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ies on Innovative Intelligence - Vol. 8 9
.9
< 5 ^
Learning Support System JU7
Organizational Learning
Joachim P. Hasebrook Hermann A. Maurer
Learning Support Systems for
Organizational Learning
Series on Innovative Intelligence Editor: L. C. Jain (University of South Australia) Published: Vol. 1
Virtual Environments for Teaching and Learning (eds. L. C. Jain, R. J. Howlett, N. S. Ichalkaranje & G. Tonfoni)
Vol. 2
Advances in Intelligent Systems for Defence (eds. L. C. Jain, N. S. Ichalkaranje & G. Tonfoni)
Vol. 3
Internet-Based Intelligent Information Processing Systems (eds. R. J. Howlett, N. S. Ichalkaranje, L. C. Jain & G. Tonfoni)
Vol. 4
Neural Networks for Intelligent Signal Processing (A. Zaknich)
Vol. 5
Complex Valued Neural Networks: Theories and Applications (ed. A. Hirose)
Vol. 6
Intelligent and Other Computational Techniques in Insurance (eds. A. F. Shapiro & L. C. Jain)
Vol. 7
Intelligent Watermarking Techniques (eds. J.-S. Pan, H.-C. Huang & L. C. Jain)
Forthcoming Titles: Biology and Logic-Based Applied Machine Intelligence: Theory and Applications (A. Konar & L. C. Jain) Levels of Evolutionary Adaptation for Fuzzy Agents (G. Resconi & L. C. Jain)
Series on Innovative Intelligence - Vol 8
Learning Support Systems for
Organizational Learning
Joachim P. Hasebrook University of Luebeck, Germany
Hermann A. Maurer Technical University of Graz, Austria
\[p World Scientific NEW JERSEY • LONDON • SINGAPORE • B E I J I N G - SHANGHAI • HONGKONG • TAIPEI • CHENNAI
Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: Suite 202, 1060 Main Street, River Edge, NJ 07661 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE
British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.
LEARNING SUPPORT SYSTEMS FOR ORGANIZATIONAL LEARNING Copyright © 2004 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher.
For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher.
ISBN 981-238-831-1
Printed in Singapore by World Scientific Printers (S) Pte Ltd
This book is dedicated to Nils.
This page is intentionally left blank
Preface
The chapters compiled in this book are based on articles and projects reflecting the implementation and evaluation of learning support systems and applied scientific research in the last seven years, 1997 to 2003. Most articles have been reviewed, mostly peer reviewed, and published in scientific journals or volumes, respectively. However, they are not always homogenous because the papers accompany and summarize relevant sections of our work with different projects in corporate, educational, and scientific institutions. We have to apologize, if this book does not always show the full coherence and homogeneity of an original scientific publication. However, we are optimistic that it is worthwhile to work through the text of this book, nonetheless: It clearly reflects not so much a scientific research program but the development of learning and information systems (in mostly) European academic and business environments. Mostly, the examples described here are taken from our work with the German Ministry of Labor, major European private banking institutions, Austrian academic organizations and a number of international companies. We want to thank all those who helped us to put together this book: The first author, Joachim Hasebrook, would like to thank Prof. Dr. Dr. Hermann Maurer, who encouraged him to become a member of international program committees and to write papers about his work; Maurer was also a thoughtful and helpful mentor during his academic career. He gratefully acknowledges the opportunity to teach courses for the online program 'Master of Distance Education' of University of Maryland University College (UMUC) and to become a member of
Vll
Preface
Vlll
UMUC's faculty; Gene Rubin, director of UMUC's online programs, and Dr. Urich Bernath, director of distance education at the University of Oldenburg, gave him this opportunity. He would like to thank his friends and colleagues who assisted in studies and statistical analyses reported here for their help, namely Prof. Dr. Gerd Doeben-Henisch, Dr. Louwrence Erasmus, Markus Gremm, Wolfgang Nathusius, and Jiirgen Wagner. Bank Academy, the non-profit organization for ongoing education of the German bank associations, has been a supportive and exciting work place. The director of the board of Bank Academy, Prof. Dr. Udo Steffens, and the member of the board of Commerzbank and director of the supervisory board of efiport Inc., Klaus Miiller-Gebel, gave him the chance to work in the new and emerging field of 'elearning' and to become a member of the board of the educational financial portal [efiport] AG, the e-learning company of Bank Academy and the major German private banks. The second author, Hermann Maurer, would like to thank Prof. Dr. Joachim for invaluable discussions and for the possibility to contribute in this book, albeit in a minor way; he wants to thank co-authors of his papers used as basis of some material in this book, particularly Eva Heinrich and Ron Oliver. He is very much indebted to Thomas Dietinger and Frank Kappe for the support of Hyperwave, and to Nick Sherbakov for many invaluable inputs. We finally want to make it clear that the basis of this book has been a set of papers by the two authors, with much additional material added and updated. The papers at issue are: Hasebrook, J., & Nathusius, W. (1997). An expert advisor for vocational guidance. Journal of Artificial Intelligence in Education. 8(1), 21-41. Hasebrook, J., & Gremm, M. (1999). Multimedia for vocational guidance: Effects of testing, videos, and photography on acceptance and recall. Journal of Educational Multimedia and Hypermedia, 8(2), 217-240. Hasebrook, J. (1999). Exploring electronic media and the human mind: A Web-based training. World Conference on Internet, Intranet and World Wide Web (WebNet), Honolulu, Hawaii. Hasebrook, J. (1999). Searching the web without losing the mind - traveling the knowledge space. WebNet Journal, 1(2), 24-32.
Preface
IX
Hasebrook, J. (1999). Web-based training, performance, and controlling. Journal of Network and Computer Applications, 22, 51-64. Hasebrook, J. (2000). Knowledge workers and knowledge robots. Invited paper. Proceedings of International Conference of Computer in Education (ICCE), Taipeh, Taiwan. Hasebrook, J. (2001). Learning for the learning organization. Journal for Universal Computer Science, 7(6), 472-487. Hasebrook, J. (2002). Cooperative and interactive distance learning: application of team-oriented and selective learning strategies in a European bank. Journal of Universal Computer Science, 8(9), 834-847. Heinrich, E. & Maurer, H. (2000). Active documents: concept, implementation and applications . Journal of Universal Computer Science, 6 (12), 1197-1202. Maurer, H. & Oliver, R. (2003). The future of PCs and implications on society. Journal of Universal Computer Science, 9(4), 300-308. Maurer, H. (2003, in press). Necessary aspects of quality in e-learning systems. Proceedings of
Quality in eLearning Conference, Geelong University, Australia,
February 2003.
We gratefully ackowledge the permission to reprint parts of the afore mentioned articles. Especially, we would like to thank the Association for the Advancement of Computer in Education (AACE, see www.aace.org), namely Gary Marks, and the editors of the Journal of Universal Computer Science (JUCS, see www.jucs.org) and the Journal of Network and Computer Applications (JNAC). Additionally, we cited some figures and tables from the following recent works of ours: Hasebrook, J., Rudolph, D.W. & Steffens, U. (2002). E-Learning Business Strategies & Opportunities. Chichester (MI): Datacom Research Report. Hasebrook, J., Herrmann, W. & Rudolph, D. (2003). European perspectives for elearning: Markets, technologies, and strategies. Thessaloniki: CEDEFOP (European Centre for Vocational Training).
Joachim P. Hasebrook & Hermann A. Maurer
Contents
Preface Prologue: Key Trends in E-Learning Benefits from Technology Key Enabling Technologies Key E-Learning Markets E-Learning for Economic Development Public and Private Expenditures for Education E-Learning in Developing Countries Developing Regions: Asia and Africa Access to Electronic Learning in Asia Access to Electronic Learning in Africa Advantages of E-Learning in Developing Countries Learning Support in Organizations
vii 5 7 8 13 17 19 20 22 22 24 26 28
Part 1: Managment Support: Introduction Beyond the Learning Organization
31 31
1. Implementing Organizational Learning: Learning for the Learning Organization Knowledge, Technology, Strategy Web-Based Learning: E-Learning Learning Organization and Organizational Learning The Market of Knowledge Applications Knowledge and Abilities Psychological Factors of Success Competences on the Balance Sheet Value Extraction and Value Creation Capital versus Talent
37 37 41 42 46 48 52 56 59 62
2. Implementing Educational Controlling: Web-Based Training, Performance, and Controlling More Training for Less Money The Cost of Training Learning Efficacy and Cost Efficacy The Process of Controlling Calculating Success Gains from Goal-Directed Planning
65 65 66 68 71 75 78
1
2
Learning Support Systems
Part 2: Performance Support: Introduction Quality of E-Learning Environments Active Documents and Active Communication Knowledge Management
81 81 83 85
3. Implementing Web-Based Training: Exploring Electronic Media and the Human Mind From CD-ROM to Internet From Help Pages to Performance Support Systems Learning to Learn The Role of Meta-Cognition Integrating Performance Support in Learning Systems Generic Performance Support
91 91 92 94 96 98 100
4. Implementing Electronic Courses: Collaborative and Interactive Distance Learning Collaborative Learning with Electronic Media The Notion of Active Documents Implementation of Active Documents The Heuristic Approach The Iconic Approach The Linguistic Approach Applications of Active Documents The Learning Environment Experiment 1: Collaborative Learning Strategies Participants of Experiment 1 Material and Procedures of Experiment 1 Design of Experiment 1 Results of Experiment 1 Comparison of WBT and Seminar Factors of Online Learning Expert Participation Team Interviews and Discussion Learning Culture
103 103 104 105 105 106 107 107 109 111 Ill Ill 112 113 113 115 118 118 119
5. Implementing Online Curricula: New and Emerging Media in Distance Education Learning Support Systems Event and Learning Management Conducting the NEMDE Course Computer Mediated Expert Communication Learning Strategies Course Structure and Objectives
121 121 123 129 130 131 134
Contents Course Objectives Course Development Assignments Focused Discussions Effective Tutoring
3 134 139 145 148 152
Part 3: Decision Support: Introduction
155
6. Implementing Expert Guidance: Expert Advisor for Vocational Guidance Career Decision Making Models for Vocational Guidance Vocational Interests of Young Adults Knowledge and System Engineering for Vocational Guidance Calculating the Goodness of Fit Matching Careers to Individual Interests Implementation of the Expert Advisor System Implementation and Product Development Evaluation of the Expert Advisor Career and System Options
159 159 161 161 162 164 165 167 170 171 177
7. Implementing Adaptive Multimedia: Effects of Individualized Testing, Videos, and Photography on Acceptance and Recall Media Effects Career Counseling Pilot Study Experiment 2: Photo and Video Participants of Experiment 2 Design of Experiment 2 Materials and Procedure of Experiment 2 Results of Experiment 2 Summary of Experiment 2 Experiment 3: Individual Information Participants of Experiment 3 Design of Experiment 3 Materials and Procedure of Experiment 3 Results of Experiment 3 Summary of Experiment 3 Field study: Comparing Electronic and Printed Media Summary of Field Study Mental Integration of Multiple Media
179 179 181 184 184 184 185 185 186 189 190 190 190 191 191 193 194 196 196
4
Learning Support Systems
Part 4: Self Learning Systems: Introduction
201
8. Implementing Knowledge Structures: Searching the Web Without Losing One's Mind Visionary Terabytes Reality Bites The Myths of Multimedia and Hypermedia Myth 1: More Media Leads to More Learning Myth 2: Hypertexts Convey Structural Knowledge Myth 3: Web is Easy, Print is Tough Complexity of Models and Reality SHOEs for Web Walkers Traveling Agents: Knowledge Robots Educating Knowbots for Education
207 207 208 210 211 212 213 215 217 219 221
9. Implementing Knowlegde Robots: Knowledge Robots for Knowlegde Workers Entering the Infoverse If It Works, It's not AI Neuroscience Aspect Information Science Aspect The Age of Intelligent Machines
225 225 227 228 234 238
Epilogue: Future Developments E-Assisted E-Learning in 2010 The Wizard in the Glasses E-Assisted E-Learning in the Future Virtual Keyboards Global and Culture-Fair Communication PDAs Revisited What We May Learn Planets of Learning Ecology of Mind Virtual Minds Maps and Minds Invisible Computing and Embedded Learning
;.. 241 241 243 245 245 246 248 249 251 253 254 256 258
Appendices
263
Bibliography
269
Index
287
Prologue
Key Trends in Global E-Learning
The major trends with the biggest impact on the global e-learning markets and learning support technologies are. * the increasing demand for academic degrees, * growing numbers of students attracted to educational hubs, and « the rapid growth of non-traditional, especially elderly, target groups. We are convinced that all effective e-learning scenarios will be centered around personal tutoring. Sustainable e-learning efforts will need sufficient private and public financing. Regular content updates by skilled subject matter experts as well as careful control of the didactical quality of the delivered content will be essential. Additionally, costeffective e-learning will only emerge from already existing systems and processes, such as corporate databases, human resource management or public administration and 'e-government'. In general, e-learning will make education more effective but not better, because technology is aimed to enhance the efficacy of processes whereas didactics' objectives are to enhance the quality of the steps and tools involved in the learning process. E-learning mostly is a piece or a system of software, although some hardware - like computers and networks - always has to be involved. Efficient software provides the opportunity to be more scaleable, flexible and personalized than without adequate software. Hardware, however, is measured - according to Moore's law - in terms of cost per unit (e.g. the price for one million instructions per second). Unfortunately, e-learning software has been 'sold' to the educational markets like a piece of hardware, promising it would cut costs for travel, accommodation, personnel and delivery of 5
6
Learning Support Systems
content. Many e-learning vendors, however, painstakingly learned that labor intensive tutoring, didactical adequate media and up-to-date contents are costly key success factors for e-learning. In a corporate environment, e-learning will fail like other forms of electronically supported learning, such as computer-based training (CBT), if it cannot become an integrated part of corporate knowledge and human resources management. In public and academic environments, e-learning will only flourish if it does not add too much effort and costs to the processes in place. E-learning will not be a 'killer application' for the further expansion of international markets for electronic devices. Instead, e-learning has to become one of the key drivers of a rapid international knowledge transmission and transition. This will lead to accelerated economic development and will give a multilingual and multicultural society incredible opportunities to support the creation of global alliances and wealth. One of our core assumptions is that e-learning does not replace traditional classroom education. Instead, it expands the market for education products and services. Thus, e-learning assists the growing population of non-traditional learners, many of whom must divide their time between work and school, to pursue an education. Further, e-learning solutions can be applied to non-education markets such as public relations, sales, and investor relations. The same tools developed to facilitate imparting knowledge to students can be used with great effect in persuading customers, investors, and commentators. Corporate training, career development, and expert enhancement are areas ripe for sustainable growth. E-learning facilitates cost-effective production and delivery of courses for specific companies, jobs, and skills. E-learning technology enables course authors and producers to readily re-use content in different courses or different versions of the same courses. Thus, e-learning courses can be more customized than traditional classroom teaching. The ability to address special needs with minimal effort ensures the broadest possible market for any given content. While there has been much interest in using the Internet for 'distance learning,' its use as a global distribution channel presents a much bigger opportunity. Highly specialized courses for which there is
Prologue
1
insufficient local demand may do well in the global market. The Internet can also increase the success of courses that do well locally. Benefits from Technology E-learning will change our minds about how much education we need, and when and where learning can take place. When education is a purely local affair, highly specialized courses are sometimes not viable due to insufficient enrolment. The ability to offer such courses to the global market makes a difference. There are also many people who would like to take courses but who do not have the time or cannot commit to attending a regular class. Education is already a big business. E-learning, by making it easy to impart information and skills to anyone, anywhere, anytime, and for any purpose will grow the education market. As always, the big winners will be those vendors that identify and serve emerging and sometimes hidden markets. Recently, the 'Organization for Economic Co-Operation and Development' (OECD; www.oecd.org) published a report e-learning: the partnership challenge (OECD, 2001) examining the status and growth perspectives of electronically supported learning and skills development in all 30 member countries and some of the more than 70 associate countries. The key findings concerning possible benefits of use of information and communication technologies (ICT) are listed in the following table 1. E-learning technology can be used almost anywhere and anytime. The lines between traditional education, self-improvement, and marketing are being blurred - just as the line between education and entertainment has blurred. The biggest growth segments unleashed by e-learning are education for non-traditional students and the use of educational methods in related areas such as public relations, sales, and investor relations. E-learning permits dramatic expansion of the education market. While 'distance learning' is the best-known example, we believe providing continuing education for busy professionals is even a much bigger opportunity.
8
Learning Support Systems
E-learning is primarily about superior solutions for self-study and online courses. These solutions, however, can be readily adapted to sales and public and investor relations. In both cases, the object is to get information across to the recipient. While the education industry correctly emphasizes the learner, that does not mean there is no longer a need for teachers. Teaching and persuading have many things in common and can share many of the same advanced tools. Corporate training and personal career development are segments ripe for considerable growth. Businesses need to impart both general skills and company-specific information to their employees. They need solutions that are highly reliable, consistent, and available in order to bring new employees quickly up to the required level of competency. Increasingly, corporations are realizing that the Internet and extranets can be used to train customers and business partners, as well as persuade investors, consultants, industry analysts, and potential customers. Table 1. Benefits of using ICT to deliver learning (OECD, 2001, p. 23) Things that cannot be done without technology the de-materialization of time and space - learning any time anywhere mass-education - access to learning for everyone Internet access to ever growing collections of educational resources and services input for task-based learning using fast search and retrieval software, or for research work learning on demand peer-group teaching / learning through distance learning via ICT Things which can be done better with technology the choice of learning style customized and personalized learning materials and services individualized tracking and recording of learning processes self-assessment and monitoring of learner performance interactive communications between participants and influences in the learning process interactive access to educational resources
Key Enabling Technologies Technology penetration has been greatest in the workplace, although other sites such as homes and community centers are increasingly wired
9
Prologue
up (see figure 1). OECD countries greatly increased their personal computer (PC) base in the 1990s with an average number of PCs installed per 100 inhabitants rising from 10 in 1992 to 24 five years later. In 1997, the Nordic countries, Switzerland, Australia, and the Netherlands had a higher ratio than all G7 countries but the US (OECD, 2001).
• 1992 total • 1997 total M1997 education
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Figure 12. Screen shot from the Skills Management Information System 'SMIS' adapted for Deutsche Bank/Private Banking (Germany) - selection boxes help to identify job roles, prior knowledge, and time schedules (left), a colored table indicates skills covered by recommended training courses (right).
Learning Organization
49
The group defines itself as follows: The HR-XML Consortium is an independent, non-profit association dedicated to the development and promotion of a standard suite of XML specifications to enable ecommerce and the automation of human resources-related data exchanges. The mission of the HR-XML Consortium is to spare employers and vendors the risk and expense of having to negotiate and agree upon data exchange mechanisms on an ad-hoc basis. By developing and publishing open data exchange standards based on Extensible Markup Language (XML), the Consortium can provide the means for any company to transact with other companies without having to establish, engineer, and implement many separate interchange mechanisms (cf. figure 13). Members of this consortium are big ICT companies like IBM, Cisco and Oracle, as well as software companies like SAP and Peoplesoft, and staff agencies like Randstad and Manpower, or financial services like Charles Schwab & Co. At the moment, about 100 companies belong to the consortium. The introduction of this standard and the early adaptation of the solutions in store put both vendors and users of software solutions and services in the areas of e-cruitment and e-learning in an exclusive position among the competitors and enable them to organize global markets. Internationally acknowledged and XML-based standards for the description of knowledge products are being developed for e-learning. The most important standard is Learning Object Metadata (LOM). Here is the self-description of the LOM Consortium [http://www.manta. ieee.org/pl484]: 'The mission of the consortium is to develop technical Standards, Recommended Practices, and Guides for software components, tools, technologies and design methods that facilitate the development, deployment, maintenance and interoperation of computer implementations of education and training components and systems. Many of the standards developed by LTSC will be advanced as international standards by ISO/IEC JTC1/SC36 - Information Technology for Learning, Education, and Training.'
Learning Support Systems
50
Name Description Competence ID (prim, key)
required (Y/N)
Taxonomy Entry Competence
Competence Evidence Application Domain Subordinated Competence
Primary Key T Description T Owner
Key • Description T Owner
Figure 13. Structural model for the description of competences according to Human Resource XML - white boxes indicate simple data types (e.g. strings), grey boxes indicate complex data types (e.g. records); source: 'Competencies (Measurable Characteristics) Recommendation, 2003 February 26'.
There are several providers for software and consulting in the field of e-learning and especially in the development and management of skills. Beside the modules for the administration of human resources (HR) by SAP and PeopleSoft, there are specialized providers, e.g. Meta4 from Spain or Infinium, and SkillsScape from the USA. Since the majority of enterprises confine themselves in their staff development to the handling of biographical and administrative data, most of the offered software solutions support the administration of human resources only. However, since the rise of the information society and its evolution into a knowledge society there is a need for a strategic reorientation from the administration to a more active development of skills in human resource management (HRM). In this context, skills-oriented management
Learning Organization
51
paradigms have lately come into existence which are now considered in corresponding management information systems (MIS). The vast majority of providers of software and service solutions in the field of HRM are still concentrating on administrative solutions, which are of little help in the proactive planning and usage of skills in enterprises.
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Figure 20. A Web-based training developed by efiport in charge of Raytheon Training and General Motors Acceptance Company combines off-line and on-line elements, such as CBT-like naYigational aids, search facilities, bookmarks and a test database.
The first author has developed a test database to create, maintain and deliver exercises and tests within various environments from one source: Print-outs, stand-alone applications, and Java applets to be integrated in
Educational Controlling
71
WBTs (Klemme & Hasebrook, 1999). A broad range of interaction types have been implemented which enable the test database to provide surveys concerning acceptance ratings, to conduct knowledge tests and to store and process the input data. Figure 20 displays an example for a test evaluation form of a WBT which has been developed in charge of General Motors Acceptance Company (GMAC): After having passed an on-line exam, the user has the option of filling in his or her name on an evaluation form and to submit the learning results voluntarily. Of course, it is possible to store the data mandatory and automatically by the system itself. However, in many European countries strict rules of personal data security and individual performance controlling must be regarded which do not allow for automatic data collection and storage. The Process of Controlling Most HRD and educational departments generally use stepwise controlling processes which consist of the following consecutive phases: « Needs analysis - define strategic and operational goals and needs * Conception and planning - define learning objectives, decide to make or to buy, apply adequate didactics and organizational preparations ® delivery and conduction - control and support learning processes, collect evaluation data on-line and offline * Evaluation and transfer - analyze evaluation data and control transition to the work place Although this schedule appears somewhat comprehensive, it does not address the needs of an on-going learning process which permanently delivers information, learning, and communication services to learning stations and work places (Paul & Siewert, 1996). Modern economic controlling does not focus on strict schedules but on the permanent improvement of process outcomes. Therefore, modern controlling is a highly interconnected process which starts with the definitions of goals, problem analyses and prognoses, which rely on benchmarks and judgement of reasonable alternatives. A decision is made based on the data from these early stages and the realization is evaluated in order to
72
Learning Support Systems
come up with an detailed comparison of problem analyses and goal definitions. This comparison is used as feedback to adjust the following goal definitions. The feed forward loop from goal definition to evaluation is used as a fact finding process whereas the feed backward loop is used to store relevant data and lessons learned (cf. figure 21). Feed forward - collecting information
Evaluation
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Problems
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Implementation
'' Alternatives
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Figure 21. A comprehensive model of a modern on-going controlling process (Paul & Siewert, 1996).
A WBT about currency management developed in charge of a major German bank illustrates how feed forward and feed backward loops may be implemented in on-line learning. The WBT is based on the Hyperwave information server (Maurer, 1998) and the learning platform TrainingSpace (formerly GENTLE; Dietinger, 1998, now eLS, see www.hyperwave.com). This software stores and maintains the user interface (e.g. buttons, frames), the structure (e.g. links, hierarchy of pages) and the actual content (e.g. HTML-pages, images) separately. Thus, all complete WBT pages are composed on demand and may contain individual information, such as notes and user defined links, without interfering with the contents of the WBT delivered to other users. We conducted a pilot study with 70 participants. Half of them were pooled in learning teams with 5 persons each and the other half studied
Educational Controlling
73
individually. All participants were allowed to take notes and write contributions to the discussion forum. All notes and contribution were typed according to their contents, that is the user decided whether she or he wants to type in a question, an answer, an agreement, a disagreement or a simple remark. All notes containing questions were sent as an email to an expert. All public notes were copied to the discussion forum. The WBT consisted of five modules consisting of approximately 120 pages each. Each user took an average of four notes per module and additionally wrote one or two messages to the forum. The notes did not only support the learning process by motivating the users to discuss the subject matter of the WBT. They also provided an tremendously useful source of information for the adjustment and improvement of the system (cf. figure 22; Kunz, Drewniak & Schott, 1994). The results of this study are reported in full detail in chapter 4 of this book. WBT clearly has the capability to support feed forward and feed backward processes: Notes can be linked to particular pieces of information in the WBT and copied to a forum. Colors and icons can indicate the content and access rights of notes and forum messages; messaging systems support the flow of information between individual learners, learning teams and subject matter experts; frequently updated information and background libraries allow the WBT to be up-to-date even in rapidly changing environments. In order to account for the various roles and uses of WBT in a modern business environment, two areas of controlling data should be regarded (Meier, 1995): A. Controlling of learning outcome * Acceptance data (e.g. surveys, interviews, group discussions); 48% of all German banks collect acceptance data. * Performance data (e.g. study time, learning outcome, stability and sustainability of the learning outcome); about 25% of the German banks collect performance data systematically. * Problem solving and transfer (e.g. case studies, workshops, observation and judgements in the work place); 73% of the German banks use at least one of these methods. « Career development (e.g. individual discussions with employees, evaluation of the individual career steps); only 52% of all banks regularly evaluate the career development of their employees.
Learning Support Systems
74
Corporate success (e.g. Controlling of corporate and.department goals, sustainability of the success); probably nearly 100% of the banks are engaged in regular evaluation of their success measurements.
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It has to be regarded, however, that most of the data mentioned above (e.g. acceptance and performance ratings) are independent and do not correlate with one another significantly (Kunz, Drewniak & Schott, 1994). Therefore, missing data cannot not be estimated referring to
Educational Controlling
75
another set of data. The other area of controlling is described in the following list: B. Controlling of transfer In the work place « Overall acceptance ratings of the learning environment * Observations (e.g. team discussion, work performance) « Judgements (e.g. regular evaluation meeting and individual judgements of employees) » Follow-up (e.g. workshops of regional teams which adapt generic training courses to their particular needs) Directly after training « Knowledge tests (e.g. self tests, examinations, comparison of preand post-tests) * Discussion between employee and employer ® 'Transfer partnership' or learning groups discussing the learning outcomes Controlling the transition from learning to working and checking the sustainability of learning outcomes are the crucial factors which improve quality and success of training - and makes it possible to calculate the success of training applications, doing away with guess work. Calculating Success Pichler (1996) conducted a national study on marketing and counseling training for retail bankers of a German bank. He found costs to be approximately 840 Euro per participant and day. The net income resulting from the training was about 2,600 Euro per participant in the first year. Comprehensive scoring models must be employed in educational controlling in order to come up with reasonable calculations of training costs and income. Kaplan and Norton (1997) have suggested such a model consisting of 'Balanced Score Cards', which take into account financial data, innovation rates and customer satisfaction. All cards are rated using scores derived from historical corporate data and benchmarking. Benchmarking and the use of control groups without training help to estimate the gains of training investments. However,
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there is no linear correlation of learning effort and learning outcome. A rough estimation states that 50% of the efforts produce about 80% of the results, that is: There is much more effort needed to get slightly better results, if the level of performance is already high (cf. figure 22; group 1 and 2). The graph depicted in figure 23 illustrates the non-linear correlation of learning effort and learning outcome. Having defined the learning objectives once, the graph identifies the investment needed to achieve these goals. Moreover, the probable learning outcome may be estimated if the actual investment has been pre-defined. The graph does not only provide a rough understanding of the correlation of the different factors. It may also be used to calculate numerical parameters of a statistical function that provides a sound estimation of the financial benefits from various levels of efforts and outcomes (e.g. Arnold, Cooper & Robertson, 1995; pp. 159). Critical parameters are: the percentage of persons of the target group that is able to fulfil the learning objectives (criterion), the percentage of persons of the target group who pass the test or exam (selection) and the correlation of criterion and selection procedure (validity). In order to calculate the following terms all individual scores are given as the z-score: x, + u z = ———
with
8 // = — V ^
and
n
Therefore, the z-score is obtained by subtracting the arithmetic mean from the individual values and division by the standard deviation. This procedure ascertains that all values are normally distributed with a mean of zero and a standard deviation of 1. With perfect selection, the average z-score of the selected learners would be the average work performance resulting from the training investment. The work performance, however,
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will depend on the accuracy of the selection, that is the validity of the test procedures involved.
Group 1 „ (high level)
Outcome actual gains
Group 2 (low level)
Outcome (objective)
Efforts/ Investment Figure 23. The non-linear function of learning efforts (investments) and learning outcome - if a learning result has been defined, the necessary effort can be identified (and vice versa).
The validity of the knowledge test can be estimated by calculating the linear correlation of the test scores and a independently measured criterion, e.g. using methods of transfer controlling. The linear correlation of two values is given by: r=
P* SS„
with
n A conservative rule of assigning financial values to performance measurements is to assume that 40% of the salary is assigned to each standard deviation of work performance. This leads to the following estimation of the financial benefits from training investments:
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benefits
= — rtestcriterion • dyear • cyear with n N = number of candidates in the training (e.g. during one year) n = number of selected candidates by test scores (e.g. in one year) r = validity of test d = duration or number of years candidates will stay c = number of candidates tested per year Gains from Goal-Directed Planning Several conclusions can be drawn from this course of reasoning: The financial gain is enhanced if there are many adequate candidates, a low selection ratio and tests of high validity. All these parameters cannot be estimated and controlled in a short period of time. Educational controlling, therefore, demands an on-going collection of adequate data during a given period of time. Initial positive results cannot be expected within the first six months. However, collecting and analyzing educational data is worth the effort: Computer programmer aptitude tests were used to select computer programmers in the US; with a selection ratio of 50% gains of between 13 and 37 million US-Dollar can be expected in one year (Arnold, Cooper & Robertson, 1995). Using educational controlling procedures may also have such enormous positive effects. All relevant data needed to calculate the financial gains can only be collected and evaluated in an on-going controlling process. Additionally, data derived from such a controlling process support the evaluation of historical corporate data as well as planning the future. Thus, Web-based training should not be viewed as a simple extension of traditional computer-supported learning approaches. It should be used to introduce a modern controlling approach which comprises exact calculation of financial investments and gains, optimal planning of organizational processes and goal-oriented definitions of strategic and operational learning objectives (Hasebrook, 1999). Web-based training will then allow the educational and IT staff to take over a strategic role to establish an innovative learning and working culture within the corporation. Web-based training will be a successful complement to
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traditional ways of delivering training if it proves to be a solid basis for goal-oriented planning and cost-effective training solutions.
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Part 2
Performance Support: Introduction
The empirical evidence does not support the mad dash to use multimedia content in education. A recent meta-analysis examines 248 research studies on computer-aided learning. 150 studies failed to show any significant benefits. The other studies showed only a slight advantage over textbooks or lectures: error rates for simple retention tests were reduced about 10%, problem solving was hardly enhanced, and study time was reduced about 30%. Though multimedia seems to save time and reduce simple errors, it has not been found very effective as a problemsolving tool. Reviewing several meta-analyses, it seems clear that the use of multimedia is not the main factor influencing learning: Measured learning gains are most likely due to instructional methods. Fortunately, there are some studies showing that multimedia can facilitate the learning process. The Software Publishers Association (1995) reviewed the impact of instructional technologies in 133 school studies from 1990 to 1994. They found better test results, increased selfreliance, and closer interaction between students and teachers. Similarly, Boettcher (1993) collected 101 success stories. Many other studies show: Multimedia can enhance communication and motivation. This does not necessarily lead to improved learning but it can facilitate learning beyond the classroom. Quality of E-Learning Environments It is worthwhile that we start this section with three points that we strongly believe in: 81
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First, e-learning must not be seen as tool to teach larger groups in a stratified way, but rather to provide individualized teaching at the right level of knowledge and cognitive skill of the individual student involved. This does not mean that it can't be cost effective and that it cannot be used for large groups, but it does mean that the material must adapt itself to the users: it must not provide a 'one size fits all'- kind of solution. Second, although most members of the e-learning community have slowly started to agree that e-learning material must provide more than a slightly interactive electronic book, it is less widely understood that digital libraries (be it self-produced or purchased from publisher) can and should be used to provide important background information. Putting it differently, courseware consisting of stand-alone units that do not make use of existing digital libraries, be it local or on the WWW, provide a focus that is much to narrow. Third, it must be recognized that no university or company can or should compete with Hollywood or TV Studios when preparing e-learning material. Good and pleasing content is necessary, but impressive multimedia material is not the answer (indeed may be distracting in some cases), but the answer is the use of a suitable e-learning environment. In this section we just want to address a few features of e-learning environments from a user perspective that are often not considered seriously enough. For a full set of functions required in a good e-learning environment see e.g. the e-learning Suite of Hyperwave [www.hyperwave.com ] (Maurer, 1996) or the efiport learning support system [www.efiport.de] (Hasebrook & Otte, 2002). First, any good e-learning system should provide pre-tests to determine the knowledge of the student involved, and if possible also the most suitable cognitive style. Note that as far as cognitive style is concerned there is widespread agreement that the performance of learners may well depend on how material is presented, yet there are few attempts to systematically exploit this in the knowledge transfer process. Second, a good e-learning system must support all paradigms for learning that we often hear about: no single paradigm is ideal for all applications. For fact learning, behaviorism (drill and practice) remains as valid as ever and should not be looked down upon, the 'cognitivistic' approach is the one often best suited, unless constructivism is a viable
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alternative. But there are other approaches like implicit learning (Holzamer, Pichler, Ahner & Maurer, 2001), situated learning (Maurer & Pivec, 2001), that also must not be ignored. Third, users should be able to work with the material to an extent that goes beyond all learning theories: we will return to this in the next section. Fourth, when e-learning is used in a networked environment (and notnetworked attempts have been successful only in very isolated cases) the network must be exploited for communication and collaboration to the fullest, including discussion forums, chats, shared work spaces and the like. Note in particular that although discussion forums are in widespread use by now, such forums rarely are powerful enough to handle largescale discussions, including the re-structuring of discussions, the merging of discussions or the extraction of parts of a discussion as a special resource used elsewhere. Systems with powerful discussion forums are e.g. eLS and WBT-Master, but some basic rules have already been formulated much earlier (Maurer, Rozsenich & Sapper, 1999). Fifth, any kind of courseware or teachware should not be seen in isolation, but always in conjunction with sufficiently large digital background libraries. Such libraries can consist of material generated in the course of other activities, or can be purchased in the form of libraries available on the WWW or material on CDs and DVDs. As is pointed out by Maurer and Tochtermann (2002) using techniques from knowledge management to be discussed in a later section, automatically generated links even in a way that they can be visualized as 'knowledge maps' such as the ones in the multimedia encyclopaedia 'Brockhaus Multimedial' should and can be used. For some aspects of digital libraries and their use consult Marchionini & Maurer, 1995; Lennon & Maurer, 1995; Maurer, 2001). Active Documents and Active Communication It is generally accepted that passively observing material on a computer screen, no matter how many pictures, diagrams, animations, movies, audio material etc. are used is not enough to create a productive learning
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situation. Much more interaction is essential. This is, after all, the basis of many learning theories. Only by letting students solve problems, collaborate with each other etc. will they be sufficiently involved in a process conducive to serious learning. However, what is often overlooked is that students should also be allowed to 'massage' material that is presented to them, by adding notes, adding links to the WWW or a background library, by attaching files, by highlighting, supplementing or erasing parts of what is shown to them etc. In each case, such changes will either be just for one student (producing a particular student's view) or for a group (producing a special view of the group collaborating). It is our experience that in this way material offered to students will expand, different persons or groups of persons ending up with often surprisingly different versions of the original teaching material (which of course is never modified as such: the modifications are only superimposed and only visible to those who have authority to see them: nobody except for the original author can change the underlying substance.) Communication is not just important to break the isolation of students in an e-learning environment but also for a much more basic reason: whatever one person says or writes, the receiver of the information will always interpret the information in the receiver's personal context, created through upbringing, culture, language, etc. This does often lead to deep misunderstandings. Our favorite example is the story of a fish who, when hearing of a flying animal does not think of a bird as we know it, but of course of a fish with wings; or when hearing of a 'four legged animal with an udder with milk' is more likely to imagine a frog with an udder with milk than a cow, simply because frogs are probably the only four legged creatures fish know. It is often claimed that a picture says more than a thousand words. And this may well be true, but although at times miss-conceptions might be resolved using pictures, this is by no means always the case: a fish who happens to see a person drinking a glass of water will be quite dumbfounded, for such action does not seem to make sense to the fish; a nomadic person in the dessert (who has never seen anything but the dessert) will not understand the picture of fog rising over a lake, nor will the traditional Indian in the Amazon jungle be able to make much sense
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of trees covered with lots of snow when shown a picture of a winter scene from Austria. The only way to make sure that information is properly understood is not by reading, hearing, seeing, but by being able to check if things have been understood and by asking questions: this is why an e-learning system that ignores the importance of communication will not work. There is one more subtle aspect about communication: We believe that communication should not be restricted to communication between persons but should be extended to cover communication between students and documents. To formulate it in an exaggerated way: We would like to see systems where a student who sees something on the screen can type in any question whatsoever and the document gives the answer. Although this sounds like absolutely impossible, the situation described can be approximated quite well if the information on the screen is viewed by many thousands of persons before it changes. In this case the concept of 'active documents' (Heinrich & Maurer, 2000; Heinrich, Johnson, Luo & Maurer, 2001) can be applied: when the first few hundred users ask questions, the answers are given by experts, but both questions and answers are stored in a database. Later questions that can be recognized to be semantically identical with earlier ones by the system can then be answered by the system, i.e. the documents. In large applications we have found that over 99.5% of all questions can indeed be answered without human intervention. The 'Knowledge Information Center' of Hyperwave is one such software module. Indeed, many of the features discussed so far, and including the knowledge management aspects to be discussed in the next section have been successfully handled by extending Hyperwave. For background information consult (Maurer, 1996; 1998). Knowledge Management Teaching and learning are clearly involving.knowledge transfer, and hence e-learning is clearly a small subset of the fairly new but increasingly important area of Knowledge Management (KM). Thus, elearning must not be dealt with in isolation but with at least a minimum
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of information about KM and its tools. Rather than defining KM, it is easier to explain KM by quoting the famous statement: 'If our employees only knew what our employees know we would be a much better organization.' Thus, the original challenge of KM is to extract knowledge from persons (without burdening them with extra work), storing the information in a computer system, and making the knowledge available to users when they need it (even if they have not asked for it). It is exactly the two parenthesized remarks in the last sentence that distinguish KM systems form ordinary information systems or databases: in ordinary information systems, information has to be input and requested explicitly. Surprising as this may sound, the automatic extraction of knowledge without imposing extra work on the persons whose knowledge is desired, and the provision of relevant information at the right moment is indeed possible to an increasingly high percentage. For details we refer to Maurer and Tochtermann (2002) and the references therein, e.g. (Ives, Torrey & Gordon, 1998; Meersmann, Tari & Streus, 1999). However we would like to at least mention three of the many tools that are currently used in KM that directly apply to elearning: the first two, 'knowledge maps' and 'active documents' we have already briefly mentioned above. And the active document concept contains in it the seed for something much larger: after all, to discover if two questions are semantically the same, one basically needs mechanisms to discover if two documents are similar. It is this similarity- recognition that proves to be invaluable in KM and in e-learning. Let us look at a number of simple examples to try to prove our point, the first one from the commercial world, the others from e-learning. In a large, world-wide distributed manufacturing company a new project is to be undertaken. The engineers draw up, according to quality assurance procedures, a detailed description of the product in a fairly standardized manner. The Hyperwave system that we have installed in one such instance translates the specifications from whatever language into (rather mediocre quality) English. This English document is compared to the English descriptions of all projects, planned or in progress in all locations of the company at issue. If it detects a strong similarity, it alerts both groups involved to avoid potential duplication.
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This 'simple' procedure has saved the company at issue more than ten million US-Dollar in a single year. Suppose you are writing a paper. As soon as you have finished your extended abstract you switch your system into supervisory mode. It now starts to check what you have written against all material available in back- ground libraries world- wide. If it finds some 'suspicious' similarity, it will alert you: you might be frustrated since your 'novel idea' turns out to be not quite as novel as you thought (but better you find out now than later) but it may also help you to show you results you can put to good use. There are many applications that directly apply to e-learning. Similarity recognition (SR) may alert a student that another one who is doing similar stuff. SR may help students to find fellow students who are experts in topics they are currently interested in. SR may help a teacher to find out an incident of plagiarism. SR can help to short-cut discussions in forum by pointing out that the same topic has already been treated exhaustively some time back. Without going deeper it should be clear by now that tools developed for KM are very much applicable to e-learning, and must not be ignored by the e-learning community as has largely been the case with some exceptions like Hyperwave and 'http://coronet.iicm.edu' mentioned earlier. Groupware is hardware and software that enables groups of people to work together. For example, groupware enables a team to access a database containing everything related to the work process, including past discussions, memos, and meeting reports. Most groupware programs use a local area network; some run over the Internet. The main functions of groupware are: « knowledge sharing; * group calendar keeping and scheduling (for project due dates, meetings, and conference calls); « real-time meetings (e.g. chat and video-conferencing); ® bulletin boards (asynchronous discussions over long periods of time that can be stored and retrieved); and * workflow management. Applications for groupware are not just limited to teams in the same company. Many projects extend beyond the narrow confines of the
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Learning Support Systems
company. For example, architectural firms typically work with a large number of subcontractors when designing or renovating buildings. But technology is not everything. It also takes social skills to make virtual teams successful. While conventional work teams have many ways to convey information, virtual teams do not. In a virtual team, the leader must tell members early on what they are supposed to do, who makes the decisions, who represents the team inside and outside of the firm, how information is processed, and how communication should take place. The following two chapters try to examine the key success factors of learning support by using multiple media and collaborative learning systems. Effective Web-based training (WBT) has a need for adaptation and contextual information, but most WBT modules provide not more than some simple help pages or hypertext facilities with keyword indices. Help pages mostly provide information how to access functions but not how to apply them - and why. Therefore, a generic Web-based Performance Support System (PSS) was designed which can be used as a stand-alone training course about 'Learning in electronic media' or as an integrated help system supporting other WBTs. The PPS provides four modules, a comprehensive glossary, a keyword and a full-text index as well as a graphical overview with brief summaries of all modules. In order to motivate users to apply learning strategies about fifty so called brain tests were integrated: Each test consists of short psychological experiments which can be easily conducted within a few seconds and illustrate important features of human perception and human memory. First experiences ascertained that it is highly motivating for students to test their own perceptions and learn about human cognition. Major companies, especially banks, invest in interactive distance learning replacing face-to-face training. Research in this field has shown that the choice of media does not influence learning very much. Learning gains are mostly due to a shift in instruction. In this study a WBT about currency management of a major German bank was examined. The communicational features of the WBT comprise a discussion forum, note taking, and automatic messaging of questions and answers between experts and students. The experimental design compared a face-to-face seminar with WBT learning. The results show that WBT participants
Performance Support
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learned as much as the seminar participants, but in about 70% of the seminar's study time. Young seminar participants performed better than older ones, while WBT learning did not produce an age effect. The results of the study demonstrate that the learners in the bank tend to choose traditional learning strategies and do not profit from co-operative and selective learning strategies, although they tend to appreciate audiovisual media. Experts were not very much engaged in the discussion process. Communicational features, however, were used quite frequently. The users who were experienced in using a CBT and showed high self esteem gained most from WBT learning.
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Chapter 3
Implementing Web-Based Training: Exploring Electronic Media and the Human Mind
From CD-ROM to Internet Learning effects of multimedia in education are disappointing, quite frequently. Van den Berg and Watt (1991) compared multimedia in competition to a classroom lecture, multimedia supplementing a lecture and multimedia replacing a lecture. They came to the conclusion that students would prefer to use multimedia as a supplement to lectures and books. Meta-analyses support statements like these (Kulik & Kulik, 1991; Hasebrook, 1995). Although, multimedia seems to save some time and reduce simple errors, it has not been found to be very effective as a problem solving tool (Mayer & Anderson, 1992). Many vendors and users prefer a stepwise migration from 'old' to 'new' technologies. For instance, Bank Academy has implemented a multimedia CBT in charge of the financial department of an international automobile manufacturer and dealer (cf. figure 24) which was implemented in five different languages and delivered on CD-ROM. One of the challenges of this project was to produce off-line and on-line training courses in a single production process. Therefore, we implemented the different CBT versions using the Hyperwave Information Server (Maurer, 1998) in order to maintain the multimedia elements. Hyperwave directly delivers Web-based training, because it includes a complete Web server, and allows to produce a 'snapshot' of the 91
Learning Support Systems
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database which can be delivered on a CD-ROM. In the first release, the training course did not provide more than a traditional multimedia CBT. But since the year 2000, the course had been put on-line and, therefore, integrates Hyperwave's on-line features, such as note taking, discussion forums and bulletin boards.
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From Help Pages to Performance Support Systems
Duchastel (1992, pg. 69) claims: 'Adaptation is essence of what is known as pedagogical knowledge1. Many researchers aim to make their multimedia systems more adaptive - a n d therefore more 'pedagogical1
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(e.g. Cox & Bma, 1995). Expert systems and Intelligent Tutoring Systems (ITS) adapt to the learner's demands, abilities and knowledge especially in subjects which can be described in formal structures (Bastien, 1992). There is an increasing number of adaptive computer programs which are equipped with media like videos and photographs. As of today, a diverse spectrum of techniques, approaches and philosophies impede the progress in intelligent learning environments (Self, 1992). There are promising results, however, supporting positive effects of intelligent learning environments teaching mathematics and programming (e.g. McGraw, 1994). In general, effects of adaptation and system-controlled tutoring have been small or medium sized, yet (e.g. Schulmeister, 1996). Despite these insights about the need for adaptation and contextual information many Web-based training modules provide not more than some simple help pages or hypertext facilities with keyword indices. Help pages mostly provide information how to access functions but not how to apply them in different learning contexts - and why to apply them. Effective learning needs a good deal of verbal and visual literacy, whereas computer literacy seems not to be the most influential factor (cf. Mayer & Sims, 1994; Mayer & Anderson, 1992). Thus, most help systems do not support learning strategies to cope with linked multimedia elements, and they do not motivate to use electronic media as an serious learning tool. Effective help systems should support the user to overcome his or her weaknesses and take advantage of her or his strength. We therefore designed a generic Web-based training system that can be used as a stand-alone training course about 'Learning in electronic media' or as an integrated help system supporting other Web applications (cf. figure 24). Thus, it can be used as a Performance Support System (PSS) to enhance utilizing electronic media in an learning and in working environment (McGraw, 1994). The PPS provides four modules, a comprehensive glossary, a keyword and a fulltext index as well as a graphical overview with brief summaries of all modules. The table of contents comprises the following topics: Learning with multimedia: Advantages and disadvantages of computer-based training - Appropriateness of multiple media - Learning
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Learning Support Systems
strategies for multimedia - Combining dynamic and static media - Self test 'Multimedia expert'. Information from the Internet: Basics about the Internet - Addresses in the Internet - Search engines and search strategies - Self test 'Internet expert'. Email and Computer Conferences: Basics about email - Writing emails - Mail and list server - Asynchronous and synchronous computer conferences - Video conferencing - Self test 'Email expert'. Learning strategies for CBT: Browsing hypertext and multimedia Using navigational tools - Using bookmarks and note taking - Graphical browsers, maps and overviews - Strategies for learning and re-learning Self test 'CBT expert'. Learning to Learn Many authors suggest that deeper understanding means that sequential verbal information is highly interconnected with analog pictorial information (e.g. Mayer & Anderson, 1991, 1992). Supporting understanding, then, demands the construction of semantically connected pieces of text and pictures, activating appropriate pre-knowledge, providing learning strategies for multimedia, and changes of media and learning perspectives to support the construction of comprehensive mental models (Albrecht & O'Brian, 1993). Research (e.g. Mayer & Sims, 1994) support the consideration of individual differences in abilities and interests in order to enhance the understanding processes. In two studies with 75 subjects we were able to confirm that individually adapted information enhances motivational and learning processes within computer-supported learning environments: Audiovisual media produced only a small effect, individual generated information, however, was very effective and was independent of subject variables like computer experience and usability judgements (Hasebrook & Gremm, 1999). These data are explained in full detail in chapter 7 of this book. Glowalla and Hasebrook (1995) conducted studies with 52 students which participated in a hypermedia learning course, all of them were
Web-Based Training
95
novice hypermedia users. In the first lesson they are 'unskilled learners', in the last lesson they were 'skilled learners'. Four month later, 43 of these students attended a re-learning course. All students received exactly the same course materials and configuration of features of the hypermedia system as in the learning sessions. Therefore, in the first lesson they were skilled learners, but 'unskilled relearners', and in the last lesson, they were 'skilled relearners'. The results show that browsing tools, such as paging and hypertext links, were used most frequently by skilled relearners, informational tools, such as a glossary and a keyword index, were used more often during learning than during re-learning. jgtefcwj
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The study reported here was conducted with this WBT. The WBT consisted The notes did not only support the learning process by motivating the users to discuss the subject matter of the WBT. They also provided a useful source of information for the adjustment and improvement of the system, because the users took lots of notes which described technical or design problems. Furthermore, a background library of encyclopaedias and news services enabled the user to access a vast amount of background information and most recent information without leaving the WBT environment.
Collaborative Learning
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Experiment 1: Collaborative Learning Strategies
Participants of Experiment 1 Outlets of the bank all over Germany were asked to nominate trainees of their corporate finance departments for a two-day seminar about currency management. Seventy persons were assigned to the one-day WBT, thirty persons to traditional face-to-face seminars resulting in 64 complete data sets of the WBT users and 30 complete data sets of the seminar participants. Only ten of these 94 persons were female; the mean age was 35.2 years (standard deviation = 12). Material and Procedures of Experiment 1 The WBT learners used the WBT described above. The WBT was based on the printed material, such as papers and slides, used in the seminar. Additionally, the trainer of the seminar groups served as the subject matter expert of the WBT development. In the beginning, all subjects filled in a survey about personal data, that is, gender, age, professional experience, prior knowledge, WBT experience and their personal expectations. Furthermore, they responded to 16 multiple-choice questions about currency management. While learning with the WBT, the users' inputs were automatically recorded by the system. All WBT participants learned about the WBT features conducting an introductory module which took them about 20 minutes to complete. Each module started with a brief overview and offered a multiple-choice self test. After having finished a module, the WBT offered an evaluation form with questions about the correctness, jobrelatedness and user-friendliness of the WBT module, which could be filled-in voluntarily. After the training, all seminar and WBT participants filled in a second survey about their experiences with the training course and responded to a multiple-choice test with 24 questions: 16 questions were taken from the pre-test, 8 questions were newly introduced. The survey was paper and pencil work, all multiple choice questions were presented at the
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computer and were rated by an expert team according to their difficulty. Test and survey were filled in anonymously and without observation in order to avoid social desirability distortion (cf. Richman et al., 1999). It took the participants about 40 minutes to fill in the survey and respond to the multiple-choice test. The WBT course took about 8.5 hours (standard deviation = 1 ) and the seminar about 12 hours of net study time to be finished. All WBT learners took part in a moderated team discussion about their experiences using the WBT. The results of these discussions were recorded by the moderator. Design of Experiment 1 The first experimental factor was the comparison of the between factor 'seminar vs. WBT learning' with respect to acceptance and performance criteria. Another set of experimental factors was realized by a mixed design within the WBT group1. As mentioned above, one half of the WBT group was automatically assigned to a learning team resulting in the between factor 'team vs. individual learning'. In every second WBT module, the learners were instructed to read the overview and to take the self test prior to the access of the module and then to decide - based on the test results - whether they want to go through all pages or only parts of the module. This instruction resulted in the within factor 'complete vs. selective learning'. Each module contained several audio and video files and a simple text version of the same content. The system automatically assigned the WBT users to different groups which had access to the audio-visual media in every second module. This resulted in the within factor 'text vs. audio-visual media'. All factors were counterbalanced by a Latin square procedure among the subjects. In summary, the experimental set-up of the WBT system resulted in a mixed design with the between factor 'team vs. individual learning' and the within factors 'complete vs. selective learning', and 'text vs. audio-visual (av) media'. 1 The design of an experiment refers to the set of variables and the method of their measurement: A between factor measures differences between groups of subjects receiving different treatments (e.g. one group attending a seminar vs. another group using a WBT); a within factor measures differences within a group (e. g. different orders of modules of the same WBT).
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Additionally, qualitative data were collected by interviews with the participating experts and by team discussions after the training program. Results of Experiment 1 All survey ratings are ranging from 1 ('very good' or 'I totally agree') to 5 ('very poor' or 'I totally disagree'). As the scores of the multiple choice items are differing according to their difficulty, all test scores are expressed as percentage of the maximum score (ranging from 0% to 100%). Due to the variable cell frequencies of the design and some missing data, the General Linear Model (GLM) procedure of the SPSS statistical software package was used to analyze the data. A GLM is comparable to mixed, multivariate analyses of variance (MANOVA).
Table 8. Test results in % of the pre-test (16 items) and the post-test (16+8 items) as a function of learning group (seminar vs. WBT), gender and age.
Pre-test Post-test Pre-test Post-test
Total n=94 56.7 76.5 43.2 72.9
Gender Female n=10 59.2 75.0 * *
Male n=84 55.9 73.3 43.2 72.9
Age in years 36-45 20-35 n=29 n=39 54.2 59.8 68.2 80.1 52.2 45.1 70.4 70.1
46-55 n=17 51.7 65.3 32.9 66.1
56-65 n=9 61.1 75.0 11.1 37.5
* no female participants in the seminar
Comparison of WBT and Seminar The study time of the WBT and the seminar differed significantly (8.5 vs. 12.0 h; F[l,92]=319,9; p4 10 CT3 A l j 'or d in
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Figure 35. Tutoring interface with 'alert system' listing all events the tutors has to care for (deadlines, open questions etc.; left) and general activity map sorted by learning groups and group members (right).
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The technological problem which has to be solved in order to support tutoring processes is the collection and ordering of data concerning the tutoring process. Process-oriented systems, such as the LSS presented at the beginning of this chapter, enable system designers to retrieve those process data from the system which are best suited to support the work of tutors and subject matter experts alike: Tutors have to be aware of certain events which could hamper or even stop the learning process, such as deadlines, open questions or poor participation. Furthermore, tutors need special statistics and overviews such as number and length of forum messages or notes listed by topic, date, and student, and overviews of learning activities, such as individual time schedules and test results. Moreover, tutor oriented system support should provide fast and easy communication on a group or student level. For instance, efiport's LSS provides all data collections, lists and graphical overviews mentioned so far. In addition, the LSS provides communication features such as individual and group home page messages, (push) news channels, feedback on test items and exercises as well as one-to-one dialogue features which are exclusively used by tutors.
Part 3
Decision Support: Introduction
Many researchers aim to make their multimedia systems more adaptive and, therefore, more pedagogical. Expert systems and intelligent tutoring systems (ITS) adapt to the learner's demands, abilities, and knowledge, particularly in subjects conforming to formal logic. A growing number of adaptive computer programs contain media such as videos and photographs. Though there are no clear borders between expert systems, ITS, and other adaptive multimedia systems. Expert systems are mainly distinguished from ITS by two key characteristics: The knowledge base of an ITS attempts to model human knowledge, the knowledge base of an expert system does not; and Expert systems are not designed to support the learning process, because they do not explain their rules, knowledge or inferences. So far, artificial intelligence (AI) has been a disappointment. A recent academic study of AI startup companies comes to the conclusion: 'If it works, it's not AI.' The revenues of AI corporations over the last decade support this view. There are basically two types of AI. The original goal was to create machines that are intelligent in a human sense. A compromise solution has emerged that merely refers to programs that perform tasks once the exclusive domain of humans. This type of AI is referred to as computational intelligence (CI). As some researchers point out, the original AI vision was to mimic human intelligence in the same way the first flying machines mimicked birds. Just as today's airplanes and helicopters don't flap their wings to achieve lift, there could be other ways to achieve intelligence than simply
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mimicking human intelligence. Two basic assumptions support the use of artificial intelligence in education: The key concepts of learning and intelligence are not fully understood and clearly defined. A theory of learning must be developed that will lead to a scheme for measuring a systems' adaptability and learning capabilities. The critical lift for CI to fly will not come from the systems' intelligence as much as its ability to communicate with humans. Basic AI- and Cl-based technologies include: ® rules-based expert systems, « neural networks, * genetic algorithms, * fuzzy logic, and i Figure 44. Acceptance ratings and cued recall as a function of list of jobs/educational programs (individually generated list vs. fixed list) and video (displayed before vs. after reading); acceptance scores range from 1 (rejection) to 30 (agreement); recall scores range from 0 (no recall) to 25 (complete recall).
Field study: Comparing Electronic and Printed Media Electronic media for vocational guidance combine various advantages: access to huge amount of data, up-to-date information, and guidance provided by surveys or quizzes. This does not necessarily mean that students enjoy working with electronic media for providing vocational orientation. Therefore, we compared four media for vocational guidance in a recent study (Hasebrook & Wagner, 1998): two of them are multimedia applications and the other two products are printed matter. A. The multimedia application were: 1. a fully interactive point-of-information (POI) with fancy graphics, animation and sound and
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2. a more restricted computer-based training (CBT) containing guided tours, texts and digital video. B. The printed material was 1. a quiz with a graphical layout based on 26 exercises (Quiz) and 2. a comprehensive survey consisting of more than 100 yes/no items (Survey) which was responded to by an individually generated letter. We measured individual acceptance ratings after having used the four different products with 75 students participating in this study (between 15 and 18 years, Mean = 16). The results show that printed matter are preferred. This result is statistically independent of sex, education, and experience in using a computer. Thus, the students enjoyed using electronic media, but they rely on printed matter. Table 19 summarizes the mean acceptance and validation scores of the four compared products.
Table 19. Means of the subjective validation of two electronic media (1. Point-OfInformation, 2. Computer-Based Training) and printed matter (3. Quiz identifying occupational fields, 4. survey with response letter), scores range from 1 (rejection) to 5 (agreement).
l.POI 2. CBT 3. Quiz 4. Survey
like to work like 'look with and feel' medium 2.24 2.13 2.24 2.19 2.95 2.79 2.97 2M
Statement like recommendations 1.96 1.78 2.89 3M
product is would buy valuable product 2.02 1.96 2.87 3.04
1.99 2.03 2.75 3.05
The scores were compared by means of paired Wilcoxon tests; all reported results are significant at least on a level of p < K . . . > . . . ... ... ... ... ...
For the first time in scientific history, educational programs and methods can be based on results of brain research. Computer simulations of the activities of certain neural circuits and structures which may be part of learning processes will help to better understand the human brain.
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Recent research has shown that the brains of infants are far more flexible and adaptable than neuroscientists believed only a few years ago: The human mind is optimized to solve problems in social and natural contexts, and not for fact learning and logical reasoning. Moreover, learning mainly is based on social learning and imitation (Bandura, 162;
Figure 50. a) Neural circuit responsible for the eye blink, reflex of a rabbit (above) and b) test environment for classical and operant conditioning experiments with pulsed neural networks implemented with Java (below; cf. Hasebrook, Erasmus & Doeben-Henisch, 2001; pg. 72).
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The German brain researcher Gerald Huethig has compiled insights about the critical failures and success factors in education which can be deduced directly from findings of recent neuroscience research (Gebauer & Huether, 2002): 1. Knowledge acquisition and learning has to be a desirable value and behavior within the family and the society, and it may not be replaced by different values such as 'fun and leisure'. 2. Children need many opportunities to actively explore and influence their environment, and they should not become passive consumers of a media-based environment (that is, a 'coach potato'). 3. Learners need sufficient freedom to be creative, innovative and to make their own experiences, thus, learning may not be restricted to directly measurable (economic) and short-term outcomes. 4. Children and adults do not learn if they are flooded with inputs, and if sensation and perception systems are over-stimulated by multiple media; learning needs a stimulating but protective and safe environment. 5. Learning does not occur if learners are prevented from making errors and from solving problems on their own; research has shown that even in ICT training learners did better when encouraged to make errors without receiving any further explanation as compared to participating in a fully enhanced but over-protective training program (Frese, Brodbeck, Zapf&Prumper, 1991). 6. Finally, children need individual care, protection and empathy because learning does not happen in an atmosphere of fear and danger, but only in a supportive and emotionally positive environment.
Information Science Aspect Computer and Information science could possibly play an important role in the archaeology of the human mind - very similar to some new findings in research which have been made possible by virtual reality simulations or re-calculation of astronomical constellations. Within the context of information science, Norbert Wiener (1961) identified the role of information in natural and human systems in a way that had never
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been recognized before. He developed the field of cybernetics, which deals with the guiding or governing of systems. Wiener suggested that many systems are determined by the feedback of information to a governing element of the system. Wiener demonstrated, for example, that when a person reaches for an object, it is done with continual visual and kinesthetic feedback of information, which is then used to guide the hand further. The hand does not just respond to a single impulse from the brain to 'grab'. Recent research indicates that the 'free will' of a person is the choice to stop an action, such as grabbing, but not to start it. Another work that had an electrifying impact of all was Claude Shannon's information theory (Shannon & Weaver, 1949). Shannon measured the amount of information going through a telephone wire. His theory was abstract, and seemingly applicable to many environments, including not only the technical but also human language and psychology. The limits of Shannon's theory for the human sciences ultimately became evident, but the legacy of a new, abstract sense of information as reducing uncertainty by measurable amounts, remained. Similarly, Noam Chomsky's theory of syntactic structures in language (1971) - common patterns underlying all different languages had an deep impact on several fields, and was inspiring the emerging field of psycholinguistics. Miller, Galanter and Pribram, three wellknown psychologists, wrote Plans and the Structure of Behavior (1960), which posited a common underlying structure to all, or virtually all, human behaviors. Finally, Gregory Bateson identified common underlying structures in learning, as well as meta-structures in communication that reference other communications. He dealt, thus, in many different ways with representations of representations. It is no accident that the cover of the 1972 paperback of his 'Steps to An Ecology of Mind" states: 'The new information sciences can lead to a new understanding of man' (Bateson, 1972). A new view of the founding works of information science provokes new research questions: The so called 'strong Artificial Intelligence' (AT) seeks to mimic human intelligence by reproducing its necessary and sufficient prerequisites. Moderate positions of the 'Computational Intelligence' (CI) are focusing on computational behavior which can be interpreted as 'intelligent' by an intelligent observer (see Hasebrook, 2000). What are
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the prerequisites for anthropomorphism: What features of hardware and software foster the illusion of being intelligent? Several kinds of so called 'self-learning automates' or algorithms exist; mostly they are only loosely tied to existing neural networks. Can we learn from nature to built more reliable and flexible self learning systems as a basis for a 'bio-engineering' of virtual intelligence? We know from research that even higher cognitive processes cannot be understood without their emotional (and sometimes social) context. Can this context be adequately modeled - and how does it influence 'self learning' systems? Robotics' research has shown that intelligent or adaptive behavior is based on a close interaction with the outside world. Moreover, the measure of learning or intelligence clearly depends on observable behavior corresponding to well defined learning tasks and environments. Our knowbot research, therefore, concentrates technical developments on interface technologies which facilitate the access to knowbots by human users. The most important way to communicate is speech. The knowbots we tested were equipped with a speech recognition and synthesis system: The speaker independent speech recognition was able to identify about fifty words in five different languages at a time. As the word recognition can be adapted according to the actual context, this small amount of words is sufficient to implement small navigational or command systems. The speech recognition unit may also be trained to understand a specific user and it is then capable to handle dictionaries of several hundreds or thousands of words. The speech synthesis can read any text, such as HTML pages, tables or documents. The user can choose between several 'speakers' with different pronunciation or intonation. Much work is still necessary in order to make speech synthesis and speech recognition 'human like' as has been envisioned by Negroponte (1995) in his already mentioned book 'Being digital', although the research field has developed rapidly as can be seen in the overview displayed in figure 51. Moreover, even traditional methods, such as statistical analysis of large bodies of text, have been revived, recently: The German researcher Franz-Josef Och, Information Science Institute (ISI) of the University of South California, could show that classical statistics applied in an innovative way can produce cross-references of
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any formerly unknown text if a large body of text of more than 3 million words can be analyzed (Och, 2003). Och is now producing statistical translation systems based on cross-referenced text bodies such as the Christian bible. He is in charge of the research organization .of the Pentagon, DARPA, in order to support the National Security Agency (NSA) to better analyze emails and other written messages in foreign, languages. Complexity of speeking style
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Figure 51. Overview of the development of speech recognition technologies (cf. Rauterberg, 1999).
Human users, the users of information systems, visitors and creators of the infoverse, are the main 'component* of a knowbot's environment. Additionally, other knowbots or standardized software agents may also enrich the knowbot environment. For this purpose, Knowbotic Systems has developed one of few worldwide available multi-agent platforms based on the FIPA standard (FIPA = Foundation of Intelligent Physical Agents). The platform FATE (FIPA Agent Template) comprises templates or suits which allow programmers to convert nearly any
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computer program into a software agent, that is, the knowbot technology provides easy-to-use ways to introduce a large variety of programs into the virtual learning environment. FATE also allows to run several platforms on different Web sites. This enables knowbots and other agents to communicate, move or replicate themselves all over the World Wide Web. Once again, XML schemas are used to implement the agent communication (cf. Zhong, 2001). The Age of Intelligent Machines ,The age of intelligent machines' is the title of a (thought) provoking book published by Ray Kurzweil in 1990. Nine years later, he published a book entitled ,The age of spiritual machines' (Kurzweil, 1999) predicting a time line when computer will not only match but exceed human intelligence. Knowbots are one of the few holistic visions of a man-machine dialogue in its actual sense, dedicated to support humans where they need help to access and select information - and to learn from them. But knowbots are not the only development in this field. A new level of smart agents and self-learning machines will develop in the near future. Figure 52 summarizes some major developments which are expected in the near future. Among them are software agents, mobile computing, and speech control. Kurzweil (1999) is providing an even more far reaching vision of human-computer interaction. His time line starts in the year 2009 and stretches to the year 2099: 2009: Computers are embedded, translation telephones are commonly used. 2019: Computers are largely invisible and embedded, threedimensional VR displays are embedded in glasses, gesture recognition and two-way natural language comprehension are the common command languages, people begin to have relationships with automated personalities. 2029: Computers have high-bandwidth connection to the human brain, neural implants to enhance cognitive abilities are available, a
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discussion about the legal rights of computers grows as computers claim to be conscious. 2099: The merger of human and machine intelligence has started, most conscious entities (being humans, computers or both) do not have a permanent physical presence as the number of software-based humans exceeds those using ,wet minds'.
2004 Ubiquitous online learning in universities
2005 Online learning in schools (K12)
2006 Software agents to search and select information
Interactive commun- Interactive ities in the TV for big WWW audiences
2007 Increasing use of speech recognition and synthesis Central remote control station for 'intelligent buildings'
2008 Increasing use of electronic cash Broadband access to information
2009 Mobile computing and eCommerce
2010 Selflearning softw. agents 3D virtual reality
Increasing use of eCommerce Figure 52. Some major developments in interactive media in the next ten years according to a recent study of the Fraunhofer Gesellschaft (Institute for System Technology and Innovation Research).
His ideas to achieve all this astonishing progress, however, proves to be somewhat over-simplistic (Kurzweil, 1999; pg. 295): ,First, carefully state your problem [...] Next, analyze the logical contours of your problem recursively by searching through as many combinations of elements [as possible]. For the terminal leaves of this recursive expansion of possible solutions, evaluate them with a neural net. For the optimal topology ofyour neural net, determine this using an evolutionary [that is, genetic] algorithm.' Of course, this receipt can only applied to first and second generation neural networks - let alone the problem that all real learning experiences, which are involving ,detection of the new', are not captured by Kurzweil's receipt. We envision future developments in networked
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computing and distributed computational intelligence where the users are no longer forced to adapt to the computer. The computers will adapt to the human capabilities to perceive and process data. The communication between and with computers will adapt to the human way of communication, namely natural language. And computers will be accessible at any time from any point with any device, such as PDAs, laptops, or mobile phones. Computer networks will also become people networks, taking into account specific deficits and potentials of computers and humans. Up to now, many individuals and companies are fascinated by the potentials and the exponential growth of the Internet. We do not think that future generations will be too enthusiastic about slow networks, unstructured information heaps and poorly equipped online shopping malls. Smart computers will be part of our every-day life, will be part of houses, cars, TV sets, refrigerators, bags, and suits. As a matter of fact, many ordinary machines are based on so-called embedded systems, that is, a small specialized computer. So, the things start to become computational things - and they will be smart things in the future. Knowbots and other smart agent technologies will support work, leisure and even cultural or social entertainment. Computers in the form of smart things will make computational intelligence as ordinary as cars or TV sets. But if the computers get nearer to their users, at the same pace the humans will get nearer to the computers: Not individual human beings nor software agent platforms will be the masters of the infoverse, but a new form of man-machine-interaction will emerge.
Epilogue
Future Developments
This book started with a prologue discussing e-learning on a global scale and how digital media can link people to knowledge and wealth. The structure of the book is built around the three layers of digital media in education (Keil-Slawik, 2003): Infrastructure, special software, and selflearning systems; the four main sections of this book are: ® Management support (infrastructure layer), ® performance support (infrastructure and special system layer), « decision support systems (special system layer), and * self-learning systems (self-learning system layer). The four main sections and nine chapters of this book were focussing on single topics such as learning support and corporate organization. The epilogue of this book will lead us back to a broader perspective: The human being, the human culture, and the impact of digital media on both. Let's have glimpses into the future - the future of our personal lives and the learning society as a whole. E-Assisted E-Learning in 2010 Laptops are becoming lighter and lighter, hand-helds are getting more sophisticated, and the mobile phone is gaining increasingly powerful computing resources. Yet we believe this is very much the beginning of an era that will start around 2010. At that point we believe mobile phones will have turned into veritable computer- powerhouses. Let us call them eAssistants. They will be not much bigger than a credit card, with a fast processor, gigabytes of internal memory, a combination of mobilephone, computer, camera (still and video), global positioning system 241
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(GPS), a variety of sensors and in continuous connection with huge nonvolatile local storage and the then existing equivalence of the internet: continuous, since there will be no charge for connect time, and probably not even for data transfer: an unlimited (time and volume) GPRS access is currently offered in the US for US$ 29,90 per month! Most importantly, the PC of 2010 will not have: 1. It will not have a hard-disk: this fragile energy consuming device with rotating parts will be replaced by a version of the memory stick as we now use them in digital cameras, but with hundreds of Gigabyte capacity; 2. it will have no screen nor keyboard as we now have; and the much reduced energy required by this device will be provided by tiny fuelcells. Of all of the above, we believe that most readers might be startled by only two things: the stated absence of screen and keyboard. Let us first address the issue of screen. Presently, there are half a dozen technologies competing to replace the screen as we now have it. They include flexible screens that can be attached to your sleeves ('wearable screens'), projectors that create images wherever you want (even on uneven surfaces of any color), and specialized eye-glasses that replace the screen, just to mention three alternatives. Which of those technologies will 'win' we do not know, nor does it matter: what matters is that wherever you go you will have a more or less zero-weight high quality display at your disposal, connected to the small computer proper by a modernized version of Bluetooth, and via the computer to a huge archive of information locally and all the servers on the internet. Of all possible technologies we particularly fancy a certain version of eyeglasses: the electronics in the eyeglasses are in contact with the computer via Bluetooth. The computer delivers (if wanted stereo) sound to the side of the glasses, that transmit it directly to the ear-bones (thus, only the wearer can hear the signals); the computer transmits (moving or still) pictures (if wanted 3D) through little mirrors through the pupils of the eyes directly to the retinas; and a tiny camera in the middle of the glasses provides the computer with what the user sees, e.g. for gesture recognition.
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Indeed, the eAssistant may also have additional sensors and I/O devices and is supported by powerful software (for sophisticated image processing of the pictures obtained by the camera) as was already mentioned in (Maurer, 2003). This will be discussed in more detail in the following sections. Let us now turn to the keyboard. First, alternative input techniques are already starting to emerge. Speech input is one of them, and is particularly attractive if 'speech that is not heard' is used (i.e. utterances with closed mouth), e.g. using microphones near the larynx. Second, techniques that use the movement of fingers, the head, or the body using tiny sensors are becoming realistic; third, by using the glasses with an integrated camera described above a 'virtual keyboard' can be made visible to the user, and the finger movements on that keyboard can be analysed by software that does image-processing of what the camera delivers. We are not trying to suggest in this chapter that any one of the technologies described above will take precedence over others but more to suggest that the screens, hard-disks and keyboards, as we know them today, will be obsolete within ten years, give or take a few years. The Wizard in the Glasses In light of what we have discussed above, it is possible to predict that the eAssistant might look similar to what is shown in figure 53 below. We want to emphasize once more that we do not necessarily believe in the 'eyeglass' version that is shown, but it is a helpful metaphor to convey the functionality we believe will be available. The computer proper O is not much larger than a credit card and has all the functionality describe earlier. It is connected wireless to the internet and to the eyeglasses plus necklace. The computer delivers on the side of the eyeglasses (if wanted stereo) sound © ; it delivers via tiny mirrors © into the eyeglasses (if desired 3D) visual multimedia material of whatever kind, such as text, pictures, animation, 3D models, movies, 3D movies, etc. This may be technically accomplished by projecting images through the pupils
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directly onto the retinas of the eyes, or by creating a virtual image in front of the eyes. ® represents a camera that has multiple uses: 1. the user can look through it (thus having infrared vision during the night, or macro vision or zoom when this is useful); 2. the user can transmit what is being seen to others (i.e. we have video-telephony, of course); finally, the pictures taken by the (still and movie) camera can be analysed by powerful image processing software.
Figure 53. The wizard in !he glasses: cAssislant and associated devices.
The camera has also a built-in compass, hence the eAssistant is not only aware of where the user is (because of the GPS system), but also in which direction the user is looking. © is a larynx-microphone that can pick up what is spoken by the user (even if done witii closed mouth: this takes a bit of practice on part of the user), and it also has a loudspeaker so that a conversation or audio outputs can be shared with others, even if those do not happen to have an eAssistant at this point in time.(If they
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had, the audio information could be sent directly to their ears using the devices © mentioned earlier). © symbolizes a device that can detect different states of brain activity. At this point in time a very limited number of states can be detected (typically the intention to move the left arm can be distinguished from the intention to move the right arm) (Purtscheller et al., 2000), but it is foreseeable that a dozen or more states will be achievable, allowing to create input for the eAssistant by thinking only. © will also have integrated further sensors, typically for the detection of head-position and head-movement or speed of movement of user, but potentially also to measure physiological parameters of the user like body-temperature, pulse, skin conductivity, etc. or even environmental parameters like temperature, humidity, air quality, air pressure. If it is not self-evident the next section should convince readers that an eAssistant as described will indeed revolutionize our world. Note that each of the features and sensors described above has been implemented in some way or another. The 'only' thing that is missing is integration of all into one small unit. However, the assumption that this will happen is basic to some of the research we are seeing today, e.g. in (Maurer, Stubenrauch & Camhy, 2003) or (Lennon & Maurer, 2001). E-Assisted E-Learning in the Future
Virtual Keyboards Input of information using the keyboard or the mouse will be replaced to a large extent by other means, such as speech recognition, gesture recognition, employing a 'virtual keyboard' and other methods that still sound unorthodox today. The 'virtual keyboard' is a good example that shows how the various components of the eAssistant interact with each other. By a spoken command 'Create keyboard' the eAssistant creates the image of a keyboard for the eyes of the user. In our eye-glass model the user will now see a keyboard floating in mid-air, and can type on it. Image processing based on what the camera delivers determines what keys have been touched: It may deliver audio feedback (producing a
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different click for each key that is hit) and video feedback by showing the text being typed, the text floating on a virtual screen above the keyboard. Using gesture recognition, movements of fingers or the hands replaces the mouse, nodding the head can be interpreted as mouse-click; or if two alternatives yes/no are offered or a two-button mouse is to be simulated, nodding or shaking the head could select one of the options. Alternatively, a simple gesture with the finger might also be used. As mentioned, simple inputs are also possible using the measurement of brain activity or other sensors: there is no limit to what one might imagine and it will be one of the interesting tasks to experiment with the combination of various techniques. Global and Culture-Fair Communication Clearly one of the functions of the eAssistant is that of a mobile phone. However, it is not necessary to press a phone against an ear, rather one can either use the loudspeaker mentioned earlier, or feed the audio-signal to the sides of the eye-glass and thus directly (via the ear-bone) to the inner ear, i.e. without other persons hearing or noticing anything. Since one can talk with closed mouth (after some practice) or spell a message by invoking a sequence of brain-states by thinking of designated actions (much like we spell a message we send an SMS) two persons can communicate over arbitrary distance in a way that other persons on the sender's or on the receiver's end do not notice it: thus, we have basically implemented telepathy in a technological manner, a fact much used in e.g. the XPERTEN- novel series (see www.iicm.edu/XPERTEN). Note that while two or more persons are communicating this way, the can also share arbitrary information, from what they currently see to information from local storage or a server, accessed via the net. It is also conceivable that the whole conversation might be recorded and stored for later perusal. Even communication with persons speaking different languages is quite conceivable: persons talks in the language of their choice; a speech recognition- translation- speech synthesizing program is translating what is said into whatever other languages are desired. Note that such
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'machine' translations will not be perfect in the foreseeable future: 'To understand a language is to understand the world' is a famous statement that indicates clearly that for even near perfect language translations one would need computers at least as 'intelligent' as humans, and aware of all facets of the world and human life: and if this can ever be achieved is still a topic of much discussion. However, good machine translation programs are certainly doing a better job than the average person after having studied a language in school for a few years! Further, misunderstandings due to the translation process can be fairly easily avoided by feedback techniques: the translated material is translated back: if this now differs from the intent of the speaker, appropriate actions can be taken. By the way, the communication between persons with different languages may be made much easier by using dynamic symbolic languages, a main aim of the project MIRACLE (Maurer, Stubenrauch & Camhy, 2003) and its forerunner MUSLI (Lennon & Maurer, 2001). The eAssistant also changes how we discuss things: while someone is telling us something, we have the possibility to check if the information provide is correct, by accessing back ground libraries (Maurer, 2001) on local storage or in the internet. Conversely, we can use information from such background sources in our statements. This is of course assuming that access to desired information is easier and more selective than what we good get today using e.g. search engines in the internet. This is where techniques of knowledge management come in (Maurer & Tochtermann, 2002; Ives, Torrey & Gordon, 1998). That techniques such as similarity recognition and active documents (Heinrich & Maurer, 2000) can make quite a difference is shown in (Maurer & Tochtermann, 2002), that semantic nets and metadata (Meersmann, Tari & Stevens, 1999 allow to produce much better search results is shown by the success of knowledge networks and is the basis of one the currently leading knowledge management systems Hyperwave (Maurer, 1996). The new technologies will create many more uses and applications for the digital libraries and repositories currently being researched and developed (Oliver et al., 2003). Clearly the access and more productive use of information is not restricted to discussions with other persons, but applies universally to all situations when information is of critical importance. This is why
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knowledge tools as outlined in (Maurer & Tochtermann, 2002) are of such importance. PDAs Revisited It does not require that much imagination to see how the eAssistant is going to change our lives. We may suffice to provide just a few examples: When we meet a person the first time, information is usually exchanged by passing business cards and talking a bit about mutual backgrounds. Of course the exchange of information on business cards together what all that is available on the internet about this person, plus the pictures taken by the camera in the eye-glasses is recorded for later use. When we see the person next time, image processing software identifies who this is (even we have forgotten it), and supplies us with a wealth of information about this person. The eAsisstant is a perfect guide. Of course it can guide us when we drive the car, something already quite common for persons who drive top-of-the-line car models with built in navigation systems. But the eAssistant is equally helpful when we are walking, and not just for routing: when we look at a building the speech command 'Explain building' will be enough for the eAssistant to give us ample information: after all it knows (by GPS) where we are and (because of the compass) in which direction we are looking, so going into a guide book or such to retrieve what we want to know is easy. Clearly, this is not restricted to buildings, rivers, lakes, mountains...but equally well applies to plants or animals. If we look at a plant the speech command 'Explain flower' activates the camera and image processing, identifies what we are looking at and gives us information on the flower, on the berry, on the mushroom, etc. We will be paying with the eAssistant rather than with credit-cards or the like. The eAssistant will be our driving license and passport. It will automatically open those doors that we are authorized to enter. It will us allow with one command to turn on the light, the water, or what have you. And this does not just apply to things near to us: while we drive to our home we can turn on the air-conditioning, or the heating in our skiing cabin. This list can be continued indefinitely, and we intend to prepare a
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more detailed study at a later point: it is our belief that an extensive list of what the eAssistant is good for will be rather mind-boggling and will be a strong incentive for the fast wide-spread deployment of eAssistants. So let us conclude this subsection with one more example from the realm of medicine: Suppose we have a sore throat. We call our doctor. He asks us to show our tongue. We use the macro mode of the camera in our eyeglasses (the camera can be taken out of its casing for such purposes) to send the picture to the doctor. While viewing the picture the doctor is supported by a computerized diagnostic system that uses image processing to find out what kind of infection we might be suffering from. Having decided what it is, the doctor makes sure that we can pick up required medication from a pharmacy near to us; after all, our current position is known (if we permit it) to the system due to our GPS. Note that sensors that supervise some of our physiological data (like bodytemperature and pulse) and monitor environmental data (like airtemperature and air quality) might alert us to take actions, or even initiate actions such as sending an ambulance to help us! There is even more to the widespread use of sensors and constant monitoring of sensory data. Suppose a person dies of some rare disease: comparing the date that has been monitored concerning this person over a long period with persons in similar circumstances who did not suffer from this disease might well discover the real reason for the disease at issue. Maybe this is the way how we will finally be able to combat mysterious illnesses such as the SDS (sudden death syndrome) in children, or the high rate of some type of cancer in certain groups of the population. What We May Learn Sophisticated learning programs that allow communication with others, with experts or with 'Interactive Knowledge Centers' or 'Active Documents' (Heinrich & Maurer, 2000) (which has been described in chapter 4 of this book) will allow us to pick up knowledge as we require it. The 'in-time' learning will be the natural thing to do, rather than learning just because certain things might be needed at some future time. The fact that we will have continuous access to information in all areas
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will mean that the learning of facts, today still an important component in myriad of areas from geography to history, from law to medicine, will become significantly less important. Thus, the eAsistant is not just going to continue the trend that we will learn in a different way, but will also deeply influence what we will want to and what we will have to learn in the future: Even activities like handwriting might become unimportant: Why use handwriting, when we have our eAssistant with rather more convenient ways of data- input - or: Why learn a foreign language for simple communication when we have automatic language translation, as explained earlier? Of course, we recognize that to understand a culture, we have to understand the language of this culture at a deep level: but for just travel or business the automatic translation devices will do. Thus, one of the main issues that will have to be investigated more than has happened so far is not HOW we learn in the future, but what we have to learn, when the eAssistant and the internet is more and more turning into an extension of our brain. Also, learning in the workplace will finally become a favored form of learning for many with help from the eAssistant and its supporting technologies and software (Oliver, 2001). Indeed this fact will have a deep influence on all of humanity. We live today in a totally tayloristic society as far as material goods are concerned, i.e. we are completely dependant on thousands of other professions and hundreds of thousands of other people for our daily life - from food, to housing, to clothing, to entertainment etc. - and we have accepted this. We have accepted that we can hardly survive as autonomous individuals any more, but only as part of large group of diverse humans. The point is, what has happened in the area of material products is now about to happen also in the area of the non-material products information and knowledge. We will become, for better or for worse, much more dependent on hundreds of thousands of other humans for what we have to know to function properly. The eAssistant is a big step in this direction: we will be profit from a powerful network sharing knowledge with others, the positive aspect, and we will become more and more dependent on this network, the negative aspect of this development. Thus, a further revolution of e-learning will be upon us if and when versions of eAssistants become widespread.
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Planets of Learning Gilly Salmon from the ,Center for Innovation, Knowledge & Enterprise' of the Open University Business School located at Milton Keynes (UK) gave a keynote presentation for 2002 ,European Computer Assisted Language Learning', Eurocall, Conference entitled: 'Future learning encounters'. Salmon describes four scenarios which he called ,planets': Scenario 1, Planet of Contentious: Landing on Contentious you find technology as a delivery system. High importance is given to content management systems, integrated learning management systems, multi media, industry standards, DVDs, digital and cable TV. Rivalry between solutions providers is still strong, though two or three market leaders are emerging. The associated pedagogy is that of the transmission model of teaching, where information is transferred from experts to novices. Content is king. E-librarians and e-lecturers have closely linked roles. Lecturers need to captivate big audiences. The Internet and digital TV spawns its own lecturing stars and the most successful assume 'rock star' status. Of course there are still a few lecturers campaigning, to actually be with their students, rather than look at them on monitors [see: www.contentious.com]. Scenario 2, Planet Instantia: IBM estimates that 25% of employees' skills become obsolete every 3 years. With the increasingly global society, language and cultural understanding has become a paramount skill. Instantia meets these requirements through sophisticated learning object approaches, with information technology seen as the basic tools. The pedagogy on this planet is usually called e-learning. The role of ambient intelligence in devices is seen as key on this planet. Every device that is connected to electricity is also connected to the Internet. Hence educational providers are able to think both creatively and in a very integrated way about learning devices. Online trainers support autonomous learning. Real or virtual trainers are available 24 hours a day, both synchronously and asynchronously. Trainers focus on skills development in employees and on ways of fostering the adoption of a strong in-house knowledge culture. Scenario 3, Nomadict Planet: On Nomadict there is less stability, less structure, less fixed time for work and leisure, retirement and education
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compared to Earth. The sense of physical place is not strong. The Planet Nomadict provides portable learning for mobile lifestyles. Travelling users replace travelling information. Learning on the Planet Nomadict is time independent and individual. The learners are seen as electronic explorers and adventurers. Learning online is now called m-learning (for mobile-learning) instead of e-learning. Teachers, academics and researchers are as mobile as their students are. Many are portfolio teachers- working for several educational institutions and providers, all over the world, at any one time. They have not only a highly developed awareness of the ways in which traditions of learning and expectations vary in different cultures but also the ability to work across discipline and levels of education. Scenario 4, Planet of Cafelattia: On Planet Cafelattia, learning is built around learning communities and interaction, extending access beyond the bounds of time and space, but offering the promise of efficiency and widening access. The key technology is the developed, entertaining, effective Internet to allow immediate and satisfying interaction between students and students, and between teachers and students. The pedagogy is based on notions of a very strong social context for learning with the model of acquisition, argumentation and application. A key activity for learners is finding and interacting with like-minded individuals anywhere. Assessment is based on complex problem solving and knowledge construction skills. Teachers see the technologies as yet another environment for learning rather than as tools. An interesting debate on Cafelattia has been around the drivers towards commonality or difference. Salmon concludes that it is likely that all the ,planets' will have elements of reality and there will be a variety of players and processes. Currently there is not as much innovation and excitement as one may originally have imagined in a global society with good Internet access: Much of the learning looks similar to that in other disciplines and applications. You can be sure that learners will be on the Web; Research in a cluster of schools and kindergartens in late 2001 showed that 50% of the 3 year olds in the group recognized components of computers, were able to turn them on and off and had mouse skills. In 2013 these children will be secondary students. Of course, closing the gap between what we
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have now in education and building a productive and successful future inevitably involves organizational change. Ecology of Mind The philosopher Vilem Flusser (who has been mentioned in chapter 8 of this book) envisioned a world where all humans are a part of a huge networked human-computer brain (Flusser, 1985). He also predicted that written languages will evolve into one global mathematical and graphical language. Whether or not we trust such predictions, we have to acknowledge that using ICT and acquiring the skills and competence to use it are mandatory to be part of modern societies: Competent usage of digital mass media, strategies of online learning and a strong basis for scientific and technical understanding are no longer ,computer literacy' but a key competence for ,social literacy'. It is interesting to note that the European discussion of this topic refers to the term ,cultural technique' which does make no sense when used in the U.S.A. for two reasons: 1. In the European culture ,technique' is a very general term for crafts and arts - in the US the conotation of technique' is much closer to ,technology'. 2. The meaning of ,culture' and ,civilization' is flipped around: The (US) English term ,culture' refers to ,civilization', e.g. in France and Germany, whereas the European term ,culture' refers to the English term ,civilization'. The ,Clash of Civilizations' (or, for Europeans: ,Clash of Cultures') has been considered to be a difference of religious values and social wealth. We may also think about the ,Digital Divide' and the dramatic ,brain drain' from the low developed regions discussed in the prologue of this book as the major ,clash of civilizations'. We would like to point out that the ,war for talent' (discussed in chapter 1 of this book) and the race to make the profit while supporting or defending the ,clash' might be the biggest divide in the world: The European Union and the European Commission has clearly stated that the growth perspectives of Europe are depending on the ability to start and to maintain a sustainable and global economy based on digital media (cf. Hasebrook, Rudolph &
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Herrmann, 2003). Another important gap might be the gap between the actual ability of the human brain to be fully ,computer alliterate' - and the fast growing and changing demands of the competence needed to master ICT. Therefore, we suppose to re-think technological developments from a ,human perspective', that is, not ask for possible technological progress but to ask for the fastest possible progress in our societies and cultures (or, for Europeans ,civilization'). Even if we do not share the idea of the near advent of 'spiritual machines' or 'artificial consciousness', we strongly support the idea of a discussion about the technological and social impact of those technologies. Many scientists consider the consciousness to be a 'virtual machine' (e.g. Daniel Bennet, 1986) or a not directly measurable effect of a meta-structure based on the innate brain structures developed in the millenniums of the evolution of the human race. Therefore, the argument goes that intelligence, such as the usage of tools and the development of language as a tool for communication, cannot be understood without the biological and social context, the 'ecology of mind' (cf. Kurzweil, 1999). Virtual Minds The description of an 'Ecology of mind' was a landmark in the development of cognitive psychology which was inspired and initiated when Gregory Bateson published his series of essay and talks in 1972. One of his most intriguing findings going beyond the simple cognitivism of the 70's was the detection of the 'learning of the unlearned': Dolphins were trained by Bateson not just by using 'shaping' - a behavioral approach which reinforces given behavior. Bateson reinforced completely new behavior, only. He found that his trainees were able to learn this complex meta-rule. The ecology of mind is supported by modern approaches of computer science and robotics, such as the works of Hans Moravec (2000), who claims that machine intelligence will automatically evolve when machines will possess an adequate computing power of more than 100 billions instructions per second and a (virtual) ecology to train their abilities. Recent scientific work, especially from genetics and archaeology, as well as some earlier psychological work is challenging this common approach of a smooth and continual
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development based on pure computing power of the relatively large human brain: Richard Klein and Blake Edgar have published their electrifying book about 'The Dawn of Human Culture', this year. Their still unproven and hotly debated hypothesis is that - following a drastic reduction of the human gene pool due to natural catastrophes some 50'000 years ago - a single or a small set of mutations triggered the development of a conscious self and therefore of language, new tools and art. Julian Jaynes' psychological work about 'The Origin of Consciousness in the Breakdown of the Bicameral Mind' (1993) demonstrates that in most evolutionary aspects - and in daily life - is a unnecessary or even hampering, e.g. while learning new behavior such as swimming or skiing. Moreover, he claims that literature before and after the historic change of the writing direction of old and modern Greek letters between 600 to 400 B.C: indicates the origin of modern consciousness and culture; consciousness then is only a reflection of the boosted activity of the left hemisphere in the right hemisphere of the brain. Surprisingly, this assumption has been supported by scientific work about reading Semitic (right to left) and Latin (left to right) languages which shows that old languages tend to be perceived and understood by both brain hemispheres whereas modern languages tend to be 'left hemispheric'. Additionally, the outstanding experiments and experiences compiled by the psychiatrist V.S. Ramachandran (1998) gave a deep insight in the plasticity of the brain. More detailed analyses of brain activities while reading and understanding different languages have been conducted with psychological and neurological impaired persons (e.g. Paradis, 1977; Paradis et al., 1982) or for teaching reading to children (Furr, 2000). We would like to encourage interdisciplinary and international research activities which foster a comprehensive 'archaeology of mind' rather than an 'ecology of mind': Ecology asks for operational parameters which can be measured in an objective and comparable manner, rules about their interrelationship and reasonable judgements about the error parameters of the models (cf. Press etal., 1989).
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Ecology is a meta-structure (or meta-science) in itself which evolves as a scientific field of scientific biology well after the fundamental models of modern biology were settled; ecology was considerably transformed when evolution and genetics were discussed together (cf. Wells, 2003). The study of the human mind has - like most other scientific theories and models - a bias towards well measurable, consistent and continual developments. However, many scientific areas begin to acknowledge that more often than expected before chaotic and revolutionary events use to have (and still have) a deep impact on evolution. The study of consciousness is not ripe for an scientific 'ecology'. But it should come into a state where methods of scientific archaeology are applied to different scientific disciplines which can contribute to lay out a first map of the development of the human mind (e.g. Kosslyn & Koenig, 1995). Jean Piaget (1896-1980), the famous Swiss philosopher and amateur biologist, requested in his book about the wisdom and the limitations of philosophy from his colleagues (cf. Piaget, 1974, 1976): Theories and models have to be laid out in a way that they can be tested in experimental procedures collecting reasonable empirical and/or experimental data. The natural sciences and the humanities are now up to go the first steps of Piaget's way applying his ideas not only to the mental development of human children but also to the mental and cultural development of the entire human race. There are many discussions about consciousness, attention, free will and the responsibility of individuals in social contexts (see Walter, 2001). An archaeology of the human mind could represent the outstanding opportunity to tie together scientific and public discussions about one of the oldest and most exciting questions of the human society. Maps and Minds In her highly influential book on 'Linguistic Diversity in Space and Time', Johanna Nichols (1992) has provided a new way of juggling genetic and areal linguistic history. She distinguishes between spread and residual zones; in her terminology the ancient Near East was a spread
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zone. Clearly, especially the far and the middle east has been affected by a number of Semitic spreads. In historical times we must reckon with three, if not, more such spreads: the early one that gave birth to the languages attested in the oldest documents, Amorite, and the controversial Aramaic spread - the language spoken by Jesus Christ. Today, it seems possible that archaeology can lay out maps of the development of mind (or certain cultural aspects, to be more precise). However, those maps are useless if they do not take into account there mental background which is not always directly reflected in the artifacts of a (deceased) culture. Hugh Brody gives a recent example about the problems to draw maps about cultural aspects in his famous book 'Maps and Dreams' (1981): Brody charted the hunting grounds of native Canadians in charge of the Canadian government; it turned out, however, that hunting was not so much influenced by territorial conditions but by dreams forecasting good hunting. As explained before, Julian Jaynes argues that consciousness arouse during a short period of time between 400 and 600 B.C. - a development marked by the shift of the ancient Greek literature. Jaynes analyses the literature, namely the Illiad, in order to better understand the state of consciousness of the writers and readers of the given time period which leads to some interesting research questions: If there are maps of language in space and time, can we draw maps about states of consciousness in space and time? If we can draw those maps, are they useful to understand certain shifts in cultural developments - or are they just temporarily territorial reflections of 'dreams', that is, mental states which can only be understood in the actual social context? Can we bring together maps of the development of language, artwork and other cultural achievements? Are those maps supported by crosscultural experiments about neurological and psychological processes, such as reading and understanding literature? It has been mentioned earlier that neurological correlates of cultural aptitudes and abilities have been found, e.g. understanding and reading different languages. It has also been pointed out that psychological research has contributed to the understanding of behavior and brain activities accompanying cognition and emotion. Finally, computer and
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information science can give us the ability to simulate certain aspects of these research findings and to test and to extend their functionality. This proposal suggests that not the natural sciences should guide the way to a better understanding of the human mind because their methods are to demanding in a statistical or mathematical sense. Nor should philosophy or the humanities drive the research activities because there methods are mostly not compatible with those used in natural and computer sciences. It is worthwhile to examine empirical sciences which mostly rely on extensive and exact observation but only on weak models. This holds true for archaeology (or astronomy, for that matter; cf. Kuhn, 1970; Hofmann, 1999). Therefore, an archaeology of mind can break the ground for sound and fast proliferating research activities discovering and unearthen the treasures of the human mind. Invisible Computing and Embedded Learning In the prologue we stated, that technology solves technological problems, only. Learning, however, is not a technological problem. Thus, ICT does not help to overcome didactical faults. We distinguished three levels of digital media in education (Keil-Slawik, 2003): « The primary level provides general infrastructure and software features used for learning, * The secondary level comprises specific software features for learning, and « The tertiary level introduces self learning and adaptive software features. We demanded that knowledge has to be available like the ubiquitous power of electricity with education as its transmitter. New media are the latest transmission technology which can carry education into low developed regions using a lean physical infrastructure. Global trends indicate that new media can help to built the link between people and wealth. As knowledge is not a factor of production easily accessible as financial capital or soil a 'war for talent' has started (cf. Martin & Moldovenau, 2003). Based on these assumption we conclude that there
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are two major unsolved (and widely ignored) problems that hamper the progress of learning support systems: • We do not have a holistic design model based on human mental processes, nor do we have an appropriate user interface design to step overfromcautomation9 to 'augmentation5. We dot not understand how to apply digital media for sustainable growth and global infrastructures because political, social, and technological hurdles are still dominating local or regional markets and standards.
Figure 54. The efiport system design model (pat. pending): All levels of digital media in education are embedded in the organization centered around skills and competencies which are connected to the actual learning objectives related to the learning options and activities.
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Nevertheless, we are optimistic that we shall be able - step by step to approximate potential solutions for the two dominating problems. We believe that the following global trends will control the development of e-learning and learning support systems. We shall experience the 'down grading' of ICT solutions and services following the global trends in service industries. For instance, people banks are carrying financial mediation into the low developed regions as 'micro banking' and 'micro finance'; traditional banking institutions, however, cannot cope with micro lending and micro credits and fall behind. Similarly, ICT producers and service providers will miss the opportunities of globalization and sustainable economic growth if they are not able to produce lean infrastructures and 'down graded' ICT solutions for community access and usage. We have seen the taylorism of the industry, and we have mentioned the taylorism of 'knowledge work'. We think that the decomposition of the value chain for economic reasons will drive the development of 'virtual experts team' where some irreplaceable experts will be the 'talents' enjoying high salaries and the rest will be in constant search for new poorly paid jobs. Therefore, the 'thinking networks' of Vilem Flusser will turn out to be 'learning organizations' built around economic values. Learning tasks will be embedded into work tasks, that is, corporate and project management will calculate with constant and relevant learning processes and foster them in order to be more efficient and effective. In the future, we may have jobs which demand only two or three hours of work per day - but the same jobs will demand several hours of daily long learning; the necessity of life-long learning will also grow because all highly developed societies will suffer from 'over-aging' putting more responsibilities on the backs of the elderly people. Until now, the biological evolution used selection to adapt individuals to the natural environment. What does it mean to adapt human beings to artificial environments? Certainly (or probably) not the transformation from hands and fingers into virtual keyboard devices. Moreover, the speed of evolution seems to be extremely slow as compared to the speed of ICT development. The visions of man-machine creatures or 'cyborgs' seem to be part of science fiction novels not reality. But the merger of men and machines has began, already. However, no flesh and metal
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cyborgs will evolve but embedded neural implants, such as intelligent biosensors with Internet access and artificial ears covered with real flesh from the biogenetic laboratories. Scientific progress allows us to manipulate genomes at the level of single genes. We already have in vitro fertilization and animal cloning; in the near future, we might have human cloning and exploitation of embryonic stem cells. We are developing machines that will surpass the human brain in raw computing power and capabilities to connect to a world of information-processing devices. Eventually, we must come to terms with the fact that genes, machines, and minds are continuous entities both in space and time (cf. Baldi, 2002). Therefore, it has been suggested that individuals may be more keen to safe their minds rather than their genes. Biological evolution is built on the adaptation and extension of information stored in the genome of a certain population. Rapid evolution in small population can develop new races within thousands and hundreds of years (instead of millions of years). We believe that a mind will not exist outside a body, but we are not sure how this 'body' will be and can be produced and maintained in the future. Digital media are changing the way we live and think every day. Generations of children will grow up with a very dense provision of digital media services. This means that digital media are not only changing our minds but also, literally, our brains, because the brain structure develops in two major steps: in early childhood and as a teenager - these are also times of massive media 'consumption'. Digitized human beings and people without extensive access to ICT will not be able to understand each other because their biographies and their brain structures are too different. Mind sets and virtual personalities representing real humans will be stored in computers. Computers will develop into even more 'intelligent machines', but we will ignore it just like we are ignoring it today: Playing chess was considered to be 'intelligent behavior' until computers started to do so; we define all computer-based behavior as 'non intelligent' - and therefore we shall not even notice when computers start to develop their own way of being 'intelligent'. The most important progress, however, will not come from 'big science' and 'intelligent technology' but from 'applied science', 'lean technology' and 'big (economic) value': Sustainability in terms of
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resources and global reach will be key technologies to win the race for global wealth. The key to develop better e-learning will be the destruction of e-learning with its learning platforms and WBTs: Learning is anywhere and anytime, because it is our nature to learn. Learning platforms will be embedded learning support systems being aware of our current knowledge and learning situation. In the past, we delivered isolated pieces WBT; today, WBT is part of the working and business processes; tomorrow, learning will be part of controlling and adapting work and business processes. The need to do (physical) work will decrease but the necessity to learn will increase even more. What we are waiting for is, that learning systems are self aware when and where they are needed. Form this point of view, we should not discuss 'Learning Support Systems for Organizational Learning' but 'Learning Organization Systems for System Learning'.
Appendices
Abbreviations
ADL: Advanced Distributed Learning Initiative AI: Artificial Intelligence AICC: Aviation Industry CBT Committee CBT : Computer Based Training CI: Computational Intelligence CMC: Computer Mediated Communication DRJVI: Digital Rights Management ERP: Enterprise Resource Planning EVA: Economic Value Added FIPA: Foundation for Intelligent Physical Agents GLM: General Linear Model GPS: Global Positioning System HRD: Human Resource Development HR XML: Human Resource extended Markup Language HR SEP: Human Resource Standard Exchange Protocol HTML: Hypertext Markup Language ICT: Information and Commnucation Technology IEEE LTSC: Institute of Electrical and Electronics Engineers Learning Technology Standards Committee IP: Internet Protocol IPR: Intellectual Property Rights ISO: International Standard Organization ITS: Intelligent Tutoring System LMX: Leadership-Membership-Exchange LOM: Learning Object Meta-Data MIPS: Million Instructions per Second 263
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MVA: Market Value Added NGO: Non-Govemmental Organization OLTP: Online Transaction Processing SCORM: Shareable Courseware Resource Model SGML: Structured General Markup Language SME: Small and Medium Enterprises / Subject Matter Expert TOC: Total Cost of Ownership TTO: Time To Operation VPN: Virtual Private Network WACC: Weighted Average Cost of Capital WBT: Web Based Training XML: extended Markup Language
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Web Links
Note: Some of the following Web links have been collected and reviewed by Gilly Salmon from Centre for Innovation, Knowledge & Enterprise, Open University Business School, Milton Keynes (UK). General Interest Farrell, G.M. (Ed.) (2001). The Changing Faces of Virtual Education ® www.col.org/virtualed. The Commonwealth of Learning (COL) Principles of knowledge management « www.know-center.at * www.bus.utexas.edu/kman/kmprin.htm Speech technology standards * www.speech.cs.cmu.edu/ ® www.computerworld.com.au/IDG2.NSF/a/0005C942?OpenDocu ment&n=e&c=CT Learning Technology Standards » www.masie.com/standards/S3_Guide.pdf * www.adlnet.org/ Commercial Consultants « www.brandonhall.com/ * www.masie.com/ Learning Support Technology Providers & Institutes ® www.aace.org ® www.efiport.com « www.hyperwave.com » www.iicm.edu ® www.isnm.de Emerging Technologies ® www.newtech.org/addresslO_en.htm * wearables.cs.bris.ac.uk/
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» wearcam.org/mcluhan-keynote.htm $ www.pjb.co.uk/mobile_comm.htm * www.trainlngzone.co.uk/item/37933 * human-factors.arc.nasa.gov/ihh/psychophysio/ « www.microsoft.com/pocketpc/ * www.datacommresearch.com ® www.xybernaut.com/ ® iswc.gatech.edu/ Collaborative Learning * csalt.lancs.ac.uk/jisc/ * collaborate.shef.ac.uk/spender.htm « www.shef.ac.uk/uni/projects/wrp/sem2.html ® cbl.leeds.ac.uk/~tim/networked_learning/ * www.icbl.hw.ac.uk/jtap-573/cultures.html * www.ucisa.ac.uk/TLIG/conf/tlig00/w26/ Online Tutoring ® oubs.open.ac.uk/e-moderating ® www.e-moderating.com « www.itee.uq.edu.au/~tutoring/Tutor_responsibilities/tutoring_pro blems_and_Performance.htm Online Assessment * www.nwrel.org/learns/resources/measurement/Outcomes_and_Pe rformance_Measurement.pdf « materials.netskills.ac.uk/info/module52.html ® www.derby.ac.uk/ciad/ ® www.scaan.ac.uk/hw_caa.doc « www.ltss.bris.ac.uk/VLEintro_5_3 .htm » www.caaconference.com/ * www.caacentre.ac.uk/ Future Developments * www.tfi.com/ * oubs.open.ac.uk/future * www.wfs.org/index.htm * www.foresight.gov.uk
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About the authors
Joachim P. Hasebrook High school diploma (Abitur) and head an offset printing office in a little city in the north of Germany. Master of science with a major in psychology and bachelor of science with a major in computer science at the University of Marburg. Ph.D. thesis about learning with multimedia and hypermedia systems at the University of Giessen, Germany. Further education at the schools of German booktraders in Frankfurt, Germany, and Executive Education at the Goizueta Business School at Emory University in Atlanta, USA. Expert opinions about effective learning with multimedia and interactive distance learning environments in charge of the German. Parliament and the Scientific Options Assessment (STOA) of the European Parliament. Project manager for electronic media and expert systems for a German publishing and software house in charge of the Federal Institute of Labout Since 1996, member of staff of Bank Academy holding the position of the Head of the Department 'Concept & Programme Development1. Temporarily, Co-CEO of Knowbotic Systems Inc., a developer of software for distributed computational intelligence. Managing director of educational financial portal [efiport] Inc., a subsidiary of Bank Academy. Chair of the Task Force Multimedia of the European Bank Training Network (EBTN) and member of international program committees, e.g. WebNet / Elearn and ICCE/ICCAI, and member of editorial boards of scientific journals, e. g. KES Journal and Journal of Universal Computer Science (J.UCS). Since 2004, Ml professor for e-learning and work design at the International School of New Media (ISNM) of the University of Luebeck, Germany (www.isnm.de).
268
Hermann A. Maurer Sp?---l---•'" ••^4^^S0S^ m&,'.: ''iwK
Learning Support Systems
Study of Mathematics at the Universities of Vienna (Austria) and Calgary (Canada) starting in 1959. System Analyst with the Government of Saskatchewan (Canada) in 1963. Mathematicianprogrammer with IBM Research in Vienna 19641966. Ph.D. in Mathematics from the University of Vienna 1965. Assistant and Associate Professor for Computer Science at the University of Calgary 1966-1971. Full Professor for Applied Computer Science at the University of Karlsruhe, West Germany, 1971-1977, and Visiting Professor at SMU, Dallas, and University of Brasilia (Brazil) for three months, each, and at the University of Waterloo, during the same period. Adjunct Professor at Denver University 1984-1988; Professor for Computer Science at the University of Auckland, New Zealand, in 1993 (on leave from Graz), then Honorary Adjunct Professor and since May 2001 Honorary Research Fellow. Full Professor at the Graz University of Technology since 1978, since October 2000 also Dean of Studies for Telematics. In addition, director of the Research Institute for Applied Information Processing of the Austrian Computer Society 1983-1998; chairman of Institute for Information Processing and Computer Supported New Media since 1988, director of the Institute for Hypermedia Systems of JOANNEUM RESEARCH since 1990, director of the AWAC (Austrian Web Application Center) of the ARCS (Austrian Research Centers) 19972000, member of the board of OCG (Osterreische Computergesellschaft) 1979-2003 and since 2001/01/01 chief scientist of the KNOW Center (K+ Center), the first research center on Knowledge Management in Austria (www.iicm.edu; www.know-center.at).
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Index
Active Documents 85, 105 ADL 205 Africa 24 Agent Intelligent-Agent 220 Agent Multi-Agent-Platform 202, 204, 237 Agent Rational 202 AI 155,201 AICC 205 Aphasia 229 Ariadne 205 Asia 22 Augmented Reality 216 BDI Model 202 Bible 226, 237 Blended Learning 125 Brain Drain 18 Career Counseling 182 Career Decision 161 Carreer Counseling 181 CBT 6 CI 155 Civilization 253 Clinical Psychology 32 CMC 140,226 COBOL 201 Cog 201 Competence Management 34 Computational Intelligence 227 Conditioning Circuit 231 Conflict Management 52 Cultural Differences 27 Customer Capital 57 Cybernetics 235 Developing Countries 18 Development Costs 67 Double Loop Learning 45 DRM 13 Dual Encoding 180 Ecology 254
Educational Controlling 34 E-Government 5 E-Learning Benefits 8 E-Learning Markets 14 E-Learning Perspectives 14 ERP 122 EVAMVA 60 Evolution 260 FIPA 205, 237 FORTRAN 201 G7 Countries 9 Gesture Recognition 238, 246 Globalization 19 GNP 19 GPS 241, 248 HR XML Consortium 48 HRD 68 HR-SEP 205 Human Capital 57 Human Culture 255 IAS 58 ICT 7 ICT Investments 9, 37 ICT vs. Didactics 28 IEEELTSC 205 Illiad 257 IMS 205 Information Theory 235 Intangible Assets 57 Intellectual Capital 57 Intelligent Robotics 201 Invisible Assets 57 ITS 28, 93, 155, 159, 180 Knowledge Management 46 Knowlegde Based Economy 46 Language 235 Language Natural 107 Learning Culture 119 Learning Organization 31, 42 Linguistics 256
288 LMS 122 LMX 55, 131 LOM 49 LSS 122, 126 Machine Learning 201 MANOVA 186 Mental Models 228 Meta Cognition 96 Meta-Analysis 211 MIPS 225 MIT 219 M-Learning 12 Moore's Law 5 Multimedia 41 Neural Networks 220,231 Neurobiology 230 New Economy 39 Nobel Prize 31 NSA 237 OECD 7 OLTP 209 Ontology 107,219 PDA 248 Personnel Budget 66 Poverty Premium 19 PSS 68, 93 Rating Standards 59 RDF 210 Reinforcement Learning 202 Robotics 236
Learning Support Systems School Connectivity 10 SCORM 205 Semantic Web 204 SGML 208 SHOE 218 Skandia Navigator 57 Skills Management 47, 48 SME 131, 140 Social Theory 53 Speech Recognition 236 Speech Synthesis 236 Spiking Neurons 231 Theories X and Y 53 TOC 38 Training Investment 77 TTO 67 Ubiquitous Computing 216 UMUC 121 Validity 76 Value Creation 59 Value Extraction 59 Virtual Keyboard 245 Virtual Reality 215 VPN 12 WACC 60 War For Talent 62 World Bank 17 XML 208 XMLQL 219 XSL 219
Learning Support Systems for Organizational Learning The major trends in e-learning are determined by the global demand of academic, elderly and nontraditional target groups for training and education. The advent of the learning organization reflects these major shifts of the educational markets within companies. Automation of learning processes does not enhance a company's productivity; augmentation of individual and collaborative learning processes is needed. This book reflects seven years of applied research (1997-2003) in the fields of adaptive multimedia systems, knowledge-based and collaborative learning environments, and intelligent software agents.
ISBN 981-238-831-1
World Scientific www.worldscientific.com 5529 he
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