovative learning environments. His research interests include online education, gaming, and what he labels a deeper psychology of technology. In addition to publishing and presenting nationally and internationally, Ferdig has also been funded to study the impact of emerging technologies. Dragan Gašević is an Assistant Professor in the School of Computing and Information Systems at Athabasca University and an Adjunct Professor at Simon Fraser University. He is a recipient of Alberta Ingenuity's 2008 New Faculty Award. His research interests include semantic technologies, software language engineering, and learning technologies. He has (co-)authored around 190 research papers published. He has been serving on editorial boards of three international journals and has edited special issues in journals such as IET Software and IEEE TSE. He has been the organizer, chair, and member of program committees of many international conferences. Fabio Gasparetti is a Postdoctoral Fellow at the Arti?cial Intelligence Lab of the Department of Computer Science and Automation, Roma Tre University. His research interests include: Personalized Search, User Modeling and Focused Crawling. He has collaborated and is still collaborating in National and International research projects regarding Internet technologies. George Gkotsis is a PhD student at the Mechanical Engineering and Aeronautics Department, University of Patras. He works as a research collaborator at the E-learning Sector of the Research Academic Computer Technology Institute, Patras, Greece. He holds a M.Sc. from the Computer Engineering and Informatics Department, University of Patras (2005), where he got his Diploma (2002). His research interests include Computer Supported Collaboration Systems, Argumentation Systems, Knowledge Management and Visualization, Web Engineering and Hypertext. Bob Heller obtained his Ph.D. in Experimental Psychology in 1992 at the University of Alberta and held a Post-Doctorate Research Fellowship from 1992-94, in the Centre of Excellence on Aging Research Network where he conducted research on driving, dementia, and aging. He joined the Centre for Psychology at Athabasca University in 2001 and became interested in conversational agents and their role in distance education. This research has evolved into an investigation of animated historical figures as pedagogical agents and their place in immersive worlds. Victor Hernandez-Gantes received an M.S. in Agricultural Education with concentration in International Agricultural Development, and a Ph.D. in Educational Research and Evaluation from Virginia Tech. He has served as Associate Researcher at the Center on Education and Work, University of WisconsinMadison, as Associate Professor at Florida State, and as Senior Educational Researcher in the Center for Educational Technologies (CET)—a center sponsored by NASA—at Wheeling Jesuit University.

399

About the Contributors

He currently leads the doctoral program in Career and Workforce Education at the University of South Florida. Over the years he has collaborated with organizations and faculty at a number of universities nationally and internationally. This synergistic collaboration has resulted in a number of research and demonstration projects in the areas of professional development, vocational and technical education, and the integration of mathematics and career education supported by the U.S. Department of Education, National Center for Research in Vocational Education, and NASA. He has published numerous articles on the impact of programs designed to connect school- and work-based learning on student learning and career development. Over the past decade he has been involved with online program development in graduate education and has written on topics relevant to program planning and about bridging online teaching and adult learning principles. Maureen Hinkley, Ed.D. is a Visiting Professor of Educational Technology and School Library Media at the Graduate School of Education, at Fairfield University in the United States. Her background was first in Library and Media Studies at the University of Northern Colorado. Later, she focused her doctoral studies in the area of transcultural educational development at Teachers College Columbia University, where her dissertation research was conducted with a teacher training program in a Central and Eastern European cross-cultural setting. More recently her research is focused on teacher development and the uses of technologies for optimal learning environments. John Hope, Ph.D., his background is teaching in New Zealand primary, intermediate and secondary schools. He left school teaching after some years as the principal of New Zealand’s largest primary school, a school featuring nationally recognised programmes for gifted students and an international reputation for use of ICT. Later in his career John became a school inspector and curriculum writer and was seconded to the University of Auckland as Director Primary Teacher Education to establish initial teacher education programmes. Following successful establishment of teacher education programmes, other University of Auckland appointments followed, including Director of the University of Auckland Principals Centre, and Associate Dean (International) positions in two faculties. He currently directs several overseas twinning degree programmes, coordinates all international activity within the Faculty of Education and has university-wide international responsibilities. Teaching and supervision interest include pedagogical applications of ICT in learning, educational leadership and gifted education. Research activity includes the same topics, but also includes research into education for international settings. George Kalkanis is Professor of Science and Information Technologies, Director of the Science, Technology and Environment Section of the Pedagogical Department of Primary Education of the University of Athens (1998 up today) and Invited Lecturer at the Physics Department of UoA (1995 up today). Formerly: Assist. Prof. of the Physics Dept. of UoA (1976-93), Fellow at CERN (1986-1992), Scientific Associate, CERN (1984-1985), Researcher, University of Wisconcin/Madison (1982-1983), Research Assistant, Harvard University (1981-1982), Research Assistant, FermiLab (1980-1981). Studies: PhD on Proton Decay HARVARD-PURDUE-WISCONCIN experiment (1980-1984), MSc in Electronic Automation (1976-78), Degree on Physics (1967-1972). Educational Activities: Teaching Physics and Information Technologies. Research Activities: New Ways on Teaching and Experimentation in Science, Modeling / Simulation / Animation of Micro Cosmos, Sensors / Actuators driven by the Computer in Science Educational Laboratory, Information Technology Application to Science and Environmental Education, Distance Learning.

400

About the Contributors

Vasilis Kallistros is a computer engineer and member of Research Academic Computer Technology Institute in Patras, Greece since 1997. He is a graduate of Computer Engineering and Informatics Department of the University of Patras, Greece (1987). He holds a masters degree from Stanford University (1989). His research interests include Computer Supported Collaboration Systems, Educational Software, Web-based Information Systems, Role-based Access Control models. Nikos Karacapilidis holds a Professor position at the University of Patras, Greece (field: Management Information Systems). His research interests lie in the areas of Intelligent Web-Based Information Systems, Technology-Enhanced Learning, e-Collaboration, Knowledge Management Systems, Group Decision Support Systems, Computer-Supported Argumentation, Enterprise Information Systems and Semantic Web. He has been appointed as Editor-in-Chief of the Advances in Web-based Learning (AWBL) Book Series (http://www.igi-pub.com/bookseries/details.asp?id=432), as well as Co-Editor-inChief of the International Journal of Web-based Learning and Teaching Technologies (IJWLTT - http:// www.igi-pub.com/journals/details.asp?ID=4286). More detailed information about his publications list, research projects involved and professional activities can be found at http://www.mech.upatras.gr/~nikos/. Nikos Karousos holds a Diploma (1998) and a M.Sc. (2000) from the Dept. of Computer Engineering and Informatics University of Patras, Greece. He is currently a PhD student in the provision of hypertext services. He works in the E-Learning Sector of the Research Academic Computer Technology Institute, Patras, Greece. His research is focused on the areas of Hypertext/Hypermedia, Web Services, Webbased Information Systems and Knowledge Management. Carol Kennedy, Ph.D. is the Principal Investigator for the Fordham University/ University of Oregon Project, establishing the NY center of the National Center for Study of Electronic Text to help at-risk readers with learning disabilities who are ESL/ELL learners. She had been the Visiting Assistant Professor/Director of the Educational Technology Master’s Degree Program at Fairfield University Graduate School of Education, creating and teaching the integration of technology into the K-12 curriculum, on-site and in blended classes. Dr. Kennedy has created and taught online graduate teacher-education programs for Seton Hall University, The New School- Teaching and Learning With Technology Graduate Certificate Program, conducted technology integration workshops for pre-service and in-service teachers at Fordham University and Long Island University. She is a curriculum writer for the AAAS ScienceNetlinks.org/Science-in-Plain-Language Wiki, and an instructional designer for Pearson Publishing’s Virtual High School creating new courses. Kinshuk is Professor and Director of School of Computing and Information Systems at Athabasca University, Canada. He also holds iCORE/Xerox/Markin Industrial Research Chair in Adaptivity and Personalization in Informatics. Hsun-Ming Lee received his PhD in Industrial Engineering with a focus on information engineering from Arizona State University, USA. He is currently an Assistant Professor of Computer Information Systems in the McCoy College of Business Administration at Texas State University - San Marcos, USA. His research interests include Web engineering, decision support systems, and supply chain management. His research has been published in leading academic journals such as Decision Support Systems, Expert Systems with Applications, and International Journal of Services and Standards.

401

About the Contributors

Carla Limongelli is associate professor in the Department of Computer Science and Automation at “Roma Tre” University, where she teaches computer science courses. Her research activity mainly focuses on artificial intelligence planning techniques, intelligent adaptive learning environments, user modeling, and user-adapted interaction. Fuhua Lin is Professor of School of Computing and Information Systems of Athabasca University, Canada. He is conducting research in Intelligent Systems, Multi-Agent Systems, Virtual Reality, and their applications. Dr. Lin has more than sixty publications, including edited books, journal papers, book chapters, conference papers, and reviews. Dr. Lin’s current main research interest is in the design and the development of reasoning models and mechanism of intelligent agents that facilitate adaptive learning. Dr. Lin has taught various undergraduate as well as postgraduate courses in Mathematics, Computer Science, and Information Systems. Furthermore, he has led and actively participated in numerous national and international research projects since 1986. Christos Mettouris is a graduate of the Computer Engineering & Informatics Department in the University of Patras. He holds a Masters degree of the same department. He is a member of the e-Learning sector of the Research Academic Computer Technology Institute (RACTI). He has published awardwinning papers in national conferences and participated in national and European research projects. His research interests include Human Computer Interaction, Web-Based Information Systems, Wireless technologies and Mobile Networks. Alessandro Micarelli is a Full Professor of Arti?cial Intelligence at the Roma Tre University, where he is in charge of the Arti?cial Intelligence Laboratory at the Department of Computer Science and Automation. His research interests include: Adaptive Web-Based Systems, Personalized Search, User Modeling, Arti?cial Intelligence in Education. Dora Nousia is a senior Computer Engineer educated at the University of Patras, and currently, director of the eLearning Sector of Research Academic Computer Technology Institute(CTI), Greece. She has designed and managed large pilot projects on the utilization of ICT in schools in Greece and abroad, and she is a consultant for various aspects of the application of eLearning into the entire educational system. She leads projects related to innovative software development for communities, collaboration and distance learning. Mike Procter obtained his BSc in Electrical Engineering in 1982 and is a registered Professional Engineer in Alberta, Canada. He has over 25 years experience in the information technology industry, with a background in realtime systems development, system and network management, project management and enterprise application deployment. He is currently an IT consultant working for Athabasca University developing software for research in animated conversational agents. Mahesh Raisinghani, is an Associate Professor in the Executive MBA program at the TWU School of Management. He is a Certified E-Commerce Consultant (CEC) and a Project Management Professional (PMP). Dr. Raisinghani was awarded the 2008 Excellence in Research & Scholarship award and the 2007 G. Ann Uhlir Endowed Fellowship in Higher Education Administration. He was also the recipient of TWU School of Management's 2005 Best Professor Award for the Most Innovative Teaching Methods;

402

About the Contributors

2002 research award; 2001 King/Haggar Award for excellence in teaching, research and service; and a 1999 UD-GSM Presidential Award. His research has been published in several academic journals such as IEEE Transactions on Engineering Management, Information & Management, Information Resources Management Journal, International Journal of Innovation and Learning, Journal of Digital Innovation, Journal of IT Review, Journal of Global IT Management among others and international/ national conferences. Dr. Raisinghani is included in the millennium edition of Who's Who in the World, Who's Who among Professionals, Who's Who among America's Teachers and Who's Who in Information Technology. Filippo Sciarrone received the degree in mathematics in 1982 and the specialization in Computer Science in 1985, both at the University La Sapienza of Rome. Since 1994, he collaborates with the Department of Computer Science and Automation, of the Roma Tre University, where he has got the Ph.D. in Computer Science in 2004. His research interests mainly focus on user modeling, machine learning and e-learning. He is currently Software Division Manager of Open Informatica srl, and holds a contract for research in adaptive e-learning with CRMPA, the Research Center of Pure and Applied Mathematics of the University of Salerno. Filippo Sciarrone collaborates with the Department of Computer Science and Automation at the “Roma Tre” University, where he received the PhD degree in computer science in 2004. His research interests mainly focus on user modeling, machine learning, and e-learning. He is currently software division manager of Open Informatica srl. Fu-Yu Shin is a teacher in Jian-Guo Elementary School in Taipei County. He teaches computer courses, such as digital image processing, media design, and applications of ICT in the school. He received his master degree in Curriculum and Instruction from National Hsichu University of Education, Taiwan in 2005. Wernhuar Tarng was graduated from the Department of Electrical and Control Engineering, National Chaio Tung University, Taiwan in 1984. After 2 years of military service, he joined State University of New York at Buffalo and received his M.S. degree and Ph.D. from the Electrical and Computer Engineering Department in 1988 and 1992, respectively. In 2003, he was a visiting scholar of the Distance and Online Learning Center, Oxford University, UK. He is currently a professor and the chairman in the Institute of Computer Science, National Hsinchu University of Education, Taiwan. His research interests include virtual reality, web-based learning, computer, and network technologies in education. Marco Temperini is an associate professor in the Department of Computer and System Sciences, Sapienza University of Rome, where he teaches programming techniques and programming of the Web. His recent research activity is on the theory and technology of Web-based distance learning, social and collaborative learning, and Web-based participatory planning. Manolis Tzagarakis holds a Ph.D. in Computer Engineering & Informatics and is currently a researcher at the Research Academic Computer Technology Institute in Patras, Greece. He has published papers in international conferences and journals. His research interests are in the areas of Hypertext and Hypermedia, Knowledge Management, Collaboration Support Systems, Web-based Information Systems, Technology-enhanced Learning, and Group Decision Support Systems. He has served the program committees of several conferences and workshops.

403

About the Contributors

Gregory Valcante earned his Master’s degree in Special Education from the College of William and Mary in Virginia and his Ph.D. from the University of Florida. He has worked as a teacher, administrator and researcher in the area of autism for 29 years and is the Director of the University of Florida Center for Autism and Related Disabilities. Dr. Valcante is a long time member of ASA. His research interests include Family Support, Collaboration & Team Building, Inclusion, Toilet Training, Social & Play Skills, and Communication Skills. Giulia Vaste got the Ph.D. in Computer Science at “Roma tre” University. Currently she collaborates with CASPUR on an E-Learning project. Her research concerns Intelligent Adaptive Learning Environments. Victor Wang, Ed.D., Faculty Mentor/Dissertation Chair, joined the faculty at Northcentral University, Arizona in 2009 and has been mentoring doctoral students and teaching research methods classes. Dr. Wang’s research and writing activities have focused on workforce education, the foundations of adult education, adult teaching and learning, training, transformative learning, cultural issues in vocational and adult education, distance education, human performance technology, leadership theory and practice, HRD/HRM and curriculum development. He has published over 100 journal articles, book chapters and books within eight academic years and has been a reviewer for five national and international journals. Currently he serves as the editor in chief of the International Journal of Adult Vocational Education and Technology. He has won many academic achievement awards from universities in China and in the United States, including the Distinguished Faculty Scholarly & Creative Achievement Award in 2009. Dr. Wang taught extensively as a professor in Chinese universities prior to coming to study and work in the United States in 1997. He has taught adult learners English as a second language, Chinese, computer technology, vocational and adult education courses, research methods, administrative leadership, human resource management and curriculum development for the past 20 years in university settings. Two of the books he has written and edited have been adopted as required textbooks by major universities in the United States, and in China. In addition, numerous universities worldwide including those Ivy League Universities have cataloged his books and journal articles. Dunwei Wen is an Associate Professor in the School of Computing and Information Systems at Athabasca University, Canada. His research interests include Natural Language Processing, Information Retrieval, Machine Learning, Intelligent Agents, Knowledge Representation, Reasoning and Discovery, and Software Architecture for Business and E-learning. Dr. Wen’s current research aims to advance theories and techniques that facilitate accessing, sharing and reusing different forms of information and knowledge in learning communities through intelligent services such as automated question-answering, knowledge querying and text mining. He has been involved in large-scale research projects for exploration based adaptive educational environments and has published over 200 research papers in international refereed journals, conferences and book chapters. He is Founding Chair of IEEE Technical Committee on Learning Technology and editor of the SSCI indexed Journal of Educational Technology and Society (ISSN 1436-4522).

404

405

Index

A

C

Active Learning 96 Active Server Pages (ASP) 149 Adaptive Educational Hypermedia (AEH) 18, 19, 20, 43 Adaptive Learning System 1, 2, 3, 4, 5, 8, 9, 11, 12 Adaptive Navigation Support 46 adult education 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 352 Advanced Distributed Learning (ADL) 217 ALEKS 227, 228, 229 ALICE 69 ANCOVA 6, 9, 10, 11 andragogical 264, 272, 276 Angel Learning 291 Animated Pedagogical Agents (APAs) 66, 67, 68, 69, 71, 74, 75 argumentative collaboration 199, 200, 201, 202, 204, 205, 207, 211, 213 artificial intelligence (AI) 80, 81, 93 Artificial Intelligence Markup Language (AIML) 69, 70, 71 Asynchronous Communications 96 Autism 232, 233, 234, 235, 245

Campus Technology 258 career and technical education (CTE) 280, 281, 282, 283, 284, 289, 292, 293, 294 Case-Based Reasoning (CBR) 47, 48, 49, 51, 63 CAST 291 Centre Europeen pour le development de la Formation Professionelle (CEDEDFOP) 144 cognitive approach 274 Collaborative Learning 145, 157 community of inquiry 316 computer-mediated environments (CME) 183 computer-supported cooperative work 199 constructivist 266, 271, 272, 274, 277 Consumer Navigation Behavior (CNB) 182, 186 Content Repository Management System (CRMS) 221 Conversational Agents 66, 76 CoPe_it! 199, 201, 202, 204, 205, 206, 207, 208, 209, 210, 211, 213, 215 Course Management System (CMS) 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139 Curriculum Design

B bCisive online 201 Blackboard , 265, 269, 275, 281, 291, 294, 345 Blended Courses 162 blended learning 157

D Decision Support Systems (DSS) 81 Degree Of Interest (DOI) 46, 54, 55 Description Logics (DL) 80, 94 Distance Education 162, 172, 281, 294, 296, 297, 298

Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Index

E E-Advisor 79, 80, 81, 82, 84, 85, 86, 92 Educating Fathers 232 Educational Systems 79, 93 Educatonal IS 46 e-Learning 3, 4, 5, 8, 10, 11, 13, 14, 17, 43, 46, 143, 144, 145, 150, 151, 158, 159, 160, 161, 216, 217, 218, 219, 221, 223, 225, 227, 228, 229, 230, 231, 316, 318, 320, 322, 323, 324, 325, 328, 329, 334, 335, 342, 345, 347, 350, 353 ELM-ART 19, 21, 22, 43, 45, 61, 62 epistemological positions 264, 270, 272, 277 ERDAS Imagine 148 European Higher Educational Area (EEES) 326, 330 European Union (EU) 323, 324, 325 EXPUSE 181, 182, 184, 186, 187, 189, 192, 193

F face-to-face learning 96, 97, 98, 99, 100, 102, 107, 112, 114, 115, 117, 299, 300, 301, 304, 305, 306, 307, 309, 310, 311, 312, 313, 333 Family Training 232, 235 Flow 181, 182, 183, 184, 185, 186, 187, 189, 190, 191, 192, 193, 194, 195, 196 Flow constructs 181, 182, 183, 185, 189, 191, 192, 193 Flow states 181, 182, 183, 184, 185, 186, 187, 191, 193 formative assessment: 166 formative evaluation 142, 152, 153, 155, 157, 158

HyperCase 47, 48, 49, 51, 61, 62 Hypermedia Technologies 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 61, 62, 63, 64, 65 Hypertext Markup Language (HTML) 122

I Imperfect Flow 181, 183, 184, 185, 186, 187, 189, 190, 191, 192, 193 Imperfect-intensive Flow 181 incremental formalization 199, 204, 205, 215 Index of Learning Styles (ILS) 20, 24, 25, 26, 35 information and communication technology (ICT) 143, 316, 317, 318, 319, 321, 322, 323, 324, 325, 326, 327, 328, 329, 332, 335, 336, 337, 338, 339, 343, 349, 350, 351, 352, 353 Innovations 248 instruction paradigm 251 Intelligent Systems 92, 93 Intelligent Tutoring Systems (ITS) 18, 19, 21, 22 Intelligent Web Teacher (IWT) 18, 20, 21 International Society for Technology in Education (ISTE) 249 Internet Information Server (IIS) 149 Internet technologies 200 Issue Based Information System (IBIS) 201, 211 item response theory (IRT) 4

J Java Database Connectivity (JDBC) 223, 224, 225, 226 Java Learning Environment (JLE) 325

G

K

Grasha-Reichmann Student Learning Style Scales (GRSLSS) 305 Gregorc Style Delineator 300, 302, 307

knowledge-based society 149 knowledge transfer 166

H

Learning Achievement 1 learning environment 96, 98, 99, 101, 106, 107, 109, 111, 113, 114, 115, 116, 117 Learning Hierarchy 1

Help Module 51, 54 Higher Education Historical Figure Agents 66

406

L

Index

Learning Management Systems (LMS) 18, 43, 99, 100, 101, 103, 111, 114 Learning Object 216, 222 learning paradigm 251 learning platform 142, 144, 149, 153, 154, 155, 156, 157, 158 Learning Responsibility 1, 6, 11 Learning Style Inventory (LSI) 301, 302, 305 learning styles 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315 Learning Template Personalization (LTP) 219, 220, 221, 223, 226, 227, 228 Lecomps5 16, 17, 21, 32, 33, 34, 35, 36, 40, 41, 42, 43, 45 Library of Thematic Cases 49, 50, 51 Linear Time Logic (LTL) 29 LS-Plan system 16, 17, 18, 19, 20, 22, 23, 24, 32, 33, 34, 35, 36, 39, 40, 41, 42, 43, 45

M Master of Science in Information Systems (MSc IS) 81, 83 Middle East 96, 97, 98, 100, 117, 121 MindDraw 201 Multimedia 232, 264, 268, 269, 275 Myers-Briggs Type Indicator (MBTI) 302, 303

N national capital territory (NCT) 187 nature of knowledge 264, 269, 270 NAUTILUS 62 NTeQ 291

O objectivist 270, 272, 273, 274, 277 Object Oriented Learning Activity System (OOLAS) 4 OMG’s Model Driven Architecture (MDA) 80, 81, 84, 93 online education 280, 281, 282, 283, 284, 287, 289, 290, 291, 292, 293, 294 online learning 300, 304, 305, 306, 307, 309, 312, 313, 315 Online Learning Community 96, 98, 99, 101,

103, 104, 105, 107, 111, 113, 114, 115, 116, 118, 119 Online Teaching 162 Ontology Agent and Database & Knowledge Base (DB&KB) 81 Ontology-Driven 79, 80, 81, 84, 85, 86, 87, 88, 92, 93 Ontology Driven Architecture (ODA) 81, 92 ontology-driven software development (ODD) 81, 84, 85, 86, 87 Open Educational Resources (OER) 321 Open Source Software 216, 218 Optimum Stimulation Level (OSL) 183, 186, 187, 190, 191

P PDDL language 24 Perfect and Imperfect-Intensive Flow (PIIF) 181, 187, 189, 190, 191, 192, 193 Perfect Flow 181, 183, 184, 185, 186, 187, 191, 193 Persona Effect 66, 67, 68, 69, 71, 72, 74, 75, 77, 78 Personalization 216, 217, 219, 227 personalized learning 16, 45 plug-in development environment (PDE) 219

R Remote Sensing 142, 144, 145, 146, 147, 148, 149, 152, 154, 155, 156, 157, 158, 160 repeat consumption behavior (RCB) 182, 184, 186, 187, 189, 192, 193 Resource Definition Framework (RDF) 80 Retrieval Module 51

S Scaffolding 1, 2, 4, 5, 6, 11, 12, 13 School of Chemical Engineering (ETSEQ) 326 SCORM 4, 13 Second Life 258, 259, 308, 309, 311, 312, 313 Secure Socket Layer (SSL) 237 Semantic Web Rule Language (SWRL) 218, 222, 229 Shareable Content Object Reference Model (SCORM) 217, 229

407

Index

Simple Object Access Protocol (SOAP) 223 Skype 258, 310 Social Constructivism , 98 social interaction 316, 322 SoftChalk 291 Standards 216, 231 Structured Query Language (SQL) 225, 230 Student-Centered Learning 248 Systems Development 79

T tacit knowledge 316, 322, 329 TADV 19 TANGOW 19, 20 teacher-centered paradigm 96, 97, 98 Teacher Education 162, 165, 172 teacher-learners 162, 163, 164, 165, 166, 167, 168, 169, 170, 171 teaching philosophies 264, 266, 269, 274, 277 Teaching Strategies 248 Technology 248, 249, 260, 264, 268, 274, 277, 299, 300, 312, 314, 315 Technology Acceptance Model (TAM) 193, 194 Technology-Enhanced Learning 248 Technology Integration 162, 164 the learning process 264, 274, 276

U United Nations Security Council (UNSC) 208 Universitat Oberta de Catalunya (UOC) 318, 323, 324, 325, 327, 328, 329, 331, 332 University Rovira i Virgili (URV) 318, 323, 325, 326, 327, 328, 329 university teaching 316, 318, 321, 323, 331 User Interface 51

408

User Needs 46

V visual, auditory, read/write, and kinesthetic (VARK) 300, 303, 307, 310, 314 visualization of collaboration 199

W Web 2.0 99, 120, 200, 201, 300, 307, 308, 309, 312, 313, 315 Web 3.0 258 Web-based Educational Hypermedia Systems (WBEHS) 46, 47, 48 Web-based Educational Systems (WBES) 16, 17, 18, 23, 42, 46 Web-Based Instruction 162 Web-based Learning , 143, 145, 149 Web-Based Training 46 Web-Based Video Training 232 Web-course 127, 128, 129, 130, 131, 134, 136, 137, 139 WebCT , 265, 269, 275, 281, 291, 294, 296, 345 web-enhanced education (WBE) 122, 123, 124, 125, 129, 131, 135, 136, 139 Web Ontology Language (OWL) 80, 81, 92, 93, 94, 218, 221, 222, 229 What You See Is What You Get (WYSIWYG) 126 Wilcoxon-Mann-Whitney test (WMW) 59, 60

X XML 216, 217, 218, 219, 220, 223, 228, 229, 230, 231