Research in Secondary Schools, Volume 17 (Advances in Learning and Behavioral Disabilities)

RESEARCH IN SECONDARY SCHOOLS ADVANCES IN LEARNING AND BEHAVIORAL DISABILITIES Series Editors: Thomas E. Scruggs and ...

Author: Thomas E Scruggs | Margo A Mastropieri

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RESEARCH IN SECONDARY SCHOOLS

ADVANCES IN LEARNING AND BEHAVIORAL DISABILITIES Series Editors: Thomas E. Scruggs and Margo A. Mastropieri Recent Volumes: Volume 12: Edited by Thomas E. Scruggs and Margo A. Mastropieri Volume 13: Edited by Thomas E. Scruggs and Margo A. Mastropieri Volume 14: Educational Interventions – Edited by Thomas E. Scruggs and Margo A. Mastropieri Volume 15: Technological Applications – Edited by Thomas E. Scruggs and Margo A. Mastropieri Volume 16: Identification and Assessment – Edited by Thomas E. Scruggs and Margo A. Mastropieri

ADVANCES IN LEARNING AND BEHAVIORAL DISABILITIES VOLUME 17

RESEARCH IN SECONDARY SCHOOLS EDITED BY

THOMAS E. SCRUGGS George Mason University, Fairfax, USA

MARGO A. MASTROPIERI George Mason University, Fairfax, USA

2004

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© 2004 Elsevier Ltd. All rights reserved. This work is protected under copyright by Elsevier Ltd, and the following terms and conditions apply to its use: Photocopying Single photocopies of single chapters may be made for personal use as allowed by national copyright laws. Permission of the Publisher and payment of a fee is required for all other photocopying, including multiple or systematic copying, copying for advertising or promotional purposes, resale, and all forms of document delivery. Special rates are available for educational institutions that wish to make photocopies for non-profit educational classroom use. Permissions may be sought directly from Elsevier’s Rights Department in Oxford, UK; phone: (+44) 1865 843830, fax: (+44) 1865 853333, e-mail: [email protected]. Requests may also be completed on-line via the Elsevier homepage (http://www.elsevier.com/locate/permissions). In the USA, users may clear permissions and make payments through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; phone: (+1) (978) 7508400, fax: (+1) (978) 7504744, and in the UK through the Copyright Licensing Agency Rapid Clearance Service (CLARCS), 90 Tottenham Court Road, London W1P 0LP, UK; phone: (+44) 20 7631 5555; fax: (+44) 20 7631 5500. Other countries may have a local reprographic rights agency for payments. Derivative Works Tables of contents may be reproduced for internal circulation, but permission of the Publisher is required for external resale or distribution of such material. Permission of the Publisher is required for all other derivative works, including compilations and translations. Electronic Storage or Usage Permission of the Publisher is required to store or use electronically any material contained in this work, including any chapter or part of a chapter. Except as outlined above, no part of this work may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without prior written permission of the Publisher. Address permissions requests to: Elsevier’s Rights Department, at the fax and e-mail addresses noted above. Notice No responsibility is assumed by the Publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made. First edition 2004 Library of Congress Cataloging in Publication Data A catalog record is available from the Library of Congress. British Library Cataloguing in Publication Data A catalogue record is available from the British Library. ISBN: 0-7623-1107-X ISSN: 0735-004X (Series) ∞ The paper used in this publication meets the requirements of ANSI/NISO Z39.48-1992 (Permanence of Paper). Printed in The Netherlands.

CONTENTS LIST OF CONTRIBUTORS

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EFFICACY OF BEHAVIORAL SELF-MANAGEMENT TECHNIQUES WITH ADOLESCENTS WITH LEARNING DISABILITIES AND BEHAVIOR DISORDERS Charles A. Hughes, William J. Therrien and David L. Lee

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THE EFFECTS OF SELF-INSTRUCTIONAL STRATEGIES ON PROBLEM SOLVING IN ALGEBRA FOR STUDENTS WITH SPECIAL NEEDS Caroline R. Lang, Margo A. Mastropieri, Thomas E. Scruggs and Miriam Porter

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VALUE ADDED OF THE SPECIAL EDUCATION TEACHER IN SECONDARY SCHOOL CO-TAUGHT CLASSES Naomi Zigmond and David W. Matta

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HOMEWORK FOR STUDENTS WITH DISABILITIES Jill Jakulski and Margo A. Mastropieri

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MAKING THE GRADE: PROMOTING SUCCESS OF SECONDARY STUDENTS WITH AUTISM SPECTRUM DISORDERS Janet E. Graetz

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EFFECTIVE CONTENT-AREA INSTRUCTION FOR ALL STUDENTS Janis Bulgren

147

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SOCIAL STUDIES AND STUDENTS WITH DISABILITIES: CURRENT STATUS OF INSTRUCTION AND A REVIEW OF INTERVENTION RESEARCH WITH MIDDLE AND HIGH SCHOOL STUDENTS Judith L. Fontana

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HOW CAN A STUDENT’S DEPRESSIVE ATTITUDE INTERFERE WITH THE USE OF GOOD SELF-REGULATION SKILLS? Angelica Moè, Cesare Cornoldi, Rossana De Beni and Luisa Veronese

207

PRELIMINARY WORK IN DETERMINING WHETHER DYNAMIC ASSESSMENT OF WORKING MEMORY HELPS IN THE CLASSIFICATION OF STUDENTS WITH READING DISABILITIES Crystal B. Howard and H. Lee Swanson

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RECENT RESEARCH IN SECONDARY CONTENT AREAS FOR STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Thomas E. Scruggs and Margo A. Mastropieri

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TECHNOLOGY AND STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Nicole S. Ofiesh

265

THE EFFECTS OF TEACHER LICENSURE ON TEACHERS’ PEDAGOGICAL COMPETENCE: IMPLICATIONS FOR ELEMENTARY AND SECONDARY TEACHERS OF STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES André A. Nougaret, Thomas E. Scruggs and Margo A. Mastropieri

301

SUBJECT INDEX

319

LIST OF CONTRIBUTORS Janis Bulgren

Center for Research on Learning, University of Kansas, USA

Cesare Cornoldi

Department of General Psychology, University of Padua, Italy

Rossana De Beni


Judith L. Fontana

Helen A. Kellar Institute for Human Disabilities, George Mason University, USA

Janet E. Graetz

Department of Human Development and Child Studies, Oakland University, USA

Crystal B. Howard

Graduate School of Education, University of California, USA

Charles A. Hughes

Department of Special Education, Pennsylvania State University, USA

Jill Jakulski

Herndon Center, Virginia, USA

Caroline R. Lang

Graduate School of Education, George Mason University, USA

David L. Lee


David W. Matta

University of Pittsburgh, USA

Margo A. Mastropieri


Angelica Moè


André A. Nougaret

Department of Human Resources, Stafford County Public Schools, Virginia, USA vii

viii

Nicole S. Ofiesh

Department of Special Education, Rehabilitation, and School Psychology, University of Arizona, USA

Miriam Porter


Thomas E. Scruggs


H. Lee Swanson

Graduate School of Education, University of California, USA

William J. Therrien


Luisa Veronese


Naomi Zigmond

University of Pittsburgh, USA

EFFICACY OF BEHAVIORAL SELF-MANAGEMENT TECHNIQUES WITH ADOLESCENTS WITH LEARNING DISABILITIES AND BEHAVIOR DISORDERS Charles A. Hughes, William J. Therrien and David L. Lee ABSTRACT This chapter presents a quantitative and qualitative review of research on the use of behavioral self-management (BSM) procedures with adolescents with learning disabilities or behavioral disorders (LD/BD). These procedures included self-monitoring, self-evaluation, self-reinforcement, self-instruction, and packages containing two or more BSM techniques. Twenty studies published from 1981 to 2002 were identified and analyzed. The analysis centered on a series of questions addressing overall effectiveness of the procedures, whether BSM produced socially valid changes, where the changes occurred (i.e. special education or general education setting), whether maintenance and generalization of the target behavior(s) occurred, and if students began to use BSM procedures on their own. Results showed a mean percentage of nonoverlapping data (PND) of 80 indicating that BSM procedures are, overall, an effective approach to behavior change. It also appears that in Research in Secondary Schools Advances in Learning and Behavioral Disabilities, Volume 17, 1–28 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 0735-004X/doi:10.1016/S0735-004X(04)17001-8

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CHARLES A. HUGHES ET AL.

some instances, these changes are socially valid in that the performance of students with LD/BD can be improved to the level of nondisabled peers. Interventions consisting of a combination of self-management procedures appear to be the most effective, however self-monitoring alone has similar impact. BSM also appears to be effective with a wide variety of behaviors, albeit with relatively discrete behaviors (versus more complex chains of behaviors used in strategic problem-solving). While there is some evidence that target behaviors were generalized and maintained, many of the studies reviewed did not measure it. Also of concern was the apparent lack of student involvement in selecting target behaviors, goal setting, forms of recording etc as well as the fact that no study measured student ability to apply BSM procedures after intervention. Implications for future research and practice are discussed. Behavioral self-management (BSM) includes a variety of techniques, including having students observe their behavior, record its occurrence, self-prompt while performing the behavior, evaluate or rate its quality, and self-deliver contingent consequences. In essence, students take over many of the classroom behavior management tasks typically performed by teachers. Thus, BSM can be viewed as the capacity to regulate ones own behavior. From an applied behavior analysis perspective, it involves the personal and systematic application of behavior change strategies that result in the desired modification of ones behavior. It involves both a behavior to be changed and another behavior (e.g. self-recording) that is emitted for the purpose of affecting that change. As early as 1975, Kazdin began supporting the use of BSM with students with challenging behaviors and, as part of that rationale, presented a number of potential disadvantages of adult-managed behavior change procedures. He noted that often adults (e.g. teachers) are unable to observe all students’ behavior all the time and thus cannot evaluate, mediate, or reinforce it. For example, teachers cannot observe covert behaviors (e.g. sub vocal self-statements), whereas students have potential access to all their behaviors – overt and covert. Kazdin also pointed out that often adults became so associated with the behavior change process that students exhibit target behaviors only in their presence, thus raising concerns about generality of behavior change. It has also been posited (Hughes et al., 1989; Nelson et al., 1991) that BSM may increase motivation via the promotion of active participation in, and ownership of, the behavior change process. Thus, BSM is purported to deal with instructional concerns including accessing student behavior for the purpose of monitoring and shaping it and student passivity and motivation. The underlying assumption then is that use of BSM results in greater frequency, durability, and generalization of behavior change. Finally, the portability of BSM has led educators

Efficacy of Behavioral Self-Management

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to consider the potential it has for helping adolescents with learning disabilities and behavior disorders succeed in inclusive settings. While much of the original research in BSM began in the 1970s, it was in the early 1980s that this procedure began to be investigated with special needs populations, specifically those students identified as having learning disabilities (LD) and behavior disorders (BD). It seemed that BSM would be an appropriate intervention for this population given many of the characteristics of these students including passivity, impulsivity, and distractibility and problems with generalizing both academic and social skills. This seemed especially true for adolescents with LD/BD given the oft-cited need of this group for increased independence and self-control (Deshler et al., 1996).

DEFINITION OF TERMS In this chapter, we review self-management studies conducted with adolescents identified as having a learning disability or an emotional/behavioral disorder. We have chosen to examine those procedures commonly falling under the rubric of BSM. These procedures include self-monitoring, self-evaluation, self-administration of consequences, and self-instruction/prompting.

Self-Monitoring Self-monitoring is the most frequently researched BSM technique with students with learning and behavioral disabilities. This procedure is the combination of selfassessment and self-recording. That is, a student decides whether the behavior of interest occurs (or does not occur) and then records it in some manner. Reid and Harris (1989, 1993) contend that the process of self-monitoring forces students to know when they do something and it is this increased awareness or attention to the behavior that is at the basis of its effectiveness. This relationship between increased self-awareness of a behavior and its impact on changing some aspect of behavior is referred to as reactivity. In order for the self-assessment part of self-monitoring to occur, the student must have a good understanding of the parameters of when the behavior occurs or does not occur. The process of self-recording can take many forms, including a check mark on a form, crossing off a completed task, or recording a frequency count on a graph. Additionally, there needs to be some form of prompt that cues the student to self-monitor. This prompt can take the form of a teacher-controlled cue such as an audible tone that plays at random intervals or can be simply asking

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the students to remind themselves (self-prompt) periodically to self-monitor. Reid and Harris (1993) caution that self-monitoring (as well as other BSM techniques) is not an appropriate method for teaching new behaviors. The assumption should be that students can already perform the behavior, but not at a rate or topography that would be considered functional.

Self-Evaluation This BSM procedure takes the self-monitoring process one step further by requiring students to not only assess whether a behavior occurred but to make an evaluation of the behavior, that is, make a judgment about the quality or acceptability of the target behavior. To do this, students are required to compare or rate the behavior against some form of standard or criteria. The criteria for deciding whether a dimension of a behavior is acceptable (e.g. number of problems completed correctly, accuracy of homework assignments turned in, amount of time engaged in a task) can be determined by the teacher, the student, or both. Thus, the guiding question underlying self-evaluation is not just whether “Did I exhibit the behavior?” but “Did I do it well?” Often students are provided numerical or Likert rating scales with which to evaluate their performance.

Self-Delivery of Consequences Composed of two approaches, self-reinforcement and self-punishment, this procedure includes self-selection of a reinforcer/punisher and self-administration of the consequence upon meeting or not meeting a set performance standard. The student typically sets the performance standard or the teacher negotiates the standard with the student. Key to this approach is that the selected reinforcers are readily accessible to the student and that other, unintended reinforcers are controlled.

Self-Instruction Often categorized as a cognitive-behavioral approach, self-instruction involves teaching students to provide their own covert verbal prompts to solve a problem or complete a multi-step task. This self-talk then functions as a controlling response that affects the target behavior. The general sequence for teaching students to selfinstruct was described by Meichenbaum and Goodman (1971) and begins with the teacher self-talking out loud while performing the behavior/skill while the


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student observes. Then the teacher self-talks along with the student followed by a period where the student self-talks and performs the task alone. During this period the teacher role is to observe and prompt. Ultimately the student is requested to continue to self-instruct but covertly.

Combination or Packages Often BSM techniques are not taught singly, but rather as a combination of two or more techniques put together as an instructional package. Over the years there have been periodic published reviews of BSM studies, all of which have concluded that this approach is generally effective. For example, in 1989, Hughes et al. presented a qualitative review in which they examined extant studies investigating the impact of BSM on students identified as having behavior disorders. Two years later Nelson and his colleagues (1991) published a similar review, but quantified intervention impact by calculating effect sizes. In 1996, Reid authored a review of research of self-monitoring with students with learning disabilities, and more recently McDougall (1998) conducted a review of BSM and its impact on students with disabilities in general education settings. As mentioned above, the over all results of literature reviews conducted over the past 20 years or so have found BSM to be effective. However, an analysis of these articles yields a number of unanswered questions that need to be answered in order to obtain a more complete picture of this intervention approach for adolescents. The questions guiding this synthesis include the following: (1) (2) (3) (4) (5) (6)

(7) (8)

(9)

Is BSM effective with adolescents with behavior and learning disabilities? Does BSM produce socially valid changes in behavior? Are some BSM techniques more effective than others? With what behaviors are BSM techniques effective? With whom and where (e.g. spled and/or general ed setting) are BSM techniques effective? Are there important procedural issues for self-monitoring? Specifically, is the type of behavior monitored (appropriate or inappropriate) an issue? And is monitoring attention to task more effective than task productivity? Does BSM promote maintenance and generalization of behavior change? To what extent do students generalize the procedures of BSM (e.g. after being involved in self-management instruction, can students plan and implement their own program with little external guidance and support)? What are common instructional components that seem necessary to teach BSM to students?

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Thus the purpose of this chapter is to provide a quantitative and qualitative review of BSM studies used with adolescents with LD and/or BD, with a focus on answering these questions.

METHODS Inclusion Criteria and Search Strategy The search strategy utilized for this study was a three-tiered model identical to that employed by Lee (in press). First, the literature was searched using ERIC and PsychINFO databases with the following key words: self-management, self-monitoring, self-evaluation, self-reinforcement, self-punishment, and selfinstruction. Second, a hand search was conducted of related journals. Finally, the reference lists of all included studies were examined (i.e. footnote chasing). In order to be included in the qualitative review a study had to contain empirical evidence on the effects of BSM (i.e. self-monitoring, self-evaluation, self-administration of consequences or self-instruction) for adolescents with LD/BD. The term adolescent was operationalized as students between 13 and 18 years old. Studies that contained at least one subject within this age range were included in the analysis. The studies also had to appear in a refereed journal between the years of 1980 and 2003. Studies included in the quantitative review also had to present graphed time-series data (i.e. single-subject research design) with interobserver agreement data. A total of 20 studies met criteria to be included in the review. Eighteen of the twenty studies additionally met the inclusion criteria for quantitative analysis. Two (Sanders et al., 1991; Shapiro, 1989) studies could not be examined qualitatively due to study design (Shapiro utilized a group design) or data presentation (Sanders et al. did not present data in a time-series format).

Measure of Intervention Effectiveness The percentage of nonoverlapping data (PND) (Scruggs et al., 1987) was used as the metric to assess the effectiveness of self-management interventions. percentage of nonoverlapping data (PND) is the percentage of intervention data points that lay above the highest baseline point for a given data series. For example, if the highest baseline point in a given series was 50, and the intervention points were 45, 60, 80, 66, 87, the PND would be 80%. In the event of a ceiling effect (e.g. when data were reported as percentages and highest baseline point was at 100%). PND was calculated using the number of points that were within the highest baseline


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data point (Schlosser & Lee, 2000). Scruggs and Mastropieri (2001) suggested that PNDs above 90 represent very effective interventions, those between 70 and 90 represent effective interventions, PNDs between 50 and 70 are questionable in terms of effectiveness, and those below 50 represent ineffective interventions. Three different variations of PND were calculated to assess the effects of self-management interventions. First, intervention percentage of nonoverlapping data (IPND) was used to assess the overall effectiveness of self-management interventions and was calculated using baselines and their corresponding intervention data series. Second, when available, generalization percentage of nonoverlapping data (GPND) was used to assess generalization and was similarly calculated using baseline and generalization data series. Finally, maintenance percentage of nonoverlapping data (MPND) was used to assess maintenance and was calculated using the lowest of the last three points of intervention and maintenance data series. Coding Categories All 20 studies were reviewed using the following coding categories: (a) classification (mild/moderate mental retardation, learning disabilities, behavior disorder, combined mild disability, no disability, and other/not specified); (b) setting (institution/residential, family home, segregated classroom/school, general education/ inclusive classroom, resource classroom, community, and other/not specified); (c) intervention type (self-monitoring only, self-evaluation only, self-instruction only, multi-component, instructional packages); (d) experimenter delivered reinforces delivered (yes, none indicated); (e) valence of behavior (positive, negative, both positive and negative, not applicable/unable to determine); (f) focus of monitoring (attention, productivity, adherence to standard or rule, accuracy); (g) dependent variable (on/off task, accuracy, productivity, inappropriate behavior, appropriate behavior, other/not specified); (h) generalization data present (yes, no); (i) maintenance data present (yes, no); ( j) generalization setting (institution/ residential, family home, segregated classroom/school, general education/ inclusive classroom, resource classroom, community, and other/not specified); and (k) maintenance setting (institution/residential, family home, segregated classroom/ school, general education/inclusive classroom, resource classroom, community, and other/not specified).

RESULTS The research questions addressed in this review were subjected to both quantitative and qualitative analyses (see Table 1). This procedure allowed for an objective

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Table 1. Citation

Subjects

Studies that used self-monitoring only Blick and Test 9 LD, 1 ED 2 (1987) MR; ages 15–17 Rooney and 5 LD; ages Hallahan (1988) 12–14

Setting

Type of Self-Management

Dependent Variable

Results/Mean (S.D.) PND

Spled

Self-monitored on task behavior using audio cue. Self-monitored on task behavior using audio cue. Assessed the impact of self-monitoring by students on adult behavior. Self-monitored on task behavior using audio cue. Some students also received teacher reinforcement. Self-monitored on task behavior using audio cue. Self-monitored academic productivity and accuracy. Self-monitored academic accuracy. Recorded and graphed percent correct.

On task behavior

63.50 (28.82)

Adult behaviors: frequency of adult assistance; students: attention

74.00 (45.03)

On task behavior

77.43 (30.68)

Student and teacher watched video-tape of student’s behavior in class. Student chose to work on reducing self-injurious behavior. In subsequent classes, teacher provided graphic feedback on student’s self-injurious behavior.

Self-injurious: hitting face

Spled

4 LD, 1 LD/BD; ages 12–17

Spled

Prater et al. (1992)

1 LD/BD; age 14 3 BD/LD; ages 13–15 3 LD/ADHD; ages 12–13

Spled & Gen. ed. Spled

Carr and Punzo (1993) Shimabukuro et al. (1999)

Studies that used self-evaluation only Osborne et al. 1 BD; age 15 (1986)

Spled-private school

Spled & Gen. ed.

On task behavior; academic productivity On task behavior; academic accuracy and productivity Accuracy; productivity; on task behavior

100.00 (0.00) 78.50 (10.02) 90.50 (12.15)

63.33 (11.93)


Prater et al. (1991)

Off task behavior disruptive behavior

78.25 (29.70)

Rate of inappropriate and appropriate peer interaction; social validation measures

76.95 (31.37)

Spled: University school

Self-evaluation within the context of group contingencies – rated adherence to classroom rules on a 6 point scale. Compared self-evaluation, group evaluation and teacher evaluation (token economy) systems.

Math performance; time on task; consumer satisfaction

14.00 (15.34)

Spled

Self-instruction training using Meichenbaum and Goodman (1971) procedures. Same as experiment 1 (above) except used math instead of reading and spelling.

Reading and spelling performance

71.25 (23.94)

Math performance

78.00 (–)

4 LD, 1 BD; ages 13–15

Spled Gen. ed.

Falk et al. (1996)

18 BD or no behavioral problems; age not stated; grades: K-8 3 ED; age 15

Pull-out for study

McQuillan et al. (1996)

Study that used self-instruction only 2 LD; ages Swanson and 13–14 Scarpati (1985) (Experiment 1) 1 LD; age 13 Swanson and Scarpati (1985) (Experiment 2)

Spled


Self-evaluated their adherence to classroom rules on a 1 through 5 point scale. Students with BD self-evaluated their behavior after watching video sessions of themselves playing a game with peers.

Smith et al. (1988)

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Table 1. (Continued ) Citation

Subjects

Multi-component interventions Warrenfeltz et al. 4 BD; ages (1981) 15–16


Dependent Variable

Spled: Residential facility

Self-monitoring procedures combined with role-play. (1) Students taught appropriate responses to supervisor’s requests. (2) Role played scenarios. Used self-monitoring sheet to record whether the employee in the vignettes responded appropriately. (3) Used self-monitoring sheet to vocational training room. Self-monitoring procedures combined with role-play. Same general procedures as Warrenfeltz et al. (1981) Intervention included goal setting and self monitoring. Students developed a plan to complete school projects and monitored the plan’s implementation.

Appropriate responses to instruction; appropriate responses to critical feedback and conversation

Kelly et al. (1983)

4 BD; ages 15–17

Spled: Residential facility

Lenz et al. (1991)

6 LD; ages 12–14

Summer program

Results/Mean (S.D.) PND

Only generalization data were graphed

Appropriate responses to instruction

70.75 (14.34)

Evaluated student managed guides; completed projects

96.06 (7.92)


Setting

3 BD; ages 12–13

Spled

Hogan and Prater (1993)

1 LD, 1 BD; ages 14–15

Spled & Gen. ed.

Trammel et al. (1994)

08 LD; ages 13–16

Spled & Gen. ed.

Self-monitoring, evaluation, reinforcement and instruction in isolation and combination Self-monitoring: appropriate and inappropriate verbalization Evaluation: How am I doing? added Reinforcement: If doing well told to say, “I’m doing great” Self-instruction: Used Meichenbaum and Goodman (1971) procedures. Self-monitoring and self-instruction within a peer tutoring model (note: peer tutoring was a separate experimental phase). Tutor (student with BD): Self-monitored disruptive behavior. Self-instruction-taught to use steps to think before acting. Tutee (student with LD): Self-monitored on task behavior using audio cues. Self-monitored homework completion. Then phase of goal setting/graphing.

Appropriate and inappropriate verbalizations

80.50 (12.57)

Tutor/tutee: Time on task; Tutor: Spelling and vocab. Tests

87.50 (19.37)

Assignment completion

95.88 (8.64)


DiGangi and Maag (1992)

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Table 1. (Continued ) Citation

Snyder and Bambara (1997)

Setting


Dependent Variable

3 LD; age 14

Spled & Gen ed.

Self-monitoring, self evaluation, self-reinforcement (circle degree of satisfaction) and goal setting. Self-monitored survival skills: Arrive to class on time, ready to begin class, has pen/pencil, paper, has text, hands in homework, completes homework.

% of demonstrated survival skills School progress reports

Votech school

Multi-component intervention aimed to teach students to manage own behavior. Consisted of 30 instructional units covering general self-management, problem solving and application of self-management principles to job-related skills.

Problem solving assessment; occupational skills assessment; tests of instructional units

Spled

Comprehensive strategy in which the student plays a role in the change process.

Varied by student: Coming to class prepared; assignment completion or percent of homework

Instructional packages Shapiro (1989) 67 LD; age not stated; grade: 12th

Sanders et al. (1991)

4 LD; ages 12–13

Results/Mean (S.D.) PND 86.00 (7.55)

After training, experimental groups’ performances were significantly better than non-trained LD and Non-LD groups on a problem solving and occupational skills assessment Each student mastered the components of the strategy; students also made improvement in their respective target behaviors


Subjects


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measure of intervention effectiveness, as well as an examination of more subjective variables (e.g. social validity of results). All but two studies (Sanders et al., 1991; Shapiro, 1989) were evaluated using PND analysis. percentage of nonoverlapping data points was calculated for each data series. This procedure yielded 139 data series from 75 participants. Characteristics of participants, settings, and interventions were analyzed using one-way analyses of variance. Main effects were followed up using Tukey’s HSD with an alpha set at 0.05. Tukey’s test was selected because it limits comparison-wise Type 1 error to p = 0.05. Correlational analyses were also conducted where appropriate. Interrater agreement for the quantitative analysis was established in two ways. First, the categorical variables were coded for each study by two coders working independently. Differences were discussed and resolved. Next, a second coder independently calculated PNDs for 17% of data series. Interrater agreement for the PND data was 100%.

Is BSM Effective with Adolescents with Behavior and Learning Disabilities? The overall PND of 80 (S.D. = 26.50) for these behavioral self-management interventions indicated that as whole BSM interventions are effective for adolescents with LD and/or BD. Further, a qualitative review of studies excluded from PND analysis also indicates the efficacy of BSM techniques. The effectiveness of the various BSM interventions seemed to be moderated by a variety of factors. For example, a correlational analysis also revealed a moderate relationship between IQ and BSM effectiveness (r = 0.38, p = 0.004, n = 82), indicating that aptitude may play a role in the success of the intervention. A negative correlation was also found for participant age and BSM effectiveness (r = −0.30, p = 0.001, n = 135).

Does BSM Produce Socially Valid Changes in Behavior? Although the magnitude of the PND and qualitative review indicates BSM interventions produced significant behavioral change, only four studies (Falk et al., 1996; Prater et al., 1991; Shapiro, 1989; Snyder & Bambara, 1997) compared the behavioral improvement obtained through their intervention to the behavior of normally achieving peers. Prater et al. (1991) compared students’ on task improvement against a randomly selected student in the same class. Their results indicate that, for 2 of the 3 students, self-monitoring improved on task behavior to

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a level commensurate or above the level of the randomly selected peer. In a selfevaluation study, Falk et al. (1996) had adult raters, na¨ıve to conditions and student labels, rate subjects’ appropriate and inappropriate social interactions. By the end of the intervention, adult raters could no longer distinguish between students with and without behavioral disorders. In a multi-component intervention, Snyder and Bambara (1997) compared subjects’ improvements with school survival skills (i.e. arrive to class on time, ready to begin class, has pen/pencil, paper, has text, hands in homework, and completes homework) to nondisabled peers. After the intervention was implemented, subjects performed as well as their nondisabled peers. In an instructional package intervention, Shapiro (1990) compared students with LD involved in the intervention to untrained students with and without LD. Students involved in the treatment condition scored significantly better than both the untrained LD and non-LD groups on a problem solving and occupational skills assessment.

Are Some BSM Techniques More Effective Than Others? To compare the relative effectiveness of self-management techniques, studies were grouped into five categories: self-monitoring only, self-evaluation only, self-instruction only, multi-components interventions and instructional packages. Six studies (Blick & Test, 1987; Carr & Punzo, 1993; Prater et al., 1991, 1992; Rooney & Hallahan, 1988; Shimabukuro et al., 1999) were classified into the selfmonitoring only category. All studies except one (Prater et al., 1991) included only the instructional components of self-assessment and self-recording. Prater et al. (1991) intervention, however, also included a teacher reinforcement component for 3 of the 4 subjects. This study was not classified as a multi-component as the reinforcers were teacher delivered and were faded by the end of the intervention. Four studies (Falk et al., 1996; McQuillan et al., 1996; Osborne et al., 1986; Smith et al., 1988) were classified into the self-evaluation only category. Two of these studies (McQuillan et al., 1996; Smith et al., 1988) involved students evaluating their adherence to classroom rules. In the remaining two studies (Falk et al., 1996; Osborne et al., 1986) participants were video-taped and subsequently watched the tapes and evaluate their performance. One study (Swanson & Scarpati, 1985), that included two experiments, was classified into the self-instruction category. Swanson and Scarpati used the self-instruction procedures created by Meichenbaum and Goodman (1971) in interventions aimed to improve students’ academic skills. Seven studies were classified into the multi-component category. This category includes both studies that combined components of self-management and studies


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that included other instructional components along with self-management instruction. Three studies combined various components of self-management instruction. Hogan and Prater (1993) combined self-monitoring and self-instruction, Snyder and Bambara (1997) combined self-monitoring, self-evaluation and self-reinforcement, and DiGangi and Maag (1992) examined self-monitoring, self-evaluation, self-reinforcement and self-instruction in isolation and in combination. Four studies combined self-management instruction with other instructional components. Two studies (Lenz et al., 1991; Trammel et al., 1994) added a goal setting component to self-monitoring and two studies (Kelly et al., 1983; Warrenfeltz et al., 1981) used self-monitoring in combination with role play. The remaining two studies (Sanders et al., 1991; Shapiro, 1989) were classified as instructional packages as the interventions were comprehensive in nature and included many instructional components. Sanders et al. (1991) implemented an instructional strategy package intended to teach students to design, implement and evaluate their own self-management programs. Shapiro’s (1991) intervention package included 30 instructional units that covered self-management, problem solving and the application of these skills to future vocational settings. A PND comparison, based on the above categories, was conducted for all studies except those classified as self-instruction and instructional packages. The self-instruction category contained too few data series to be included in the inferential analysis and both instructional package studies were excluded from the quantitative analysis (see Fig. 1). The number of data series that employed selfmonitoring, self-evaluation, or multi-component interventions was similar (see Fig. 1). However, an inferential analysis yielded overall differences between the

Fig. 1. Percent of Data Series Across Type of Self-Management Intervention.

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self-management techniques, F(3, 131) = 7.78, p = 0.001. A follow-up analysis indicated that self-monitoring alone (M = 81.27, S.D. = 24.09, d = 0.57)1 and multi-component interventions (M = 91.76, S.D. = 34.45, d = 1.18) produced greater changes in behavior than self-evaluation alone (M = 65.11, S.D. = 12.05). In an attempt to determine if some BSM techniques are more effective than others, DiGangi and Maag (1992) compared the self-management procedures of selfmonitoring, self-evaluation, self-reinforcement and self-instruction in isolation and in combination. Their results indicate that the combination of self-instruction, self-monitoring, self-evaluation and self-reinforcement and the combination of self-monitoring and self-instruction were the most effective. When examining the components in isolation, self-instruction was the most effective whereas selfmonitoring and self-evaluation were the least effective.

With What Behaviors are BSM Techniques Effective? Off/on task behavior and measures of accuracy were used most by researchers as dependent variables to determine the effectiveness of the self-management strategies (see Fig. 2). The PNDs for each of the behaviors examined fell within or very close to the effective range (70–90%) as outlined by Scruggs and Mastropieri (2001). However, there were differences in the effectiveness of BSM among behaviors, F(5, 129) = 4.25, p = 0.001. Further analysis revealed that BSM was more effective at increasing student productivity (M = 94.05, S.D. = 10.01) and

Fig. 2. Percent of Data Series Across Dependent Variables Used in Self-Management Studies.


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other classroom related behaviors (M = 94.35, S.D. = 8.73) (e.g. scores from a checklist, teacher interaction) than affecting on/off task behavior (M = 69.47, S.D. = 31.46; academic productivity d = 1.04, classroom-related behavior d = 1.05) or increasing appropriate behavior (M = 68.00, S.D. = 29.97; academic productivity d = 1.34, classroom-related behavior d = 1.36). In addition to, task and academic skills, a qualitative examination of the studies reviewed indicates BSM techniques may also be effective at reducing self-injurious behavior (Osborne et al., 1986), improving students’ problem solving ability (Shapiro, 1989), and increasing students’ compliance with supervisors’ instructions (Kelly et al., 1983; Warrenfeltz et al., 1981).

With Whom and Where are BSM Techniques Effective? Figure 3 shows the percentage of data series across participant characteristics. Students with LD served as participants most often followed by students with behavior disorders. Most of the students were evaluated in special education settings (see Fig. 4). The quantitative analysis of participant characteristics indicated overall differences among categories, F(3, 131) = 7.86, p = 0.001. Follow-up analyses indicated that BSM techniques were more effective for participants with LD (M = 87.40, S.D. = 20.05, d = 0.81) or combined LD/BD (M = 93.75, S.D. = 17.68, d = 0.90) than for students with a behavior disorder alone (M = 67.40, S.D. = 30.86). No differences in PND were found across intervention settings, F(4, 130) = 1.09, p = 0.364.

Fig. 3. Percent of Data Series Across Student Classifications.

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Fig. 4. Percent of Data Series Across Settings.

Are There Important Procedural Issues for Self-Monitoring? One key aspect of self-monitoring is selecting a behavior to monitor as well as the valence of that behavior. Valence relates to whether the behavior monitored is socially positive or negative. In the studies examined here, students monitored: (a) appropriate only (positive valence); (b) inappropriate only (negative valence); or (c) both appropriate and inappropriate behaviors (neutral valence). Monitoring of only appropriate behavior occurred in 56% of the data series (see Fig. 5). Because there

Fig. 5. Percent of Data Series Across Valence of Self-Monitoring.


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Fig. 6. Percent of Data Series Across Behavioral Focus of Self-Monitoring.

were only 3 data series where participants monitored only negative aspects of their behavior, we dropped the only inappropriate category from the valence analysis. The resulting data suggested that students who monitored both appropriate and inappropriate aspects of their behavior (M = 91.78, S.D. = 13.55, d = 0.52) had better outcomes than students who monitored only positive aspects (M = 80.50, S.D. = 25.31), F(1, 112) = 6.30, p = 0.014. The valence of behavior can be further focused into the monitoring of attention, productivity, adherence to a standard or rule, and/or accuracy (see Fig. 6). Our analysis yielded differences among foci of monitoring, F(2, 132) = 9.98, p = 0.001. Follow-up analyses indicated that participants who monitored productivity (M = 90.16, S.D. = 13.34, d = 1.01) had better outcomes than those who monitored rule adherence (M = 68.23, S.D. = 31.25).

Does BSM Promote Maintenance and Generalization of Behavior Change? Strong interventions withstand the test of time. Their effects maintain even when the external support structure of the intervention has been withdrawn. Maintenance data, collected after formal BSM procedures were discontinued, were collected for 32% of data series. The overall MPND was 75 (S.D. = 30.77), which indicates that BSM procedures produce lasting changes in behavior. The maintenance data were subjected to the same analysis procedures as the intervention data. No significant effects were found for MPND across participants, settings, or procedural variations of BSM.

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In addition to maintenance of behavior changes, the effects of an intervention should be observed across settings, tasks and people. This portability is advantageous in that a student can be taught a BSM strategy in one setting and then apply or generalize the strategy to other settings. Generalization data were only collected for 12% of data series. The overall GPND for generalization was 72 (S.D. = 31.19). Unfortunately, an inferential analysis could not be conducted on the GPND data because of the low number of data series. Across settings was the most commonly reported (n = 9) form of generalization. The majority of these studies (n = 6) reported generalization from a special education to a regular education setting (Hogan & Prater, 1993; Osborne et al., 1986; Prater et al., 1992; Smith et al., 1988; Snyder & Bambara, 1997; Trammel et al., 1994) while the remaining studies (n = 3) reported generalization from one restrictive setting to another (Kelly et al., 1983; Swanson & Scarpati, 1985; Warrenfeltz et al., 1981). Generalization across academic tasks (i.e. reading, math, spelling and/or written expression) was reported in three studies that measured academic accuracy and/or productivity (Carr & Punzo, 1993; Shimabukuro et al., 1999; Swanson & Scarpati, 1985). Only Swanson and Scarpati (1985) explicitly reported generalization data across people. Two studies (Sanders et al., 1991; Shapiro, 1989) taught generic selfmanagement models with the explicit goal for students to use the model to plan and implement their own programs. Neither of these studies, however, measured students’ ability to utilize these models outside of the training sessions. The remaining studies (n = 18) appeared to have made no attempt to encourage students to apply BSM techniques on their own. In fact, in only two additional studies (Falk et al., 1996; Osborne et al., 1986) were students even involved in the initial selection of the target behavior. In the remaining studies (n = 16) teachers and/or the experimenter selected the behavior that was targeted for change.

What are Common Instructional Components used to teach BSM? A PND analysis could not be conducted as most studies provided little information on how students were taught to use BSM procedure(s). A qualitative review indicated that four instructional components, providing a rationale for behavior change, defining the behavior of interests, modeling, and practice, were commonly (n greater than 4) used in the BSM studies reviewed. Prior to beginning the BSM intervention, four studies (Blick & Test, 1987; Lenz et al., 1991; Shimabukuro et al., 1999; Snyder & Bambara, 1997) provided students with, or helped them generate, a rationale of why it would be beneficial to change the behavior of interest. Additionally, five studies (Carr & Punzo, 1993; Hogan & Prater, 1993;


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Prater et al., 1991, 1992; Rooney & Hallahan, 1988) ensured students could define and/or recognize the behavior of interest before beginning the intervention. Modeling/providing examples (n = 14) was the most commonly cited instructional technique followed by student practice (n = 11) to teach students the actual application of the BSM procedure(s). Additionally five studies (Blick & Test, 1987; Hogan & Prater, 1993; Kelly et al., 1983; Prater et al., 1992; Warrenfeltz et al., 1981) did not permit students to begin the intervention portion of the study until they reached performance and/or accuracy criteria during practice sessions.

DISCUSSION Similar to other reviews of BSM (Hughes et al., 1981; McDougall, 1998; Nelson et al., 1991; Reid, 1996), we found that the procedures falling under this approach frequently result in changes in behavior. The overall PND for the 18 studies was 80%, which puts in into the effective category according to Scruggs and Mastropieri (2001). However, we not only wanted to gauge overall effectiveness, we also wanted to examine whether improvements were socially valid. Three of the studies examined social validity in the context of how well study participants, after intervention, exhibited frequency of target behaviors in relation to peers. In a fourth study, target students were assessed as to whether their behavior was indistinguishable from peers according to outside observers. In all studies, average gains reached criterion for social validity. However, the fact that only 20% of the studies investigated social validity is of concern. If some measure of social validity (e.g. comparison with peers) is not taken, it is difficult to assess the functionality or usefulness of the behavior change. What is encouraging is that for these four studies, a number of behaviors were examined (i.e. on task, social interactions, school survival skills, and performance on a problem solving test) and a number of procedures were used (i.e. self-monitoring, self-evaluation, and a combination of approaches). This provides emerging evidence that most of the BSM techniques can have a functional impact on a number of target behaviors, thus increasing the range of applicability of this approach. Our next question, Are different BSM procedures more effective than others? was posed in order to identify interventions and/or intervention components that may have differentially affected behavior. While tentative, results do suggest that multi-component packages are the most effective. What is interesting is that self-monitoring appears to be almost as effective as a BSM packages. In fact, while the PND was higher for multi-treatment packages, there was no statistically significant difference between the PNDs for these approaches. The instructional implication for this finding is that because self-monitoring is simpler, easier and

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less time-consuming to teach than a multi-component package, it may be more parsimonious to use self-monitoring. Why teach three techniques when one is just as good? It should be noted that DiGangi and Maag (1992) found that a combination approach was the most effective in increasing appropriate verbalizations and decreasing inappropriate verbalizations. Additionally, they noted that self-instruction alone was better than self-monitoring. While this is counter to the results discussed above, it may be that the difference is due to the dependent variable(s). That is, if the behavior in question is verbal in nature, it may make sense that a verbal intervention would be a better match. Additionally, since self-instruction is an antecedent, it may be a better fit when thinking about what you are going to say in a social situation rather than self-monitoring, which occurs after the behavior. Another guiding question of this review dealt with the target behaviors used in BSM studies. Analysis of the studies showed that there are indeed a wide variety of behaviors that improved due to this form of intervention. On-task behavior is still the most frequent dependent variable used in BSM studies, but in more recent years, target measures have expanded. While this is encouraging in terms of a wider range of applicability, it should be pointed out that most of the behaviors are relatively discrete, simple behaviors vs. more complex tasks related to problem solving, or strategic learning. This point has been made in other reviews (e.g. Hughes et al., 1989; McDougall, 1998) and is an area that continues to need investigation. Because self-management has been touted as a method that promotes successful inclusion due to its portability and application in general education classrooms (King-Sears & Cummings, 1996; Reid, 1996), we looked at the settings where the studies took place (i.e. where it was taught, and where data were collected). As past reviewers of BSM have noted (e.g. Hughes et al., 1989, 1991; McDougall, 1998), most instruction and data collection takes place in the special education classroom. However, examination of Table 1 does indicate that in the 1990s more researchers began to collect data in general education settings. But, as Hughes et al. (2003) note in their review of interventions used with adolescents with learning disabilities, instruction in BSM procedures (as well as other interventions) most often occurs in a pull out situation and then data are collected in the general education classroom. This is not a shortcoming inherent to BSM but rather may point out that instructionally intensive interventions like BSM, because of time constraints and the instructional activities needed to teach them to mastery, are difficult to implement in the general education classroom. The encouraging news is that efforts are being made to transfer (or at least measure) behavior change into the general education setting. Additionally, for the few studies where instruction did take place in the general education classroom, PNDs were about the same as when BSM was taught in a pull-out setting.


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We also looked at whether disability category had an impact on BSM effectiveness. We found some indication that students with LD benefit more than students with BD. While speculative, this difference may be due to the greater frequency of oppositional behavior of students with BD, as well as documented differences in academic performance and aptitude (e.g. IQ) between these two groups (Ruhl & Berlinghoff, 1992). As mentioned earlier in this chapter, we found a moderate correlation between intelligence and BSM effectiveness. Additionally, problems with both expressive and receptive language often found with students with BD may further hinder student ability to monitor, evaluate and self-instruct (Ruhl et al., 1992). This is not to say that students with BD do not benefit, only that more time and effort may be needed to obtain these benefits. Because self-monitoring is the most frequently researched technique it has been examined the most extensively. In the past authors such as Reid (1996) have investigated issues related to valence as well as whether it is more effective to monitor accuracy of performance or attention/on-task. With regard to valence (i.e. monitoring whether a positive behavior increases or whether a negative behavior decreases), it appears, based on the studies included in this review, it is better to monitor both positive and negative than to monitor positive. It should be noted that in the studies that had students monitor both, the behaviors in question were related; that is, they were incompatible (e.g. two sides to the same coin). For example, students would monitor both appropriate verbalizations and inappropriate verbalizations. Because there were so few studies that looked at negatively valenced target behaviors only, we were unable to include them in the comparison. However, Reid noted that, while tenuous, it appears that monitoring positively valenced behaviors is more effective than monitoring negatively valenced behaviors. The other variable related to self-monitoring was whether it is better to monitor performance or attention. Because many of the earlier self-monitoring studies used attention (e.g. students asked themselves Am I paying attention when cued) as the focus of monitoring as well as a dependent variable, the question was raised as to whether increases in attention actually lead to increased (and accurate) performance. Past reviews (e.g. Reid, 1996) indicated that monitoring performance appears to be more effective in increasing productivity. Our findings offer further confirmation: monitoring productivity yielded significantly better results. However, this finding should be tempered. It is still unclear whether monitoring productivity (or attention for that matter) results in greater accuracy. It has been contended that it does not, given that self-monitoring does not teach the student to perform the skill better, only more frequently (Reid, 1996). Thus, it may be that accuracy will only increase if the student monitors their production of skills/ behaviors at which they are already accurate.

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As mentioned earlier, one of the purported advantages to self-management is its portability and thus it is seen as a tool to help students maintain and generalize their behavior. Almost 15 years ago, Hughes and colleagues (Hughes et al., 1989, 1991) noted that the promise of BSM as a generalization tool had been largely unfulfilled. They found that for the most part BSM studies did not measure or include procedures to promote generalization. This current review shows, at least with studies including adolescents with LD/BD, there has been a small improvement over the years. A third of the series analyzed had maintenance data and indicated that maintenance occurred regardless of factors such as setting, type of BSM procedure, or disability categories. It is difficult to pinpoint why BSM would be so effective in maintaining behavior. Possibly, since the behavior was already in the students’ preintervention repertoire and that BSM increased the occurrence of the behavior, a fluency effect occurred. That is, the more you do something and the more automatic it becomes, the more likely you are to do it again. The picture for other forms of generalization is not as clear. Generalization was assessed in only 12% of the data series. The little data there does indicate a moderate PND. The type of generalization most often measured was across settings. For example, behaviors shaped with BSM in a pull-out setting began to improve in the general education classroom. Generalization across tasks/behaviors and across subjects was virtually ignored. It is important to point out that in most of the studies reporting generalization, there was little planning or promoting of generalization; typically, data were collected but no systematic programming of generalization occurred. Another aspect of generalization we wanted to examine was whether once students were exposed to or were taught how to use BSM procedures, would they begin to use them on their own after training ceased; that is, did they generalize the procedures of BSM? This is a core issue if one assumes that true self-management involves such behaviors as selecting one’s own goal(s), deciding what procedures will help them meet the goal and then monitoring effectiveness. None of the studies clearly measured this. Two studies did attempt to teach these BSM techniques to students. And, while students were able to take over some of these roles, generalization outside the training setting was not measured. Even more discouraging was that, in the majority of studies, students were not even involved with selecting their own goals. Much more work is obviously needed in generalizing target behaviors shaped by BSM procedures as well as BSM techniques themselves. The final question we looked at in this review was What instructional components are used when teaching BSM? Most of the instruction described in the studies could be described as explicit. Students were provided rationales (for monitoring, evaluating), models of target behaviors and how to self-monitor, self-evaluate etc. Following demonstrations or procedures students were then afforded opportunities


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for guided practice. This direct and explicit approach is not surprising given the support for this approach in the literature for adolescents with LD/BD (Deshler & Schumaker, 1993; Ruhl & Berlinghoff, 1992; Swanson & Hoskyn, 1998). Future Directions Based on our review and those written over the past decade and a half, we can say with some confidence that BSM is effective in changing the behaviors of adolescents with LD/BD. And this is true for all procedures falling under the rubric of BSM, for a variety of behaviors, settings and students. However, much more needs to be done before BSM can be recommended as an intervention to promote inclusion or complex behaviors such as strategic learning. Too, we know very little about how (or if) students can be taught to implement BSM by themselves independent of teacher prompts and supports in a setting other than the training environment, thus becoming truly self-regulating. Perhaps intervention approaches that include BSM components in concert with other more encompassing approaches may be one way to approach the issue of ownership and portability. Recently, the concept of self-determination, especially for adolescents and young adults, has been getting increased attention in the special education literature (Wehmeyer et al., 2000). This approach has been described as including not only BSM procedures but focuses on increasing self-awareness (of one’s interests, strengths, weaknesses), self-advocacy, decision-making and goal setting (Algozzine et al., 2001). The goal of self-determination is to promote autonomous behavior that is self-regulated, similar to the stated goals of BSM. When examining the empirical support of this approach with adolescents with LD/BD, we identified three studies (Hoffman & Fiedl, 1995; Powers et al., 2001; Zhang, 2001). These studies examined the effectiveness of self-determination programs using BSM procedures such as goal setting, self-evaluation and self-monitoring. While results were positive, it is interesting to note that the dependent variables were all related to performance on a scale or checklist rather than changes in actual behavior. Thus it seems that while self-determination as an intervention and outcome may hold promise in putting the self in self-management. However, more work needs to be done to link BSM to more global constructs like self-determination.

NOTE 1. Standardized mean differences were calculated using pooled standard deviations of the groups being compared (Olejnik & Algina, 2000). Cohen (1988) suggested the

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following terms for evaluating values of d: Small effect = 0.20, medium effect = 0.50, large effect = 0.80.

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∗ Lenz, B. K., Ehren, B. J., & Smiley, L. R. (1991). A goal attainment approach to improve completion

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Scruggs, T. E., Mastropieri, M. A., & Casto, G. (1987). The quantitative synthesis of single-subject research: Methodology and validation. Remedial and Special Education, 8, 24–33. ∗ Shapiro, E. S. (1989). Teaching self-management skills to learning disabled adolescents. Learning disabilities Quarterly, 12(4), 275–287. ∗ Shimabukuro, S. M., Prater, M. A., Jenkins, A., & Edelen-Smith, P. (1999). The effects of selfmonitoring of academic performance on students with learning disabilities and ADD/ADHD. Education and Treatment of Children, 22(4), 397–414. ∗ Smith, D. J., Young, K. R., West, R. P., Morgan, D. P., & Rhode, G. (1988). Reducing the disruptive behavior of junior high school students: A classroom self-management procedure. Behavioral Disorders, 13(4), 231–239. ∗ Snyder, M. C., & Bambara, L. M. (1997). Teaching secondary students with learning disabilities to self-manage classroom survival skills. Journal of Learning Disabilities, 30(5), 534–543. Swanson, H. L., & Hoskyn, M. (1998). Experimental intervention research on students with learning disabilities: A meta-analysis of treatment outcomes. Review of Educational Research, 68, 277–321. ∗ Swanson, H. L., & Scarpati, S. (1985). Self-instruction training to increase academic performance of educationally handicapped children. Child and Family Behavior Therapy, 6(4), 23–39. ∗ Trammel, D. L., Schloss, P. J., & Alper, S. (1994). Using self-recording, evaluation and graphing to increase completion of homework assignments. Journal of Learning Disabilities, 27(2), 75–81. ∗ Warrenfeltz, R. B., Kelly, W. J., Salzberg, C. L., Beegle, C. P., Levy, S. M., Adams, T. A., & Crouse, T. R. (1981). Social skills training of behaviorally disordered adolescents with self-monitoring to promote generalization to a vocational setting. Behavioral Disorders, 7, 18–27. Wehmeyer, M. L., Palmer, S. B., Agran, M., Mithaug, D. E., & Martin, J. E. (2000). Promoting causal agency: The self-determined learning model of instruction. Exceptional Children, 66, 439–453. Zhang, D. (2001). The effect of Next S.T.E.P. instruction on the self-determination skills of high school students with learning disabilities. Career Development for Exceptional Individuals, 24(2), 121–132.

THE EFFECTS OF SELF-INSTRUCTIONAL STRATEGIES ON PROBLEM SOLVING IN ALGEBRA FOR STUDENTS WITH SPECIAL NEEDS Caroline R. Lang, Margo A. Mastropieri, Thomas E. Scruggs and Miriam Porter ABSTRACT This study was intended to determine the effects of self-instructional training on algebra problem solving performance of students with learning disabilities, students for whom English is a second language and students who were at risk of failing algebra. Four high school algebra classes consisting of 74 students, of whom 17 were classified as having learning disabilities, 37 had English as a second language, and 20 were considered at-risk for math failure, were assigned randomly to either a self-instructional training condition or a traditional instructional condition. All students were administered pretests, immediate posttests, and delayed posttests of algebra problem solving, pre and post strategy usage questionnaires, and attitude measures. After training, results indicated that both groups’ performance increased from pretest to immediate posttest and pretest to delayed posttest, but no statistical difference was found between groups. The self-instruction group significantly outperformed the traditional instruction group on independent strategy use. Significant correlations were obtained between strategy

Research in Secondary Schools Advances in Learning and Behavioral Disabilities, Volume 17, 29–54 © 2004 Published by Elsevier Ltd. ISSN: 0735-004X/doi:10.1016/S0735-004X(04)17002-X

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CAROLINE R. LANG ET AL.

usage and immediate and delayed posttest scores, indicating that students who successfully learned the strategy had better performance on the math problem solving tests. No significant differences were found across groups in attitude change. Future research issues are discussed with respect to strategy instruction for at risk learners. The importance of mathematics is emphasized nationally in Goals 2000 (National Education Goals Panel, 1997) and the Standards of the National Council of Teachers of Mathematics (NCTM, 2000). As the 21st century progresses, higher levels of math skills are necessary to be successful in the work environment. Furthermore, it is important that all students have access to opportunities to learn these conceptual higher-level math skills. With the implementation of federal initiatives such as No Child Left Behind and IDEA 1997, and the states’ implementation of high stakes testing, all students, including students with disabilities and those considered at risk not only are guaranteed access to the general education curriculum but also held to the same levels of standards as their typically achieving peers. The National Council of Teachers of Mathematics (NCTM, 2000) in their most recent reform positions, call for more rigorous math requirements focused on open-ended, constructivist learning approaches, and problem solving. The focus on conceptual understanding is important, but presents many challenges for students with disabilities and those who are at risk for succeeding math. Many such students have documented deficits in math (e.g. Cawley et al., 2001). Such deficits often increase as student enter secondary school and enroll in more conceptually challenging math classes such as algebra. Many students with learning disabilities, students for whom English is a second language and low performers in mathematics have required additional instructional supports in order to become successful in math. NCTM, however, provides little specific guidance for instructing students with such diverse learning needs, especially in high level math classes such as algebra. While there is interest in the development of effective algebra interventions for these at risk high school students, at present only a few efficacy studies exist. Many researchers have discussed the importance of early concept development, computation strategies, problem solving strategies, use of manipulatives, mnemonics, and self-monitoring strategies in learning algebra (e.g. Mastropieri & Scruggs, 2004). Although similar strategies have been applied successfully with the elementary level population, there are few studies that have been geared toward secondary level students and algebra (e.g. Hutchinson, 1993; Maccini & Hughes, 2000; Mastropieri et al., in press). Other researchers have addressed the teaching of algebra by implementing practice activities using peer tutors (e.g. Allsopp, 1997).

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Allsopp (1997) examined the effectiveness of using class wide peer tutoring (CWPT) in heterogeneous middle school math classrooms to teach students in beginning algebra problem-solving skills. Two hundred sixty-two 8th grade students, between the ages of 12 and 15 years were participants in this study; 38% were at risk of math failure. Teachers were given in-service on the algebra problem-solving curriculum and class wide peer tutoring. CWPT procedures consisted of: Peer tutoring social skills; Transition to tutoring pair; Retrieval and return of tutoring materials; Practice in tutoring; Tutee responding behavior; Error correction procedures; and Point assignment procedure. In phase two, students were trained in classroom groups in CWPT procedures 40 minutes each day for four days consecutively. A video was viewed and procedures were explained. Students were divided into groups and role-played. The last day of these phases, researchers observed students to ensure correct procedures were being followed. In phase three, a pretest was given to both conditions. Both groups were then instructed using the same material, Solving Division Equations: An Algebra Program for Teaching Students with Learning Problems, but taught differently. In group A, students worked independently and in group B, students used CWPT to practice skills. In group B, one student in each pair had an answer key. Teachers monitored performance and tutoring behavior. Posttests were given to both groups and one week later a maintenance test was given to show evidence of retention of the material. The results revealed that neither one of the strategies were more effective than the other. In fact, both groups improved significantly from pre to post tests. Teachers noted that in the future, they would use class wide peer tutoring in a more limited fashion (i.e. review lessons). Hutchinson (1993) examined the effects of a two-phase cognitive strategy on algebra problem solving of students with learning disabilities. Twenty adolescents (12 instructed, 8 not instructed) received one to one instruction, in learning assisted classes in mathematics. Procedures were used to teach students to solve three types of word problems: relational, proportional, and two variables (x and y). Over the next four months students in the treatment group received instruction for one 40-minute session on alternating days. The comparison group received their regular math instruction during the four months. The 40-minute sessions consisted of the following: stating the purpose, reviewing progress, assigning five problems for silent and think aloud practice, providing feedback, testing, and reviewing progress and purpose of next session. This instructional cycle

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continued until students received four out of five correct solutions. At the end of four months all students were tested immediately, on application problems, and at a six-week delay interval. In the instructed group, six subjects reached criterion (80%) for all three types of word problems, four subjects met criterion for two types of word problems, and two reached criterion for only one type of word problem. While there was a significant increase between the instructed pretest group and the instructed posttest group, there was no significant increase between the comparison pretest group and the comparison posttest group. It was concluded that the strategy was effective for helping students become problem solvers. Maccini and colleagues (Maccini & Hughes, 2000; Maccini & Ruhl, 2000) completed two studies using the STAR cognitive strategy and a concrete to semiconcrete to abstract teaching sequence with secondary students with learning disabilities (n = 6 and n = 3, respectively) to teach algebra problem solving using single subject design methods. Maccini and Hughes (2000) taught students from one to two months depending on how long it took to obtain 80% accuracy on each assessment. Students were taught using the “Strategic Math Series (STAR),” which consisted of six elements including Search the problem, Translate the problem into words or pictures, Answer the problem, and Review the problem. Upon mastery students were given 10 transfer word problems. Five participants improved in: (a) percent of correct problem representation; (b) percent correct on solution and answer; and (c) percent of strategy usage from baseline to instructional phase. Overall, participants strongly agreed the STAR program helped them to become better problem solvers. In a follow-up study, Maccini and Ruhl (2000) replicated their findings, but only one of the three students demonstrated transfer performance. In the preceding studies, researchers in each study taught high school age students Algebra I using self-instructional strategies in interventions ranging from one week to four months in one to one or small group settings using single subject designs. Both studies emphasized the strategy using students with learning disabilities, but not with students who were low performers in mathematics or students for whom English is a second language. These students do not qualify for special education services but are in need of an intervention to help them be successful in algebra. These students are falling behind in mathematics and there is little or no research that has been done to support possible interventions for them. Since passing algebra has become a requirement for successfully graduating from many high schools, this study addressed one aspect of algebra problem solving for students who have experienced difficulties in mathematics. This study was intended to determine the effects of self-instructional training on the algebra

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problem solving performance of students with learning disabilities, students for whom English is a second language, and students who were at risk of failing algebra. This study replicated and extended both the Hutchinson (1993) and the Maccini and Hughes (2000) and Maccini and Ruhl (2000) studies by implementing self-instructional strategies with students who are at risk for poor performance in mathematics, including students with learning disabilities, students for whom English is a second language, and students who were low performers in math to examine the effects in the areas of academic performance, attitude, strategy usage and retention in problem solving. The following research questions are addressed in this study: Would self-instructional strategy training vs. traditional instruction affect academic performance for students on problem solving in Algebra I on immediate and delayed test performance? Would self-instructional strategy training vs. traditional instruction affect strategy usage for students on problem solving in Algebra I? Would self-instructional strategy training vs. traditional instruction change students’ attitudes towards problem solving in Algebra?

METHOD Design After receiving relevant permissions from the school parents, students, and the institutional Human Subjects Review Board, four classes were matched on achievement level and then randomly assigned to either the self-instruction problem solving condition or the traditional instruction problem-solving condition. Participants School District This study was conducted in a school district located in a large metropolitan area with an approximate enrollment of 11,000 students and 14 schools (12 elementary, 2 middle, 2 secondary). Students from sixty-six countries speaking 45 different languages were represented in the district with the following racial/ethnic groups: African American 46.5%, Asian/Pacific 5.9%, Hispanic 24.7%, Native American 0.2%, and Caucasian 22.6%. Fifty-two percent of the students received free or reduced lunch status.

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Students The final sample included 74 students who were classified as students with learning disabilities (LD), English as a second language (ESL), and low performers (at-risk) in mathematics who were enrolled in four Algebra I classes. Students were selected based on their low scores in Algebra. All students scored 60% or less on a pre-test, which was designed to test the subject’s problem solving ability. There were 45 males and 29 females, including 2 Caucasian students, 28 Hispanic students, 26 African-American students, 1 Pacific Asian student, and 17 students from other ethnic and racial groups. Twenty-five students’ first language was English, 28 were native Spanish speakers, and 21 students spoke other languages such as Amharic, Krio, and Tagalos. Students’ ages in months ranged from 177 to 300 months. Students were enrolled in grades nine through eleven. Thirty-two of 74 students passed a state test, the Literacy Passport Test (mathematics section only, 6th grade level). Twenty-eight students of the remaining 42 were exempt from this test due to ESL status. Seventeen of the students were receiving special education services at the time of the study. Fifty-seven students were considered Table 1. Student Demographic Data By Instructional Condition. Self-Instruction (n = 36)

Traditional Instruction (n = 38)

Total (N = 74)

Gender Male Female

21 15

24 14

45 29

Grade 9 10 11 12

5 25 6 0

3 32 2 1

8 57 8 1

Student classification SLD/LD At-risk ESL

5 10 21

12 10 16

17 20 37

Age (in months) Mean S.D.

207.86 20.44

204.32 11.02

206.04 16.28

Previous math grade 98–99 Mean S.D.

3.08 1.23

2.79 1.21

2.93 1.22

Previous math grade 99–00 Mean S.D.

3.33 1.55

2.79 1.14

3.05 1.37

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at-risk for poor performance in mathematics. This included 37 students who were participating in the ESL program and 20 students classified as general students at-risk for poor performance in mathematics based on previous performance in past years. Demographic data for all students are presented in Table 1. Instructor The instructor and first author was a fully licensed math teacher with several years experience teaching algebra to all types of high school aged students.

MATERIALS Materials for both conditions were based on the Glencoe Algebra 1: Integration, Applications, and Connections textbooks and supplemental materials (Glencoe, 1998). This particular textbook was aligned with the Standards in the state in which the study was conducted and appeared consistent with the National Standards of Mathematics set forth by The National Council of Teachers of Mathematics (NCTM, 2000). The unit on problem solving from the text was selected for this study. Materials for both conditions included: (a) experimenter’s scripts; (b) student folders; (c) supplemental mathematics materials (word problem worksheets); (d) condition-specific materials; and (e) testing materials including questionnaires. Lesson Plans Lesson plans were prepared for daily activities and to standardize presentations across classes and conditions for testing and daily instruction. For example, content on a lesson plan in the traditional condition consisted of: Students take out folders, distribute daily worksheet, instructor models and instructs two or three problems on board, students work individually with assistance from the instructor, instructor reviews problems, folders are collected, and the session concludes. In the self-instruction condition, a daily lesson consisted of: students take out folder and strategy checklist, distribute daily worksheet, instructor models and instructs two or three problems on board, students work individually with assistance from the instructor, instructor reviews problems and strategy steps, folders are collected, and the session ends. Student Folders Folders were prepared for all students in both conditions. Folders for both conditions contained notebook paper, pencils, and daily word problem worksheets.

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The self-instruction condition folders also included self-instruction strategy steps worksheets and strategy checklist worksheets. Supplemental Mathematics Materials Daily worksheets were developed from a sample pool of problems and were identical for both conditions, except that more worksheets were used in the traditional. These problems were taken from the AGS Pre-Algebra textbook (AGS, 1998) and the Glencoe Algebra 1: Integration, Applications, and Connections textbook (Glencoe, 1998). These textbooks were selected due to the large number and variety of word problems contained in each book. A sample worksheet is in Appendix A. Condition-specific materials are now described. Condition-Specific Materials Self-Instruction Condition Materials Two worksheets containing the self-instruction strategy steps were constructed including the self-instruction worksheet and the strategy checklist. The selfinstruction strategy steps were: (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k)

if I use this strategy I will be successful, read the problem, what is known? what is not known? represent the knowns, represent the unknowns, do I need more than one equation? what is the equation? substitute the knowns into the equation, solve the equation, and have I checked my answer?

The self-instruction worksheet included the steps and provided space for every step while solving word problems. The self-instruction checklist required students to write out the steps on their own paper and then check off steps as they completed them. A sample checklist is in Appendix B. Traditional Instruction Condition Materials The traditional instruction condition did not receive the self-instruction worksheets. Supplemental practice worksheets containing additional practice problems were developed for this condition, such that students actually received more

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practice problems than students in the self-instruction condition. Instructional procedures for problem solving were derived from the teacher’s guide materials that accompanied the textbooks and the algebra teacher’s experience on best instructional practices for teaching these types of problems. Testing Materials and Questionnaires Pre and post tests were developed that contained 10 word problems consisting of 5 one-step word problems, 4 two-step word problems and 1 three (or more)-step word problem. Computations included all four basic functions: multiplication, division, addition, and subtraction. The following is a sample problem: “Suppose you are traveling in a car at a constant speed of 75 km per hr for 1 21 hr. How far will you travel?” Pre and post strategy usage and attitude questionnaires were developed based on modifications of surveys from previous research (Shiah et al., 1995). The pre-experiment questionnaires included students’ attitudes towards mathematics, students’ attitudes towards problem solving, and strategy usage for solving mathematics word problems. For example all students across both conditions had to respond to (on the pre-attitudinal questionnaire), “Word problems are difficult to solve,” by circling a smiling face (agree), straight face (neutral), or sad face (disagree). The pre-strategy questionnaire consisted of one question across both conditions, “What do you do when you solve word problems?” This was an open response question, where students answered individually. The post-experiment questionnaires included students’ attitudes towards mathematics, students’ attitudes towards problem solving, strategy usage for solving mathematics word problems, and condition-specific strategy steps recall. On the post-attitudinal questionnaire, the traditional instruction condition answered the same questions from the preattitudinal questionnaire. The self-instruction condition answered condition specific questions. For example the self-instruction students were asked, “Verbal skills made learning solving word problems easier.” Across both conditions, the poststrategy questionnaire included the same question as the pre-strategy questionnaire with two additions: (a) what did you like most about the algebra instruction you had? and (b) what did you like least about the algebra instruction you had?

PROCEDURES Both Conditions The same instructor taught all classes and conditions. She introduced the purpose of the research. Students were told that the instructor was interested in knowing

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how to help students learn how to solve algebra word problems better. Students were also told that they would be taught some effective ways to learn and remember algebra problem solving techniques. Prior to the beginning of the training, a pretest, attitudinal questionnaire, and a strategy usage questionnaire were administered to all students. Following this phase, condition-specific daily instruction took place over approximately a 2-week period. Daily instruction followed the format of providing daily review, teacher presentation, and guided and independent practice throughout the unit. Immediately following the instruction, an immediate posttest and a condition specific post strategy and attitudinal questionnaires were administered to all students. Following a period of 2 weeks, a delayed post-test was administered. During post testing no time limits were imposed, only pronunciation questions were answered, and no assistance in the solving the problems was provided. Condition-specific procedures are now described.

Self-Instruction Condition During the first session self-instructional strategies were introduced. Students were provided folders, and asked to place their names on the folders. After explaining the contents in the folder, the instructor presented the new strategy. A few word problems were modeled using the self-instruction strategy steps. The following was an example of an entire word problem using the self-instruction strategy steps: Today I am going to show you a new way to solve word problems. I have a new strategy that I think will be helpful. Watch as I go through an example. First we will say before every problem, “If I use this strategy, I will be successful.” Now let’s read the problem. Notice our first step says read the problem (see chart on overhead with the steps). I will read the problem aloud to the class Problem No. 1 – Suppose you are traveling in a car at a constant speed of 75 km per hr for 1 21 hr. How far will you travel? Now the second step is to say aloud and decide: What do we know? (Point to step on overhead) Well we know the constant speed (rate at which we traveled) is 75 km per hr and we traveled 1 21 hr (time). Now the third step is to say aloud and decide: What don’t we know? (Point to step on overhead). We don’t know how far we traveled (the distance) in that 1 21 hr. Next in step four we say aloud and decide: How can we represent the unknowns? Since we want to know the distance we traveled in 1 21 hr., we can represent the unknown with d = distance. In the fifth step, we say aloud and decide: How can we represent the knowns? Well 75 km represents the rate = r and 1 21 hr represents the time we traveled – t. The sixth step is probably going to be the hardest step and we say aloud and decide: Do we need more than one equation? This question is really determined by the question: How can we represent the unknowns? The number of unknowns determines whether we need more than one equation(s). How many unknowns do we have in this problem? Only one (d = distance) This means the answer to the first question is “no”. Now since we know we only need one equation, we say and decide what is the equation? We are looking for the distance. If you

39 recall, distance equals rate multiplied by time. Therefore, our equation is d = (r)(t.) We are almost done. We must say aloud: Substitute the knowns into the equation(s). We replace r with 75 and t with 1 21 . d = (75)(1 21 ). We must now say aloud, solve the equation. In order to solve this, we must multiply 75 and 1 21 . When we do this we find that d = 112 21 km. In seven steps we have found the answer to our problem: You will travel 112 21 km in 1 21 hr at a rate of 75 km. Last step we must say aloud, have I checked my answer? In this step, you must ensure that you have done the correct computations, you back through each step. Once this is done you are finished.

After reviewing several examples, students were coached and guided through three additional problems while using their self-instruction worksheets. Feedback was provided as necessary. Before the ends of the session strategy steps were reviewed and folders were collected. During days two through five of instruction, folders and new worksheets were distributed, followed by daily review, modeling of word problem solving using the self-instruction strategy steps by the instructor. Students were instructed to try problems independently after two modeled examples using a practice problem and strategy worksheets. Individual questions were answered. Worksheets were reviewed and students were asked to write down as many strategy steps as they could remember and feedback was provided. During days six through nine of instruction, procedures were similar with the exception of the substitution of the self-instruction checklist for the self-instruction worksheet. Students were guided through practice word problems. Strategy step review continued and by day seven all students had learned the strategy steps.

Traditional Instruction Condition Day One During the first session, students were taught using traditional methods of teaching algebra problem solving skills. Folders were distributed and the method of instruction was introduced to students. The instructor provided instruction for solving word problems then modeled additional word problem examples. The following problem was an example of a word problem using traditional instruction: To solve word problems we look for statements to make equal quantities. Then we use equal signs and algebraic phrases to write an equation showing this equality. I will show you an example of what I mean by the above statement. Problem No. 1 – Suppose you are traveling in a car at a constant speed of 75 km per hr for 1 21 hr. How far will you travel? We are looking for a number, so we would call it our unknown (“x”). What is our unknown? Since we know we are looking for distance, we want to find a formula that will allow us to find the distance. The distance formula is d = (r)(t) (r = rate, t = time). We know now we are looking for the distance, so let’s go back and look in the problem to see if we can find the rate and time. Going

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CAROLINE R. LANG ET AL. back we see that there is a constant speed of 75 km per hr (rate) and a total of 1 21 hr (time). We now have enough information to fill in our equation. d = (75)(1 21 ), d = 112 21 km. We now have found how far we would travel going at that speed and amount of time.

After modeling several examples the instructor coached and guided students through three problems. Problems were reviewed, folders were collected, and the training session concluded. During subsequent days, traditional instruction consisted of daily review, teacher presentation, and guided and independent practice. Folders practice worksheets were distributed and the instructor modeled several problems. Students then worked individually on completing the worksheets. Questions were answered and feedback was provided as necessary. Worksheets were reviewed as a class and folders were collected at the end of the session. Fidelity of Implementation Since the researcher of this study was also the instructor for the training of the students, all sessions were audiotaped to ensure fidelity of treatment implementation. A graduate student, who determined whether instructional procedures were followed, reviewed a sample of audiotapes and noted no deviations from instructional procedures.

SCORING Rubrics were developed to score the testing materials, strategy usage questionnaires (pre and post), and an attitudinal questionnaires (pre and post); descriptions follow next. Testing Material The pretest, immediate posttest, and delayed posttest contained 10 problems worth 10 points each (maximum score 100 points). For correct computation, but incorrect solution, students were given five points. For correct computation and a correct solution, students were given full credit (10 points). For example, students were asked: “Suppose your first three scores in a mathematics class are 87, 92, and 81. Write an expression. Evaluate the expression.” If the student wrote the expression correctly, but did not get the correct solution then the student received five points. If the student had the correct expression and the correct answer then the student received 10 points (full credit).

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Attitudinal Questionnaire The pre-attitudinal questionnaire contained likert-type items in which students had to select a smiling face, a neutral face, or a sad face, the smiling faces represented agreement with the items; the neutral faces represented neutral answers; while the sad faces represented disagreement with the items. For positively worded items, a score of “three” was assigned to a smiling face, “two” to a neutral face, and “one” to a sad face (e.g. item numbers one, three, and seven). For negatively worded statements a score of “one” was assigned a smiling face, a “two” to a neutral face, and a “three” to a sad face (e.g. item numbers two, four, five, and six).

Strategy Usage Questionnaire For open-ended items, responses were grouped by similarity of response categories. These items included expectations of grades, previous grades, strategy usage, and likes/dislikes of intervention. Scoring criteria for question one on the pre and post-strategy usage questionnaire was: (a) 1 = no solution to solve word problems; (b) 2 = a one step answer to solve word problems; (c) 3 = combination of two steps to solve word problems; (d) 4 = three steps to solve word problems; (e) 5 = four to five steps to solve word problems; and (f) 6 = use of all strategy steps to solve word problems. Questions two and three on the post-strategy usage questionnaire consisted of answers, which were placed, in hierarchy order of importance. Tell me what you do when you solve word problems (Pre-Strategy Usage): 0 = Nothing, Answer not clear; 1 = (One of the following individual answers); Think about it, Check mistakes, Solve the problem, Use calculator, Read it, Try to understand it, Do the best I can, Guess, Ask teacher; 2 = (One of the following combination answers) Read and solve it, Read and look for keywords, Read and understand; 3 = Read it (more than once), ask self what to do, look at numbers, find operation; 4 = read problem; look for keywords to tell how to solve problem. If I don’t understand I re-read the problem; 5 = Strategy Steps/Self-questions/Checklist taught during instruction.

Reliability of Scoring A trained researcher scored all protocols. In addition, a trained graduate student, who was unaware of experimental conditions, scored 10% of all tests. One hundred percent agreement of scoring was obtained between the two scorers.

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RESULTS Results are presented first for the problem solving measures, followed by the strategy and attitudinal measures.

Problem-Solving Results Descriptive information for all academic performance measures across both conditions is presented in Table 2. On the pretest, the self-instruction condition scored a mean of 9.72 (S.D. = 12.01), and the traditional instruction condition scored a mean of 10.92 (S.D. = 11.67). On the immediate posttest both conditions increased significantly, with the self-instruction condition obtaining a mean score of 23.89 (S.D. = 17.97) and traditional instruction condition obtained a mean score of 25.92 (S.D. = 20.98). On the delayed posttest both conditions increased significantly from pretests with the self-instruction condition obtaining a mean score of 28.89 (S.D. = 24.35) and traditional instruction condition obtained a mean score of 29.21 (S.D. = 22.94). These data were entered into a two (instructional condition) by three (time factor) analysis of variance (ANOVA), with repeated measures on the time variable that included the pretest, immediate posttest, and delayed posttest scores. The analysis yielded a statistically significant effect for the time variable, F(2, 71) = 37.878, p = 0.000. A statistically significant effect was not observed for the condition variable F(1, 72) = 0.109, p = 0.743, or for the time by condition interaction, F(2, 71) = 0.077, p = 0.926. Follow up tests on the time variable yielded a statistically significant effect on the pretest vs. the immediate posttest, F(1, 72) = 57.844, p = 0.000 and the pretest vs. the delayed posttest, F(1, 72) = 57.301, p = 0.000. However, a statistically significant effect was not observed on the immediate posttest vs. delayed posttest, F(1, 72) = 3.392, p = 0.070. Table 2. Mean Performance on Problem-Solving Tests.

Pretest M Immediate M posttest Delayed M posttest

Self-Instruction (n = 36)


Total (n = 74)

9.72 (12.01) 23.89 (17.97) 28.89 (24.35)

10.92 (11.67) 25.92 (20.98) 29.21 (22.94)

10.33 (11.77) 24.93 (19.47) 29.05 (23.48)

Note: Values enclosed in parentheses represent standard deviations.

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Table 3. Mean Performance on Problem Solving Tests by Student Classification.

Pretest (ESL) M Pretest (LD) M Pretest (at-risk) M Immediate M posttest (ESL) Immediate M posttest (LD) Immediate M posttest (at-risk) Delayed M posttest (ESL) Delayed M posttest (LD) Delayed M posttest (at-risk)



Total (n = 74)

13.57 (13.61) 5.00 (7.07) 4.00 (6.58) 29.29 (18.66) 13.00 (13.96) 18.00 (14.94) 32.38 (24.48) 18.00 (14.83) 27.00 (27.91)

10.63 (10.31) 5.83 (7.01) 17.50 (15.50) 26.56 (17.10) 14.58 (11.17) 38.50 (28.68) 24.38 (18.96) 25.83 (19.29) 41.00 (29.98)

12.10 (11.96) 5.42 (7.04) 10.75 (11.04) 27.93 (17.88) 13.79 (12.57) 28.25 (21.81) 28.38 (21.72) 21.92 (17.06) 34.00 (28.95)


Population Differences Results Findings were analyzed across the three types of students who were participants, including LD, ESL, and at-risk. Descriptive data for students by special education classification are in Table 3. Problem-solving data were entered into a two (instructional condition) by three (special education classification) by three (time factors) analysis of variance (ANOVA), with repeated measures on the time variable that included the pretest, immediate posttest, and delayed posttest scores. A statistically significant two-way interaction was not observed for time by condition for students with learning disabilities, F(1, 15) = 0.495, p = 0.492, ESL students, F(1, 35) = 0.903, p = 0.348, or at-risk students, F(1, 18) = 3.822, p = 0.066.

Strategy Results Tables 4 and 5 contain descriptive information for all strategy measures across both conditions. On the pre-strategy usage questionnaire, the self-instruction condition scored a mean of 1.50 (S.D. = 1.00), and the traditional instruction condition scored a mean of 1.55 (S.D. = 1.16). On the post-strategy questionnaire the students in the self-instruction condition increased their mean scores to 3.11(S.D. = 1.98), students in traditional instruction condition mean score decreased to 1.29 (S.D. = 0.96). Overall, 67% of the students in the self-instruction condition used the strategy during the immediate posttest and 53% on the delayed posttest. Non parametric Mann-Whitney U tests were conducted to determine whether differences between experimental conditions on strategy use were

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Table 4. Percentages for Pre- and Post-Strategy Usage Questionnaire Item One. Self-Instruction (%)

Traditional Instruction (%)

Pre-strategy Did nothing One step Two step Three step Four step All strategy steps

11.1 (n = 4) 50 (n = 18) 19.4 (n = 7) 16.7 (n = 6) 2.8 (n = 1) 0

21.1 (n = 8) 31.6 (n = 12) 21.1 (n = 8) 23.7 (n = 9) 2.6 (n = 1) 0

Post-strategy Did nothing One step Two step Three step Four step All strategy steps

8.3 (n = 3) 22.2 (n = 8) 19.4 (n = 7) 0 0 50 (n = 18)

21.1 (n = 8) 39.5 (n = 15) 31.6 (n = 12) 5.3 (n = 2) 2.6 (n = 1) 0

statistically significant. It was observed that students in the two conditions did not differ at pretest, z = −0.175, p = 0.861; however, the two conditions did differ significantly at posttest, z = 3.79, p = 0.000. On the post-strategy usage questionnaire (item two) students in the selfinstruction condition achieved a mean score of 2.69 (S.D. = 1.82) while the students in the traditional instruction condition had a mean score of 1.84 (S.D. = 1.39). On item three, students in the self-instruction condition, achieved a mean score of 3.31 (S.D. = 1.92) while students in the traditional instruction condition had a mean score of 2.53 (S.D. = 1.96). Total strategy scores were computed for items one through three and these scores were compared across the two treatment conditions. A statistically significant difference was observed, t(72) = 4.27, p = 0.000, with the self-instruction condition significantly outperforming the traditional instruction condition. Table 5. Mean Performance on Strategy Questionnaire. Strategy Usage Questionnaire

Pre-strategy (item one) M Post-strategy(item one) M Post-strategy(item two) M Post-strategy(item three) M



Total (n = 74)

1.50 (1.00) 3.11 (1.98) 2.69 (1.82) 3.31 (1.92)

1.55 (1.16) 1.29 (0.96) 1.84 (1.39) 2.53 (1.96)

1.53 (1.08) 2.18 (1.79) 2.26 (1.66) 2.91 (1.97)


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Table 6. Mean Performance Scores of Pre-Attitudinal Questionnaire. Pre-Attitudinal Questionnaire Item #1 M Item #2 M Item #3 M Item #4 M Item #5 M Item #6 M Item #7 M



Total (n = 74)

2.17 (0.65) 2.22 (0.76) 1.83 (0.88) 1.86 (0.72) 2.06 (0.79) 1.92 (0.60) 2.39 (0.64)

2.13 (0.47) 2.00 (0.70) 2.16 (0.75) 2.21 (0.70) 2.21 (0.84) 2.05 (0.77) 2.29 (0.80)

2.15 (0.57) 2.11 (0.73) 2.00 (0.83) 2.04 (0.73) 2.14 (0.82) 1.99 (0.69) 2.34 (0.73)


Correlational analyses were completed between strategy usage and performance on the immediate and delayed recall tests to determine whether students who learned and used the strategy were more successful on solving algebra problem solving. On the immediate posttest Spearman’s rho yielded statistically significant correlations r = 0.388, p = 0.019. Likewise on the delayed posttest Spearman’s rho yielded statistically significant correlations r = 0.561, p = 0.000.

Attitudinal Results Due to the item differences in the post-attitudinal questionnaire between conditions only four items from the pre-attitudinal and post-attitudinal questionnaire could be compared across both conditions (items one, two, six, and seven). Tables 6 and 7 contain descriptive information for all measures across both conditions (pre- and post-attitudinal questionnaire). On the pre-attitudinal questionnaire (items one, two Table 7. Mean Performance Scores of Post-Attitudinal Questionnaire. Post-Attitudinal Questionnaire Item 1 M Item 2 M Item #3 M Item #4 M Item #5 M Item 6 M Item 7 M



Total (n = 74)

2.00 (0.71) 2.22 (0.68) N/A N/A N/A 2.08 (0.73) 2.61 (0.69)

2.17 (0.72) 2.16 (0.72) 1.84 (0.72) 2.24 (0.71) 2.32 (0.74) 2.13 (0.62) 2.24 (0.63)

2.09 (0.72) 2.19 (0.70) 1.84 (0.72) 2.24 (0.71) 2.32 (0.74) 2.11 (0.68) 2.43 (0.66)


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six and seven, the self-instruction condition scored a mean of 8.69 (S.D. = 1.60), and the traditional instruction condition scored a mean of 8.47 (S.D. = 1.89). On the post-attitudinal questionnaire the self-instruction condition obtained a mean score of 9.22 (S.D. = 1.73) and traditional instruction condition obtained a mean score of 8.66 (S.D. = 1.38). These scores did not differ statistically, F(1,72) = 2.425, p = 0.124. Items three, four, and five were compared from both pre- and post-attitudinal questionnaires within the traditional condition. On the pre-attitudinal questionnaire the traditional condition scored a mean of 6.58 (S.D. = 1.50) and on the post-attitudinal questionnaire 6.39 (S.D. = 1.53). When students in the self-instruction condition were asked if using checklist and verbal skills help them to solve word problems better the following results were found: On a scale from one to three (three being the highest), students scored a mean of 2.58 (S.D. = 0.60) on item three (“I like using verbal skills to learn how to problem solve in Algebra I”), 2.72 (S.D. = 0.57) on item four (“I like using checklists to learn Algebra I topics”), 2.72 (S.D. = 0.45) on item five (“Verbal skills made learning solving word problems easier”), and 2.64 (S.D. = 0.68) on item six (“Checklists made learning solving word problems easier”). In total, this condition scored a mean of 10.67 (S.D. = 1.55) on these four items.

DISCUSSION Findings from this study comparing the difference between self-instruction training in algebra for high school students who were at risk of failing indicate that both instructional treatments produced significant increases in learning form pretest to posttest which also maintained over a delayed recall interval. Although, both conditions made improvement from pretest to immediate posttest, and immediate posttest to delayed posttest, no statistically significant differences were obtained across conditions. However, statistical improvement from pretest to immediate posttest and immediate posttest to delayed posttest for each condition were evident. The results revealed that neither one of the strategies were more effective than the other. In fact, both were effective for helping students to learn problem solving. There are several possible explanations for this outcome. In past studies where statistical significance was found (Hutchinson, 1993; Maccini & Hughes, 2000) there were many differences found in procedure and methods from this study. It is necessary to review those two studies previously discussed in chapter two, to justify the results found in this study. Recalling Hutchinson’s study (1993), participants received individual instruction on alternating days in 40-minute sessions for four months. This approximately works

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out to 40 forty-minute sessions of instruction. There were two groups, instructed and comparison, with 12 and 8 students respectively. Prior to the intervention, a pretest consisting of ten problems was given to each student; this score was used as a baseline for comparison. Instructed subjects received strategy instruction in algebra problem solving individually in learning disabilities resource setting during regular school hours. This training consisted of: (a) Instructor state purpose of session/show progress graph; (b) Instructor assigns five problems and prompt card for self-questioning; (c) Student reads questions/student reads problem silently/student thinks aloud for problems one and two; (d) Instructor provides prompt feedback for problems three and four/instructor provides feedback after student completes problem five/instructor fades out verbal response; (e) Instructor tests student; and (f) Instructor shows progress graph/discusses purpose of next session. This cycle would continue until the student received four out of five correct solutions. The comparison group received their regular instruction in their resource class during this time. In fact, it appears that the comparison group obtained no instruction related to the intervention given to the instructed subjects. Immediately, at the end of four months all students were tested. After the posttest, students were given application problems (transfer of knowledge) in which they also had to receive four out of five correct. Six weeks later students were tested again to see if this strategy helped them to maintain the information over a length of time. Hutchinson’s (1993) findings appear to be based on a significant training amount of one to one instruction over four months compared to no instruction for the comparison group. Possibly these findings could be attributed to time on task. In Maccini and Hughes’ (2000) study, six students with learning disabilities participated in a single subject research design. Students received training from 40 minutes every day for one to two months depending on how long it took them to obtain 80% accuracy on each assessment. All students had to score below 80% to begin the training. The first set of students were trained and the treatment was then applied to the remaining students after the first set of students received a 80% or higher score on the first assessment. Students were taught using the “Strategic Math Series (STAR),” which consisted of six elements: (1) Provide advance organizer (identify new skills an give rationale for teaching it); (2) Describe/model think aloud protocols: (a) Search the word problem (read the problem, ask what facts are known and unknown, and write down the facts); (b) Translate the words into an equation in picture form (choose a variable, identify the operation, represent the problem, draw a picture, and write an algebraic equation); (c) Answer the problem; and (d) Review the solution (reread the problem, ask the question, “does the answer make sense and why?” and check answer);

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(3) (4) (5) (6)


Conduct guided practice; Conduct independent practice; Give posttest; and Provide feedback (positive and corrective).

Upon mastery, students were given 10 transfer word problems. Five of six participants improved in: (a) percent of correct problem representation; (b) percent correct on solution and answer; and (c) percent of strategy usage from baseline to instructional phase. The sixth student was frequently absent, therefore could not complete many of the objectives. The participants improved percent of accuracy on problem representation from baseline to maintenance. Maccini and Hughes (2000) found that students with learning disabilities after one to one intensive instruction learned to solve algebra problems, compared to students with learning disabilities who had no instruction. To compare, this present study had a much larger more diverse population (n = 74) than the preceding studies. The population consisted of students with learning disabilities, at-risk for poor performance in mathematics, and ESL students. Those previous studies only included students with learning disabilities. This study also had classroom sizes of 13, 18, 20, and 23 participants, much larger than the two preceding studies. Also in this study, students were not taught on an individual basis, but in a regular classroom setting. In addition, both groups in this study were instructed, but taught differently whereas in Hutchinson’s (1993) study only one group was instructed. The intervention time in this study was only four weeks consisting of 45 minutes of training for eight consecutive days, whereas Hutchinson’s (1993) training consisted of 40 minutes every other day for four months and Maccini and Hughes’ (2000) training consisted of 40 minutes every day for one or two months depending on the individual subject. In this study no significance was found when comparing performance of conditions with each other. Whereas, in Hutchinson’s (1993) and Maccini and Hughes’ (2000) studies, significant results were found. Given this, possibly a smaller number of participants or one to one instruction paired with longer intervention time were key to teaching self-instructional strategies and finding statistically significant results between conditions. In a prior study conducted by Allsopp (1997), 262 eighth grade students, between the ages of 12 and 15 years were participants in this study; 38% were at risk of math failure. A pretest was given to both conditions. Students were trained in classroom groups in CWPT procedures 40 minutes each day for four days consecutively. Both groups were instructed using the same material, but taught differently. A posttest was given and one week later a delayed posttest was

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given. No significant difference was found from pretest to immediate posttest, and immediate posttest to delayed posttest. There are many similarities in Allsopp’s (1997) study and this study. In both studies both groups were instructed, but taught differently. In addition, students were not taught with one to one instruction but in regular classrooms. Intervention times were relatively similar with 8 days vs. 17 days on training and a one-week wait for the delayed posttest (Allsopp, 1997) vs. a two-week wait for delayed posttest in this study. Both conditions in each study made improvement from pretest to immediate posttest and immediate posttest to delayed posttest. Though these studies showed no statistical significance between conditions, the findings are ecologically valid. The reality of the secondary school curriculum encompasses many content areas. With the increased importance and emphasis on standards in each state, teachers are mandated to cover many topics in a school year. Therefore, they cannot spend a huge amount of time working on one skill. In addition, teachers whom are teaching these students do not have the capabilities to teach one on one when most classroom sizes consist of 25 students to 1 teacher per classroom. Several key factors appear to contribute to the lack of findings in this present study. First, students taught in one to one situations may learn more than students who are not taught in one to one situations. Second, interventions of longer duration and intensity may yield more powerful results. Third, students who receive such intensive one to one instruction are likely to perform better than students who receive no training. Fourth, 42 students had not passed the Literacy Passport Test (mathematics section only) at the time of training. This included 28 students who were exempt from taking the test due to ESL status. This test assessed students on a sixth grade level of mathematics. Therefore when the study began many of the students were not equipped with basic skills in mathematics at the outset of the study. Fifth, a large part of the sample population was comprised of ESL students. These students had difficulty in learning and applying the material due to language barriers. It is important to realize that ESL students are a fast growing population in the school system. The facts show that Hispanics are the fastest growing minority in the U.S. According to Ovando and Collier (1998) and based upon census figures, language minority groups, particularly Hispanic/Americans (growth rate, 53%) grew faster than white populations between 1980 and 1990. The changing demographics in U.S. public schools requires that all educators become aware of the development of literacy skills among all segments of the school age population. Literacy is key in learning mathematics. In addition, appropriate and timely literacy development is essential for all children. The

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bar of what is considered functional literacy has been raised, and the current expectation is that literacy skills should be universal (Snow et al., 1998). Sixth, the students in the self-instruction condition were required to complete 11 steps (strategy steps) for each word problem. The number of steps for the traditional instruction varied, in fact there was never an exact number required. This resulted in the self-instruction condition only completing an average of 7 out of 10 problems on the daily worksheet, whereas the traditional instruction condition completed each daily worksheet. This may have placed the self-instruction condition at a disadvantage based on the number of problems completed during the eight training sessions. They completed a total of approximately 56 problems, while the traditional instruction group completed 80 problems. Therefore, giving the traditional condition more practice with 24 more word problems. Finally, the two conditions did not test at the same level on the pretest. The performance of the traditional instruction condition was higher than the performance of the self-instruction condition. Since the students were chosen at random and the conditions were randomly picked there was not evidence that this would occur before the study began. It was also difficult to analyze statistical differences among conditions when the numbers were not evenly distributed in terms of special education classification. In the self-instruction condition there were only five students with learning disabilities whereas there were 12 students with leaning disabilities in the traditional instruction condition. Also in the self-instruction condition there were 31 students and in the traditional instruction condition there were 26 students. Students with learning disabilities in both conditions performed significantly lower on the pretest and made less gains than the students who were at-risk for poor performance in mathematics across both conditions. Overall, it seems that additional training time, smaller groups, and more balanced groups in terms of special education classification may have resulted in findings that differ from those reported here. Further research could help determine the most effective means of teaching word problem solving to students with learning disabilities and students who are at-risk for poor performance in mathematics. Further research is also necessary to verify whether these interpretations are valid.

Strategy Usage Effects While the traditional group strategy usage dropped from pre- to post-strategy usage, statistical data showed that the self-instruction condition improved significantly

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from pre- to post-strategy usage. Over the course of the two-week intervention, participants in the self-instruction condition mastered the strategy steps within three to four days of the beginning of the training. This suggests that the steps were easy to learn and the students had no trouble committing them to memory in a short period of time.

Relationship Between Training and Strategy Effects A significant correlation relationship between strategy usage and immediate and delayed posttest for the self-instruction condition was found. This means that the students who learned and applied the strategy performed better on solving algebra word problems on both posttests. This indicates that the strategy instruction was successful for some students. It may be that more time in learning the strategy would have resulted in more students learning and applying the strategy on algebra word problems. This finding was very encouraging and indicated that a streamlined strategy for solving algebra word problems has promise. Furthermore, analyses of student protocols indicated that approximately 50% of the students learned the strategy by the end of training. This means that at least half of the students actually learned the strategy and the other half may have known it, but did not transfer that knowledge on to the tests. This could also mean the length of training time was ample for some students and insufficient for others. This finding reinforces that some students needed a longer intervention time and also additional practice problems applying the strategy.

Attitudinal Effects No major differences were noted when comparing the student’s pre- and postattitudinal questionnaire responses. In the traditional group there was absolutely no numerical change in attitudes towards problem solving. When comparing partial items from the pre- and post-attitudinal questionnaire (items one, two, six and seven), the self-instruction condition’s attitudes improved more than the traditional instruction condition, but not statistically significant. On the post-attitudinal for the self-instruction condition, 89% of the students liked using verbal skills and checklist to solve word problems and stated the verbal skills and checklist made it easier to learn how to solve word problems. Perhaps due to a limited intervention time, changes in attitudes could not occur in such a short period of time.

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CONCLUSIONS Educators continue to search for effective methods to educate all students and maintain high standards. The present and future standards that these students are being held accountable for will never be accomplished without instruction that is tailored to meet their individual learning styles. The diverse learning needs of all students must be addressed when creating these standards, curriculum development, and in teacher preparation of lesson plans. Self-instructional strategies may have potential to help students to problem solve in mathematics. Based on this, it is quite adequate in the researcher’s opinion that further research be conducted on problem solving, taking into account the value of time, strategy usage, and attitudes towards mathematics. The untapped potential for students with learning disabilities, ESL students, and students who are at-risk for poor performance in mathematics to learn problem solving in Algebra I must be opened and investigated.

REFERENCES Allsopp, D. (1997). Using class wide peer tutoring to teach beginning heterogeneous classrooms. Remedial and Special Education, 18, 367–379. Cawley, J., Palmer, R., Foley, T. E., Salmon, S., & Roy, S. (2001). Arithmetic performance of students: Implications for standards and programming. Exceptional Children, 67, 311–328. Hutchinson, N. L. (1993). Effects of cognitive strategy instruction on algebra problem solving of adolescents with learning disabilities. Learning Disability Quarterly, 16, 34–63. Maccini, P., & Hughes, C. (2000). Effects of a problem-solving strategy on the introductory algebra performance of secondary students with learning disabilities. Learning Disabilities Research and Practice, 15, 10–21. Maccini, P., & Ruhl, K. L. (2000). Effects of a graduated instructional sequence on the algebraic subtraction of integers by secondary students with learning disabilities. Education and Treatment of Children, 23, 465–470. Mastropieri, M. A., & Scruggs, T. E. (2004). The inclusive classroom: Strategies for effective instruction (2nd ed.). Columbus, OH: Prentice-Hall. Mastropieri, M. A., Scruggs, T. E., Davis, T., & Ritu, R. (in press). Instructional interventions in mathematics for students with learning disabilities. In: B. Y. L. Wong (Ed.), Learning About Learning Disabilities (3rd ed.). San Diego: Academic Press. National Council of Teachers of Mathematics (2000). Principles and standards for school mathematics. Reston, VA: Author. National Education Goals Panel (1997). National education goals report summary, 1997. Washington, DC: Author. Shiah, R. L., Mastropieri, M. A., Scruggs, T. E., & Fulk, B. J. M. (1995). The effects of computer assisted instruction on the mathematical problem solving of students with learning disabilities. Exceptionality, 5, 131–161.

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APPENDIX A Word Problems Worksheet (E) Class: Name: Directions: Answer each question to the best of your ability. Use your checklist and script for each problem. If you need assistance please raise your hand. Do not work with any other student. Problem No. 1 Suppose you are traveling in a car at a constant speed of 75 km per hr for 11 /2 hr. How far will you travel? Answer: Problem No. 2 Find the perimeter of a rectangular field 103 ft long and 210 ft wide. Answer: Problem No. 3 Suppose your first three test scores in a math class are 87, 92, and 81. Write an expression that represents your average scores. Evaluate the expression. Answer: Problem No. 4 A windbreaker regularly sells for $32. You save $8 during a sale. What is the percent discount? Answer: Problem No. 5 What is the area of a circle with a radius of 6 cm? Answer:

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APPENDIX B Self-Instruction Checklist

VALUE ADDED OF THE SPECIAL EDUCATION TEACHER IN SECONDARY SCHOOL CO-TAUGHT CLASSES Naomi Zigmond and David W. Matta ABSTRACT This naturalistic observation study sought to identify the activities undertaken by the special education co-teacher in co-taught high school content subject classes in urban, rural, and suburban high schools, and to understand the contributions of the special education teacher, the value-added, to the educational experiences of the students in the class. The work focused on what is accomplished when ordinary special education teachers go about doing their assigned co-teaching jobs. We found that, as a group and across subject areas, special education co-teachers spent more time in contact with students than not, and most of their contact time helping individual students or small groups of students through an assigned task. There were substantial differences in the distribution of co-teacher activities across subject areas. One of the most common features of a high school classroom in the 21st Century is student diversity. Not only have classrooms become more diverse with respect to race, religion, and ethnicity, but also more students with disabilities than ever

Research in Secondary Schools Advances in Learning and Behavioral Disabilities, Volume 17, 55–75 © 2004 Published by Elsevier Ltd. ISSN: 0735-004X/doi:10.1016/S0735-004X(04)17003-1

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before are being included in general education classrooms. Data recently reported in the 23rd Annual Report to Congress (U.S. Department of Education, 2002) indicate that more than 70% of students with disabilities between the ages of 12–17 are being served primarily in general education settings. There are a wide variety of factors that account for the overall increase in diversity in America’s classrooms, but the specific increase in the numbers of students with disabilities can be traced to an evolution in the federal mandate for special education services. Before 1975 and the passage of the Education for All Handicapped Children Act (reauthorized and renamed the Individuals with Disabilities Education Act, or IDEA), the responsibility for educating students with disabilities rested in the hands of the special educator. As a multidisciplinary evaluation revealed the need for specialized instruction and specialized curricula, students with disabilities were pulled out of the mainstream of education and provided with a separate, special education program delivered by special education personnel. Most students with mild-to-moderate disabilities were not pulled out of general education classrooms full-time; even in the early days of the free, appropriate public education mandated by federal law, students with learning disabilities, students with emotional and/or behavior disorders, and students with mild/moderate mental retardation disabilities remained in (or were re-integrated into) general education classes if they could manage the content and requirements of the curriculum once appropriate accommodations and adaptations were made by the general education teacher (GET). But their special education (i.e. the specialized instruction, the specialized curricula and additional support services) was delivered outside the general education classroom. This balance of special curricula and specialized instruction provided by a special education teacher (SET) in a special education setting to address some of a student’s educational needs, and adapted and accommodated general education curriculum and instruction provided by the GET in a general education setting to students who could manage it, met the early requirement for services to students with disabilities in the least restrictive environment (LRE). But with successive reauthorizations of IDEA, the interpretation of LRE narrowed, and the balance between special and general education placements for students with disabilities shifted. As the term inclusion replaced the term mainstreaming in the lexicon of special education, the social and political climate supported retention of all students with disabilities in general education settings, unless a necessary and justifiable reason could be articulated for a student with disabilities to receive instruction in some other setting, such as a special education resource room or a part-time self-contained classroom. Within this revised conception of the delivery of special education services to students with disabilities, the special education that students received was considered an ancillary, not primary, educational service, and the SET

Co-Teaching

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was seen as providing support to students in general education settings rather than being the primary deliverer of instruction or curriculum (Schumaker & Deshler, 1988; Wang & Reynolds, 1985). This newer conception of special education has received enthusiastic support as special education and students with disabilities have been caught up in a national press to ensure that all of America’s students are prepared for work in an increasingly competitive global society. The emphasis nationwide has been on improving results of educational efforts by specifying desired achievements for students, and developing systems of accountability to evaluate the attainment of those desired achievements. This “standards-based reform” is characterized by three major elements: higher content standards, the use of assessments aimed at measuring how schools are helping students meet the standards, and an emphasis on holding educators and students accountable for student achievement. In keeping with the general trends toward greater accountability in education, IDEA 97 required that students with disabilities participate, and demonstrate competence, in the standards-based assessments developed within each state. More recently, the No Child Left Behind (NCLB) legislation reiterated this requirement that students with disabilities participate in statewide accountability assessments and that their results be reported along with their classmates’. Furthermore, NCLB requires that students with disabilities be held to the same Adequate Yearly Progress standards as everyone else. An underlying assumption of the standards-based reform movement is that creating high educational expectations for students and adding accountability for their educational results will ensure the students higher quality educational experiences. A presumption has been that these higher quality educational experiences are not available in a special education classroom taught by a SET; rather they are available in the general education classroom where instruction is delivered primarily by the content specialist, the GET.

THE ROLE OF THE SPECIAL EDUCATION TEACHER As the setting for educating students with disabilities has shifted, and accountability for their achievement of the same standards as non-disabled peers has been written into law, the role of the special education teacher (SET) has changed. If students with disabilities are in general education classes, the role of the SET is to support those students within that general education curriculum (Schumaker & Deshler, 1988; Wang & Reynolds, 1985). The most common service delivery model for implementing this support role, particularly in secondary schools, is co-teaching (Mastropieri & Scruggs, 2004).

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Co-teaching is a continuation and extension of the team teaching arrangements made popular in the 1960s (Bair & Woodward, 1964; Reinhiller, 1996). When co-teaching is implemented, two certified teachers, one general educator and one special educator, share responsibility for planning, delivering, and evaluating instruction for a diverse group of students, some of whom are students with disabilities (Friend & Cook, 1992). It is assumed that by having two teachers assigned to the class, students will receive more instruction and will be more involved in learning in ways that are not possible when only one teacher is present. Co-teaching draws on the strengths of both the general educator who understands the structure, content, and pacing of the general education curriculum and the special educator who can identify unique learning needs of individual students and enhance curriculum and instruction to match these needs. According to its advocates, co-teaching is supposed to accomplish three goals: First, co-teaching is expected to make available to all students, including those with disabilities who are accessing the general education curriculum, a wider range of instructional alternatives than would be possible with just one teacher. Second, co-teaching is expected to enhance the participation of students with disabilities as full classroom members. Third, co-teaching is expected to improve performance outcomes for students with disabilities. In theory, when co-teaching is implemented, both educators are delivering substantive instruction, and the instruction from both teachers occurs within the confines of a single classroom. Proponents of co-teaching describe a number of roles the SET might play in a co-taught class (Bauwens et al., 1989; Cook & Friend, 1995; Mastropieri & Scruggs, 2004). The SET might (listed alphabetically): Add comments to the instruction delivered by the GET to clarify the presentation; Observe the students while the GET teaches; Provide supplemental, supportive, or alternative learning activities to a group of students; Take over instruction to relieve the GET; Teach “academic survival skills” (Bauwens et al., 1989, p. 19) or strategies for addressing special learning needs; Teach a different lesson or segment of a lesson to a part of the class; Teach a parallel lesson to half the class; Team-teach with the GET; Tutor individual students or groups of students. In describing co-teaching, advocates assume that one or another of these roles will be played out in a collaborative working relationship with the GET after both teachers have planned together; reached agreements about such fundamentals as behavior management, grading, and curriculum coverage; and established

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high levels of trust and commitment. In practice, when co-teaching is implemented, the roles and responsibilities of the SET (and the GET) appear to vary widely, depending on “the goals of the lessons and the needs of the students” (Vaughn et al., 2000, p. 107). There is now a significant body of literature that defines co-teaching, and many writers have put forth guidelines and suggestions to help individuals in its practice (Bauwens et al., 1989; Cook & Friend, 1995; Gately & Gately, 2001; Reeve & Hallihan, 1994; Vaughn et al., 1997; Walther-Thomas et al., 2000). There is also some reason to believe that co-teaching will look differently in elementary and secondary schools (Boudah et al., 1997; Weiss & Lloyd, 2002). In case studies and surveys done at the secondary level, reports are mixed on both the implementation of co-teaching and student outcomes in co-taught classrooms (see Boudah et al., 1997; Harris et al., 1987; Nowacek, 1992; Trent, 1998). Many question the contributions that can be made by a SET in secondary school content subject classes given the structure of secondary schools: the voluminous nature of the content to be covered, the limited amount of time teachers are in contact with students, and the autonomy and independence of teachers in secondary school courses and departments (Cuban, 1984; Cusick, 1983; Schumaker & Deshler, 1988).

A STUDY OF CO-TEACHING IN SECONDARY SCHOOLS As part of a larger study of the efficacy of the co-teaching service delivery model, we set out to describe the role of the SET in co-taught high school content subject classes in urban, rural, and suburban high schools. This naturalistic observation study sought to identify the activities undertaken by the SET and to understand the contribution of the SET, the value-added, to the educational experiences of the students in the class. The focus of this work was not on what could be accomplished by a SET in a secondary school co-taught content subject class, but rather what is accomplished when ordinary SETs go about doing their assigned co-teaching jobs.

Research Plan Sample Teachers from 14 high schools in Western Pennsylvania and Western New York State volunteered to be part of this study. Of the 14 high schools, six were in urban school districts, six in suburban districts, and two in rural districts. School sizes ranged from 370 to 1,567 students with a median school size of 1,251 students.

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Table 1. Observations by Content Subject and Grade Level. Subject Math Science English Social studies

Grade 9

Grade 10

Grade 11

Grade 12

41 19 23 20

3 24 15 1

6 10 17 3

0 0 4 15

Depending on the school, the teaching arrangements for these pairs of teachers were referred to in several different ways: consultant teaching, co-teaching, inclusion, and mainstreaming. Regardless of the terminology used, in order to participate in the study, the special education and general education teacher had to be assigned for the same instructional period to a secondary class with both general education students and students with disabilities. Forty-one co-teaching pairs agreed to participate in our study. Each co-teaching pair was observed at least three and up to six times during the second semester of the school year, for a total of 201 observations of the 41 classes. Most of the observations (170) were conducted in Western Pennsylvania schools, while 31 were conducted in Western New York State schools. There were observations recorded in 10 Math classes, 10 Science classes, 14 English classes, and 7 Social Studies classes. Table 1 summarizes the observations across all the schools by subject and grade level. The courses observed ranged from remedial to advanced across subject areas. Class sizes ranged from 5 (in a low level, basic geometry class) to 32 (in a “comprehensive” or basic level economics class). The balance of special education to general education students assigned to the class was, on average, 30%, but ranged from 1 of 25 (4%) in a 9th grade English class to 14 of 17 (82%) in an 11/12th grade science/technology class. Observation Protocol A narrative observation protocol was developed, and observers were trained to document teacher behaviors and student behaviors in narrative notes. Every five minutes, the observer would describe the roles each of the teachers took on in the classrooms. Reliability of narrative notes was checked by having two observers take notes during the same class period. If the observers both captured the same essence of the class during 80% of the 5-minute segments, the narrative notes were considered reliable. Reliability checks were done at the conclusion of training and once during the data collection period for each of the 41 pairs of teachers. Reliability was judged to be better than 80% throughout data collection using the formula [agreements/(agreements + disagreements) × 100].

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The handwritten narrative notes taken by the observers were typed and saved as text documents. The researchers read printouts and developed a coding scheme based on the kinds of roles that were assumed by the SET. Coding was to be done in four stages. At the first reading of the 5-minute segment, the decision was, “Is the SET mentioned in the text?” Narrative segments in which there was no mention of the SET were coded in one of two ways: If the SET was clearly out of the room (had not yet arrived to class, had stepped out to deal with a student or to do an errand), the segment was coded as special education teacher absent; if there was simply no mention of the SET and no reason for the teacher to be out of the room, the segment was coded as missing data. If the segment did mention the SET, a second decision was, “Is the SET making contact with students?” If not, the observer made the third decision by coding the activities of the SETs in that segment into one of three categories: observing, drifting, taking notes; doing clerical work (taking attendance, talking on the telephone, grading papers, working on a computer); or planning or conferring with the GET. If the teacher was making contact with students, the third decision was to code the activity of the SET in the segment in one of three other categories: team teaching; individual or small group teaching or tutoring; or functioning as the lead teacher. Team teaching was coded if whole class instruction was going on, both teachers were actively involved in the lesson, the GET was most serving as the lead teacher, and the SET provided occasional remarks or instructions. Individual/small group teaching was coded if the SET was providing supplemental assistance to one or several students while “something else” (the main lesson) was going on. Lead teacher was coded if there was whole class instruction but the GET was not the primary instructor. Generally, this code was assigned when there was little or no mention of the GET in the 5-minute narrative segment, or if the SET was clearly in charge of the lesson. When one of these three “contact” teaching codes was assigned, a fourth level of coding was required. Coders had to decide whether the contribution of the SET was substantive, or procedural. Substantive instruction was considered any verbal contribution to the class that related to learning and knowledge whether it came in the form of new lesson material, reinforcing of previously taught material, reviewing course content, or testing. Procedural instruction was considered any other kind of instruction, not related to knowledge and learning, but rather relating to how to do an activity, how to use classroom materials, or how to behave in class. Only one code was assigned to each 5-minute observation segment. If more than one code applied to a particular 5-minute segment, coders were instructed to code the most active role being assumed by the SET: to favor a “contact” code over a “no-contact” code; to favor lead teacher over team teacher; to favor substantive over procedural; and to favor observing over planning or clerical work. Figure 1

62 NAOMI ZIGMOND AND DAVID W. MATTA

Fig. 1. Special Education Teacher Activities During Each 5-Minute Segment of Transcribed Observation Notes.

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provides a schematic of the coding system used to capture the contributions of the SET in co-taught classes. Once the two research assistants had been trained to 85% reliability on the coding system, they coded all of the narrative observation notes. Coders doublecoded 20% of the 201 observations independently to establish reliability. Reliability of coding 5-minute segments was better than 89%, again using the formula [agreements/(agreements + disagreements) × 100]. The observations were imported into, and codes were entered using, the Q. S. R. NUD.IST Version 4.0 software program making it possible to disaggregate narrative notes by code and to calculate the frequency of codes across observations.

Findings Overall, there were 1,663 5-minute narrative segments that received activity codes (discounting the 304 segments coded as missing data or teacher absent). As evident in Table 2, 1,153 segments (69.4%) were coded for “teacher contact with students,” most often identifying the teachers as engaging in individual or small group interactions (776 segments; 46.7%). SETs were seldom coded as taking the lead in instruction (95 segments; 5.7%). They also rarely spent an entire 5-minute block doing clerical work (69 segments; 4.2%) or planning/conferring with the GET (70 segments; 4.2%). They did, however, spend more time standing back and observing, drifting, or taking notes (371 segments; 22.3%) than they did teaching collaboratively (team teaching) with the GET (282 segments; 17.0%).

Taking the Lead in Instruction Our data set indicates that the SET seldom took (or was permitted to take) the lead in instruction. SETs were coded as leading instruction during only 38 of the 201 observations (18%) involving 21 of the 41 pairs of co-teachers, and in only 95 of Table 2. Distribution of Narrative 5-Minute Segments by Code. Distribution of Coded 5-Minute Segments No Contact With Students

Number %

Contact With Students

Observes

Clerical

Planning

Team Tch

Indiv/Sm

Lead Tch

371 22.3

69 4.1

70 4.2

282 17.0

776 46.7

95 5.7

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the 1,663 (5.7%) 5-minute segments. In 10 of those segments, the observer noted that the GET was actually out of the room, so these were not real instances of co-teaching. The remaining 85 observation segments of lead teaching (now only 5.1% of segments) were distributed across all subject areas. Taking the lead in instruction did not always mean “teaching content.” In many instances, the SET took charge to oversee a class activity in which the students were to work in groups or teams. For example, observers narrated a 20-minute block in a biology class in which the SET was in charge: 10:26 The SET led the remainder of the class. He asked the students to break into four groups.1 Each group is to create questions about excretion. The students were to use their notes in developing the questions. The GET and SET will use the questions on the test for extra credit. 10:31 The SET set up a board so the students could write their questions on the board, and the SET would type them into the SET’s laptop computer. GET is circulating and answering students’ questions. SET also circulates. 10:36 Students bring their questions to the SET. He answers questions about the technology. 10:41 SET told the students they could pick up extra credit questions later in the day. Students are off-task as they wait to write their questions on the board. In English, too, we saw the SET clarify an independent or small group assignment that the students were to complete as a library or homework assignment. 2:03 The SET introduces the activity that the students will do during library time tomorrow. The SET states, “This is something we’re going to try . . . [the students will be assigned teams]. Each team will have one answer sheet. Everyone in your group needs to know all the sources selected, the references with the page number and section. So, we need to talk about different sources used for research.” The SET writes RESEARCH on the board and asks questions to elicit the different kinds of research sources, asking where they could look to find information giving date, history, people . . .2 2:08 The SET continues with questioning. Students give Encyclopedia, maps/atlas, and dictionary as sources of different kinds of information . . . 2:13 The SET continues to give prompts and cues to elicit more research sources. Students offer the Internet. The SET informs them that for this project they will not use computer sources. The students add Almanac as a 4th source. And 10 minutes later . . . 2:23 The SET gives directions for the teams. “Each team will get a set of questions. The questions are not the same for each group. You have to supply the answers.

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You have to supply the source. Where it says name, you need to put all team members’ names. We’ll be in the library tomorrow and one day next week.” The SET discusses prizes for the wining team . . . 2:34 [Bell] The SET collects the team packets and dismisses the class. “Be sure your team captains gave me the packet. Have your names on them.” Monitoring group work, monitoring independent seatwork, or monitoring the students taking a test accounted for more than half of the occasions in which the SET was coded as lead teacher. In some of the remaining “lead teacher” segments, the SET took responsibility for engaging students in a review of previously covered material. We saw a special education English co-teacher completing the homework check or reviewing vocabulary words in preparation for an upcoming test. Often, the review activity was conducted as a game. In a social studies class, for a discussion of valued occupations, the GET of an African American History course used the format of a “survivor” game (voting off the island less valuable occupations). During the last five minutes of the class, the SET was in charge: 8:40 SET asked about politician and no one kept him. SET asked about carpenter and farmer – all groups said they’d keep both occupations. SET continued quickly with five more occupations that were not kept. In a Global Studies class, the special education social studies co-teacher led a vocabulary review game: 9:10 Teams of students skim the vocabulary handout. SET states the rules of the review game and indicates that he should be the only one talking. GET kept score. 9:15 SET asked the review questions and students answered them for points. SET encouraged the class to concentrate. GET kept time. SET encouraged the team that had no points. There were also review games in an economics class, and reviews of what had been seen on a video in both American History and African American History classes. In a science classroom, we saw the SET lead a bingo-like review game using science vocabulary words and definitions. One math SET took the lead for 35 minutes to manage the students in a review game in which they received cards on which problems had been written, completed the problems, and passed the cards to another student until the entire set had been completed by each student. During this review activity, the math GET either sat at his desk preparing a unit test for the class, or left the room. In a different math class, the SET was seen conducting the warm-up activity at the beginning of one class:

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9:25 GET passes out worksheet 8.1 on identifying exponents. SET tells students to begin working on problems 1, 2, and 3. GET goes to one student and explains something to him. SET circulates making sure students have their pencils and are beginning on the warm-up problems. On rare occasions, we observed the SET teach new content. We noted one instance in science when the SET spontaneously interjected her own ideas and concerns into a class discussion on DNA. From a seat at the back of the classroom, this teacher captured the attention of all the students who “turn in their seats and listen attentively to what she is saying.” And, in social studies, more than in any other subject area, we saw the SET lead discussions of new content material or provide substantive elaborations of the content being presented. In one African American History class, the SET took over a 20-minuite block. She directed students in reading the next chapter in their text, interrupting now and then to elaborate on the content being read, to ask probing comprehension questions, or to moderate a discussion: 8:20 As students organized, SET asked what law stated – if a slave crossed the Mason Dixon line he could be brought back? SET asked students to read answer in textbook. SET had another student read from textbook, then led a discussion on events that led to slaves wanting to escape . . . 8:25 . . . SET introduced a book she brought on the biography of Harriet Jacobs. She asked a student to read a passage in the book about her. The passage told about Harriet Jacobs escaping to the swamp, then being told the Underground Railroad wasn’t ready so she was taken to a crawl space in her grandmother’s house. Another student read about what the crawl space was like . . . 8:30 . . . SET asked students to guess how long she stayed in the attic – the answer was three years. 8:35 SET asked a student to read a part in the textbook about another slave – Tom Brown. SET also explained that the public school system began after slavery ended with a purpose to teach ex-slaves how to read and write. . . . This same special education social studies co-teacher on two other occasions used information from her personal experiences (as a Black woman in the African American History class, and as someone who recently served jury duty in the Civics class) to take over class instruction to elaborate on ideas being presented. The “new content” that we saw one special education English co-teacher teach involved reading aloud to the students as they followed along in their books. Another showed students how to use a word processing program on the computer. In preparation for a writing assignment, the English class moved to

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the computer lab, and the SET spent 15 minutes walking students though word processing: 8:20 The SET was putting an example on the screen for the students to see (name, course, date, title). The SET asked the students what a line under names or words mean. . . . The SET reviewed how to center. Time was given for the students to catch up. 8:30 The SET asked the class to think of a good way to begin the paper. One student read what she wrote and the SET put it on the screen. . . . The SET took time to review what the red and green lines meant. 8:35 The SET put another student’s example of a beginning on the screen. . . . The SET asked the class, “How are we going to save this for the next time we return?” The SET demonstrated how to save on the teaching computer. Narrative notes were re-read for particular instances of the SET providing “strategic” instruction, since much of the special education literature suggests that students with learning disabilities need to learn how to be strategic (Mastropieri & Scruggs, 2004), and that the SET generally has unique training in teaching strategic approaches to content and skill mastery. In the 95 segments across the four subject areas in which the SET was coded as “lead teacher,” only two segments include notations referring to a strategic approach to instruction. One observer caught the SET in an American History class giving “suggestions for note-taking [from the textbook].” In a global studies class, the observer wrote: 9:05 SET was drifting around the room then led a discussion on a review of the notes using a handout. He gave strategies to the class to remember names and concepts. For example, with Montesquieu, the SET told the class it had three syllables and it was associated with three branches of government.

Providing Individual or Small Group Support Across all subject areas, SETs spent most of their time in the support role, interacting with individual students or with small groups of students while a lesson, led by the GET, was on-going in the class, or while students were engaged in independent seat-work. Nearly half of the encounters (41%) were coded as procedural, meaning that the SET appeared to be directing or redirecting the students rather than helping them with the content. For example, in a 9th grade Earth and Space Science class, the observer noted: 10:05 GET opens class by announcing a test on Monday. Both teachers are in the front of the room. GET is clearly in charge; he knows when the test

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is and what is on it. SET goes to several individuals to make them take their notebooks out. In a 10th grade English class, the observer wrote: 9:16 The GET sits on a student desk in the front of the class and asks, “Who’s first?” A student volunteers to read her story first. The SET goes over quietly to a special education student at the far side of the room to encourage her to volunteer next. . . . In an American History class for 9th graders, the observer noted: 11:40 GET begins the class. SET goes over and checks with each of her students to see if all their work is done. She [the SET] told me [the observer] that she hounds the students, because the GET counts completed worksheets more than he counts tests so she makes sure they [the special education students] have their worksheets completed. In the remaining 59% of small group or individual interactions, narrative notes indicated that the SET was providing “help.” This help took a number of forms. Sometimes the support involved coaching an individual student who was having trouble completing an assignment. In math, the SET often gave help to an individual. For example, one observer noted: 10:20 Upon entering the SET immediately went to a student (F, white vest) while the GET was discussing the topic of slope, finding the slope of a line using the slope formula. GET had the slope equation written on the blackboard and had just given a problem to solve when a student entered the class and showed her pass to the GET. SET meanwhile drifted to another student (F, black sweater) on the other side of the room and began helping her. GET continued working on the problem she was using as an example. SET moves back to (F, white vest) who had raised her hand and appeared to have a problem. Another student (F, blue shirt) raised her hand and SET went to her desk and also responded to the student sitting in front of her (M, white sweatshirt). In an English class, the observer noted: 2:28 The GET circulates and assists individual students who ask for help. The SET works one-on-one with S8 (male) then with S1 (male). The SET guides S1 through writing his poem. S1 wants it to be comedy and about nature. His topic is: “Bigfoot.” The SET holds up her fingers to help S1 get the correct number of syllables. The SET moves over to assist S16 (male) then calls back to S1, “You may take poetic license and use Big-feets, but it’s still just two syllables.”

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On the day of a social studies test, the observer wrote: 11:45 GET passes out the test. SET goes over specific instructions with each of her students, making sure they understand the directions. Makes sure they have their test number and their name on their test. SET helps each one of them individually. She eliminates two choices on a multiple choice question if they ask for help. Sometimes the support involved working with a group of students. In an 11th grade English class in which groups of students were working together on a writing assignment based on a story recently read, the observer noted: 10:32 GET went to the setting group and SET went to the theme group. Then the GET moved to the theme group and the SET moved to the author group. 10:37 GET gave out stickers for participation. SET read aloud to author group from Ethan Frome and asked, “Are we being very specific?” In a 12th grade American Problems in Democracy class, as the students worked in groups on an assignment to be completed using a computer search of web-sites, the observer noted: 8:00 SET is working with the Alaska group. SET asks GET a question then goes to the Utah group. SET goes to the Missouri group and looks at their printout of information. He makes suggestions. SET goes to the Minnesota group and talks to them about St. Paul. GET is still working with girls on PowerPoint. All students are on task.

Team Teaching Team teaching was coded if the SET was contributing to an ongoing whole class lesson and both teachers were actively involved in the instruction. The “team teaching” segments seemed to take on one of four characteristics. In the majority of these segments, the two teachers seemed to operate in tandem – first one and then the other, going back and forth within a single 5-minute interval. For example, in a social studies class: 8:55 GET asked students to open their textbooks. SET reviewed notes that were on an overhead that students were copying for a test the next day . . . GET talked about the monarchies during the scientific revolutions and how . . . A second kind of “team teaching” occurred when the GET was in charge of the lesson, and the SET interrupted with a comment or clarification. We saw this in a freshman English class:

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10:36 . . . As the GET introduces the lesson, the SET moves over to the door and checks the files where student portfolios are kept. The SET also circulates and prompts students to get their journals out . . . GET gives an overview of the day. GET continues to elaborate on narrative writing, informing the class . . . The SET interjects with a question, “Mr. A., if I am going to tell about a storm can I (the SET models telling a story about a storm)?” The GET answers, “Yes, that’s just one way. You could do others.” The GET continues . . . In the third kind of “team teaching” segments, the two teachers were actually teaching together. In some cases the GET was talking and the SET was at the blackboard or the overhead projector serving as the “scribe.” Nevertheless, there appeared to be real parity in the distribution of teaching responsibilities. In an 11th grade English class, the observer noted: 11:18 Fourteen students are in their seats ready to begin; five more are up at the front of the room. As the bell rings, the GET directs those not in their seats, “OK guys. Come on!” The SET reminds the students that their journals/notebooks will be due on Monday and notes “five points off if not in.” The SET asks students to open their notebooks to the page that says “Character.” The SET then writes the word “Character” on the board. As the GET informs the class what character names should be on their list, the SET acts as scribe, using blue chalk, and prints HOLDEN CAULFIELD on the blackboard. The GET asks the students what names they have already. The SET lists the names as the student tells them to her. Then the GET goes to the board and adds JANE GALLAGHER. The fourth kind of “team teaching” codes was subcoded as “procedural.” In these segments, the SET helped with the lesson by redirecting students onto the task at hand, or explained how to use equipment or complete an activity. In an Economics class, the observer made the following notations: 12:17 The GET throws out a few questions (to try to energize the group). “Who thinks the government should intervene?” The GET continues, “Who thinks the government should not intervene?” The GET asks the SET, “Do you see something here?” The SET says, “They’re not participating!” The GET turns the discussion to voting. . . . The SET listens and observes, or drifts to prompt students to listen or to get their heads up if it looks like they are sleeping.

Analysis by Subject Area The size of the data base, and in particular the number of observations done in each of the four major subject areas, permitted an analysis of the role and

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Table 3. Number and Percent of 5-Minute Narrative Observation Codes Across Subject Areas. Subject

Distribution of Coded 5-Minute Segments No Contact With Students Observes

Math Science English Social studies

Clerical

Contact With Students

Planning

No.

%

No.

%

No.

59 61 132 119

15.1 15.9 23.5 36.5

9 22 29 9

2.3 5.7 5.2 2.8

14 18 21 17

% 3.6 4.7 3.7 5.2

Team Teaching No.

Indiv/Sm

Lead Teaching

%

No.

%

No.

29 7.4 57 14.8 119 21.2 77 23.6

270 205 226 75

69.1 53.4 40.2 23.0

10 21 35 29

Total

% 2.6 5.5 6.2 8.9

391 384 562 326

contribution of the SET subject-by-subject, as well as overall. Given our own and others’ conversations with high school level SETs, we expected to find differences across subject areas, and hypothesized that the SETs’ contributions in math and science classes would be more limited because of the “technical” content demands of these subjects. We believed that SETs would more easily be able to call on personal experiences and general knowledge when they co-taught in English and social studies. Our beliefs were both substantiated and challenged. Tables 3 and 4 summarize the data by subject area. As expected, there were significant differences in the distribution of codes across the four subject areas (␹2 = 195.3; 15 df). There were also differences in the percent of SET interactions coded as “substantive” across the four subject areas. Special education math coteachers were least likely to be found team teaching and almost never took the lead in instruction (see Table 3). They were the least likely to provide substantive instruction in either their team teaching and lead teaching (see Table 4). In science, SETs did slightly more team teaching and lead teaching, and their contributions were likely to be more substantive than in math. As predicted, the English SETs did Table 4. Percent of Interactions of Special Education Co-Teachers Coded Substantive (vs. Procedural) Across Four Subject Areas. Subject

Math Science English Social studies

% of Interactions Coded Substantive Team Teaching (%)

Indiv/Sm Grp (%)

Lead Teacher (%)

34.5 61.4 64.7 75.3

69.6 60.0 56.6 54.7

20 52.4 85.7 89.6

Overall (%) 64.7 59.7 61.8 69.6

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more team teaching and lead teaching, and their contributions were substantially more substantive. Social studies SETs were the most likely to add substantively to instruction and did the most team teaching and lead teaching of all. A surprising finding, however, was that social studies SETs also spent the greatest amount of classroom time standing around, not interacting with students (44.5% of coded segments), while math SETs were not engaged in instructional contacts with students in only 21% of segments. For special education science co-teachers, the percent of segments with no contact with students was 26.3; for English teachers it was 32.4. The difference is attributable, in large part, to the amount of time spent interacting with individual students or small groups. The math general education teachers and the science general education teachers were more likely to assign independent seatwork, providing more opportunities for the special education co-teacher to interact with individual students or small groups.

DISCUSSION We set out to observe special education and general education co-teachers doing their jobs as they understood them. We solicited participation from districts and schools that were not part of a special program, that had implemented a co-teaching service delivery model at their own initiative, that had provided for their teachers whatever training and guidance they felt appropriate, and that did not consider themselves “showcase” implementations of the co-teaching model although they believed that they were doing a “good job.” We believed that this selection of sites made it more likely that we would see a wide range of co-teaching implementations and find out what ordinary teachers do in ordinary schools. Our expectations were confirmed: we saw a very diverse set of co-teachers doing a very diverse set of activities. We were pleasantly surprised to find that high school SETs spent more time making contact with students (teaching or coaching the whole class, small groups, or individual students) than they did just standing around or doing clerical work. Nevertheless, there was a lot of standing around. For more than 23% of the 1,663 5-minute segments, the SET was coded as observing, drifting, taking notes, or otherwise not engaged with students. But across subject areas, SETs spent as much as 79% (in math) and as little as 55.5% (in social studies) of their time active and engaged in substantive or procedural instructional interactions. Although SETs were seldom responsible for introducing new material, they did occasionally add comments to the general education teachers’ presentation that enriched the lesson. More often, the SET worked together with the GET, or in tandem with the GET (taking turns), reviewing material already covered.

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We were also pleased to find that, by far, the majority of the contributions of the SET to classroom instruction were coded as “substantive” rather than “procedural.” Substantive instruction was considered any verbal contribution to the class that related to learning and knowledge, whether it came in the form of new lesson material, reinforcing of previously taught material, reviewing course content, or administering a test. Procedural instruction was considered any other kind of interaction, not related to knowledge and learning, but rather related to paying attention, using appropriate materials, or behaving in class. Across subject areas, between 60 and 70% of SET interactions were coded as substantive. This was true in math and science as well as in English and social studies. The conventional wisdom that SETs have little to contribute to a high school math or science class was not borne out in these data. Observers recorded a large number of individual/small group interactions (especially in math and science, not as much in English, much less in social studies) but little sustained teaching in those segments. The interactions would more appropriately be characterized as “helping” than “teaching” or tutoring. The teacher-student interactions were brief and specifically related to a stumbling block in the lesson, rather than intensive, relentless instruction with guided practice to mastery. In 201 observation periods, we saw only one or two instances of the more elegant teaching arrangements described in the co-teaching literature, such as station teaching, parallel teaching, alternative teaching, etc. (see Bauwens et al., 1989; Cook & Friend, 1995; Vaughn et al., 1997). Observers virtually never saw two lessons going on at the same time, an arrangement that takes advantage of the expertise of two trained teachers sharing one instructional space. In fact, we saw nothing out of the ordinary in the 201 observations in 41 classrooms in 14 high schools. So, what was the value-added of the SET in secondary school content subject classes? The second teacher was a nice addition, an occasional relief for the GET, and more attention to students when class is organized for small group (team) or independent seatwork. But none of what we saw would make it more likely that the students with disabilities in the class would master the material. We did not hear the SETs chime in with carefully-worded elaborative explanations. We rarely heard SETs rephrase something already said to make the explanation clearer. We virtually never saw the SET provide explicit strategic instruction to facilitate learning or memory of the content material. If students with disabilities were mastering the content and earning passing grades in these high school courses, it was not because of something special the SET was doing in this class. If students with disabilities were not mastering the content, and not earning passing grades, given what we know about the usefulness of strategic, intensive, relentless instruction for students

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with learning disabilities, the kinds of coaching and team teaching we saw was not likely to make much difference in academic achievement. For us, this research raises questions about what co-teaching is for. If students with disabilities and their teachers are placed in general education classes to make it possible for the students to be exposed to the curriculum and instruction being delivered by the GET, then co-teaching in the classes we observed was successful. The general education curriculum was being delivered, the special education teacher was helping out, and the students were learning (or not learning) the material being covered. If, however, the inclusion aims to provide students with disabilities with opportunities to master essential curriculum content in preparation for full participation in statewide accountability assessments, and if we believe that students with learning disabilities truly have learning disabilities, then there is nothing about the co-teaching going on in these classrooms that would lead students to mastery. The SETs we saw shared the instructional burden but did not make a unique contribution. When students were organized into teams or small groups, or given independent seatwork assignments, the SET was there to answer a question or help with a solution. But there was no sustained instruction for students having particular difficulties, no re-teaching of students who had not reached mastery, and no strategic instruction for students who tend to need explicit instruction in strategies. The SETs in these 14 high schools certainly provided support to students with disabilities in inclusion classes. Two questions remain. “Is this a sufficient role for a highly trained SET?” and “Is this the special education to which students with disabilities are entitled?”

NOTES 1. The italics identify the sentence or phrases in the narrative notes that prompted the code assigned. 2. This notation indicates that there is more to the narrative in this 5-minute segment, but that part of the text is not about the role of the special education teacher.

ACKNOWLEDGMENTS This research was supported by a Field Initiated Grant (No. H324C000035) from the U.S. Department of Education, Office of Special Education Programs. We wish to thank Kathleen Magiera, Jane Partanen, Connie Emmerling, Debbie Lawler, Laurel Leigh, and Laura Moin for their contributions in project management, data collection, and data coding.

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REFERENCES Bair, M., & Woodward, R. (1964). Team teaching in action. Boston: Houghton-Mifflin. Bauwens, J., Hourcade, J., & Friend, M. (1989). Cooperative teaching: A model for general and special education integration. Remedial and Special Education, 10, 17–22. Boudah, D., Schumaker, J., & Deshler, D. (1997). Collaborative instruction: Is it an effective option for inclusion in secondary classrooms? Learning Disabilities Quarterly, 20, 293–316. Cook, L., & Friend, M. (1995). Co-teaching: Guidelines for effective practices. Focus on Exceptional Children, 28(3), 1–16. Cuban, L. (1984). How teachers taught: Constancy and change in American classrooms. New York: Longman. Cusick, P. (1983). The egalitarian ideal and the American high school. New York: Longman. Friend, M., & Cook, L. (1992). The new mainstreaming. Instructor, 101(7), 30–32, 34, 36. Gately, S., & Gately, F., Jr. (2001). Understanding co-teaching components. Teaching Exceptional Children, 33(4), 40–47. Harris, K., Harvey, P., Garcia, L., Innes, D., Lynn, P., Munoz, D., Sexton, K., & Stoica, R. (1987). Meeting the needs of special high school students in regular classrooms. Teacher Education and Special Education, 10, 143–152. Mastropieri, M., & Scruggs, T. (2004). The inclusive classroom: Strategies for effective instruction (2nd ed.). Upper Saddle River, NJ: Pearson Education. Nowacek, E. (1992). Professionals talk about teaching together: Interviews with five collaborating teachers. Intervention in School and Clinic, 27, 262–276. Reeve, P., & Hallihan, D. (1994). Practical questions about collaboration between general and special educators. Focus on Exceptional Children, 26(7), 1–12. Reinhiller, N. (1996). Co-teaching: New variations on a not so new practice. Teacher Education and Special Education, 19(1), 34–48. Schumaker, J., & Deshler, D. (1988). Implementing the regular education initiative in secondary schools: A different ball game. Journal of Learning Disabilities, 21, 36–42. Trent, S. (1998). False starts and other dilemmas of a secondary general education collaborative teacher: A case study. Journal of Learning Disabilities, 5, 503–513. U.S. Department of Education (2002). To assure the free appropriate public education of all children with disabilities: Twenty-third annual report to Congress on the implementation of The Individuals with Disabilities Education Act. Washington, DC: Office of Special Education Programs. Vaughn, S., Bos, C., & Schumm, J. (2000). Teaching mainstreamed, diverse, and at-risk students in the general education classroom (2nd ed.). Boston, MA: Allyn & Bacon. Vaughn, S., Schumm, J. S., & Arguelles, M. E. (1997). The ABCDEs of co-teaching. Teaching Exceptional Children, 30, 4–10. Walther-Thomas, C., Korinek, L., McLaughlin, V., & Williams, B. (2000). Collaboration for inclusive education: Developing successful programs. Needham Heights, MA: Allyn & Bacon. Wang, M., & Reynolds, M. (1985). Avoiding the “Catch 22” in special education reform. Exceptional Children, 51(6), 497–502. Weiss, M., & Lloyd, J. (2002). Congruence between roles and actions of secondary special educators in co-taught and special education settings. The Journal of Special Education, 36(2), 58–68.

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HOMEWORK FOR STUDENTS WITH DISABILITIES Jill Jakulski and Margo A. Mastropieri ABSTRACT The purpose of this chapter is to present a summary of the literature related to homework. First, information on the search procedures is provided, including the criteria for inclusion in this review. Second, a historical overview of homework in the United States is provided, including definitions and major changes in public opinion over time. The third section addresses the difficulties experienced by students with emotional disabilities in regard to homework. The fourth section reviews the homework policies presently in place at local school districts across the U.S. The fifth section discusses the effects of homework when basic classroom strategies, cooperative homework teams, self-management and goal setting, and assignment completion strategies are used. The sixth section describes the homework practices used, as reported by teachers and students. The seventh section describes the problems experienced by students with disabilities, from the perspective of teachers, parents, and students. A final section describes the kinds of problems associated with home-school communication. Homework has been part of American educational system for more than a century, and is generally accepted as an important component of the educational process. It is part of most teachers’ instructional repertoire, and it affects the lives of most families (Cooper & Nye, 1994). Homework is also considered an integral part of raising standards and making course content more challenging. Research in Secondary Schools Advances in Learning and Behavioral Disabilities, Volume 17, 77–122 © 2004 Published by Elsevier Ltd. ISSN: 0735-004X/doi:10.1016/S0735-004X(04)17004-3

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Homework has been defined in many ways, although few formal definitions exist in the research literature. Keith (1986) defined homework as work that teachers typically assign for completion outside the normal class period. Olympia et al. (1994, cited in Jenson et al., 1994) define homework as academic work assigned in school that is designed to extend the practice of academic skills into other environments during non-school hours. Cooper (1994) defines homework as tasks assigned to students by school teachers to be carried out during non-school hours, and can be classified according to its amount, purpose, skill area, degree of individualization, degree of choice for the student, completion deadline, and social context. According to Cooper and Valentine (2001), the objectives of homework can be classified as instructional or noninstructional, and serve one or more of four purposes: practice and review; preparation; extension; and integration. The most common types of homework, practice and review, are meant to reinforce previously taught material. Practice and review assignments are considered the most basic form of homework and lead toward attainment or mastery of skills. Although the research is not consistent in its findings, there is general agreement that homework can be a positive experience that leads to increased levels of academic achievement (e.g. O’Melia & Rosenberg, 1998; Trammel et al., 1994; Vinograd et al., 1986; Whiteley, 1990). In Cooper’s meta-analysis of the research on the effects of homework (1989), he found that students who did homework generally outperformed students who did not. Cooper also found that time spent on homework was more positively associated with achievement for high school students than for middle school students, and for middle school students more than elementary school students. This supports findings by Keith and Page (1985) and Walberg (1984), who reported that more time spent doing homework, resulted in higher grades and achievement test scores. Homework has also been associated with students’ improved attitudes toward school, and improved study habits (Cooper & Nye, 1994). Homework comprises up to 20% of the time students spend on school-related and academic tasks (Cooper & Nye, 1994). In a 1985 Gallup poll of attitudes toward public schools, 40% of the respondents indicated a belief that elementary school children should be assigned more homework, while 38% felt that the present homework levels were adequate. At the high school level, 47% of the respondents indicated that more homework was appropriate, while 31% disagreed. Parents of children who were achieving at the average or below average ranges, as well as nonwhites and inner city parents were more likely to endorse increased homework requirements.

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Although virtually all students are faced with the complexities associated with homework completion, it is especially problematic for students with disabilities (Epstein et al., 1993; Polloway et al., 1992). When considering students with and without disabilities (learning and/or emotional), students with disabilities experience significantly more problems associated with homework than do students without disabilities (e.g. Epstein & Foley, 1995; Epstein et al., 1993; Gajria & Salend, 1995; Polloway et al., 1992; Salend & Schiff, 1989; Soderlund & Bursuck, 1995). The purpose of this chapter is to review what is known about homework and students with disabilities.

LITERATURE SEARCH PROCEDURES Computer assisted searches were conducted for relevant literature using the Education Resources Information Center (ERIC), PsycInfo, and Dissertation Abstracts International data bases. Descriptors used in the searches included the following: homework; special education; disabilities; emotional disturbance and/or emotional disabilities; learning disabilities; parent attitudes; student attitudes; teacher attitudes; teacher practices; and student practices. Previous homework reviews were acquired and examined, as were the reference lists of all articles obtained. In addition, a hand search of recent issues of all major special education journals such as Behavioral Disorders, Learning Disability Quarterly, Journal of Special Education, Remedial and Special Education, Journal of Emotional and Behavioral Disorders, and Learning Disabilities Research and Practice were examined for relevant articles.

Criteria for Inclusion Initially, all articles were included for consideration if the word “homework” was used in the title of the study or as a keyword. From that large sample, studies were included which: (a) included students with learning disabilities or emotional disabilities; (b) had a primary purpose was related to some aspect of homework; (c) were based on empirical, data-based research related to homework; and (d) was published in 1990 or later. The final sample included studies that occurred in public school settings, and were qualitative and quantitative in nature. Hand searches yielded some studies that did not include students with disabilities, but were determined to be relevant to this project.

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HISTORICAL OVERVIEW OF HOMEWORK Since the early 1900s, homework has frequently been a topic of considerable debate among educators and has garnered support and opposition several times over throughout the decades. In the early 1900s, the mind was viewed as a muscle that benefited from mental exercise, e.g. memorization of concrete material such as multiplication tables, names, and dates (Cooper, 1989). Because the assignments almost always involved memorization, homework was viewed favorably, as memorization was considered to be good mental exercise. Students were required to spend long hours preparing for daily recitations and examinations that would determine their eligibility for promotion (Gill & Schlossman, 1996). During the second decade of the 1900s, doctors led the campaign to abolish homework (Gill & Schlossman, 1996), identifying health issues as the primary argument against homework. Conditions such as curvature of the spine due to carrying of heavy books, eyestrain, and stress were cited as the detrimental results associated with homework. National publications commonly denounced homework, suggesting it was a health hazard to children. In the 1930s and 1940s, homework began to be viewed unfavorably. As the emphasis in education shifted from the arduous hours of drills and memorization to facilitation of problem solving and students taking initiative and an interest in learning, schools were expected to educate “the whole child”. They were responsible for children’s intellectual growth as well as for nurturing their physical and emotional growth (Gill & Schlossman, 1996). Healthy and active play was viewed as important, and a trend for less homework emerged. After the Russian launch of the Sputnik satellite in 1957, Americans’ thinking began to change again, bringing homework back into a favorable light. The general public feared that the lack of rigor in the American educational system left students unprepared to compete with the rest of the world. Homework then became a tool to increase knowledge acquisition for students, and accelerating the pace of learning. In the 1960s, homework was once again viewed less favorably, and was seen as placing excessive pressure on students to produce, and the emotional consequences of too much homework were repeatedly noted. Many, such as Wildman, in a 1968 article in the Peabody Journal of Education, noted a concern that too much emphasis on school would lead to the neglect of other areas of personal fulfillment. Further, he noted that some physical effects from the pressures of homework were being seen in organic disorders, such as ulcers and nervousness. Once again, because of the shift in the perception of homework during this time, its use and importance decreased. Beginning with the 1983 A Nation at Risk: The Imperative for Educational Reform, the educational reformers of the 1980s and 1990s called for such


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things as higher academic standards and more homework for students (National Commission on Excellence in Education, 1983). Students were seen as devoting considerably less effort to schoolwork than students in other countries or students from previous generations. During the last fifteen years, the concept of homework has received mixed reviews. Although educators may see homework as a means to an end, in the wake of increased academic pressures imposed by school districts and state and federal governments, many also feel that increasing homework demands will only lead to students feeling overly stressed and burnt out. Such has been the trend over the last hundred years; it seems likely that the emphasis and support/disdain of homework will continue to waiver back and forth, depending on the political, personal, and educational influences of the time.

Students with Emotional or Behavioral Disorders The Individuals With Disabilities Education Act (U.S. Department of Education, 2001), identifies students as “severely emotionally disturbed” as: (i) The term means a condition exhibiting one or more of the following characteristics over a long period of time and to a marked degree, which adversely affects educational performance: (a) An inability to learn which cannot be explained by intellectual, sensory, or health factors; (b) An inability to build or maintain satisfactory interpersonal relationships with peers and teachers; (c) Inappropriate types of behavior or feelings under normal circumstances; (d) A general, pervasive mood of unhappiness or depression; or (e) A tendency to develop physical symptoms or fears associated with personal or school problems. (ii) The term includes children who are schizophrenic [or autistic]. The term does not include children who are socially maladjusted unless it is determined that they are seriously emotionally disturbed. Although federal legislation uses the term “seriously emotionally disturbed”, many others are used synonymously, including emotionally disabled, behaviorally disabled, emotionally handicapped, emotionally impaired, and socially and emotionally maladjusted (Kavale et al., 1996). In this chapter, emotional disability will be used.

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Homework for Students with Emotional Disabilities When students with disabilities participate in a general education curriculum, it is generally expected that they will complete homework assignments along with their nondisabled peers (U.S. Department of Education, 2001). Parents and teachers expect that all students be held to high standards, yet we know that students with disabilities frequently demonstrate difficulties related to homework completion. Even at the elementary level, for example, students with disabilities are more likely to not do their homework than their nondisabled peers. At all grade levels, students with emotional disabilities and learning disabilities experience more problems with their homework than do their nondisabled peers (Epstein et al., 1993; Polloway et al., 1992). Typically, these students need to be reminded to complete their homework, they daydream frequently, and they often procrastinate regarding their homework (Epstein et al., 1993). Several researchers have reported that academic achievement of children and adolescents with emotional disabilities is often not commensurate with their chronological age (Epstein et al., 1989; Scruggs & Mastropieri, 1986). Frequently their academic performance is more similar to that of students with learning disabilities. Further, mathematics was the weakest area for these students (Epstein et al., 1989). There exists a broad foundation of research about homework in general; however, much of the data are based on survey research from the perspectives of parents and teachers, and few studies focus on students with emotional disabilities. Although there is a general assumption that students with learning disabilities and students with emotional disabilities experience similar problems in regard to homework, it is important to add to the research in regard to students with emotional disabilities. Further, because much of what we think we know about homework has been driven by the perceptions of parents and teachers, it may be important to consider the views and perspectives of the students.

HOMEWORK POLICIES Roderique et al. (1994) conducted a nationwide survey and reported the results of 267 school districts from which information was gathered about the types of homework policies in place at local school districts. Only 35.2% (n = 94) of the respondents indicated that their district had a homework policy, of which 79.3% (n = 73) indicated that the policy was recommended, and 20.7% (n = 19) indicted that it was required. Of the districts responding that they had a homework policy, 83.0% (n = 78) indicated that it was evaluated periodically.


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Responding to the question regarding the allowance of modifications for students with disabilities, only 64.4% (n = 58) indicated their policy included such. The most frequent comments included modifications from the Individualized Education Program (IEP) (n = 4), assignments consistent with student needs (n = 5), and modifications left to teacher discretion (n = 7). Only 20.7% (n = 18) indicated that the policy allowed for assistive devices provided for use at home.

THE EFFECTS OF HOMEWORK Eleven studies were reviewed that examined the impact of homework on areas such as rate of completion, rate of accuracy, and achievement. Two studies used daily homework assignment to assess its effect on performance and skills acquisition (Cobb & Peach, 1990; Rosenberg, 1989). Two studies assessed the effect of cooperative homework teams on homework completion, percent correct, and achievement (O’Melia & Rosenberg, 1994; Olympia et al., 1994). Four studies implemented self-management, self-recording, or goal-setting procedures to assess their impact on homework completion and accuracy (e.g. Carrington et al., 1997; Miller & Kelley, 1994). Other studies examined the effect of homebased self-management on homework performance and academic achievement (Callahan et al., 1998); the impact of interactive homework assignments on students’ homework completion rates and accuracy levels (Van Voorhis, 2001); and the impact of an assignment completion strategy on homework completion rates and homework quality (Hughes et al., 2002). Investigations in this section involved students with and without disabilities in elementary and secondary grade levels.

Daily Homework Assignments Rosenberg (1989) developed a two-experiment investigation designed to assess the effectiveness of daily homework assignments on the acquisition of basic skills. Six students from eight to ten years of age participated in the first study. Each student was identified as having learning disabilities and had been identified as needing work on the acquisition and fluency of basic multiplication skills. Following two days of pretesting, a unit of unknown facts was developed. From that, forty facts were selected as the instructional unit of which 20 were assigned to each of the experimental conditions: direct instruction and direct instruction with supplemental homework. Three types of dependent variables were used: measures of math performance, rate of homework return, and percentage correct on returned homework assignments. Students received 30 minutes each day

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of direct instruction lessons on a prearranged number of math facts assigned to each condition. Each lesson consisted of six activities: (a) introduction and review of group rules; (b) administration of daily performance checks; (c) review of previously covered work and assigned homework; (d) demonstration of and controlled practice in math facts scheduled to be taught; (e) independent seatwork; and (f) assignment of homework. Conditions differed only with respect to the assignment of homework to the direct instruction with homework condition. Measurement of the students’ math performance yielded inconsistent results. Three of the six students demonstrated acquisition of the multiplication facts, while the results of the other three students were less positive. Homework completion rates of the six students also varied with homework return rates ranging from 20 to 100%. The average percentage correct on homework assignments also varied, ranging from 20% correct to 100%. Only two of the six students appeared to have benefited from the supplemental homework assignments. However, upon further analysis, the author noted the following patterns: homework was effective only when: (a) rate of completion equaled or exceeded 70%; (b) the percentage correct on homework averaged 70% or better; and (c) a student demonstrated at least moderate acquisition of material during checks of performance. The second experiment was designed to test the effectiveness of homework assignments designed to address those factors. Four elementary students with learning disabilities who met the same criteria as those in the first study were participants. Students ranged in age from nine to ten. However, since the students participating in this study had mastered basic math facts, spelling was selected as the target skill for the intervention. Using a Dolch word list and students’ vocabulary, a pre-experimental condition spelling list of 100 unknown words was developed and then sequenced according to level of difficulty. Using a stratified randomization procedure, fifty words were then assigned to each of the two experimental conditions: direct instruction and direct instruction with homework plus reinforcement and parental support. The homework condition in this second study was designed to maximize the probability of correct homework being returned daily. Parental cooperation was encouraged and parents were asked to administer a daily practice test and sign all written homework assignments. In addition, a token economy system was developed so that students could earn tokens based on the completion of their homework. Dependent variables included daily spelling performance, rate of homework completion, and percentage correct on homework. Results of this second study indicate that all four of the students benefited from the spelling instruction. Moreover, three of the four participants demonstrated even greater benefits from the direct instruction with homework condition. These students averaged a homework return rate of over 90%, and a percentage correct


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rate of more than 90%. In contrast, the student who showed the least benefit had a homework return rate of 71% and an average of 83% correct. These results taken together suggest that homework can be a positive tool to increase achievement levels for students with learning disabilities when planned, assigned, and implemented in a structured a responsible manner. Cobb and Peach (1990) examined the effects of homework on the academic performance of twenty-three summer school students, five of whom were identified as having learning disabilities. Students were in classes for three hours daily over twenty-two consecutive school days. Each week, new skills were introduced, and tests were given at the end of the first and third weeks. Students were required to complete practice-type homework assignments each day during the first and third weeks. During the second and fourth weeks, new skills were introduced, but no homework was required. Findings of this investigation are limited in that no major differences were detected between the two conditions. There was no significant difference in student achievement after two weeks of homework assignments, no significant difference in achievement mean scores between students with learning disabilities and students without disabilities, and no significant difference in achievement mean scores between students with learning disabilities and students without disabilities after two weeks without homework assignments. The lack of findings may have been due to an insufficient training period, minimal strength of the treatment variable, or the small number of students with learning disabilities.

Cooperative Homework Teams Two studies examined the effect of homework teams on math performance (O’Melia & Rosenberg, 1994; Olympia et al., 1994) O’Melia and Rosenberg (1994) examined the effect of cooperative homework teams on mathematics performance of students with disabilities. Using the rate of homework completion, the percentage correct on homework, and a norm-referenced global measure of math achievement as outcome measures, 171 students enrolled in grades six through eight from 20 different math classes were selected to participate in this study. All participants were identified as having learning disabilities or emotional disabilities, as well as an existing deficiency in basic mathematics skills. All students participating in this study were in a math special education class with a certified special education teacher. Students were given a placement test to determine their specific basic skills deficiencies and were then assigned to three- and four-member cooperative homework teams based on the results of the placement tests. Teachers then developed lesson plans and assignments

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accordingly. At the end of each day’s math lesson, an instructionally relevant homework assignment, consisting of eight computation and two story problems, was assigned to all students. Each homework assignment was expected to be completed in 15–20 minutes, with each student working individually. The following day, students in the experimental group (cooperative homework teams) met for approximately ten minutes. During that time, each team member turned in his individually completed assignments to a student checker who, using teacher-made answer sheets, graded teammates homework and reported the grades to the teacher and then passed the assignments back to the team members for review. The cooperative homework teams members then helped each other review errors and make corrections. Corrected homework was then collected and graded again. At the end of the week, individual scores were used to develop a team mean, and points were awarded to individuals based on assignment completion and the percentage correct. Weekly award certificates were also given to teams who met or exceeded the pre-selected criteria. Post-intervention measures indicated significant increases in two outcome measures. Students in the cooperative homework teams increased their rate of homework completion by 12.5%, whereas those in the non-cooperative homework teams increased their completion rate by less than 1%. Students in the cooperative homework teams increased their percentage correct on homework assignments by 10.4% while students in non-cooperative homework teams groups increased their percentage correct by only 3.3%. Although there was an increase in math achievement scores for both groups there was no significant difference between the two experimental conditions. Finally, post-hoc analysis suggested the cooperative homework teams were more effective for students in seventh and eighth grade than for those in the sixth grade. Using an intervention that combined aspects of cooperative learning, selfmanagement, and independent group-oriented contingencies, Olympia et al. (1994) employed an intervention that combined aspects of cooperative learning, self-management, and interdependent group-orientated contingencies within a regular classroom setting. Sixteen students in the sixth grade participated in this study. Selection was based on the following criteria: a completion rate of less than 50% of their homework in mathematics, or accuracy on returned homework averaging 50% or less during the previous marking period (at least six weeks); an unsatisfactory grade in mathematics during the previous marking period; and a score within the lower 50th percentile on a criterion-referenced group-administered math achievement test. Data were compared to that of 27 sixth grade students who were enrolled in the same mathematics section but who did not participate in the study. Following a baseline condition of thirteen days in which no interventions were employed, followed by a two-day training period, two teams were randomly


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assigned to one of two conditions: student-selected goal group; and teacherselected goal group. In the self-selection of performance criteria group, teams of students monitored, recorded, and self-reinforced homework completion and accuracy. Team points were awarded based on assignment completion and accuracy levels at a minimum of 80%. After three days, students were allowed to select their own performance levels. Individual and team points were determined based upon the criterion selected by each individual and team. In the teacher selection of performance criteria group, students followed the same procedure, but were expected to meet a target goal of 90% completion in order to earn team reinforcement. After five weeks of intervention, a three-week return to baseline condition was in effect. Regarding homework completion, there were improvements over baseline performance for a majority of the students participating in the homework teams procedures. A slight increase was seen in students who were allowed to set their own goal over those who were given a specified goal by the teacher. Only a 3% difference was found in accuracy rates across the two groups. On standardized measures of academic achievement and curriculum-based measures of classroom performance, students who participated in the self-management training demonstrated significant gains.

Self-Management and Goal Setting Four studies investigated the effect of self-monitoring and contingency contracting on homework-related performance. Trammel et al. (1994) designed a study to investigate the effect of a self-monitoring procedure on homework performance of students with learning disabilities. Eight students, in grades 7 through 10, who consistently failed to complete daily homework assignments in their regular classrooms, participated in the study. The baseline condition ranged between 12 and 22 days. The self-monitoring instruction phase was then initiated for each student and lasted 11 consecutive school days. Using an assignment sheet, students charted homework completion for each particular day, provided the assignments were completed with at least 70% accuracy. Teachers collected data on students’ reports of completion, and regular classroom teachers kept weekly logs of each student’s homework completion. The next phase involved the self-graphing of each student’s progress, based on homework-completion data. Based on the previous three days of the selfmonitoring, students set individual goals for homework completion during the next three days. Goals were required to exceed the average level of the preceding three days. After each three-day period, students were required to set another goal at least at the level of the previous goal. The maintenance phase involved the

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removal of the performance graph and the assignment sheet. Assignment sheets were completed at students’ own discretion without rewards or visual reminders. Teachers continued to collect data on the rate of assignments completed. The results of this study indicated that self-monitoring was successful in enhancing homework, enhanced by self-evaluation and self-graphing. Students’ regular classroom teachers reported an improvement in attitudes relating to homework, and students and parents also reported positive satisfaction. In a study conducted by Miller and Kelley (1994), the effects of goal-setting and contingency contracting on students’ homework performance were examined. Four parent-child dyads were developed based on a selection criteria that included the following: scores at least one standard deviation above the mean on the Homework Problems Checklist (HPC); homework accuracy rates below 80% or on-task rates below 70% during baseline observations; and average achievement in math and reading. The students, who were in grades 4 though 6, and their parents were interviewed. The parents completed the HPC and the Conners Parent Rating Scale (CPRS), and ranked the child’s subjects based on difficulty level. Teachers completed the Conners Teacher Rating Scale (CTRS) and were interviewed regarding their perceptions of each child’s homework performance. During the baseline condition, the most problematic assignments were completed first. Parents recorded the amount of time spent on homework problems in all academic subjects, as well as the type of problems completed, the number of each type completed, and the number of problems completed correctly. Following the baseline, each parent and child dyad negotiated contracts shat specified daily and weekly rewards contingent on achievement of homework goals and bringing all necessary materials home. Results of this study showed increased work accuracy for all subjects, and an increased level of stability in responding across treatment phases for three of the four participants. Only two of the participants demonstrated clear increases in the percentage of on-task behavior during treatment phases and marked decreases during baseline phases. Carrington et al. (1997) used a behavioral self-management technique to improve homework-related behavior. Forty-two non-special education students in grades two through eight were randomly assigned to one of two groups. One group was issued Winning at Homework (W-H) materials, a children’s self-management system for handling homework-related problems, based on alternation of brief periods of work and play. The second group did not receive the material until the end of six weeks. Before and after each six week period, parents of students in both groups completed questionnaires about the students’ homework problems. After learning W-H, parents rated their children’s homework problems as significantly improved. Both groups showed almost identical improvement in their ratings for


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homework behavior at the end of their six weeks of W-H practice, and parents reported the same positive behaviors almost one year later. Bryan and Sullivan-Burstein (1998) collaborated with a team of elementary and secondary general education and special education teachers to conduct three studies over a two-year period in which they assessed strategies to improve the spelling and math homework completion and weekly quiz performance of students with and without learning disabilities. In the first study, parents of 123 students provided information by completing the Homework Problem Checklist, and teachers provided information regarding students’ homework habits. Using that information, groups of students were identified as follows: students with learning disabilities who demonstrated homework problems; students with learning disabilities who did not demonstrate homework problems; average-achieving students who demonstrated homework problems; and average-achieving students who did not demonstrate homework problems. Of the students participating in this study, 14 were identified as having learning disabilities and no homework problems, and 29 were identified as having learning disabilities and homework problems. All teachers who participated in this study held either special education or elementary education certifications. All students who participated were in a general education classroom; students with learning disabilities received special education assistance. An eleven-week intervention research plan was developed based on teachers’ review of research and planning, and included four stages: baseline data collection (two weeks); reinforcement for completed homework assignments (three weeks), assignment of real-life homework assignments (three weeks); and reinforcement and real-life assignments (three weeks). Baseline and reinforcement conditions differed only in that on Fridays, students were given a reward if they had returned all assignments for that week. Homework assignments were given four times a week and a quiz was given once per week. During the real-life homework condition, assignments were designed to help students make a link between schoolwork and activities in their home lives. The real-life plus reward condition was identical except for the reintroduction of giving rewards on Friday for homework completion. Results indicated that students in the real-life plus reinforcement condition completed significantly more math and spelling homework than students in the baseline condition in math, and in the reinforcement, real-life, and combined conditions than in the baseline in spelling. Students with learning disabilities and homework problems performed significantly better on spelling tests than averageachieving students with homework problems, yet the same two groups differed from average-achieving students only in the baseline condition on math and spelling tests.

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The second study was developed to examine the impact of a homework planner on the homework completion of students with learning disabilities and average-achieving students with and without homework problems. Included in the 123 participants were 33 students with learning disabilities who had problems with homework and six students with learning disabilities who did not have homework problems. All students were given homework planners at the beginning of the school year, and faculty were given an inservice on how to use the planners. Two weeks of instruction were given to the students on how to use the planners, and parents were invited to sign the planners each night. Data analysis was based on homework completion during the baseline period in both years (study one and study two). Students with learning disabilities and homework problems but without homework planners completed less homework than all other groups. Average-achieving students with homework problems completed significantly more when they had planners than average-achieving students with homework problems who did not have planners. In the third study, using the same grouping characteristics as described above, the impact of graphing spelling and math homework completion was assessed. Following two weeks of baseline data collection, a two-week graphing condition was implemented. During this time, students completed graphs based on homework completion and timeliness of completion. Results indicated that graphing resulted in significant increases in spelling homework completion, but there were no significant effects for math homework completion.

Home-Based Self-Management Programs Callahan et al. (1998) reported the results of a ten-week study that included 26 sixth and seventh grade students identified as at risk and their parents, using an intervention of parent-facilitated self-management strategies. Parents and students were provided training sessions in which they learned how to implement components of self-management and positive reinforcement. During the baseline and intervention phases, students received math homework assignments Monday through Thursday. Parents and teachers were asked to deal with the math homework assignments as they would any other assignments. During the intervention phase, the parent-facilitated self-management procedures were implemented, which incorporated elements of self-management strategies: self-monitoring; self-recording; self-reinforcement; and self-instruction and goal setting. Parents provided positive reinforcements, based on a reinforcement menu developed by each parent-child team. Twenty of the 26 participants in this study completed increased amounts of homework assignments as a result of the intervention, and 22 of the 26


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showed significant increases over baseline levels in homework quality. Based on the analysis of students’ individual data collection forms, which included the assignment number, date assigned, whether or not the assignment was completed and returned the next school day, the number correct, and a space for general comments regarding student performance and parent participation, the single most important factor in determining whether or not the program was having a positive effect on students’ homework performance appeared to be the amount and quality of parent participation. Students whose parents implemented the strategies accurately and consistently experienced more success than students whose parents did not. Van Voorhis (2001) investigated the effects of teachers’ use of interactive and non-interactive science homework assignments on family involvement in student homework, homework completion and accuracy, student science achievement, and student and parent attitudes about science homework. A total of 253 students in grades six and eight participated in this study. Students in grade six were in low, average, and honors classes; at the eighth grade level, students were in average and honors classes. Six classes were assigned to a group that employed an interactive homework condition called Teachers Involve Parents in Schoolwork (TIPS), and four classes were assigned to a non-interactive (ATIPS) homework condition. The TIPS assignments were used to guide students to conduct interactions with family members and were assigned no more than weekly or twice a month. Students were given several days to complete the work. Results of this study indicated no significant differences in homework accuracy or homework return rates of TIPS and ATIPS students. However, the level of family involvement was a significant predictor of students completing more accurate assignments.

Assignment Completion Strategies Hughes et al. (2002) conducted a study designed to validate the effects of strategic instruction in a seven step assignment completion strategy for nine students with learning disabilities who were in grades six through eight. All students were participating in mainstream academic classrooms for at least three periods per day, and were identified by their teachers as having extreme difficulty completing and turning in homework assignments in those classes and disorganized in their approach to assignment completion. The intervention used for this study was called PROJECT Strategy, which focused on the sequence of necessary behaviors involved in assignment completion. Working through the steps of the strategy, students completed three forms: a monthly planner; a weekly study schedule; and an assignment sheet, all contained

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within a designated assignment notebook. The first-letter mnemonic device PROJECT represented the following steps: prepare your forms; record and ask; organize; jump to it; engage in the work; check your work; and turn in your work. All nine students began the baseline condition at the same time and were administered at least two simulation probes at that time. At least three general education classes were targeted for each student. The intervention included an instruction period that was scheduled four times a week for approximately 30 minutes per session that taught students to utilize PROJECT Strategy. Six weeks after strategy instruction ended, the instructor collected students’ assignment notebooks and randomly selected weeks to score. Results of this study were positive, indicating that students with learning disabilities can benefit from strategies designed to increase the rate and quality of homework assignment completion. During the baseline condition, students rarely used any of the strategy steps, earning an average of only 1.7% of their points. In contrast, during the instructional condition, students earned an average of 28% of their points, and 60% of their points during the maintenance phase. Homework completion yielded similar results, showing 54, 58, and 70%, respectively. The quality of homework assignments also increased, with students meeting the assignments requirements an average of 45% of the time during baseline, 56% of the time during instruction, and 66% of the time during the maintenance condition.

Summary Effects of Homework Eleven studies examined the impact of homework on areas such as rate of completion, rate of accuracy, and achievement. Rosenberg (1989) found that the effectiveness of math and spelling homework was maximized for middle school students when the rate of completion are percent correct are high, and moderate acquisition of the content taught. Using daily homework assignments designed for the purpose of practice of concepts taught, as well as bi-monthly achievement tests, Cobb and Peach (1990) found no significant differences in achievement between the control and experimental group, or between students with and without disabilities. In this study, neither rate of return nor accuracy of assignments were used as outcome measures. Two studies utilized homework teams as the intervention. Examining the effect of cooperative homework teams on mathematics performance for sixth, seventh, and eighth grade students with learning and emotional disabilities, O’Melia and Rosenberg (1994) found that cooperative homework teams created a positive interdependence among students, provided opportunities for social and academic


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reinforcement, and immediate grade improvements. Cooperative homework teams resulted in significant increases in the area of homework completion rates and rate of accuracy; however, they did not significantly influence achievement. In another study that incorporated individual and group contingency contracting, Olympia et al. (1994) observed improvements in the area of homework completion, compared to the baseline data, with a slight increase in those students who were allowed to set their own goals. Four studies employed self-monitoring techniques as strategies to improve homework completion rates, homework accuracy, and weekly quiz performance, and improve homework-related problems. Trammel et al. (1994) and Bryan and Sullivan-Burstein (1998) reported positive results in the area of homework completion. The students without disabilities who participated in Bryan and Sullivan-Burstein’s study were classified into two groups: average-achieving with homework problems; and average-achieving without homework problems. Students with learning disabilities and average-achieving students with homework problems benefited from the innovations more so than did the average-achieving students without homework problems. Using parent-child dyads, and the intervention of goal-setting and contingency contracting, Miller and Kelly (1994) reported increased levels of homework accuracy for all subjects and an increased level of stability in responding across treatment phases for three of the four participants. The treatment efficacy with regard to on-task behavior was less clear. Carrington et al. (1997) implemented a self-management strategy, Winning at Homework, with students who demonstrated homework-related problems. At the end of the treatment, parents of the participants rated their children’s homework problems as significantly improved. Results were similar after one year, showing long-term treatment efficacy. Bryan and Sullivan-Burstein (1998) developed a study that examined the impact of self-management on homework completion rate and weekly quiz performance. Students with disabilities were included in the study, as were average-achieving students with and without disabilities. Results of this study indicated that the intervention was more beneficial for students with learning disabilities and average-achieving students with homework problems than for average-achieving students without homework problems. Home-Based Self-Management Three studies utilized specific homework strategies for students with and without disabilities using home-based self-management strategies. Callahan et al. (1998) reported the results of a ten-week study that incorporated parent-facilitated selfmanagement strategies. Results showed that 20 of the 26 participants completed

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increased amounts of homework assignments following the intervention. Twentytwo of the 26 participants also showed increases in homework quality over the baseline. Students whose parents implemented the strategies accurately and consistently experienced more success than students whose parents did not. VanVoorhis investigated the benefits of interactive and non-interactive science homework assignments on family involvement in student homework, homework completion, and accuracy. No significant difference was found in completion or accuracy rates for interactive or non-interactive students. However, the level of family involvement was a significant predictor of accuracy. Hughes et al. (2002) conducted a study to validate the effects of strategic instruction in a seven-step assignment completion strategy. The strategy was taught in school but students were required to continue the execution of the strategy at home. The results of this study showed that 8 of the 9 middle school participants mastered the use of the strategy. In addition, the completion rates and homework quality improved for most of the students.

HOMEWORK PRACTICES Homework Practices Used by Teachers Three studies examined the practices used by teachers in relation to homework (Polloway et al., 1994; Salend & Schliff, 1989; Struyk et al., 1995). A total of 934 teachers were included in these studies, 88 of whom were special education teachers; the remaining teachers were general education teachers. Of the 88 special education teachers, all taught students with learning disabilities in self-contained or resource classrooms. Of the total pool of 672 teachers, 145 taught high school, 184 taught middle/junior high, 306 taught elementary, and 37 taught across grade levels. Salend and Schliff (1989) surveyed 88 elementary and secondary special education teachers of students with learning disabilities. Fifty-five of the teachers taught in self-contained classrooms, and 33 taught in the resource room. Six teachers taught primary classes (ages 6–8), 44 taught intermediate classes (ages 9–12), 29 taught junior high school students (ages 12–15) and 9 taught high school students (above 15 years old). The questionnaire used included eight scaled items where respondents selected one choice from a list of choices, and five categorical items, on which respondents could select all choices that applied. Results of this survey indicated that teachers are using homework as an instructional tool for a variety of reasons. Further, teachers were using a variety of homework practices such as varying the instructional goals and types of homework assignments, individualizing homework assignments, and presenting homework assignments visually well as orally. Despite the variety of practices


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utilized by teachers, 85% reported difficulties with students completing homework assignments. Using the “group mind” process, Polloway et al. (1994) developed a survey that focused on homework practices of general education teachers who taught students with disabilities. Included were nine questions on the following homework topics: frequency; amount; type; teaching strategies prior to and after assignment completion; homework adaptations; strategies for communicating with families; and professional responsibility for adaptations. Of the 441 teachers surveyed, 256 taught elementary school, 79 taught middle/junior high school, 69 taught high school, and 37 taught across school levels. In regard to the frequency of homework assigned, 43 teachers reported assigning homework one time a week at the elementary level (17.1%), 12 at the middle/junior high level (15.8%), and 7 at the high school level (10.5%). Teachers who assigned homework two to four times per week included, 159 (63.3%), 53 (69.7%), and 47 (70.1%), from the elementary, middle, and secondary levels. Twenty-eight elementary teachers (11.1%) reported that they assigned homework five times a week, whereas 7 middle/junior high teachers (9.2%) and 9 high school teachers (13.4%) also reported assigning homework on a daily basis. Teachers reported estimating the amount of homework per night, along the following time continuum: less than 30 minutes; 30–60 minutes; 1 to 1 21 hours; and more than 1 21 hours. One hundred fifty-one (63.4%) of the elementary, 47 (62.7%) of the middle school, and 35 (51.5%) of the secondary teachers reported that their homework required less than 30 minutes per night. In the category of 30–60 minutes, teacher reports were 85 (35.7%), 27 (365), and 31 (45.6%), for the elementary, middle, and secondary teachers, respectively. Less than 1% of the teachers reported that their homework required 1 hour or more except for two teachers (2.9%), who reported that the homework required 1 to 1 21 hours per night. When asked to identify the type of homework assigned most frequently, completion of unfinished work was the most common (144; 50.9%), followed by practice (63; 22.2%), enrichment (25; 8.8%), make-up (25; 8.8%), preparation for future work (16; 5.7%), and test preparation (10; 3.5%). Using a scale of 1 (not helpful at all) to 4 (very helpful), teachers rated preparation for tests and practice of skills already taught as most helpful in the category of perceived helpfulness of specific types of homework, with ratings in the somewhat to moderately helpful range. Rated as least helpful were enrichment activities and preparation for future classwork. Most in-class structures were rated as somewhat to moderately helpful, and no significant differences were found among elementary, middle, and high school teachers. Providing additional teacher assistance, providing a peer tutor for assistance, providing auxiliary aids, checking more frequently with students about assignments and expectations, and allowing alternative response formats were

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identified by teachers as somewhat to moderately helpful adaptations for students with disabilities. Elementary teachers rated giving fewer assignments, adjusting assignment length, and adjusting evaluation standards as more helpful than high school teachers. In regard to consequences for incomplete homework, teachers rated talking to students about why the assignment was not completed and assisting students in completing the assignment as most helpful. Putting students’ names on the board were rated as least helpful. Elementary teachers rated making adaptations in assignments as more helpful than middle and high school teachers, and lowering a student’s grade as less helpful. Teachers rated as somewhat to moderately helpful at all levels giving praise for assignment completion and corrective feedback in class. High school and middle school teachers rated recording performance in a grade book as more helpful than did elementary teachers. Elementary teachers rated requiring a parent’s signature on assignments, recommending homework strategies for parents to use at home, and sending home a note to parents as more helpful than did middle and high school teachers. A significant difference was found between elementary and high school teachers in regard to scheduling a conference with parents about homework and sending home assignment sheet/notebook. More than 60% of the respondents indicated that general education teachers were responsible for homework adaptations for students with disabilities. More than 26% indicated the responsibility falls to the special education teacher, and almost 12% said the responsibility was equal between general education and special education teachers. Both studies support the previous findings (e.g. Roderique et al., 1994) suggesting that homework is an integral part of the general education curriculum and that it must be considered carefully if students are to be successful in more inclusive classroom settings. In addition, like the results of Roderique et al. (1994), the results of these three surveys indicate that homework is assigned on a regular basis across all levels. Further, the amount of homework assigned increases as students progress through grade levels. The results of each study are based on teachers’ self-reports, which may deem the accuracy as questionable without validating the results through means such as direct observation or journals.

Views of Students Nine studies examined homework from the perspective of students, six using surveys, and three using interviews. The perspectives of 3,422 students in grades one through twelve were included in this grouping. Of the 3,422 students, 504


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had disabilities, including learning disabilities, emotional/behavior disorders, educable mental handicaps, and other cross-categorical handicaps. Vaughn et al. (1993) investigated the perceptions of 179 elementary, middle, and high school students regarding adaptations made by general education teachers. A total of 60 students with learning disabilities were included, as were 59 general education students identified as low average and 60 general education students identified as average/high-average. The instrument used in this study was the Students’ Perceptions of Teachers Scale (SPT), which was designed to elicit students’ perceptions of teachers’ adaptations on teaching methods and behaviors in seven key instructional areas, including homework. Using a 4-point rating scale, students are asked to rate the teaching behaviors of two fictional teachers, one who makes adaptations, and one who does not make adaptations. In general, students in this study indicated a preference for teachers who make adaptations. Students with learning disabilities indicated more preference for teachers who make adaptation on homework than did their peers in the low average and average/high-average groups. Although students in the learning disabilities group indicated a favorable view toward all students getting the same homework assignments, they viewed it less negatively than did students in the low average and average/high-average students. Students in middle school and high school indicated stronger preferences for everyone having the same homework than students in elementary school. Bryan and Nelson (1994) compared students at different levels in different settings on their reports of homework assignments and parental supportiveness of homework, and on their opinions regarding such issues as individualization of assignments and grading. Bryan and Nelson (1994) utilized the Elementary and Junior High Survey to obtain the perspectives of 1,527 students in grades four through eight. Of the 1,527 students, 1,242 were in regular education classrooms (RE), 234 were in resource room programs (RR) and 51 were in self-contained special education classrooms (SPED). The students ranged in age from 9 to 15 years old and were in grades four through eight. Disability areas represented by this population of students included learning disabilities, emotional and behavioral disorders, and educable mental handicaps. The Elementary and Junior High Survey was adapted from previous published research and included items that assessed how often students get homework each week (five days through no homework); how much time is spent doing homework each day (0 to 60+ minutes) in each subject area (reading, math, language arts, social studies, science, and spelling); type of homework assigned (e.g. more of the same work, special project to try at home); conditions under which they do their homework (e.g. while watching television, at school); type of family assistance (e.g. parent helps, parent corrects) while doing homework; teacher practices regarding the homework (e.g.

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grades, comments, sends notes home); consequences for failure to do homework (e.g. teacher sends note home, teacher scolds or gets angry); students’ opinions about how well they do on homework; and the individualization of assignments and grading. Teachers read each of the thirty-five items aloud to students. In regard to the amount of homework assigned, comparison of elementary students in RE and RR and junior high students in SPED indicated that elementary students in SPED were assigned less homework. In contrast, junior high students in SPED reported being assigned more homework than did junior high students in RE and RR. When comparing the results of students in RE and RR, elementary students reported being assigned more homework in reading and spelling than did junior high students in RE and RR, but less in language arts, science, and math. Elementary students in SPED reported spending less time doing math, social studies, and spelling homework than did elementary students in RE and RR, and junior high students in SPED. Elementary students in RE and RR reported spending more time on math and spelling, but less on social studies than did students in junior high RE and RR. Elementary students in SPED were less likely than students in RE and RR to be assigned weekend projects or special projects, and that elementary students in RE and RR had more projects than junior high students in RE and RR. Homework assignments that covered content not yet learned in school, were less likely to be assigned for elementary students in sped than students in RE and RR and junior high students in SPED. Elementary students in RE and RR and junior high students in sped were more likely to have time to work on homework assignments in school than were elementary students in SPED. Further, elementary students in RE indicated that they had more time during lunch to work on homework assignments than did elementary students in RR and SPED, and elementary students in RR indicated that they had more time during lunch to work on assignments than did elementary students in SPED. Bryan et al. (1995) used the Primary Homework Survey (PHS), a simplified version of the Elementary and Junior High Survey (Bryan & Nelson, 1994) to assess elementary and junior high school students’ experiences and perceptions in regard to homework. This instrument included thirty-five items that examined the frequency and types of homework, parental assistance, teacher grading, and students’ feelings about homework. A total of 809 students in grades one through three were surveyed, including 701 students in regular education classrooms (RE), 91 students in resource rooms (RR), and 17 in self-contained special education classrooms. Students’ disabilities included learning disabilities, social emotional disorders, behavior disorders,


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educable mental impairments, and cross-categorical disabilities. As teachers read each item out loud, students completed their individual surveys. When comparing RRs to those in REs, students in RRs reported getting a lot of homework each day, homework was dull and boring, homework was too hard, and homework was a waste of time. Students in RRs were more likely than students in REs to report that their teachers wrote comments on their homework, but were less likely to report that all students got the same homework. Students in RRs were also less likely to tell their parents about school, and had parents who were less likely to remind them to do their homework. Contrary to the results reported by Bryan and Nelson (1994), this study did not indicate significant differences in the types of homework assignments given to students in different settings. Students in SPEDs reported that they were less likely to finish their homework and that they did more poorly on homework than their peers in RRs and REs. When asked if their homework was too hard, 38% of the SPED agreed, and 27% of the RR students agreed, compared to just 14% of the RE students. In an effort to examine the homework practices and views of students with and without learning disabilities, Gajria and Salend (1995) used the Student Survey of Homework Practices. Forty-eight students with learning disabilities and 48 students without disabilities in grades 6 through 8, with a mean age of approximately 13.5 years were surveyed. The Student Survey of Homework Practices consists of 27 statements designed to examine students’ attitudes and practices with regard to completion of homework assignments (e.g. “I get easily distracted when I do my homework,” “Being with friends is more important to me than doing my homework,” and “After I finish my homework, I do not check to see that I have completed all of my assignments”). Ten statements on the Student Survey of Homework Practices were similar to those on the Homework Problem Checklist. For each of the 27 items on the Student Survey of Homework Practices, students were asked to rate the frequency of each statement using the same Likert-type scale as was used on the Homework Problem Checklist (never = 0; at times = 1; often = 2; and very often = 3). In their two groups of students, Gajria and Salend found mean ratings for students with learning disabilities ranged from 0.81 to 2.06, while the range was 0.39–1.38 for students without disabilities. Each rating of homework practice was higher for students with learning disabilities than for students without disabilities. Results indicate that students with learning disabilities experience attentional problems, such as allocating and maintaining attention to their homework assignments. This included items such as “lose interest in homework after 30 minutes,” and “easily distracted,” and “needs someone to assist during homework.”

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Similarly, in a study by Polloway et al. (1992), parents and teachers rated students with learning disabilities at least one point higher on items of a similar nature. Motivational difficulties were also reported to be significantly higher for students with learning disabilities than those without disabilities. Specifically, items such as “must be reminded to start homework,” “takes a long time to start homework,” “takes a long time to complete homework,” “complains about homework” and “is unsure about which homework to start first” were rated as significantly higher. These results are also similar to Polloway et al. (1992) in that the same population of students was rated higher than typically achieving peers by teachers and parents on such items as “complains about homework,” “avoids beginning homework tasks,” and “takes extremely long to complete tasks.” This study indicates that a third area, effective study skills, may greatly affect completion of homework assignments. Students with learning disabilities rated items such as “experience problems in estimating time for homework,” “fail to check if all homework is complete,” “quit doing homework if it appears difficult,” and “start with the easiest assignment, thereby have no time or energy to complete other tasks” as significantly higher than the ratings of the same items by their peers without disabilities. Difficulty in breaking up projects or lab reports into small segments to work on little by little was another factor noted by students with learning disabilities. However, both groups also reported some similarities of attitudes. Both groups reported that homework is not important, they sometimes forgot what homework was assigned, forgot to bring home needed materials from school, misunderstood assignments, procrastinated, failed to follow homework schedule, and offered excuses for incomplete assignments. Both groups also reported starting homework without first planning their study time or making a list of their assignments. Cooper et al. (1998) analyzed the results of 709 teacher/parent/student triads on the Homework Process Inventory, a survey instrument designed to assess aspects of homework practices and procedures. Different versions were designed, one each for lower- and upper-grade students, their teachers, and their parents. The Homework Process Inventory consists of five sets of questions designed to address each of the following: (a) whether teachers, students, and parents differed in their beliefs about the amount of homework assigned by teachers and the proportion completed by students; (b) whether each group’s attitude about homework was consistent; (c) the relationship between reports of amount of homework assigned and proportion completed to students’ standardized test scores and class grades; (d) teachers’ and students’ attitudes about homework compared to reports of the amount of homework assigned and completed; and (e) relationship between teacher and student attitudes toward homework and achievement. Results indicated generally weak correlations between reports of the amount of homework


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assigned and student achievement. Positive correlations were found between the portion of homework completed by students and achievement, and were stronger at the upper-grade levels than in the lower-grade levels. Nelson et al. (1998) designed a survey to examine the preferences of middle school students in regard to homework adaptations. Of the 211 seventh and eighth grade students who participated in this study, 17 were students with learning disabilities or behavior disorders, and 194 were students without disabilities. Using the Student Preferences for Homework Adaptations Questionnaire (SPHAQ), a 19-item, two-part questionnaire, Nelson et al. asked students to rate each homework adaptation on a Likert-type scale in terms of the degree to which they would like that adaptation to be made for them. The adaptations identified as most liked included “give assignments that are finished at school”; “allow a small group of students to work together to complete an assignment”; “allow extra credit”; “begin assignment in class and check for understanding”; “give reminders about due dates”; and “give shorter, more frequent assignments”. Students said they liked assignments that are finished at school because they believe they are able to get more help at school than at home. This includes the opportunity to work with peers. Checking for understanding and allowing extra credit assignments, according to students’ beliefs, improved performance in class. Reminders about due dates and frequent assignments help students with organization. Regarding least liked homework adaptations, “give fewer assignments than given to other students; “give different assignments than given to other students”; “require the use of an assignment notebook”; and “give shorter assignments than given to other students” ranked as the least preferable because they were inequitable and would negatively affect students’ emotions and self-concept. Several students specifically stated the opinion that students who are in need of different assignments should be in a different type of class. Overall, the results of this study indicated that middle school students have favorable perceptions of homework adaptations, in contrast with the findings of Vaughn, Schumm and Kouzekanani (1993); Vaughn, Schumm, Niarhos and Daugherty (1993); and Vaughn, Schumm, Niarhos and Gordon (1993). The difference between this study and the Vaughn et al. studies was that in the Nelson et al. study students were asked how they would like each adaptation made for them. In the other studies, students were asked to rate the degree to which they preferred each of two teachers, one who made adaptations in homework and one who did not. Two studies employed interviews to examine students’ experiences and perceptions regarding homework. Sawyer et al. (1996) interviewed ten students with learning disabilities to examine their experiences and perceptions related to the homework they receive in general education classes. All students were in

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grades nine, ten, eleven, or twelve, and were mainstreamed in at least one general education class for which homework was assigned on a regular basis. Students were asked nine open-ended questions, with 47 follow-up questions to be used as needed for further probing. Students identified a number of factors that make homework easy. The way the homework is assigned was identified as a major factor. Homework assigned earlier in the class period allowed for students to ask questions, make sure they understood the assignment before leaving class, and sometimes have an opportunity to get an early start at completing the assignment. In addition, students reported they liked it when teachers explain the assignments and provide examples. A second major factor students identified was available assistance, whether a general education teacher, special education teacher, coach, friend, or parent. A specific routine and structure was the third major factor identified by students as making homework easier. Although the structure and routine provided by teachers and family members was noted, students’ set personal routines and management was the most beneficial, and identified as the fourth major factor that made homework easy. Fifth, patience was the most preferred trait described most often by students as a personal trait of an adult who helped them with homework. The ability level of students was the sixth major factor identified that can make homework easy. When students feel they have a strong understanding of the material, or when the type of assignment or type of problems assigned is perceived as easy or manageable, students feel the homework is doable. The seventh factor identified reflected students’ attitude and effort toward the class, and was often affected by how they felt about their teacher of the particular subject. When they feel the subject matter is important or relevant to their personal life or needs, they are more likely to do the assignments. Regarding the factors that make homework difficult, the students in Sawyer et al. identified similar factors, although for different reasons. The first factor, the way in which homework is assigned, was identified by students who indicated that often times teachers assign homework at the end of the class period. They also reported that teachers assign it too quickly and sometimes orally only. Further, when the homework is assigned without explanation or examples, students become frustrated and less likely to attempt the assignments. The second factor, assistance for students, was salient because students felt that some teachers are not consistent in the language they use when teaching or assigning homework. They described teachers who appear to become annoyed when students ask questions, alleging that the students are not paying attention, rather than attempting to re-explain content or directions. Students experience similar problems at home when they do not have parents who are willing/able to help explain assignments or provide assistance to them.


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Students’ ability levels as well as their attitude and effort were the third and fourth major factors identified as making homework difficult. Certain content areas, skill area, and types or homework made assignments difficult. In addition, students reported a feeling of understanding of concepts while in class, but later at home, a feeling of lack of understanding, making assignment completion more challenging. Students’ dislike for the subject area, as well as their feelings of lack of assistance, made homework difficult, and resulted in students’ decreased tendency to attempt assignments. Nicholls et al. (1994) interviewed 48 elementary school students, twelve each from grades one through four, about schoolwork, homework, and personal learning projects. Of the 48 students 14 were identified as having learning disabilities. Students were individually interviewed, using questions designed to go beyond students’ initial reactions to homework and schoolwork. Students with learning disabilities indicated a lack of motivation as well as a lack of connection between life experiences and learning. When asked about the level of fulfillment attained from learning, more than half of the students with learning disabilities (eight) described almost all learning as an imposition. Of the remaining six students with learning disabilities, four indicated that school learning was an imposition. In comparison, of the thirty-four students without disabilities, only two said all learning is an imposition, and eleven said school learning was an imposition. Sixteen of the thirty-four students said all learning is living. Jakulski (2003) interviewed 12 students with emotional disabilities regarding their perceptions about homework in math classes. Some students were identified as having co-morbidity of disabilities (e.g. learning disabilities). Participants were all middle school students who were receiving math instruction in the range of continuum of settings from least restrictive to more restrictive in public schools ranging from: full-inclusion, team-taught math class (in which a special and general educator co-taught the class), self-contained class for learning disabilities, to self-contained classes for students with emotional disabilities. Students and their teachers were interviewed, observed in their math classes, and classroom artifacts including homework assignments and completion and correction rates were examined. Findings indicated that all students, regardless of placement, were unclear how homework impacted their final grades. Students had preferences regarding how homework is assigned and those preferences were not always compatible with teachers’ procedures for assigning homework. As the supportive nature of the classroom setting decreased when students moved from self-contained to team-taught to inclusive setting, teachers’ expectations of students with respect to homework and independent learning increased dramatically. Finally, and perhaps most significantly, students’ emotional issues significantly influenced students’ feelings about homework. These emotional issues surfaced at school and home and

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often carried throughout both settings in unpredictable fashions. These findings indicated that some teachers might unknowingly contribute to the challenges associated with homework completion for students with emotional disabilities, given the unpredictability and the severity of their emotional disability, teachers’ variability in style for distributing, collecting, and grading homework assignments. Moreover, students’ lack of knowledge with respect to how homework contributes to their grades and their lack of support system for completing challenging assignments underscores a need for continuum of service placements for such students.

Summary Homework Practices Used by Teachers Three studies examined the practices of general education teachers of students with and without disabilities. The results of these studies indicate that quality homework practices such as varying instructional goals and they type of homework assignments, individualizing homework, and presenting homework visually and auditorally can be beneficial. Supporting the findings reported by Roderique et al. (1994), teachers in these studies said that homework is assigned regularly across all levels of schooling and that the amount and frequency of the assignments increases with time. Consistent with the findings of Rosenberg (1989), data from Polloway et al. (1994) indicate that teachers’ feel that practice assignments are the most helpful, as opposed to assignments for the purpose of maintenance or content acquisition. Views of Students Through the use of surveys and interviews, eight studies examined the views of students with and without disabilities. Although some variance existed throughout the studies, results support the findings of previous studies that examined the views of teachers and parents in regard to the type and frequency of assignments given and the increase of them over time (e.g. Roderique et al., 1994). These studies also support and replicate the findings of Polloway et al. (1992) in regard to students with learning disabilities having problems allocating and maintaining attention to homework. These students also have more trouble with motivation. Regarding preferred adaptations, Nelson et al. (1994) found that middle school students had favorable perceptions of homework adaptations, which was in contrast to findings reported by Vaughn et al. (1993), who said that although students prefer adaptations in some areas, they did not have favorable perceptions of adaptations in the area of homework. The findings of Nelson et al. (1994) were


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also similar to those reported by Sawyer et al. (1996) in that students preferred in-class homework assignments because it gave them an opportunity for help.

HOMEWORK PROBLEMS Views of Parents and Teachers Four surveys compared the responses of special education and general education teachers and parents regarding homework problems experienced by students with and without disabilities. All of the studies used the Homework Problems Checklist (Anesko et al., 1987), which lists 20 statements about problems that may occur when a student does homework. For each statement, the respondent rates the frequency of each problem’s occurrence using an established scale (never = 0; at times = 1; often = 2; very often = 3). Checklist scores on this instrument can range from 0 to 60 points. The total sample of the studies included teacher and parent responses regarding 325 students. Of that, 124 students had learning disabilities, 102 students had behavior disorders, and 99 had no disabilities. Polloway et al. (1992) compared the homework problems experienced by students with learning disabilities to those of their nondisabled peers. The parent-teacher results from a total of 90 students were used, including one parent and one special education teacher for each of 45 students with learning disabilities, and one parent and one general education teacher for each of 45 students without disabilities. Matching the students’ approximate age, race, and sex, parent and general education teacher surveys were completed for 45 nondisabled students. The age range for the nondisabled students was 7–17 years, and 8–17 years for the students with learning disabilities. Students were grouped by age to allow for comparisons across groups. Results from the Homework Problems Checklist yielded teacher ratings for students with learning disabilities ranging from 0.64 to 1.9. Parent ratings for the same group ranged from 0.67 to 1.77. For nondisabled students, teacher ratings ranged from 0.04 to 0.69. Parent ratings ranged from 0.16 to 1.05. Students with learning disabilities were rated as experiencing significantly more homework problems than were there nondisabled peers. Compared to parents, teachers rated three items significantly higher for students in this group: “must be reminded to sit down and start homework,” “fails to complete homework,” and “forgets to bring back class assignments.” Parents rated two statements significantly higher than teachers: “procrastinates, puts off doing homework,” and “responds poorly when told by parent to correct homework.” These results indicate that students with learning

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disabilities experience more motivation and distractibility problems than their nondisabled peers. In a very similar study, Epstein et al. (1993) included a third group: students identified as having behavior disorders. The age ranges for each group were as follows: nondisabled students (n = 37) 7–16; students with learning disabilities (n = 37) 8–16; and students with behavior disorders (n = 37) 7–16. Data collection procedures were identical to those described in the Polloway et al. (1992) study. Special education students in both studies received special education services in special classes, resource settings, or through consulting teacher arrangements with general education teachers. For students with no disabilities, teacher ratings ranged from 0.05 to 0.73, and parent ratings ranged from 0.19 to 1.11. For students with learning disabilities, ratings were 78–1.97, respectively, and for students with behavior disorders, ratings were 0.68–2.24 and 0.89–2.27, respectfully. Teachers of students with learning disabilities and behavioral disorders, as well as parents of students with learning disabilities, identified “easily frustrated by homework assignment” as being the most problematic. “Procrastinates, puts off doing homework” was the item identified as the most problematic by parents of students with behavioral disorders, and second most problematic by parents and teachers of students with learning disabilities. As in the previous study, the results indicate that students with disabilities are perceived to have substantially more homework problems that their nondisabled peers. Teacher scores for the student with learning disabilities and behavioral disorders were significantly higher than those with no disabilities. These results were supported by those reported by Gajria and Salend (1995) who, using a survey instrument similar to the HPC, examined the homework practices and views of 48 students with disabilities and 48 students without disabilities. Two studies compared the problems of students with behavior disorders to those of their nondisabled peers (Epstein & Foley, 1995; Soderlund & Bursuck, 1995). Epstein and Foley (1995) conducted a study to investigate the homework performance of elementary, middle, and high school students with behavior disorders in contrast to their nondisabled peers. Using data collection procedures similar to those used by Polloway et al. (1992) and Epstein et al. (1993), the final sample included teacher- and parent-completed surveys for 42 pairs of students. For each group, there were 38 males and 4 females. The age range of students with behavior disorders was 7–18 years; for the nondisabled student group, 7–17 years. For students identified as behavior disordered, the total mean score for teacher ratings was 30.17, and 30.86 for parent ratings. For students without disabilities, the ratings were 8.29 and 11.29, respectively. Teacher and parents ratings indicate that students with behavior disorders were perceived to have significantly more


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problems than their nondisabled peers on each of the twenty items on the Homework Problems Checklist. In addition to significantly higher ratings as compared to the parent and teacher ratings of students without disabilities, the teachers and parents of students with behavioral disorders identified “easily distracted by noises or activities of others,” “daydreams or plays with objects during homework session,” and “easily frustrated by homework assignments” as three of the top five most problematic issues. Using only secondary students as the sample, Soderland and Bursuck (1995) compared the responses of parents and teachers of twenty students with behavior disorders and twenty students with no disabilities. The age range of students with disorders was 12–18; for nondisabled students the age range was 12–17. Like Epstein and Foley (1995), results indicate parent and teacher perceptions are that significantly more problems are experienced by students with behavior disorders than their nondisabled peers. For students with behavioral disorders, the total score mean for teacher and parent ratings were 30.60 and 31.50, respectively. For nondisabled students, the total score mean for teacher ratings was 9.85, and 12.25 for parent ratings. For individual items, the mean teacher ratings ranged from 0.85 to 2.30 for students with behavior disorders. The parent ratings of the same group ranged from 1.15 to 2.00. Teacher and parent mean ratings for nondisabled students were 0.15–0.79 and 0.21–1.05, respectively. Similar to the results reported by Epstein and Foley (1995), the three most significant problems identified by teachers were “easily distracted by noises or activities,” “responds poorly when told by parent to do homework,” and “procrastinates, puts off doing homework.” “Procrastinates, puts off doing homework” and “easily distracted by noises or activities” were also identified by parents as being the most significant problems.

Summary Views of Parents and Teachers Four surveys compared the responses of special education and general education teachers and parents regarding the homework problems experienced by students with and without disabilities. All studies utilized the Homework Problem Checklist as the primary data tool. Polloway et al. (1992) confirmed the existence of homework difficulties experienced by students with learning disabilities. Specifically, the study reported that students with learning disabilities experience more difficulties with motivation and distractibility than their nondisabled peers. Three studies (Epstein & Foley, 1995; Epstein et al., 1993; Soderlund & Bursuck, 1995) expanded upon the study by

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Polloway et al. (1992) by including parents and teachers of students with emotional disabilities in the sample. In all three studies, both special education groups were reported to have experienced more significant homework difficulties than their nondisabled peers, supporting the findings of Salend and Schiff (1989). Although a significant difference between the two special education groups was not evident, the total scores of students with emotional disabilities did exceed the scores of students with learning disabilities, supporting the results of Gajria and Salend (1995). The findings of Soderlund and Bursuck, who examined only the problems of middle and high school students with emotional disabilities compared to their nondisabled peers, suggest that the homework problems of students with emotional disabilities are far more pervasive than same-age peers without disabilities. This finding supports those of Epstein et al. (1993).

HOME-SCHOOL COMMUNICATION PROBLEMS Identification of Problems Five studies were designed for the purpose of identifying home-school communication problems. Jayanthi et al. (1995) used focus groups, designed to gain greater insight into the attitudes, perception, and beliefs of parents and students in regard to the communication problems that exist between home and school. The participants were parents and teachers of students with disabilities in grades five through twelve. Primary and follow-up questions were asked of all participants. Participants identified several major homework problems, as well as five areas of contributing factors to the problems. Problems regarding the initiation, timeliness, frequency, consistency, follow-through, and clarity and usefulness of communication were identified as the five most troublesome areas. All participant groups identified a failure to initiate communication as a major problem. Both groups of teachers felt that this was more of a problem with parents of students with disabilities than parents of students without disabilities. Several factors contributed to the communication problems, according to the participants, including a lack of time and opportunity; a lack of knowledge, understanding, and awareness; and differing attitudes, abilities, and behaviors; differing parent/teacher perceptions and expectations. Other factors contributing to homework communication problems identified by parents and teachers included IEP meetings, parental priorities, and telephones, poor teacher-to-teacher communication. Struyk et al. (1996) developed a survey focused on the identification of homework communication problems. One hundred thirty-eight surveys from


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high general education teachers were utilized for this study. When asked to rank order communication problems between parents and teachers (both general education and special education), high school teachers indicated as most serious the feeling that parents of students with disabilities did not communicate with general education teachers often enough. When asked to rank communication problems between teachers, of most concern to the general education teachers was that special education teachers did not communicate with them early enough in the school year regarding homework. Regarding the availability of teachers to communicate with parents, the high school teachers expressed that they had too many students with disabilities in their general education classes, and that the amount of paperwork and record keeping required of them limit the amount of time available to communicate to special education teachers and parents. Also noted was frequent conflicts in availability times when trying to reach parents. In regard to the knowledge level of the general education high school teachers regarding students with disabilities, the teachers indicated that they did not have a clear understanding of their responsibility to communicate with the special education teachers about homework, and that they were not aware that they were directly responsible for communicating with parents of students with disabilities regarding homework. The majority (74.9%) of the high school general education teachers indicted that they had similar expectations regarding parents’ responsibilities related to homework. Similarly, 61.8% indicated that their expectations about student performance on homework were like those of their special education counterparts. In regard to parent communication practices, 74.9% indicated that the general education teacher was responsible, and 64.6% indicted that they agreed that communication was often lost or intercepted before getting to the parent. Buck and Bursuck (1996) developed a survey that included 14 questions related to homework problems, with a primary focus on communication. Of these, seven were forced-choice, six required comparative rating of choices, and one used a Likert-type scale. A total of 576 teachers responded, representing all geographic regions of the United States. Respondents taught students with disabilities (learning disabilities 91.3%; emotional disabilities 70%) in elementary, middle, and high schools, and worked in collaborative/consultation, resource, self-contained, and itinerant positions. Data provided by the teachers indicated that many of them worked in cross-categorical settings or with students who had multiple diagnoses. Teachers were asked to rank-order items for each topic area identified (i.e. parental skills and effort; parental attitudes about homework; general education teachers’ communication about homework with special education teachers). For the first topic, parental skills and effort, identified as most serious by the teachers

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were lack of parental follow through, untimeliness of communications, and low frequency of communications. For the second topic, parental attitudes toward homework, ranked most serious were parents’ failure to care about their child’s homework, parents’ belief that homework is not as important as other school issues, and parents not wanting to communicate with teachers. For the third topic, how well general education teachers communicated with special education teachers about homework, teachers identified lack of initiation of communication, untimeliness of communication, and a low frequency of communication from general education teachers as the most seriousness. In regard to the ability of general education teachers to perform their role in the communication process, teachers ranked the general education teachers’ lack of awareness of the abilities/disabilities of students with disabilities who are mainstreamed in their classes. Teachers also ranked as most serious the amount of paperwork and record keeping as hindrances to communication time with parents. Almost 74% of the respondents indicated that communications sent home to parents were often lost or intercepted by the students. Almost 73 and 51% of the respondents believed that general education and special education teachers have similar expectations regarding the expectations of parents’ roles, as well as the two groups of teachers’ expectations of students with disabilities in terms of homework. Nearly 62% of the teachers responded that general education and special education generally agreed about who is responsible for communication with parents about students’ homework, with 42% indicating their belief that the responsibility for this is shared by both teachers. Epstein et al. (1997) developed a survey that focused on communication problems associated with homework. The survey included thirteen questions: seven forced-choice; one Likert-scale; and five requiring respondents to rank-order problem statements. A total of 502 general education teachers responded to this survey, representing all geographic regions of the United States, and all grade levels. The first communication problem area focused on how often and how well parents and general education teachers communicate about homework. The most serious problems identified by general education teachers were lack of parental follow-through, lateness of communication about problems, and the frequency of communication. In regard to the parent attitudes about homework, most seriously ranked were lack of importance placed on homework by parents, and defensiveness of parents. When asked about the role of the special education teacher, ranked most serious were not beginning communication with general education teachers early enough, and not beginning communication with general education teachers often enough. Regarding their ability to communicate with parents, the general education teachers identified as most problematic the reduced time available for communication


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due to paperwork and record keeping, the conflict of time availability between teachers and parents, and the large numbers of students with disabilities in their classes. In regard to the knowledge base of general education teachers, a lack of knowledge about the abilities/disabilities of special education students, and the lack of knowledge about adaptations for homework were identified as most serious. The majority of the respondents (79.1%) believed that general and special education teachers have similar expectations of parents, and 64.1% believed that the two groups of teachers had similar expectations about students with disabilities with respect to homework. As for who is responsible for communication with parents, 76.4% indicated that the two teacher groups agreed, and 65.2% indicated a belief that communication was often lost or intercepted by the student before getting to a parent. Using a national survey, Munck et al. (2001) investigated the perceptions and experiences of parents of children with and without disabilities regarding homework load and problems related to communication with teachers. Specifically, questions regarding how often and how well general education teachers in mainstreamed classes communicate about homework; the knowledge, attitudes, and behaviors of general education teachers regarding students’ individual needs; determining who is primarily responsible for communicating about day-to-day homework requirements; the expectations of general education teachers about what students should do in respect to homework; and the probability of communications sent from teachers via students being received by parents. Three hundred and forty-eight parents participated in this study, eighty-three of whom were parents of students with disabilities, including learning disabilities (72%), emotional disabilities (15%), and other disabilities. Forty-one percent of those parents indicated that their children were in general education classes for the majority of the school day. Two instruments were used: Homework Problem Survey I (HPS I) for parents of students with disabilities, and Homework Problem Survey II (HPS II) for parents of students with no disabilities. With the exception of two demographic questions about disabilities included on the HPS I, both surveys were identical, containing fourteen close-ended questions asking for information regarding the student and homework, the ranking of homework problems according to their seriousness, and parents indicating that they agreed or disagreed with statements about their child’s teacher or homework. In regard to the category of homework assignments, parents of special education students indicated most frequently that homework was assigned five nights per week, compared to parents of students without disabilities, who indicated that homework was assigned four nights per week. Both groups of parents indicated that students spend approximately the same amount of time on homework, but

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special education parents reported spending approximately sixteen minutes more per night assisting their children than did parents of nondisabled students. With regard to communication problems, both groups of parents indicated a lack of communication initiation and infrequent communication as the most serious problems identified in the survey, with special education parents indicating a feeling of more seriousness than general education parents. Contrary to the views of general and special educators (Buck et al., 1996; Epstein et al., 1997) parents did not identify lack of time and availability as serious problems. Parents in both groups also agreed upon the most serious problems related to teachers’ knowledge, attitudes, and behaviors. Parents indicated the most serious problems being that teachers do not know enough about their children’s needs to help them with homework, and that they do not know how to adapt homework so they children can get it done. Forty-three percent of the special education parents and 20.5% of the general education parents indicated that communications sent from teachers to the home are often lost or intercepted by the child, and 38% of the special education parents indicated an uncertainty about whether to contact the general education teacher or the special education teacher regarding assignments from mainstream classes. Overall, the results of this study support prior research in which a lack of initiation of communication, its frequency, and educators’ lack of knowledge regarding students’ disabilities and appropriate homework adaptations. . . .

Recommendations for Improving Home-School Communication Four studies considered recommendations for improving home-school communication. In a study designed to generate recommendations for solving communication problems between home and school related to homework for students with disabilities in their general education classes, Jayanthi et al. (1995) used focus groups as the primary data collection method. A total of 32 participants, including 8 parents of students with mild disabilities, 13 special education teachers of students with disabilities, and 11 regular education teachers who had students with disabilities in their classes. The parents and teachers represented students in grades 5 through 12. Primary and secondary questions were asked of participants, based on previous exploratory research (Jayanthi et al., 1995) on homework communication problems. The recommendations suggested by the participants fell into five themes: time and opportunity, knowledge, attitudes and abilities, bypass, and other. In the area of time and opportunity, the use of technology was suggested to make parents and teachers more accessible to each other, as was having parent-teacher conferences


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in the evening. Regarding the knowledge theme, a recommendation concerning logistical information (such as who, when, and where to contact each other) was made, and the modes for communicating information on a regular basis was also discussed. Participants felt that face-to-face communication was more useful and productive than written communication. The recommendations made in the theme of attitudes and abilities suggest ways to overcome barriers to communication. For example, the need for more positive communication was identified by parents and teachers as important, as was the need for increasing student responsibility for homework assignments. The fourth theme, bypass, include recommendations that suggest skirting the communication issue by utilizing strategies that reduce or avoid the need for home-school communication. Recommendations included not giving homework, modifying homework, providing peer tutors, and using community resources. Bursuck et al. (1999) surveyed 673 special education teachers from across the United States. The teachers represented all grade levels, most disability areas (learning disabilities 91.1%; emotional disabilities 71.8%), and a variety of teaching positions (consultative/collaboration, self-contained, etc.). The survey developed by Bursuck et al. (1999) included ten questions: two addressed the amount of training teachers received in homework communication strategies; one used a Liker-type scale to rank their skill in collaborating with general educators and parents in the area of homework; seven asked teachers to rank-order recommendations for improving homework communication in different areas (i.e. student responsibility, general education and special education communication. In regard to efforts made by general education teachers to communicate with parents, the special education teachers, across all grade levels, identified the use of daily student assignment books as the most important. This supports the findings of others (Bryan & Sullivan-Burstein, 1997; Jenson et al., 1994; Trammel et al., 1994). Also ranked as important, and similar to results found by Epstein et al. (1998), were attending IEP meetings and other conferences and meetings, reminding students of due dates on a regular basis, and providing parents at the beginning of the year with a list of suggestions for assisting their children with homework. In regard to the efforts parents make to communicate with their children and the teachers, teachers ranked having parents check with their children daily about homework as the most important recommendation. Also identified as important were regularly attending conferences, and signing their child’s assignment book daily. Having the assignment notebook signed by the parent, however, was ranked higher by the elementary teachers than by the middle school teachers, and higher by the middle school teachers than by the high school teachers. Telephone homework hotlines, computerized student progress reports, and audiotaped assignments accessible by telephone were ranked as the most

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important recommendations in regard to the effectiveness of various types of technology designed to increase communication between parents and general education teachers. In regard to strategies designed to increase the level of students’ responsibility for their own homework, the special education teachers identified the maintenance of a daily assignment book as the most important strategy. Teachers also ranked two items, that students should ask the teacher for help if they do not understand an assignment, and students should learn to manage their time more efficiently, as important recommendations in this category. As to the effects of increased homework opportunities on student performance, after-school help sessions and peer tutoring programs were ranked highest. The use of community volunteers to help students with homework, study halls during school hours, and student clubs to recognize homework completion were also ranked as important. When communicating with general education teachers, the special educators ranked providing information about the students’ strengths and weaknesses and sharing information about effective homework adaptations as most important. In an effort to determine the perceived effectiveness of recommendations for improving home-school communication on homework, as identified in a study using focus group interviews by Jayanthi et al. (1995), Epstein et al. (1999) developed a survey that included eleven questions: three forced-choice; seven requiring rankings on a series of problem statements; and one Likert scale question. The responses from a total of 639 general education teachers who also teach students with mild disabilities in their classrooms were used. In regard to communicating with parents about homework, 189 (30%) of the respondents indicated that the general education teacher should assume the primary responsibility, while 177 (28%) said the responsibility should be assumed by the special education teacher. Two-hundred-sixty-seven respondents (42%) indicated that homework communication should be the joint responsibility between general education and special education teachers. When asked to rank order recommendations for how general education teachers can communicate with parents and students, teachers ranked highest: (a) requiring that students keep daily assignment books; and (b) providing parents at the start of school with a list of suggestions on how parents can assist homework. Middle and high school teachers ranked the requirement of keeping a daily assignment book as the most important, while elementary teachers ranked the recommendation as second most important. Although the next two highest-ranked items were: (a) “general education teachers should remind students of due dates on a regular basis”; and (b) “general education teachers should attend IEP meetings and all other conferences between schools and parents,” elementary teachers ranked them as being slightly more effective.


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Regarding parents’ efforts to communicate with teachers and their children, teachers at all levels ranked as highest, parents should check with their child about homework daily. Ranking second highest for elementary and high school teachers, and third highest for middle school teachers was, “parents should regularly attend parent-teacher conferences,” and ranked third highest for elementary and high school teachers and second highest for middle school teachers was, “parents should sign their child’s assignment book daily.” Across all teaching levels, the highest ranking item to adapt policies to facilitate communication was, “schools should provide release time for teachers to communicate with parents on a regular basis.” Ranked second highest for elementary and middle school teachers and third highest for high school teachers was, “schools should schedule parent-teacher conferences in the evenings for working parents.” Ranked third highest for elementary and middle school teachers and second highest for high school teachers was, “schools should require frequent written communication from teachers to parents about homework.” In the area of increased student responsibility, teachers rank-ordered each of the four items identically: (a) students should keep a daily assignment book; (b) students should ask the teacher for help if they do not understand an assignment; (c) students should learn how to manage their time more effectively; and (d) students should attend parent-teacher conferences. Elementary teachers ranked students’ attendance at parent-teacher conferences as more important than did middle and high school teachers. When asked to rank-order seven statements strategies that would enhance the communication between general and special education teachers, the recommendations ranked highest were: (a) special education teachers should provide general education teachers information about the strengths and weaknesses of students with disabilities; and (b) general and special education teachers should communicate to one another their views of staff roles and student expectations about homework. In a study developed to validate the recommendations reported by the focus groups of Jayanthi et al. (1995), Harniss et al. (2001) surveyed 120 parents of students with disabilities and 400 parents of students without disabilities. The mean age of the general education students and special education students were 10.95 years and 13.2 years, respectively. Of the 120 parents of students with disabilities, 78% were parents of students with learning disabilities, 13% were parents of students with behavior disorders, and 10% were parents of students with other disabilities. The surveys used in this study were the Homework Recommendation Survey I (HRS I) for parents of students with disabilities, and the Homework Recommendation Survey II (HRS II) for parents of students without disabilities.

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The surveys were based on previous exploratory research conducted to identify recommendations for homework communication problems. Each survey was identical, and included 14 close-ended questions, except two questions dealing specifically with disability issues on the HRS I. With respect to the frequency with which homework is assigned, two-thirds of the parents of students with disabilities indicated that homework is assigned three or four nights per week, and parents of students without disabilities indicated homework is assigned two or three times per week. In regard to the amount of time spent on homework each night, parents of students with disabilities reported an average of 91.82 minutes per night, compared to 73.19 minutes per night reported by parents without disabilities. Parents of students with disabilities reported spending more time each evening helping their children with homework, compared to parents of students without disabilities (53.49 minutes and 28.47 minutes, respectively). When asked to rank items describing ways teachers could improve home-school communication, both groups ranked as most effective the item stating that teachers should require that students keep a daily assignment book. Parents of students with disabilities ranked second the item stating that teachers should attend school meetings and all other conferences between schools and parents, while parents of students without disabilities ranked it fifth out of the six items. Parents of students without disabilities ranked as second most effective the item stating that teachers at the beginning of the year should provide parents with a list of major course assignments for the year, while parents of students with disabilities ranked the item as third most effective. When asked to rank the actions parents could take to improve communication, both groups ranked the items from most effective to least effective in this order: (a) parents should check with their child about homework daily; (b) parents should regularly attend parent-teacher conferences; (c) parents should provide teachers with their expectations about home-school communication to teachers; (d) parents should sign their child’s assignment book daily; (e) parents should provide teachers with their telephone numbers and tell teachers when and where they can be reached; and (f) parents should call teachers early in the morning so that teachers can call back before the end of the school day. Although the rankings were identical, parents of students with disabilities ranked the recommendation for parents to check with their child daily about homework as less effective than did parents of students without disabilities, and parents of students without disabilities ranked as somewhat less effective than did parents of students with disabilities the recommendation for parents to provide teachers with their expectations. In regard to the actions a school could take to improve home-school communication, both groups ranked them similarly. Ranked from most effective to


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least effective were: (a) schools should require frequent written communication from teachers to parents about homework, such as monthly progress reports; (b) schools should schedule parent-teacher conferences in the evenings for working parents; (c) schools should provide release time for teachers to communicate with parents on a regular basis; (d) schools should provide incentives for teachers who are able and willing to improve home-school communication; (e) schools should designate one person in the school for parents to communicate with about homework; and (f) schools should provide parents with a list of teachers with home and work phone numbers, and how and when to contact them. Both groups of parents ranked the recommendation of scheduling parent-teacher conferences in the evenings for working parents, although parents of children without disabilities ranked it significantly more important than did parents in the other group. And, parents of students with disabilities ranked as significantly higher the recommendation that there be one person designated to communicate with parents about homework, than did the parents of students without disabilities. Both groups of parents ranked in the same order the strategies to increase student responsibility. Ranked highest was the to teach children to ask for assistance from the teacher if they did not understand an assignment. Ranked as second most effective was teaching children how to manage their time more effectively. No statistical differences were found between groups. The final question on this survey asked parents to rank thee supports schools could provide to improve homework. Both groups rank ordered the items identically, and no statistical differences were found between groups. Ranked as the two most effective were: (a) “schools should schedule after-school sessions where students can go to get extra help on their homework”; and (b) “schools should begin peer-tutoring programs, where more-able students help less-able students do their homework.”

Summary Identification of Problems Using focus groups and various surveys, six studies were designed for the purpose of identifying communication problems between home and school, especially in relationship to homework for students with disabilities in general education classes. Jayanthi et al. (1995) used focus groups that included special education and general education teachers and parents to identify six major homework-communication problems: initiation; frequency; timing; consistency; follow-through; and clarity and usefulness of the communication. Communication problems between general education and special education teachers were noted.

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Epstein et al. (1997), in a survey of general education teachers of students with disabilities, supported the results of Jayanthi et al. (1995). In both studies, general education teachers ranked the low frequency of communication initiated and maintained by teachers and parents of students with learning disabilities as particularly problematic. In addition, teachers in both studies reported their belief that parents of students with disabilities do not follow through on what they say they will do. Regarding communication between home and school, Munck et al. (2001) found that parents did not view a lack of communication with teachers as serious, which contradicts findings of Buck et al. (1996) and Epstein et al. (1997). Recommendations for Improving Home-School Communication Jayanthi et al. (1995) used focus groups to generate recommendations for improving home-school communication. From their work, five themes of recommendations emerged: time and opportunity; knowledge; attitudes and abilities; bypass; and other. The use of technology was suggested as a way to make parents and teachers more accessible to each other, and the need for modes of communicating information on a regular basis was discussed. Special education teachers in the study conducted by Bursuck et al. (1999) identified the use of a daily assignment book as the most important way to bridge communication between home and school. This supports the findings of others (Bryan et al., 1997; Jenson et al., 1994; Trammel et al., 1994). Like Bursuck et al. (1999), Epstein et al. (1999) reported that when asked how teachers and parents can communicate, teachers ranked the use of daily assignment books as the highest, supporting previous research findings, as well (Bryan et al., 1997; Jenson et al., 1994; Trammel et al., 1994). Results of this study support and elaborate on the three conclusions reported by Jayanthi et al. (1995).

CONCLUSIONS The literature reviewed in this chapter suggests that there is general agreement among parents, teachers and students that homework is assigned regularly across curriculums and assignments increase in length with the increases in grade levels. The literature also confirms that students with disabilities experience more difficulties associated with homework than do their same-age peers who do not have disabilities. Of the 36 studies reviewed in this chapter, eight studies considered homework from the perspective of students, and only three included students with emotional disabilities for the purpose of comparing their problems to those of students with learning disabilities and/or their nondisabled peers. Of the eight that considered


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homework from the perspective of students with learning disabilities, two (Nicholls et al., 1994; Vaughn et al., 1996) used an interview format that allowed students to provide meaning and depth in their responses. Both studies, while useful, included students with learning disabilities only, rather than also including students with emotional disabilities. Further, the results of one (Nicholls et al., 1994) are extremely limited because the elementary students interviewed were from economically advantaged homes and included no diversity. Three studies compared the homework problems of students with emotional disabilities to those of students with learning disabilities and/or nondisabled peers (Epstein & Foley, 1995; Epstein et al., 1993; Soderlund & Bursuck, 1995). The data from all three studies, based on the reports of teachers and parents, indicate that students with disabilities experience more problems than do nondisabled peers. Further, results indicate that the problems experienced by students with emotional disabilities are even more extreme than those experienced by students with learning disabilities. Even though it seems clear that students with disabilities experience more difficulties associated with homework than do students without disabilities, there is still little information derived directly from students with emotional disabilities. Given the difficulties that we know students with emotional disabilities face in regard to homework, it is important, and therefore warranted, to further examine homework from their perspective.

REFERENCES Bryan, T., & Nelson, C. (1994). Doing homework: Perspectives of elementary and junior high school students. Journal of Learning Disabilities, 27, 488–499. Bryan, T., Nelson, C., & Mathur, S. (1995). Homework: A survey of primary students in regular, resource, and self-contained special education classrooms. Learning Disabilities Research & Practice, 10, 85–90. Bryan, T., & Sullivan-Burstein, K. (1998). Teacher-selected strategies for improving homework completion. Remedial and Special Education, 19, 263–275. Buck, G. H., & Bursuck, W. D. (1996). Homework-related communication problems: Perspectives of special educators. Journal of Emotional & Behavioral Disorders, 4, 105–114. Bursuck, W. D., Harniss, M. K., Epstein, M. H., Polloway, E. A., Jayanthi, M., & Wissinger, L. M. (1999). Solving communication problems about homework: Recommendations of special education teachers. Learning Disabilities Research & Practice, 14, 149–158. Callahan, K., Rademacher, J. A., & Hildreth, B. L. (1998). The effect of parent participation strategies to improve the homework performance of students who are at risk. Remedial and Special Education, 19, 131–141. Carrington, P., Lehrer, P. M., & Wittenstrom, K. (1997). A children’s self-management system for reducing homework-related problems: Parent efficacy ratings. Child & Family Behavior Therapy, 19, 1–22.

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Cobb, S., & Peach, W. (1990). The effects of homework on academic performance of learning disabled and nonhandicapped math students. Journal of Instructional Psychology, 17, 168–171. Cooper, H. (1989). Synthesis of research on homework. Educational Leadership, 47, 85–91. Cooper, H. (1994). The battle over homework: An administrator’s guide to setting sound and effective policies. Thousand Oaks, CA: Corwin Press. Cooper, H., Lindsay, J. J., Nye, B., & Greathouse, S. (1998). Relationships among attitudes about homework, amount of homework assigned and completed, and student achievement. Journal of Educational Psychology, 90, 70–83. Cooper, H., & Nye, B. (1994). Homework for students with learning disabilities: The implications of research for policy and practice. Journal of Learning Disabilities, 27, 470–479. Cooper, H., & Valentine, J. C. (2001). Using research to answer practical questions about homework. Educational Psychologist, 36, 143–153. Epstein, M. H., & Foley, R. M. (1995). Homework problems: A comparison of students identified as behaviorally disordered with nonhandicapped students. Preventing School Failure, 40, 14–18. Epstein, M. H., Kinder, D., & Bursuck, B. (1989). The academic status of adolescents with behavioral disorders. Behavioral Disorders, 14, 157–165. Epstein, M. H., Munk, D. D., Bursuck, W. D., Polloway, E. A., & Jayanthi, M. (1999). Strategies for improving home-school communication about homework for students with disabilities. The Journal of Special Education, 33, 166–176. Epstein, M. H., Polloway, E. A., Buck, G. H., Bursuck, W. D., Wissinger, L. M., Whitehouse, F., & Jayanthi, J. (1997). Homework-related communication problems: Perspectives of general education teachers. Learning Disabilities Research & Practice, 12, 221–227. Epstein, M. H., Polloway, E. A., Foley, R. M., & Patton, J. R. (1993). Homework: A comparison of teachers’ and parents’ perceptions of the problems experienced by students identified as having behavioral disorders, learning disabilities, or no disabilities. Remedial and Special Education, 14, 40–50. Gajria, M., & Salend, S. J. (1995). Homework practices of students with and without learning disabilities: A comparison. Journal of Learning Disabilities, 28, 291–296. Gill, B., & Schlossman, S. (1996). “A sin against childhood”: Progressive education and the crusade to abolish homework, 1897–1941. American Journal of Education, 105, 27–66. Harniss, M. K., Epstein, M. H., Bursuck, W. D., Nelson, J., & Jayanthi, M. (2001). Resolving homework-related communication problems: Recommendations of parents of children with and without disabilities. Reading & Writing Quarterly, 17, 205–225. Hughes, C. A., Ruhl, K. L., Schumaker, J. B., & Deshler, D. D. (2002). Effects of instruction in an assignment completion strategy on the homework performance of students with learning disabilities in general education classes. Learning Disabilities Research & Practice, 17, 1–18. Jakulski, J. (2003). Through their eyes: The perspectives of students with emotional disabilities in regard to homework. Unpublished doctoral dissertation, George Mason University: Fairfax, VA. Jayanthi, M., Nelson, J. S., Sawyer, V., Bursuck, W. D., & Epstein, M. H. (1995). Homeworkcommunication problems among parents, classroom teachers, and special education teachers: An exploratory study. Remedial and Special Education, 16, 102–116. Jayanthi, M., Sawyer, V., Nelson, J. S., Bursuck, W. D., & Epstein, M. H. (1995). Recommendations for homework-communication problems. Remedial and Special Education, 16, 212–225. Jenson, W. R., Sheridan, S. M., Olympia, D., & Alfreds, D. (1994). Homework and students with learning disabilities and behavior disorders: A practical, parent-based approach. Journal of Learning Disabilities, 27, 538–548.


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Kavale, K. A., Forness, S. R., & Duncan, B. (1996). Defining emotional disturbance or behavioral disorders: Divergence or convergence. In: T. E. Scruggs & M. A. Mastropieri (Eds), Advances in Learning and Behavioral Disabilities (Vol. 10, Part A, pp. 1–45). Greenwich, CT: JAI Press. Keith, T. Z., & Page, E. B. (1985). Homework works at school: National evidence for policy changes. School Psychology Review, 14, 351–359. Miller, D. L., & Kelley, M. L. (1994). The use of goal setting and contingency contracting for improving children’s homework performance. Journal of Applied Behavior Analysis, 27, 73–84. Munck, D. D., Bursuck, W. D., Epstein, M. H., Jayanthi, M., Nelson, J., & Polloway, E. A. (2001). Homework communication problems: Perspectives of special and general education parents. Nicholls, J. G., McKenzie, M., & Shufro, J. (1994). Schoolwork, homework, life’s work: The experience of students with and without learning disabilities. Journal of Learning Disabilities, 27, 562–569. Olympia, D. E., Sheridan, S. M., Jenson, W. R., & Alfreds, D. (1994). Using student-managed interventions to increase homework completion and accuracy. Journal of Applied Behavior Analysis, 27, 85–99. O’Melia, M. C., & Rosenberg, M. S. (1994). Effects of cooperative homework teams on the acquisition of mathematics skills by secondary students with mild disabilities. Exceptional Children, 60, 538–548. Polloway, E. A., Epstein, M. H., Bursuck, W. D., Jayanthi, M., & Cumblad, C. (1994). Homework practices of general education teachers. Journal of Learning Disabilities, 27, 500–509. Polloway, E. A., Foley, R. M., & Epstein, M. H. (1992). A comparison of the homework problems of students with learning disabilities and nonhandicapped students. Learning Disabilities Research & Practice, 7, 203–209. Roderique, T. W., Polloway, E. A., Cumblad, C., Epstein, M. H., & Bursuck, W. D. (1994). Homework: A survey of policies in the United States. Journal of Learning Disabilities, 27, 481–487. Rosenberg, M. S. (1989). The effects of daily homework assignments on the acquisition of basic skills by students with learning disabilities. Journal of Learning Disabilities, 22, 314–323. Salend, S. J., & Schliff, J. (1989). An examination of the homework practices of teachers of students with learning disabilities. Journal of Learning Disabilities, 22, 621–623. Sawyer, V., Nelson, J. S., Jayanthi, M., Bursuck, W. D., & Epstein, M. H. (1996). Views of students with learning disabilities of their homework in general education classes: Student interviews. Learning Disability Quarterly, 19, 70–85. Scruggs, T. E., & Mastropieri, M. A. (1986). Academic characteristics of behaviorally disordered and learning disabled children. Behavioral Disorders, 11, 184–190. Soderlund, J., & Bursuck, B. (1995). A comparison of the homework problems of secondary school students with behavior disorders and nondisabled peers. Journal of Emotional & Behavioral Disorders, 3, 150–155. Struyk, L. R., Cole, K. B., Bursuck, W., Epstein, M. H., & Polloway, E. A. (1996). Homework communication: Problems involving high school teachers and parents of students with disabilities. American Secondary Education, 25, 9–16. Struyk, L. R., Epstein, M. H., Bursuck, W., Polloway, E. A., McConeghy, J., & Cole, K. B. (1995). Homework, grading, and testing practices used by teachers for students with and without disabilities. The Clearing House, 69, 50–55. Trammel, D. L., Schloss, P. J., & Alper, S. (1994). Using self-recording, evaluation, and graphing to increase completion of homework assignments. Journal of Learning Disabilities, 27, 75–81.

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U.S. Department of Education (2001). Twenty-third annual report to congress on implementation of the Individuals with Disabilities Education Act. Washington, DC: Author. Van Voorhis, F. L. (2001, April). Teachers’ use of interactive homework and its effects on family involvement and science achievement of middle grade students. Paper presented at the annual meeting of the American Educational Research Association, Seattle (ERIC Document Reproduction Service No. ED454049). Walberg, H. J. (1984). Improving the productivity of America’s schools. Educational Leadership, 41, 19–30.

MAKING THE GRADE: PROMOTING SUCCESS OF SECONDARY STUDENTS WITH AUTISM SPECTRUM DISORDERS Janet E. Graetz ABSTRACT The transition from elementary to secondary school involves major changes for students that are reflected socially, academically, and environmentally. Increased emphasis on social interactions, school procedures, and academics make high school potentially stressful. For students with autism spectrum disorders (ASD), these new academic and social challenges may be particularly anxiety-producing as they reluctantly leave familiar surroundings and friends and transition to high school. Many of the characteristics of students with ASD may be incompatible with the demands of life in high school. This paper examines the skills that are required for students to be successful in high school and compares them to the skills of many adolescents with ASD. Following a description of individuals with autism spectrum disorder, the paper presents an overview of curriculum analysis and possible curricular changes to assist these students in high school. To enhance the support of the curriculum, subsequent information in this chapter includes the use of visual supports and the implementation of technology. Additional strategies are then presented including information on peer tutoring, and the use of social scripts and social stories. The final section discusses components of high school that may prove challenging, such

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as block scheduling and the use unstructured time. It concludes with a description of the effective secondary teacher and a look at future directions for this topic. Caroline sits in her ninth grade classroom, compliant to teacher requests and yet inattentive. Her classmates have been in school with Caroline for the past five years and are accustomed to her infrequent outbursts or inappropriate behavior. Although Caroline appeared to have friends in elementary school, her presence in high school has not resulted in the same friendships that she had known before. Classes are constantly changing and Caroline now must deal with a multitude of different students instead of the few well-chosen friends by her teacher. Other changes are also noteworthy. Caroline now faces a multitude of sensory issues that were less noticeable in elementary school. She is expected to change clothes for P. E., find a locker amid a sea of gray metal lockers, navigate her way from class to class through noisy, crowded hallways, sit attentively for 50 minutes while in class, and try to understand a schedule of classes that differs from day to day. Welcome to high school. For even the most competent secondary student, high school can be overwhelming. For a student with autism, it can seem an almost impossible task. Unfortunately, while recent studies explore transition issues for students with Asperger syndrome, little longitudinal research exists that explores how other students with autism spectrum disorder (ASD) adjust to high school (Adreon & Stella, 2001; Myles & Adreon, 2001). Recent research in special education has concentrated on autism and more specifically, on young children with autism (National Research Council, 2001). There is no doubt that it is important to concentrate many of our efforts on young children with autism. Hopefully, with intense early interventions, children can acquire needed skills for communication and appropriate social behaviors while diminishing some of the characteristics of autism that impede learning. Research on young children with ASD has yielded a variety of interventions and teaching strategies that promote learning. Some of the interventions include the use of discrete trials (Delprato, 2001; Schoen, 2003), peer tutoring (DiSalvo & Oswald, 2002; Pierce & Schreibman, 1995), structured teaching (Panerai et al., 1998; Schopler et al., 1995), technology (Hagiwara & Myles, 1999; LeBlanc et al., 2003) and social skills interventions (Krantz, 2000; McGrath et al., 2003; Nikopoulos & Keenan, 2003). While these interventions are noteworthy for young children with ASD, research is scant on effective interventions and teaching strategies for secondary students with ASD. An initial literature review found that of 935 articles published in ERIC and Psycho Info, 574 articles addressed young children with autism and 361 of the articles involved adolescents (including high

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school students) with autism. Within the ERIC database, 181 empirical studies focused on young children with ASD while only 31 studies focused on adolescents with ASD. Within this group, the majority of studies focusing on adolescents addressed Asperger syndrome. Approximately 75% (100 of 136 studies) of published dissertations (Dissertation Abstracts) focused on young children with autism. The lack of existing research in secondary classrooms compels us to review effective teaching strategies and interventions in elementary grades and analyze what components of these interventions are applicable to students with ASD in secondary settings. This paper examines present interventions and teaching strategies that promote success for secondary students with ASD. It begins by examining the structure of secondary schools and reviews skills needed by all students to be successful in this environment. The paper then examines the learning characteristics of students with ASD and examines how these characteristics are incompatible to the skills required by secondary students. Following this analysis, the article presents successful teaching strategies and interventions that have an empirical basis. Finally, the article discusses the secondary teacher and teacher qualities that enable students with autism to experience success.

FROM MIDDLE SCHOOL TO HIGH SCHOOL Major changes occur between elementary and middle school, and from middle school to high school. These changes are reflected socially, academically, and environmentally. High school exists as a social milieu characterized by spatial locations (classrooms) where learning is interwoven with student interactions. The opportunities for socialization are highly structured, occur throughout the school, and are the result of active participation on the part of the students. Students who do not participate actively in socialization can develop a “passive” adaptation where the student develops few personal qualities and fails to interact with others (Kelly, 1979). This failure to interact (for typically developing adolescents) may lead to feelings of alienation and subsequent demonstrations of misbehavior (Isakson & Jarvis, 1999; Kulka, Kahle & Klingel, 1982). Students’ feelings of “belonging” may positively impact their motivation to succeed and participate in school (Goodenow, 1993). At the same time, adolescents in high school seek to become autonomous of parents as they expand their friendship base outside of the family (Kimmel & Weiner, 1985). For this reason, students become more dependent upon the friendships of their peers (Isakson & Jarvis, 1999; Powell et al., 1985). Compared to middle school, students in high school also experience more pressure to succeed academically and prepare for life beyond high school.

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Teacher expectations and demands now increase as students prepare to enter college. Students are now expected to demonstrate organizational skills needed to remember assignments, complete more complex homework assignments (Mullins & Irvin, 2000), and organize work as needed for many different teachers. The environment of the high school classroom is also now significantly different than middle school. Classes in high schools may follow block scheduling and have students sitting for 45–90 minutes in a class period. At the same time, students are introduced to departmentalized teaching and it may be impossible to form the close relationships with teachers that were seen in earlier grades. Classes may be held throughout a large building and students are expected to navigate their way through hallways to lockers and on to classrooms (Weller & McLeskey, 2000). Within this structure of block scheduling and changing classes, growing expectations are made to interact with diverse students and form peer relationships. These social, academic, and environmental changes may result in higher levels of stress than was experienced in middle school. To be successful in high school, each student must also have coping strategies to deal with the demands of this new environment. Coping strategies may include reliance on family or friends or on the support of specific teachers. Educators need to be cognizant of stressors that exist and recommend the use of different coping strategies to successfully meet the challenges of high school. These are just some of the challenges faced by typically developing adolescents as they enter high school. For the student with ASD, these challenges are amplified. The specific skills required by secondary students to experience success in high school (communication, socialization, and organization) are typically the deficit areas for students with ASD. The characteristics of ASD coupled with the environment of high school make their opportunities for success much more difficult.

CHARACTERISTICS OF STUDENTS WITH ASD The characteristics of individuals with ASD were first described by Kanner (1943) and have since been expanded to include further characteristics (Schopler, 1983). These characteristics may be viewed as mild to severe and are complex in a variety of domains. The Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) examines three areas-social development, communication, and activities of interest when assessing a child for ASD (American Psychiatric Association, 1994). Additional diagnostic instruments include the Aberrant Behavior Checklist (Aman & Singh, 1986) and the Gilliam Autism Rating Scale


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(Gilliam, 1995) which are appropriate for obtaining information regarding the presence or absence of behaviors in older children with ASD. For high school students with ASD, deficits in communicative and social behaviors, the desire for sameness, and difficulties with complex information processing impact their success in secondary classrooms. Because of their limited understanding of the world, older students with ASD may also exhibit increased anxiety and frustration that may result in even greater self-isolating behaviors, excessive bodily movements, and aggression toward others (Gillott et al., 2001; Green et al., 2000). These difficulties are compounded by the lack of emotional maturity and physical changes in their bodies as they approach puberty (Dalrymple, 1989; Realmuto & Ruble, 1999). The following section examines critical areas that impact success for secondary students with ASD: communicative behaviors, social behaviors, the desire for sameness, and difficulties in understanding complex information.

Communicative Behaviors Communication issues for students with ASD usually become evident in elementary school and remain evident throughout adolescence. In elementary grades, children with autism are “learning to communicate” as opposed to high school where they are now “communicating to learn.” Bondy and Frost (1994) state that children who acquire effective communication skills prior to the age of six are more likely to develop speech and acquire higher functioning skills required as an adult. Research indicates that many adolescents with Asperger Syndrome become verbal but that other children with ASD remain nonverbal or display very limited verbal skills (Adams et al., 2002; Howlin, 2003; Safran et al., 2003; Shriber et al., 2001). Difficulties are frequently seen in the areas of content, form, and use (Quill, 1995). Students with ASD have limited vocabularies, are inflexible with their speech, and may find it impossible to understand the words of their classmates. In addition to a lack of flexibility in speech, students with autism may also demonstrate an inability to change conversational topics easily. Younger students in elementary grades may have found it amusing that Joey, a student with ASD, always wants to talk about Star Wars. In high school, perseverating on a specific topic (and perhaps one that is inappropriate for his age) may contribute to other children isolating themselves from the student. The students’ teachers may also impact their communicative success. In elementary school, students frequently had one teacher for the year (or for several years) and frequently developed a rapport with that teacher. This rapport frequently enabled the teacher to understand the specific communication system

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of the student. This may be one reason why elementary teachers tend to view the child with disabilities more favorably than some high school teachers. Deficits that involve complex language also impact students’ success in high school. As students are now reading text to gain information and problem solve, difficulties in reading and story comprehension, verbal inference making, and comprehension of idioms and metaphors all contribute to their failure to understand what is read and said. In some cases, students may appear very verbal and high school teachers may interpret this as understanding. Unfortunately, a large gap may exist between what is said and what is understood (Minshew, 2001).

Social Behaviors Social interactions are closely linked to communication and language issues. Many individuals with autism are characterized as object-referenced as opposed to people-referenced (Quill, 1995). For a young student with autism in the first grade, this behavior may not seem too out of place since other young children seek objects (toys) instead of peers. As most children mature, this focus changes. As previously stated, high school students seek friends and through these friendships develop a sense of belonging. In addition, when adolescents enter high school, they may experience disruptions in friendships. Classmates that they knew in middle school and who supported them in classes, may no longer be present. Characteristics of ASD, such as awkwardness with others, rigid responses, and inappropriate social responses limit their social interactions (Fouse & Wheeler, 1997). High school students with autism may not willingly seek out others and attempt to communicate with them. The secondary student with ASD may continue to apply the social behaviors that he used in elementary grades (as limited as they may be) but now find that they are unacceptable in this new setting. While typically developing peers adjust to the new demands and new ways of making friendships in high school, the student with ASD will have great difficulty in assimilating new skills unless they are specifically taught.

Desire for Sameness Flexibility, a trait needed by high school students to be successful, may not be included in the repertoire of behaviors for a student with autism (Baranek et al., 1997; Luteijn et al., 2000). Many students with ASD prefer places and people to remain the same in their lives. Flexibility will be required to participate in various schedules throughout the week. In addition, flexibility is also required as


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students participate within various classrooms with numerous academic activities. A secondary student may enjoy the time he is afforded on the computer and be unwilling or unable to stop that activity for another. Resistance to change and restricted interests can negatively impact the success of the student in high school.

Processing Difficulties Minshew (2001) identified four domains that reveal deficits in individuals with ASD. These domains include motor functioning, complex language, complex memory, and reasoning. The affected domains of memory and reasoning impact students as they attempt to learn and remember complex information presented in high school. Because of the deficit, students with ASD may be unable to recall information that is easily learned by their peers. In elementary grades, these deficits may not be prominent since information demands are less complex. In high school, presentation of large amounts of information, for which students can attach little meaning, cannot be recalled. Material is presented in large chunks with little processing time for students. Many teachers use a lecture format with accompanying group work or individual projects to present curricula material. Students with autism frequently have difficulty with auditory input which is just a part of their sensory processing difficulties (Gillberg et al., 1997; National Research Council, 2001; Wainwright-Sharp & Bryson, 1993). Because they may lack the ability to understand a teacher’s directions, or just understand pieces of what is said, their thinking is frequently fragmented and may result in increased anxiety (Greenspan, 2000). Unless adaptations are provided, information presented by high school teachers to students with autism may never be understood. Minshew (2001) also lists memory (for complex information) as an affected domain for individuals with ASD. They may be unable to memorize information because of its complexity or because they are unable to attach meaning to it. This deficit in memory impacts learning, language, and problem solving. The impairments in basic memory and working memory make the acquisition of new material a formidable task (Minshew & Goldstein, 1993). Students are presented a vast amount of information regarding many subjects and students with autism may be unable to attach meaning to presented information. These impairments in communicative behaviors and social behaviors, the desire for sameness, and the difficulties in understanding complex information all impact students’ academic and social success in high school. To be successful, students with ASD require specific teacher strategies and interventions that help to impact these affected domains. Fortunately, strategies and interventions exist that address

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these issues. Many of these strategies are components of successful programs that are successful in elementary grades. Other issues are unique to students in secondary settings. The following section examines specific issues regarding educating students with ASD in secondary classrooms. It begins by providing an overview of the transition to high school and how a successful transition can prepare the way for a successful high school experience. Subsequent sections discuss curricula focus, classroom supports, block scheduling, peer tutoring and peer interactions, and the use of unstructured time.

TRANSITION TO HIGH SCHOOL The transition from middle school to high school can be stressful and overwhelming. Research indicates that student achievement in science, social studies, and reading has suffered as a result of this increased stress when students transition from middle school to high school (Alspaugh, 1998). In addition, reported stressors during the transition at the beginning of the ninth grade predicted lower grade point average at the end of the first semester of ninth grade. In a study by Isakson and Jarvis (1999), increased stressors at the beginning of ninth grade also predicted lower grade point average at the end of the second semester of ninth grade. Stressors during the transition to high school included concerns about extracurricular activities, relationships with peers, and problems with parents. For students with ASD, the transition issues are just as important but perhaps somewhat different. For these students, the change of schools, the new curriculum and relationships with peers may be critical concerns. Specific steps should be taken to support students with autism spectrum disorders to reduce anxiety and ensure success.

Transition-Team Planning When a student moves from the middle school to high school, staff from both schools should meet to discuss student needs. In most cases, this may mean a series of meetings that includes therapists, teachers, paraprofessionals, guidance counselors, and administrators. Goals should focus on: (a) identifying the specific supports presently provided and those that will be needed by the student in the new setting; (b) determining how the supports will be provided; (c) determining who will provide the supports; and (d) determining how the supports will be evaluated. If possible, the high school teachers should visit the student in the middle school to see how present supports are implemented (Black, 1999).


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The High School Visit For many students with disabilities, the only transition activities that they may have experienced as they entered middle school may have been a visit to the new school, a visit to the classroom, and some orientation events (Mullins & Irvin, 2000). Unfortunately, for many students entering high school, the transition events are even fewer. The student with ASD must be provided an opportunity to visit his new school and to see the various classrooms. This visit may occur with middle school staff with whom he has developed a rapport. During the visit to the high school, staff can take pictures of the new environments (classrooms, gym, cafeteria, office, etc.). Once back at the middle school (prior to June when school ends) staff can talk with the student regarding the pictures and the new school. Staff can also encourage students to compare his present classroom with his new classroom. If the student has difficulty understanding “when” he begins at the new school, a teacher can create a visual calendar that marks the time until his start in high school. During the visit, staff can note the noise and crowd level within the school. How does the student respond to the crowded hallways and sound of slamming lockers? What aspects of the new environment may be problematic for the student (a fixation on soda machines which are located by the gymnasium)? How does the school indicate that classes are changing and how does the student respond to those sounds? How will the student access his lunch in the cafeteria? How many choices will he be asked to make when getting his lunch? Does he pay for his lunch with money or with a card? How long will he be expected to sit once he finishes lunch? What supports will need to be in place (visual supports, peer buddies) so that the student can navigate the hallways? These are just some questions that visiting staff may wish to ask.

Teacher Training and Preparation High school teachers may already feel overwhelmed with their class load and have great hesitations regarding students with autism. The general education teachers should meet with the special education teachers to discuss the student supports and implementation of specific interventions. The general education teacher should become familiar with visual supports, curricular adaptations, sensory accommodations, and behavioral strategies for the student. Since both the special education teacher and general education teachers will have different schedules, it is important to find some time to regularly discuss concerns before problems become unmanageable. At the same time, paraprofessionals need to be assured of

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their role in the general education classroom and specifically understand their role with the student.

CURRICULA FOCUS The Individuals with Disabilities Education Act (IDEA) of 1997 ensures that all students with disabilities would have access to the same curricular content as their same-age peers. In elementary grades, teachers may have presented the same curricular material to all students with few adaptations. Most curricular content in grades one through three presented simple facts and teachers generally used a hands-on approach to learning content. If the science content was exploring living things (worms, for example) a first grade teacher may bring in worms for students to see. The class would take days investigating the shape, color, movement, and eating patterns of the worms. In addition, they might create worm pictures and puppets that enhance their understanding of the little critters. After third grade, it appears that curricular content is presented more quickly and that after sixth grade, there were fewer opportunities for hands-on exploration of topics. Since students with ASD have difficulties processing complex and vast amounts of curricula information, teachers may need to rethink the curriculum content. King-Sears (2001) describes three steps for teachers to consider when analyzing the curriculum for students with special needs. These steps are appropriate for students with ASD as well. The first step is to analyze the general education curriculum as it already is and determine what features are “user-friendly” for students with ASD and which may need to be modified or adapted. Are there materials already available that address students with diverse learning styles? What aspects of universal design are included in the present curriculum? Story et al. (1998) describe universal design as the design of products and environments that are usable by all people, to the greatest extent possible, without the need for adaptation or specialized design. If curricula materials already address universal design then perhaps no adaptations or modifications are necessary. Unfortunately, universal design appears to still be in a state of infancy in regards to public school education. Architects have designed buildings with the concept of universal design but creators of curriculum materials have been slow to address this topic. Simmons and Kameenui (1996) describe a model of universal design for curriculum that includes the following features: (1) a focus on Big Ideas: targets the concepts, principles, rules, that underlie and/or span critical ideas in the curriculum; (2) conspicuous strategies or overt instruction on the steps needed to accomplish tasks; (3) mediated scaffolding which provides support as needed and leads students to higher levels of understanding; (4) strategic integration which links Big Ideas across curricula; (5) review which


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allows for application of information; and (6) primed background knowledge which ascertains whether the student has background knowledge and experience to learn new information. King-Sears (2001) states that teachers should also see how the present curricula materials can be “enhanced” for students with disabilities (step 2). What features are present that could be altered to make content more accessible? If textbook material is visually overwhelming and “too busy” then teachers can devise ways of simplifying text material that makes it more appropriate. Step 3 addresses the issue of what a teacher will do if a student is still unable to succeed in the general education classroom with the enhancements suggested in steps one and two. Giangreco and Doyle (1996) suggest four curricular changes that may be considered: accommodations, adaptations, parallel construction, and overlapping curriculum. If accommodations are considered, the curriculum content and the difficulty do not change. To make accommodations, the teacher examines (and perhaps changes) the input and output methods used by the student. If the student has difficulty reading text, it may be provided on a tape recorder. It may also be necessary to provide more visual supports, graphic organizers, and supports to increase student organization skills (e.g. use of Inspiration Software, www.inspiration.com for recalling facts). An adaptation implies that the content is the same as with other students but the conceptual level for the standard changes. In this case, a student with ASD may be asked to match terms and their definitions as opposed to defining the terms from memory (King-Sears, 2001). A parallel curriculum implies that the student is studying the same content area (for example, science) but the outcome within the content area has significant changes. Students may be writing a lengthy science paper and a student with ASD is creating an art project that depicts the life of mammals. If students with ASD have difficulty learning and remembering complex information, teachers should analyze the curricula materials and the “big ideas” that are important for each student with ASD to know. For example, if the science class is studying mammals, what aspects of this science topic are important for a specific student with ASD? An overlapping curriculum usually involves dramatically different goals and may not involve teaching the general education curriculum. Students following this type of curriculum may be more involved in a functional life skills program that assists the student in skills needed for independent living. Academic programming may address functional reading and functional math (Duran, 1996). A student following a functional life skills program may also be more involved in communitybased instruction. Educators need to analyze the high school curriculum and determine how the student with ASD will interact with the established curriculum. Are the principles of universal design in place within the school? Teachers may make changes for

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one student with ASD one year but cannot assume that these changes will be appropriate for their next student with ASD. The goals for each student need to be evaluated as part of the IEP process and throughout the school year as needed.

CLASSROOM AND SCHOOL SUPPORTS The presence of classroom strategies and supports can promote learning and discourage inappropriate behaviors for students with ASD. Frequently, it is the lack of procedures and routines that result in behavior problems and time off task. The implementation of specific supports complement the learning style of adolescents with ASD and address the communication and social irregularities frequently associated with this disorder. Classroom supports include the use of visual strategies, technology, peer tutoring and peer mediation, the use of scripts and the use of social stories. School supports include evaluating block scheduling and the use of unstructured time. The following section describes these topics as they apply to high school students with ASD.

Visual Supports Because of the auditory processing difficulties experienced by many students with ASD, visual supports may be an integral part of the day. Visual supports can be used to teach a student a schedule, to understand the steps within an assignment, to engage in a series of activities, and to generally gain independence with the school. McClannahan and Krantz (1999) discuss the use of visual timers, schedules, and activity boards. Although the focus of their book is on young children with autism, the visual suggestions are appropriate for older students, with some adaptations. To reduce the stigma of a large visual schedule, a smaller schedule may be posted inside a locker or on a student’s desk. If the student has a different folder for each class, the sub-schedule for each class (i.e. put book on shelf, place homework on teacher’s desk, sit down at desk) can be taped to the notebook. If the student is somewhat independent in transitioning from class to class, visual reminders can be placed strategically in the hallway to assist the student. It may also be appropriate for the student to help in the creation of these visual supports. Visual supports are a tool for life and are not a support that you may try to extinguish over time (Hodgdon, 1999). Even if the adolescent has never been introduced to visual supports, they can be introduced in high school and used throughout the school. Staff need to remember to use them and to reevaluate their success over time.


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Technology Technology has been used for years to support individuals with disabilities. Stowe and Turnbull (2001) state that there are two facets for technology use for individuals with disabilities: assistive technology and computer technology. Both are used to help individuals compensate for a loss of functioning (communication) and to restore functioning. Students with ASD may use assistive technology in classrooms to reduce deficit areas (such as communication). For students with ASD, access to computers may also provide a different means for curricular presentation (input) and responses (output). Computer software can also assist the student with ASD to self-organize assignments and provide means to curricular supports such as graphic organizers. Programs such as Inspiration provide visual displays that help students to understand information. (If the student has become familiar with Kidspiration™ while in elementary school, then he may more easily learn Inspiration in high school). In addition to computer usage to aid in understanding curriculum content, technology can be used to teach complex skills and behaviors. Video modeling is a teaching technique that enables a student to view the appropriate behavior or task that is to be learned (Charlop & Milstein, 1989; Charlop-Christy et al., 2000). While this has been used successfully with young children with ASD, research is scarce regarding this as an intervention for secondary students. Aspects of video modeling may be promising for older students with ASD. The intervention incorporates watching scripted scenarios that depict desired behavior. The use of the television is age appropriate and usually an object of interest for students with ASD. High school peers could become the actors in the scenarios and assist the student in learning the desired behaviors.

Peer Tutoring and Peer Relationships As stated previously, many students with ASD appear socially detached from the world (Waterhouse et al., 1996) and lack skills that promote socialization. Research studies have investigated the use of social skills training in schools (Mesibov, 1984; Ozonoff & Miller, 1995; Pierce & Schreibman, 1995) but little consensus exists as to how to incorporate teaching social skills into secondary classrooms while maintaining focus on academic and curricula content (Prater et al., 1999). Previous studies investigated social skills curricula intended for individuals with behavioral disorders (Kransny et al., 2003) but not specifically for individuals with ASD. A few studies have examined group social skills interventions for students with ASD (Howlin & Yates, 1999; Ozonoff & Miller, 1995; Williams,

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1989). Other studies addressed interventions that were applicable to individuals (see Weiss & Harris, 2001). Specific techniques addressed in these studies that promote social behaviors for adolescents include the use of peer mediation, scripts, and social stories.

Peer Mediation Peer mediation involves the use of classmates to improve and increase social interactions (Kamps et al., 1998). It has been used to increase social interactions for students with ASD in a variety of settings such as lunchrooms, the playground and while students transitioned from one activity to the next (Haring & Breen, 1992; Kamps et al., 1997). Interestingly, peer mediation and self-monitoring strategies appear to be more effective when used together. Self-monitoring requires that the students are able to assess their own behavior, self-record the behavior, and at times self-reinforce for appropriate behavior. Although much of the existing research on peer mediation focuses on young children with ASD, the use of peers to model appropriate social skills provides promise for high school students with ASD as well. Social skills training can take place as peer tutoring occurs in the classroom. Students with ASD can be taught how to request, attract and maintain another’s attention, and share while participating in classroom activities (Wetherby & Prizant, 1999). Specific strategies that have proven successful with students with severe disabilities include student modeling (of the appropriate behavior and task), praise/compliments, questioning, and assuming a leader role in activities (McEvoy et al., 1990). Social skill development is especially important for adolescents as they acquire leisure skills. As students with ASD participate in games and free time activities with peers, it will be important to instruct them as to the rules of games and expected behavior during activities. Older students with ASD may gravitate back to activities and objects that are inappropriate for their age. The unstructured time of recreational activities can be especially difficult. Teachers will need to teach appropriate social behaviors needed for leisure skill activities and ensure that the time is structured.

Scripts When students do not know how to respond to their classmates, scripts may provide opportunities for conversations. Kyparissos (1997) successfully taught adolescents


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with autism conversational exchanges with peers which generalized to other settings. Students with ASD were taught to ask scripted “wh” questions to extend verbal exchanges. With fading, unscripted exchanges gradually increased as the scripted interchanges decreased. For adolescents with ASD who have very little language, the use of scripts to initiate conversation during classroom activities may enhance verbal exchanges at other times.

Social Stories Social stories have also been implemented for students with ASD to promote appropriate social interactions. Social stories consist of a brief narrative that presents a social situation and the desired response to the situation (Gray & Garand, 1993). The social story usually consists of text and pictures and is written from the perspective of the student. Although the majority of research on social stories addresses young children with autism, select studies report success with social stories for adolescents (Graetz, 2003; Kuttler et al., 1998; Rogers & Myles, 2001; Swaggart et al., 1995). The use of social stories may be used to help students understand social situations or to help understand the task analysis of an assignment. They may be read by the student or read to the student. If the social story is recorded, then students can be taught to access the story as needed or at particular times throughout the day.

Block Scheduling Although research exists that explores the topic of block scheduling for higher incidence disabilities (Canady & Rettig, 1993; Jorgensen, 1997; Weller & McLeskey, 2000) little research exists that examines block scheduling and students with ASD. Block scheduling attempts to limit the number of classes offered during the school day thereby increasing the length of each class to perhaps more than 90 minutes. Students with ASD may be more tolerant of a schedule that limits the number of times they need to change classes. At the same time, students are frequently asked to sit for the extended time. Many individuals with ASD need opportunities to move their bodies and may find block scheduling intolerable. For some students with ASD, teachers will need to provide structured opportunities for movement and build this into the schedule. Shore (2001) suggests that teachers provide opportunities for students to move throughout the day. While teachers in elementary grades may be able to implement this (taking a note to the office, wiping the boards, running an errand),

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it becomes more difficult in high school during block scheduling. Teachers will need to be creative to develop tasks that provide motion for students but are not disruptive to the class. If a paraprofessional is assisting the student, he/she may walk the student during the class period. If there is a drinking fountain close to the classroom, the student may be allowed to walk to the water fountain for a drink and then return to the classroom. Another challenge of block scheduling is that students will have different classes each day. Students with ASD may forget which day it is and go to the wrong classes with the wrong books and assignments. To eliminate these problems, teachers may have each student post a visual schedule on the inside of the locker. The days can be color-coded to match corresponding cards that are placed by teachers’ doors. While the implementation of block scheduling may mean increased class length, it may also provide opportunities for team teaching. When two teachers share the duties of the classroom, it provides more opportunity for teachers to understand the learning styles of students and make needed changes to the curriculum (Weller & McLeskey, 2000). As more high schools move toward longer periods of block scheduling and include more students with ASD, it will be important to consider the characteristics of block scheduling and how it relates to students with ASD. Providing environmental and academic supports will increase chances for success.

Dealing with Unstructured Times Although a high school student’s day is fairly rigid and structured, there will be times during the day that, although seemingly “structured” to the typical student, may seem completely unstructured to a student with ASD. These unstructured times include changing classes, the time before and after school, lunch, and study periods (Adreon & Stella, 2001). Changing Classes Adolescents with ASD enjoy structure and frequently enjoy familiar surroundings. For this reason, changing classes every hour can become a daunting chore. Additional difficulties exist in the hallways that are frequently crowded and noisy. Many students with autism will not enjoy the close proximity of other students as classes change. In order to prepare the student for the changing of classes, have a timer or clock available that informs him how much time is left. A visual red timer provides a visual reminder, without an audible one, that lets the student how much time is remaining in the class. When the student is walking in the hallways, it may be necessary to mark a path that is recognizable for the student. Signs can


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be placed against the wall and be color coded to indicate the path to the next class. The student may touch each card as he progresses along the hallway. This will also enable the student to stay close to the wall and thereby alleviate being caught in crowds of people as classes change. Myles and Adreon (2001) suggest that students with Asperger Syndrome may also benefit from leaving class a few minutes early to avoid the crowds of students in the hallway. They suggest that a peer buddy help the student to navigate hallways and find their way to class. Time Before and After School Frequently, the special education buses arrive before general education buses and therefore students with ASD may arrive early and have extended time before classes begin. Unstructured time in the morning can result in perseverative and inappropriate behaviors. It is important that the students enter the school and check their schedule. Schedules may include the use of visual pictures and/or written text. Since staffing may be reduced during these time periods, students are encouraged to self-monitor their own behavior (Koegel & Frea, 1993; Strain et al., 1994). During these times, students may also select appropriate solitary leisure skills or engage in a leisure skill/game that involves a peer. Lunch High school lunch periods may occur at different times during the week and students may again have periods of unstructured time. Peers may assist students during these time periods and act as escorts to other settings when finished eating.

THE TEACHER AND CLASSROOM CULTURE The classroom teacher will ultimately set the tone for student success. Mastropieri and Scruggs (2000) state that effective teachers are those who implement effective teaching strategies. Strategies that are successful for students with disabilities include the use of the SCREAM variables: structure, clarity, redundancy, enthusiasm, appropriate pace, and maximized engagement. These strategies can be particularly effective for students with ASD. It will be important for the classroom teacher to have a structured classroom so that, each day, the student with ASD is familiar with the routine and tasks. Assignments and directions can be clarified by simplifying them or presenting them with pictures or visual symbols. Teachers can present the “big ideas” that are most important for students to know and review them repeatedly. In addition, the teacher can determine the appropriate pace for the presentation of new information.

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Hopefully, these effective teaching strategies will already be incorporated in the secondary classroom. Research indicates that if the strategies and interventions for students with disabilities are not similar to existing classroom practices, teachers are less likely to implement the new intervention (Albin et al., 1996; Shapiro, 1996). Although the implementation of some teaching strategies will be the responsibility of the special education teacher, in many instances the implementation of a specific intervention or the adaptation of the curriculum will be implemented by the general education teacher. If the mode of instruction is similar to current practices of the teacher, then they may be more likely to be implemented. Shapiro (1996) has also noted that teachers may be more likely to implement an intervention that has proven successful before. If a high school teacher experiences success with an intervention for a student with autism, then perhaps he/she will implement the intervention with other students. The amount of time that an intervention r requires may also influence whether it is likely to be used (Martens et al., 1985). Some high school teachers may find that they are to implement the intervention amid an already busy class. Researchers have found in elementary grades, that teachers implement interventions that require the least amount of direct teacher time (McConnell et al., 1992) and that they were least likely to implement those that required their direct time. All school personnel, including special and general education teachers and therapists would benefit from personnel development to ensure that they have the skills to teach students with disabilities (Park et al., 2003). Students with ASD present unique challenges and trainings should be provided for professionals working with these students.

FUTURE DIRECTIONS It is important that we ensure the success of all students in secondary classrooms. For students with ASD, success in high school means more than placement in a classroom. It means having access to the curriculum and opportunities for social interactions with classmates and teachers. An array of supports and strategies need to be in place and are the result of careful planning and collaborative efforts of middle school and high school personnel. Present research focuses on young children with ASD. It is unknown whether the strategies and interventions found successful in elementary school are applicable to the secondary classroom. It is unknown which components of successful programs for young children remain effective for adolescents. As the knowledge base of ASD expands, hopefully it will include research that explores older students with ASD. The increased numbers of “young” children with autism


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will soon by the adolescents entering our high schools. Are we prepared to meet their needs?

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EFFECTIVE CONTENT-AREA INSTRUCTION FOR ALL STUDENTS Janis Bulgren ABSTRACT A current vision of education in America today is that all students be science literate. To accomplish this, educators and teachers need to be aware of the challenges involved in promoting science literacy: science literacy encompasses a wide range of knowledge, including construction of knowledge, use of that knowledge, and recall of critical facts necessary to apply scientific information in the world today. In addition, teachers and educators need a knowledge of the issues of “inclusion” since students of diverse abilities, including those with disabilities and others at risk for school failure, are being educated, as much as possible, in general education classrooms taught by content experts. A bridge to span the gap between the challenges of science literacy for all students and the complexities of student diversity is Content Enhancement – instruction that responds to the needs of students of diverse abilities while maintaining content integrity by focusing on the critical information that all students need to know. In Content Enhancement, the teacher helps students learn by organizing information, providing explicit instruction when necessary, and assuring that students are active partners with the teacher and other students in the construction of knowledge. Graphic organizers and instructional sequences have been developed to help teachers organize information at the course, unit and lesson levels; learn to answer large, difficult questions with ideas that can be generalized to other settings; explore


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and manipulate knowledge by developing analogies and comparisons; and respond to assessments.

INTRODUCTION A current vision of education in America embraces the ideal that graduates can identify and solve problems, making contributions to society throughout their lifetimes (National Research Council (NRC), 1996). The goal is to develop intelligent novices – persons who can “independently find, select, evaluate and master information from the vast quantities being generated annually in nearly every knowledge domain” (Fensham et al., 1994). Ultimately, the goal for education today is that all students achieve literacy in areas such as science (NCR, 1996). However, a great number of students have difficulty acquiring content area information and skills; studies suggest that American schools are not preparing students to engage in desirable tasks such as scientific reasoning (National Center for Education Statistics, 1999). The Alliance for Excellent Education (2002) maintained that some of our most vulnerable adolescents, amounting to six million students at the secondary level, are at risk of failing to graduate from high school or of graduating without adequate preparation for success. According to this group, less than 75% of all eighth grade students graduate from high school in five years, and in urban schools, these rates dip below 50%. The Alliance contended that this indicator of academic underachievement reflects not only on language arts, but on students’ chances of mastering content in other areas as well. This parallels contentions by the NRC (1996) that definitions of literacy have progressed from being able to sign one’s name to being able to decode words and then to reading for new information. Literacy now means understanding the current state of one’s own knowledge, building on it, improving it, and making decisions in the face of uncertainty (NRC, 1996). Efforts in areas such as science education have been directed to this goal. However, Novak (1998) contended that even the 100 million dollars allocated annually since 1990 by the National Science Foundation, as part of a program to encourage change in schools, are not enough to reform schooling in America. Therefore, in reality, much of the response to instructional goals associated with science literacy is likely to fall on teachers in content classrooms, especially those in classrooms that contain diverse student learners. To respond to this goal, teachers, according to the NRC (2000), are guided by three core learning principles. These involve drawing out and working with students’ preexisting understandings; teaching some subject matter in depth, providing many examples in which the

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same concept is at work and assuring firm foundations of factual knowledge; and teaching metacognitive skills that are integrated into the curriculum in a variety of subject areas. To accomplish these goals, teachers must create a classroom that is learning-centered, knowledge centered, and community-centered using formative assessments to inform the design of instruction and monitoring of progress. In order to respond to the challenges contained in the goal that all students be science literate, educators and teachers need to be aware of: (a) the challenges involved in promoting science literacy; (b) issues of inclusion and learning diversity that complicate the challenge; and (c) data-based instructional techniques that enhance content learning for all students in inclusive general education classrooms.

SCIENCE LITERACY Science literacy encompasses a wide range of knowledge, including construction of knowledge, use of that knowledge, and recall of critical factual information necessary to apply scientific information required in the world today. However, to assure science literacy, teachers must understand how students learn. In offering insights about how students learn, the NRC (2000) discussed “constructivism” – how existing knowledge is used to build new knowledge. In this view, students gain knowledge from personal experiences as well as from classroom lectures. It is important that teachers attend to students’ knowledge bases and students’ interpretations of information, particularly as they guide students in the development of new knowledge and assure the accurate understanding of that new knowledge. The constructivist approach to learning is, however, complex. For example, Matthews (2000) noted that as many as seventeen varieties of educational constructivism have been identified. As a result, scholars have engaged in an analysis of general principles involved in constructivism. In a review of the literature on constructivist principles of learning and teaching methods, Olsen (1999) identified the following common perspectives among the several approaches to constructivism: (a) curriculum that responds to students’ interest and autonomy in the classroom; (b) increased social interaction and discussion of knowledge construction; (c) the use of variety in promoting student learning; (d) an emphasis on important ideas, sometimes from multiple perspectives; and (e) most notably, an emphasis on increased student thinking. These principles help teachers identify how to teach and also help determine what is important to teach. These components parallel other thinking about important ideas and critical information that students must learn. For example, Wiggins and McTigue (1998)

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argued that teachers must rethink their approach to instructional planning and decide what to teach by sorting information into three levels: information that should be enduring; information that is important to know and tasks that are important to do; and information with which students should have only some familiarity. Erickson (1998), too, indicated that instruction should revolve around essential learning. Lenz et al. (2003) argued that teachers must plan for and teach around information that all students must know, most students should know, and some students should know. All of these approaches guide teachers in thinking about, and planning for, what they teach based on what is truly important. This is no small planning task when seen in the context of demands that students must meet related to understanding content-area information such as learning concepts; applying or generalizing learned concepts to novel situations; comparing and contrasting concepts; learning rules and propositions; specifying relationships between concepts; integrating main ideas and details; learning procedures, processes, or sequences of actions; learning cause-and effect relationships; and exploring problems, making judgments, and arriving a solutions (Mayer, 1987). Another component of the approach discussed by the NRC (2000) involves students’ active engagement as they use what they have learned. For example, standards-based reform movements, such as those in science education, call for students to engage in scientific inquiry and scientific argumentation. Inquiry, as defined in the National Science Education Standards (NCR, 1996) is a set of “interrelated processes by which scientists and students pose questions about the natural world and investigate phenomena; in doing so, students acquire knowledge and develop a rich understanding of concepts, principles, models and theories” (NRC, 1996, p. 214). Furthermore, the role of argument in education has been given a central role in the social construction of scientific knowledge and the interpretation of empirical data (Driver et al., 2000). As a result, students are often challenged to question the relationships between evidence and explanation, to construct and analyze explanations, to communicate scientific arguments (Driver et al., 2000; NRC, 1996, 2000) and to use knowledge and technology to answer questions of importance in our society (Fensham et al., 1994). Complicating this drive to focus on important ideas and critical thinking skills is the reality that, in many cases, rather than replacing other demands, this challenge is added to already intense demands such as the ability to recall great amounts of information (NRC, 1996). The NRC noted that the new science of learning does not deny that facts are important for thinking and problem solving. However, knowledge than can be used is not merely a list of disconnected facts. Facts must be connected and organized around important concepts, co-contextualized and generalized. These instructional procedures are predicated on learning principles such as those of Carver (2001) who proposed designing a model learning program


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that builds on prior knowledge; makes thinking explicit; emphasizes links; provides practice opportunities, and expects individual variability. Individual variability in classrooms is a growing reality in that more and more students of diverse abilities are included in general education content classrooms to benefit from instruction by expert science teachers. Fortunately, there appears to be agreement among both general education teachers and special education teachers that all students need to be able to respond to authentic tasks such as those described by Driver et al. (2000) in which students are helped to construct and use knowledge. Educators with a focus on special education students, such as Harris and Graham (1996), supported this view and reiterated that constructivism is a philosophy positing that children are active, self-regulating learners who construct knowledge in developmentally appropriate ways within a social context, building on prior knowledge and experiences that allow them to participate fully in learning. Harris and Graham noted that the advantages of this approach seem obvious and provide a direction in our educational system that is needed for all students.

INCLUSION AND DIVERSITY Based on national legislation over many years from the Elementary and Secondary Education Act, originally enacted in 1965 and reinforced by the No Child Left Behind (NCLB) Act of 2001, more and more students identified for special education services are educated in general education content classrooms. This is a movement called “inclusion” that results in the placement of students of diverse abilities in general education classrooms taught by content experts. Inclusion, according to Hallahan et al. (1996), calls for “all students, regardless of the nature or severity of their disabilities, to be included in their neighborhood schools and to be included in regular classes for all or nearly all of the school day” (p. 433). Inclusion is an extension of “mainstreaming” that began in the late 1960s and the regular education initiative (REI) of the 1980s, which called for general educators to take more responsibility for the education of students with mild, or “high incidence disabilities” (HID) and for greater collaboration between general and special education. Students with HID are those with specific learning disabilities (LD), behavior disorders (BD), and mild autism, among others. Students who are included in general education classrooms have been determined to be capable of learning in general education classrooms, although adaptations and accommodations (based in Individual Education Plans (IEPs) may be necessary for them to achieve optimal benefits of instruction. To achieve the goal of science literacy for all, it is necessary that researchers, educators, teachers, parents, teachers, and agencies have common understandings

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about educational goals and how to achieve them. Fortunately, agreement seems to exist on several points. First, educators in content areas and special education experts share the understanding that students of diverse abilities will continue to be a part of general education content classrooms (Bay et al., 1992; Hodgkinson, 1991) and participate in the same classroom instruction and the same statewide assessments as other students. Furthermore, projects such as those of Cawley et al. (2002) demonstrate that regular education and special education teachers can work together to improve performance for students with HID such as those with LD and severe emotional disturbances in junior high general education science classrooms if the training is of sufficient magnitude for teachers to become proficient and have the opportunity to bond together in their goal of implementing a program. Fortunately, research has also shown that students who are low achieving (LA) (i.e. students who have failed in two or more required academic classes in the previous semester) as well as those who are normally achieving (NA) and high achieving (HA) have been shown to benefit from the adaptations and accommodations that teachers may develop for students with HID (Bulgren et al., 1988, 1994a, b, 1997, 2000, 2002). Such projects pave the way for inclusion of a wide variety of students in general education classrooms. The trend toward inclusion means that teachers must be more aware of the needs of students of diverse abilities, such as those with HID, who often have problems with several information-processing components, including sensory memory, short-term memory, working memory, long-term memory, and executive processing, as well as integrative problems between and among these various information-processing components (Swanson & Ransby, 1994). Wong (1996) noted that the primary characteristics of students with LD are processing problems, such as problems with written or spoken material which can impair their ability to learn to read, but can also underlie problems in arithmetic, writing and spelling. These problems can give rise to secondary characteristics that pertain to motivation, self-esteem, self-efficacy, and metacognition. Therefore, teachers need to mediate instruction by determining what is most important for students to learn and how it can be presented so that all can understand; organizing information to improve understanding; using instructional techniques that let students know what is to be learned and how it is to be learned and used; checking and supporting prior knowledge needed to construct new knowledge; and planning for and facilitating active learning on the part of all students, including those who need accommodations and adaptations. Fortunately, research indicates that students in general education classrooms are amenable to adaptations teachers might make. Vaughn et al. (1991) found that students appreciate teachers who adapt instructional procedures, provide special assistance, and arrange class groupings. Students were particularly receptive to


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adaptations that promoted learning, and students saw teachers who provided these adaptations as better able to meet their needs. This suggests the need for and acceptance of teachers as mediators of learning for students of diverse abilities in inclusive content area classes; these are teachers who know their content area, their students’ needs, and methods that facilitate learning. This is what Elmore called the “core of educational practice,” which is “how teachers understand the nature of knowledge and the student’s role in learning, and how these ideas about knowledge and learning are manifested in teaching and class work” (Elmore, 1996, p. 2). The pivotal role of the teacher as instructional mediator between what students need to know and do and the learning environment that promotes learning can never be underestimated, nor can the challenge implicit in this task be minimized. However, even if the teachers are able to respond to the challenge to become learned in theory, expert in content area knowledge and procedures, and cognizant of the learning needs of diverse students, a gap may still exist between teacher knowledge and use of research-based instruction leading to success for all, including students with HID in general education classes.

CONTENT ENHANCEMENT A bridge to span the gap between the challenges of science literacy for all and student diversity will be proposed; that bridge is Content Enhancement – instruction that responds to the needs of students of diverse abilities and maintains content integrity so that all citizens are science literate (Bulgren & Lenz, 1996; Lenz et al., 1990; Schumaker et al., 2002). Studies on Content Enhancement instructional procedures conducted over the past 20 years have determined the effectiveness of a number of graphic organizers and associated instructional procedures designed to help all students, including those with disabilities, learn and use content information in inclusive general education classes. Content Enhancement was designed to respond to the needs of teachers as they analyze curriculum and content standards, the learning needs of a variety of students, the demands associated with complex content information, and the need to create learning partnerships in communities of learners. To this end, Content Enhancement instructional procedures are compatible with understandings such as those of the NRC: all students come to the classroom with preconceptions about how the world works, and if their initial understanding is not engaged, they may fail to grasp the new concepts and information that are taught (NRC, 2002); students must have a deep foundation of factual knowledge, understand facts and ideas in the context of a conceptual framework, and organize knowledge in ways that facilitate retrieval and application in order to develop competence in an area

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of inquiry (NRC, 2002); and students need to acquire a metacognitive approach to instruction than can help them take control of their learning (NCR, 2002). In addition, the critical role of ongoing evaluations to assess learning is recognized (Erickson & Novak, 1998; NRC, 2000; Wiggins & McTighe, 1998). Content Enhancement has also been designed with an awareness about how students with HID learn. Therefore, components are built into Content Enhancement that provide ways that help call students’ attention to what is important and expected, provide graphic organizers to help students who learn in a variety of ways, embed strategic thinking prompts, and emphasize review of knowledge and processes of learning. Fortunately, research on many of the Content Enhancement instructional procedures have indicated that students who are HA, NA and LA as well as those with HID can all benefit from this instruction (Bulgren et al., 1988, 1994a, b, 1997, 2000, 2002; Lenz et al., 1983). Content Enhancement instructional procedures are developed around graphic organizers. In general, graphic organizers include semantic webs, matrices and other graphic formats, many of which have been subjected to intensive study and commentary. Gordon (1996) presented rationales for using explicit graphic formats. On the one hand, they allow teachers to identify students’ misconceptions or gaps in knowledge structures and to predict student performance. On the other hand, they provide the potential for students to graphically depict their own thinking structures. Novak (1998), too, has argued for the use of organizers, suggesting that those like semantic maps allow students to display cognitive understandings and that those like V-mapping guide students in inquiring about important questions. Novak (1998) further argued that meaningful learning and acquisition of powerful conceptual frameworks play a central role in the ability to engage in rational thought, but that students need explicit guidance in learning about learning and using tools and strategies to facilitate meaningful learning. A variety of other graphic forms also provide ways to make connections and identify relationships. Research involving graphic organizers to help structure passages from texts using a hierarchical format revealed that their use produced significantly higher student performance whether in teacher-directed, studentdirected with text, or student-directed with clues conditions (Horton et al., 1990). In addition, research on the use of relationship charts in the form of matrices used with semantic feature analysis also indicated that this form of graphic organizer resulted in significantly higher scores on vocabulary tests for students who used it compared to those who did not (Bos, Anders, Filip & Jaffe, 1989). Components incorporated into Content Enhancement graphic organizers are based on prior research showing how students’ understanding of critical information can be enhanced by focusing on attributes, properties or characteristics by which things are placed in categories or classes; the rules by which these attributes


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are joined in a concept class; hierarchical patterns of superordinate, coordinate and subordinate concepts; examples of concepts that promote learning; and advance organizers to help students learn content information and strengthen students’ cognitive structures (Ausubel, 1963; Ausubel et al., 1968; Bruner et al., 1956; Gagné, 1965; Klausmeir & Associates, 1979; Klausmeir & Ripple, 1971; Merrill & Tennyson, 1977). In addition, ways to help students recall important information are the focus of other Content Enhancement Routines (Bulgren et al., 1994a, b, 1997). The importance of helping students learn to acquire factual information as part of the overall learning process is also supported by other research (Ferro & Pressley, 1991; King-Sears et al., 1992; Scruggs & Mastropieri, 1990a, b). For both teachers and students in a learning community in which all the partners are aware of learning techniques and supports, other components are also included in Content Enhancement instructional techniques to establish common understandings and procedures. For example, in addition to the graphic organizers themselves, each graphic contains embedded steps that help students approach a specific learning task, e.g. understanding the structure of a course of unit, clarifying a concept, answering a critical question, or engaging in a variety of thinking strategies. Although the teacher does not necessarily ask students to memorize these steps, students have scaffolded support for approaching the thinking challenge. In addition, Content Enhancement utilizes ways to focus students’ attention and cue expectations, engage the students actively in the learning process, and participate in reviews of both content and processes to assure understanding. Therefore, efforts have been made to incorporate elements into Content Enhancement instruction that help all students have the support they need to learn. It is important, however, to consider what Content Enhancement is not. First, Content Enhancement does not replace teacher knowledge or expertise; the expert teacher is the determiner of what is to be taught and how instruction is designed. Therefore, Content Enhancement procedures were not developed to displace the critical role of the expert teacher; rather, they are one more tool for all teachers to use as they recognize the needs of their students, content area standards and growing assessment demands. Indeed, the teacher must make important decisions regarding how Content Enhancements supporting student learning are integrated with overall instruction. For example, only the expert teacher knows when material is so difficult that students need support in the form of organizational maps to see relationships or when students need an analogy to learn. Second, Content Enhancement was not designed to replace curriculum or to supplant other proven learning activities or instructional techniques. Rather, the techniques can be incorporated with other proven instructional procedures or activities that support learning for all students. For example, cooperative study group activities may be used with Content Enhancement development or generalization

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activities, and many of the Content Enhancement techniques can be used to revisit, review, and reaffirm understandings students gain from hands-on experimentation, projects, or activities. As a corollary, Content Enhancement techniques should never be incorporated randomly into instruction. They must be used at points where the teacher determines a specific technique can contribute to learning. Third, although discussion of Content Enhancement techniques are often illustrated through one of the many graphic organizers by showing a completed version, the graphic itself is never presented to the students in a completed form, nor is it considered an end in itself. Rather, it is the result of an interactive instructional session in which students and teachers are learning partners in constructing an exploration of concepts, manipulation of relationships, or explanations of conclusions; the power lies in the process of construction. Therefore, although the teacher has a completed graphic organizer in hand before instruction begins, each organizer is developed interactively with students from scratch beginning with a blank organizer. As a result, the prepared graphic that the teacher has in mind at the beginning of the class session may or may not be the one that is developed by the class. Students bring new examples, questions, and prior knowledge that make the final version richer and more meaningful under the skillful guidance of the teacher. This process is facilitated by elements common across all Content Enhancements: the use of a graphic organizer to make sure that verbal and visual presentation of content information is accompanied by mediated co-construction of learning. Despite these recurring patterns of learning and instruction in Content Enhancement, however, they are only as valuable as the expert teacher and engaged students make them as they come together to learn. As Novak indicated, “Educating is more than a science; it is also an art. It requires personal judgment feelings, and values” (p. 9).

The Teacher as Mediator of Learning: The Planning Process Teacher mediation involves both mediation of content knowledge acquisition and the processes involved in strategic approaches to learning. First, helping students construct knowledge is a complex, nuanced challenge, requiring careful planning of content and consideration of how to involve students in the construction of meaning. Fensham et al. (1994) noted an agreement among many science educators that construction does not mean that “anything goes,” or that any student can claim that his or her meaning is as good as that of a scientist. Indeed, construction, the authors agreed, is not simply discovery. Construction can be guided, that is, the teacher guides students to make sense of facts and allows students to explore


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in appropriate and productive directions without inhibiting any students’ views or thoughts. These authors recognized this as an advanced skill requiring teachers to have both pedagogical and content knowledge. Similarly, Jones et al. (1987), building on the work of Feuerstein (1985), explained that teacher mediation means that a teacher intercedes between the learner and learning environments to help students organize and interpret information. The teacher provides support for learning but also conceptualizes skill instruction as a means of attaining content objectives so that students can become independent learners who can use strategies. Some students, at least at the outset, need explicit instruction on what is being taught, why it is important, what procedures will be used in the class, and what is expected of each student. For the most part, many teachers do not provide explicit instruction, that is, lead students through the rationales, procedures and expected outcomes associated with instruction (Bulgren & Lenz, 1996). A central principle of Content Enhancement is that teachers must inform students about instruction and guide them in how to benefit from that instruction in order to move to the level of independent learners. Mercer et al. (1996) in a review of interpretations of constructivism supported the finding that some students do, indeed, need explicit instruction. As a result, they proposed a continuum of explicit-to-implicit instruction to accommodate a diversity of learning needs. Using the area of mathematics to illustrate their proposal, they noted that a variety of instructional activities, strategies and techniques fit within a continuum of explicit-to-implicit instruction and match the learning and motivational needs of different learners. Second, teachers need to plan not only to assure participation in learning, but also to enhance students’ level of strategy knowledge. It is important that teachers recognize that some students already know and use learning strategies – techniques, principles or rules that enable a student to learn to solve problems and complete tasks independently. The teacher recognizes that students who use learning strategies have ways to approach learning tasks; these strategies guide their personal thinking and action, helping them to reflect on outcomes and self-monitor actions. The teacher as “expert” also recognizes when students do not have knowledge and use of learning strategies; that is, they are not learning independently in efficient and effective ways nor do they have skills associated with metacognition, that is, a knowledge and awareness of one’s own cognitive processes (Mayer, 1987) to help them decide on appropriate strategies. In considering both knowledge and strategic approaches to learning, Bulgren and Lenz (1996) found that the teacher plays a critical planning and decisionmaking role in determining which information is most important for students to learn. In Content Enhancement, this is accomplished with a model of planning cued by the acronym “SMARTER.” SMARTER Planning involves the following steps: selecting critical content outcomes and questions; mapping the organization

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of the content, analyzing difficulties in learning; reaching enhancement decisions; teaching according to those decisions; evaluating, and reteaching based on that evaluation (Bulgren & Lenz, 1996). Choosing the most critical information can be guided by the planning techniques such as Curriculum Pie (Lenz et al., 2003). These planning techniques were developed to help teachers select a relatively small critical mass of information that all students must know, a somewhat larger amount of information that most will learn, and an extremely large amount of content information that only some students, due to high interest or career goals, will learn, The Curriculum Pie (Fig. 1) helps teachers think about those issues and the different ways students will be expected to think about and use the knowledge such as: (a) acquisition of core content facts, concepts, principles and procedures; (b) manipulation for understanding and reasoning; and (c) generalization for application and problem solving (Lenz et al., 2003). Based on decisions made in this planning process, Content Enhancement provides ways to help teachers select and organize critical content information; elicit, support and build on students’ prior knowledge; develop deep knowledge of content including facts and relationships; choose to focus on metacognition associated with analysis and problem solving patterns; and prepare students for assessments. As the teacher proceeds through the SMARTER planning, he or she has an array of supports in the form of Content Enhancement graphic organizers to promote learning, facilitating organization, understanding, recall, and application of information. Teacher as Mediator of Learning: Learner- and Knowledge-Centered Instructional Supports Content Enhancement graphic organizers and instructional routines have been designed to help teachers mediate student learning, explore and use prior knowledge, assure deep understanding, promote strategic thinking, and assure success on assessments. Organizational Supports In the content classroom, cognitive processing characteristics of students with academic disabilities may manifest themselves in the inability to organize information independently, which makes it difficult to focus on important ideas as distinguished from less important details. In Content Enhancement, graphic organizers help students organize information and highlight what is most important. This requires the teacher to organize the information that has been selected as most important during SMARTER planning and to transform information in ways that it becomes more accessible to all students.


Fig. 1. The Curriculum Pie: Planning for the Type of Outcome Expected for Students.

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One use of graphic organizers is to help teachers plan for instruction that manages and organizes extensive amounts of complex information. Learning demands include comprehending information from texts, which may be extensive in scope and detail. With regard to texts, one need only look at the rapidly expanding size of textbooks to appreciate this challenge. To add to the problems associated with large amounts of information, some teachers see the text as the same as the curriculum (Thornton, 1991), and many accept texts as the major source of content (Borko & Niles, 1987). Science experts have long recognized the importance of organizing this information, but this recognition may become even more critical with a large text from which teachers must select the most important information or, in some cases, even reorganize and add to the information presented. In other cases, a teacher who is an expert mediator in his or her content area often sees the main textbook for the course as only one source of information to be used rather than the sole determiner of course content. This is often the case in which a teacher is, indeed, an expert in huge bodies of knowledge related to his or her subject area. As a result, many teachers may use sources other than the required text, including his or her own expertise, to teach all that is required of students; this often involves recalling and manipulating content information from multiple sources and generalizing that information for use in inquiry and performance tasks. Content Enhancement provides graphic organizer tools for this purpose. In Content Enhancement, graphic organizers have been developed to help organize information at the course, unit and lesson levels (Bulgren & Lenz, 1996; Lenz et al., 1993, 1994, 1998) by which pieces of critical information are represented in networks using conceptual graphic structures. For example, see Fig. 2 for a Unit Organizer that illustrates how a teacher and students might organize a unit of information and key relationships for understanding a biology unit on the topic of “Flow of Energy through Systems.” In addition to the name of the unit in Section 1, relationship to the units that come before and after are cued in Section 2 and Section 3, the bigger picture placement in the study of Biology is written in Section 4, the relationships in the unit are placed in a map with line labels to indicate connections and a paraphrase of the title of the unit to assure understanding in Section 5, relationships and thinking patterns are listed in Section 6, critical questions are placed in Section 7, and a schedule is presented in Section 8. See the bottom of Fig. 2 for a blank expanded Unit Organizer that the teacher and students construct interactively in class to develop a deeper understanding of the unit organization. In keeping with the instructional routine common across Content Enhancement, each of the routines such as the Unit Organizer Routine follows a pattern in which students are informed of the importance of the instructional technique, the targeted content, and expectations for learning and participation when the teacher cues the students prior to instruction; each graphic organizer is


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Fig. 2. Example Unit Organizer for the Unit “The Flow of Energy Through Systems” and Blank Expanded Unit Organizer.

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developed interactively with students supported by embedded strategic steps; and a review component is used in which the process and content of the learning are reinforced. Establishment and Use of Prior Knowledge Prior knowledge, so critical to constructing new knowledge, may be less extensive for students who have not had a wide variety of previous experiences (NRC, 2000). This lack may be due to a variety of factors including time spent in special education resource rooms by students with disabilities receiving much-needed instruction in requisite basic skills or by frequent moves from district to district where curriculum sequences may differ. As a result, many students with special needs or others at risk for school failure may require scaffolded experiences to bring forth or even compensate for these deficits. A graphic organizer that promotes learning by developing an analogy between a known concept and a new concept is a Concept Anchoring table (Bulgren et al., 1994a). See Fig. 3for a Concept Anchoring Table that helps students explore and understand the concept of a cell and its parts. Using a known concept such as a fast-food restaurant, analogies between parts of a cell and work areas and machines are developed, e.g. the nucleus of a cell is like a manager’s office in that both are control centers. This example illustrates another common component of many Content Enhancement techniques in that it provides a vehicle for formative evaluation of students’ readiness to proceed with learning. For example, in Fig. 3, Step 3, teacher and students are cued to discuss and write what they already know about a concept on a blackboard or other writing surface; in some versions, space is provided for this on the Anchoring Table itself. This exploration of prior knowledge is done prior to the development of the rest of the Anchoring Table and provides the foundation for the development of understanding. In addition to the Anchoring Table, other Content Enhancement graphic organizers have been designed to assist in the exploration of prior knowledge as well. This occurs as teachers elicit, and students offer, information and experiences they can contribute to the discussion. For example, graphic organizers such as the Concept Diagram in Fig. 4 provide space on the graphic itself for students to jot down what they and others have to contribute about the concept before the graphic is co-constructed by the entire class. Deep Knowledge It is also important that students develop a deep knowledge of key concepts and facts. The graphic device that has been developed to focus on a single concept is a Concept Diagram (Bulgren et al., 1995). (See Fig. 4 for a Concept Diagram

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Fig. 3. Example Concept Anchoring Table for the Concept “Organelles Within the Plasma Membrane of a Cell.”

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Fig. 4. Example Concept Diagram for the Concept “Cell Membrane” and a Blank Alternative Version of the Concept Diagram.


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developed to explore the concept of “cell membrane.”) By completing Step 1 and Step 2, students begin with an understanding of how a concept (cell membrane) fits into a larger category (cell component). Then, the exploration and scaffolding of prior knowledge, built into many of the Content Enhancement graphic organizers, are cued as teacher and students share what they know about a concept as shown in Step 3 of Fig. 4. After students explore their prior knowledge and volunteer key words they co-construct the graphic: they cooperatively identify characteristics that are always, sometimes or never present in any member of a concept class, assure deep understanding by comparing examples (plasma membrane) and non examples (cell wall) with teacher mediation, then independently practice identification of an new, previously unencountered item (heart valve) to determine if it is an example or non example of the concept. Finally, the class as a group constructs a definition of the concept. See bottom of Fig. 4 for a blank alternative version of the Concept Diagram that would be constructed interactively by teacher and students. Content Enhancements are designed to be blended with other classroom activities that the teacher selects to promote understanding. For example, classroom interactions using a Content Enhancement graphic organizer can be used after students have been engaged in experiments or explorations that illustrate important knowledge or in a dialogue allowing a student to explain his or her own understandings or ask questions about another student’s understanding. The teacher can propose tasks for student independent explanations or generalization of understanding, organize group learning activities, or set the stage for student questioning. Strategic Knowledge Within each of the Content Enhancement graphic organizers are steps that help teachers and students respond to each learning challenge; however, the steps serve a dual purpose in that they may be recalled through an acronym. See Fig. 5 for a completed sample Comparison Table (Bulgren et al., 1998) comparing the concepts animal cell structure and plant cell structure. On a Comparison Table, teacher and students are guided through the steps by an acronym “COMPARING” which reminds the teacher and students to communicate targeted concepts; obtain the overall concept; make lists of known characteristics; pin down like characteristics; assemble like categories; record unlike characteristics; identify unlike categories; nail down a summary; and go beyond the basics. These steps are guided by numbers as well as reminder words and phrases on the table itself. In Fig. 5 on pages 166 and 167, see the blank Multiple-Concept Comparison Table designed for comparison of more than two concepts. Although these strategic steps are used in the development of each graphic organizer, teachers often choose not to emphasize the specific goal of memorizing steps. However, through teacher guidance in the cooperative development of the

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Fig. 5. Example Concept Comparison Table for the Concepts “Animal Cell Structure” and “Plant Cell Structure” and Blank Table for Comparing Multiple Concepts.

information on the organizer, or even by learning as the teacher models such thinking, students are provided with repeated experience in thinking patterns and problem-solving activities. Therefore, the schema for approaching content-area challenges is made clear for students. It is up to the teacher as to how and when to highlight the strategic steps required in a specific content area. As teachers guide students to call upon a host of strategies for solving problems and analyzing situations, Content Enhancement presents opportunities for both thinking about how to use a specific strategy and thinking about a range of strategy choices in a metacognitive fashion. Assessment Knowledge Thinking challenges are also embedded in Content Enhancement graphic organizers that encourage questioning, explanation, and generalization of understanding. For example, prompts on the Concept Diagram and Comparison Table include thinking challenges that allow students to explore characteristics of new examples


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Fig. 5. (Continued )

of a concept or to challenge the students to use the knowledge they have acquired (See Step 6 in the Concept Diagram in Fig. 4 and Step 9 in the Comparison Tables in Fig. 5). These challenges promote manipulation of conceptual knowledge on the part of students and formative evaluation opportunities for the teacher. However, a specific way to explore critical questions and prepare students for assessments is also one of the components of Content Enhancement. (See Fig. 6 for a Question Exploration Guide to answer the critical question “How do green plants get their food?”) With a Question Exploration Guide, the teacher and students actively collaborate to analyze a critical question, explore both explicit and implicit key words and factual information needed to answer the question, break down or “unpack” a large, difficult question into smaller, more manageable questions, construct a main idea answer, and use the main idea answer in both related material and ways that promote generalization of the main idea. This graphic organizer directly addresses assessment challenges in national standards and benchmarks (e.g. National Research Council, 1996), district guidelines, and classroom assessments. Only by an awareness of these challenges can the teacher plan and teach

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Fig. 5. (Continued )

in ways that support responses to assessments based on standards and the needs of students. In addition, within the Content Enhancement repertoire are ways to help students recall important information. For example, students may be introduced to keyword devices, visual imagery, or acronyms as indicated by content demands. For example, students may use the first letters of words in a sentence to recall the names of organelles within cells such as the nucleus, ribosomes, mitochondria, reticulum endoplasmic, apparatus Golgi, lysosomes and vacuoles. One such sentence might be “Nucleus regulation makes great efficient living vehicles.” See Bulgren et al. (1995) for examples of recall devices. The Teacher as Mediator of Learning: Community Partners in the Learning Process The goal of helping all students become active participants in a community of learners is often urged (Lenz et al., 2003; NCR, 2000). Reid and Stone


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Fig. 6. Example Question Exploration Guide for the Critical Question, “How do Green Plants Get their Food?”

(1991) discussed cognitive instruction, an approach to learning and teaching in which they characterized students as active apprentice learners who benefit from participation in goal-oriented, collaborative activities. In this model, strategies are modeled, demonstrated and discussed as they are used in meaningful contexts. In arguing for this approach, Reid and Stone contended such an approach utilizes the best from theories such as those of Vygotsky and Piaget, emphasizing that these approaches are not conflicting or incompatible; rather, each theory contributes a perspective that the other lacks. A common component of all of these theories is that students can and must learn to be active, involved, motivated learners, learning from each other as well as experts; they can call upon a wide range of strategies to use as partners in a learning community. Content Enhancement is no exception. Content Enhancement supports learning communities by incorporating principles and building on an instructional routine common across all Content Enhancement instruction that supports learning shared by all members of a class. First, the Course Organizer (Lenz et al., 1998) incorporates community-building procedures that are developed with students at the beginning of the school year.

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Relative to knowledge, places are provided on the Course Organizer for a course map of the units, important course questions, ways of learning, critical concepts, and course projects and experiences. Relative to community, places are also provided for a list of ways that members of the class will work together on creating a learning community, a list of the ways that learning and behavior will be managed, and a list of the strategies that will be used and reinforced as students learn the content. Second, in Content Enhancement, each instructional routine, although targeted for a particular instructional goal such as learning by comparing relationships or answering a critical question, is surrounded by common instructional procedures to help students participate fully in the construction of knowledge. This is an instructional sequence involving “cueing” in the form of advance organizers to set expectations, rationales, and procedures; “doing” in the form of participation in the exploration of knowledge guided by individual graphic organizers and strategic steps; and “reviewing” content and process. These provide the means for teachers to involve students as partners in a community of learners based on the needs of each and every student. To summarize, regardless of the Content Enhancement graphic organizer selected, the teacher has an instructional tool that combines a visual format with a variety of verbal formats. Then, incorporated into each graphic organizer are steps that guide strategic thinking about the selected learning task; these are prompts for approaching a variety of tasks strategically – tasks ranging from understanding a single concept to generalizing understandings to real world situations. These are incorporated into a common instructional sequence to promote a learning community. The teacher and the students should revisit and reflect upon the enhancements and thinking processes together. Classroom instruction is not a guessing game that places the burden on the students to figure out what the teacher thinks is the most important information. The students’ energy that might have been expended in that guessing game will be better spent exploring what they already know, what they can contribute to the learning discussion, and how they can build new knowledge from that base. This is particularly important for students with learning disabilities, who often do not recognize the usefulness or even the existence of innovative teaching practices when the teacher uses them (Lenz et al., 1987). Harris and Graham (1996) argued that students must be provided with the level of support they need to acquire strategies, skills, conceptual learning, flexible applications, and understanding – giving them whatever level of support is needed, be it explicit, direct explanation or discovery. Therefore, all approaches should be considered in planning for instruction, and integration of different approaches can result in meaningful forms of instruction on a continuum of instruction (Lenz


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& Ehren, 1999). This results in complex teaching skills and interactive learning such as that described by Borkowski and Muthukrishna (1992) as guided and direct, as well as transactional and constructive.

CONCLUSION In conclusion, the teacher is in charge of setting up the experiences that engage students as they explore and construct learning as a community. The teacher can never be replaced as a determiner of student needs and selection of instructional methods. Ultimately the teacher is responsible for planning, monitoring, and mediating instruction. The teacher may devise experiences through which students can construct knowledge, but the learning situation is always under the watchful and expert eye of the teacher, who can direct learning and insert prompts and scaffolds, as needed. All Content Enhancement instructional procedures are predicated on learning principles such as those of Carver (2001) who proposed designing a model learning program that builds on prior knowledge; makes thinking explicit; emphasizes links; provides practice opportunities; and expects individual variability. Content Enhancement principles provide an echo of these: (a) students learn more important information if that information is distinguished from unimportant information; (b) students learn more information when the structure or organization of that information is made evident and when relationships among pieces of information are made explicit; (c) students learn abstract content easier if it is presented in concrete form and made explicit and procedures are explained; (d) students are more likely to learn new information if it is tied to information they already know; and (e) students learn more when they are actively engaged in learning activities. Of course, any principle can be contested when taken out of context of meaningful instruction and learning. Principles embody assumptions that can only be fully realized in a classroom in which teachers implement them with high levels of understanding and expertise. For example, active learning requires high level engagement; the use of concrete examples must be balanced with abstractions students need to understand complex ideas; explicit instruction must be balanced with challenging tasks to assure that students do not become dependent on teacher directions; the vast array of prior knowledge, both correct and incorrect, must be monitored to assure learning; and important ideas can be acquired in a variety of ways, not the least of which is inquiry, judgment and evaluation experiences. Ultimately, the Content Enhancement teaching routines can bridge the gap between learning challenges for all students, including those with special

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needs, and the complex demands of construction of knowledge in inclusive content classrooms. This view of teaching and learning in inclusive content courses brings with it several implications. Olsen (1999) in his review of constructivism contended that such an approach means extensive rethinking of the goals of education, how to achieve those goals, extensive curriculum revision and different forms of assessment. He contended that along with extensive curriculum revision, better and more extensive teacher in-service will be needed, as well as increased time on fewer topics and identifying what is most important for students to learn. These are especially important principles if students with disabilities are to learn new and demanding uses of information. Ongoing research, in-service and pre-service professional development, and school-wide adoption of these educational goals will be necessary. In response, the research on instruction such as Content Enhancement is ongoing – building on, learning from, and growing with educators, researchers and thinkers who call on teachers to educate all of our students in ways that ensure a lifelong and productive use of knowledge. The ultimate goal is to assure that graduates of American schools, both students with and without disabilities, can identify and solve problems, making contributions to society throughout their lifetimes.

ACKNOWLEDGMENTS The author wishes to acknowledge the contribution to the Content Enhancement figures illustrating the Biology unit by Melinda McKnight, Lynn Martens, and Kylee Sharp. Professional development information associated with Content Enhancement may be obtained by contacting Director of Development, University of Kansas Center for Reserved on Learning, 517 J. R. Pearson Hall, Lawrence, Kansas 66045, by calling 785-864 4780 or accessing www.ku-crl.org.

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Borko, H., & Niles, J. A. (1987). Description of teacher planning: Ideas for teachers and researchers. In: V. Richardson-Koehler (Ed.), Educators Handbook: A Research Perspective (pp.167–187). New York, NY: Longman. Borkowski, J. G., & Muthukrishna, N. (1992). Moving metacognition into the classroom: “Working models” and effective strategy teaching. In: M. Pressley, K. R. Harris & J. T. Gutherie (Eds), Promoting Academic Competence and Literacy in School (pp. 477–501). San Diego, CA: Academic Press. Bos, C. S., Anders, P. L., Filip, D., & Jaffe, L. E. (1989). The effects of an interactive instructional strategy for enhancing learning disabled students’ reading comprehension and content area learning. Journal of Learning Disabilities, 22(6), 384–390. Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). The study of thinking. New York: Wiley. Bulgren, J. A., Deshler, D. D., & Schumaker, J. B. (1995). The content enhancement series: The concept mastery routine. Lawrence, KS: Edge Enterprises. Bulgren, J. A., Lenz, B. K., Deshler, D. D., & Schumaker, J. B. (1995). The concept comparison Routine. Lawrence, KS: Edge Enterprises. Bulgren, J. A., & Lenz, B. K. (1996). Strategic instruction in the content areas. In: D. D. Deshler, E. S. Ellis & B. K. Lenz (Eds), Teaching Adolescents with Learning Disabilities: Strategies and Methods (2nd ed., pp. 409–473). Denver, CO: Love Publishing. Bulgren, J. A., Schumaker, J. B., & Deshler, D. D. (1988). Effectiveness of a concept teaching routine in enhancing the performance of LD students in secondary-level mainstream classes. Learning Disability Quarterly, 11, 3–17. Bulgren, J. A., Schumaker, J. B., & Deshler, D. D. (1994a). The content enhancement series: The concept anchoring routine. Lawrence, KS: Edge Enterprises. Bulgren, J. A., Schumaker, J. B., & Deshler, D. D. (1994b). The effects of a recall enhancement routine on the test performance of secondary students with and without learning disabilities. Learning Disabilities Research and Practice, 9(1), 2–11. Carver, S. M. (2001). Cognition and instruction: Enriching the laboratory school experience of children, teachers, parents, and undergraduates. In: S. M. Carver & D. Klahr (Eds), Cognition and Instruction: Twenty-Five Years of Progress. New Jersey: Lawrence Erlbaum. Driver, R., Newton, P., & Osborne, D. (2000). Establishing the norms of scientific argumentation in classrooms. Science Education, 84(3), 583–590. Elmore, R. F. (1996, Spring). Getting to scale with good educational practice. Harvard Educational Review, 66(1). Erickson, L. (1998). Concept-based curriculum and instruction: Teaching beyond the facts. Thousand Oaks, CA: Corwin Press. Fensham, P., Gunstone, R. F., & White, R. T. (1994). Content of science: A constructivist approach to its teaching and learning. London: Falmer Press. Gagné, R. M. (1965). The conditions of learning. New York: Holt, Rinehart & Winston. Gordon, S. E. (1996). Elicting and representing biology knowledge with conceptual graph structures. In: K. M. Fisher & M. R. Kibby (Eds), Knowledge Acquisition, Organization, and Use in Biology. Springer-Verlag. Harris, K. R., & Graham, S. (1996). Constructivism and students with special needs: Issues in the classroom. Learning Disabilities Research & Practice, 11, 134–137. Hodgkinson, H. (1991). Reform vs. Reality. Phi Delta Kappan, 73(1), 8–16. Horton, S. V., Lovitt, T. C., & Bergerud, D. (1990). The effectiveness of graphic organizers for three classifications of secondary students in content area classes. Journal of Learning Disabilities, 23(1), 12–22.

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SOCIAL STUDIES AND STUDENTS WITH DISABILITIES: CURRENT STATUS OF INSTRUCTION AND A REVIEW OF INTERVENTION RESEARCH WITH MIDDLE AND HIGH SCHOOL STUDENTS夽 Judith L. Fontana ABSTRACT Inclusion, state mandated achievement tests, current instructional materials and practice and the academic needs of an increasingly diverse student population have converged necessitating an in-depth review of instructional strategy research accomplished with students with mild disabilities. After confirming the value of social studies content this chapter provides context for the exploration of instructional strategies for social studies instruction by first investigating research on social studies textbooks, teacher use of these texts and some student characteristics that make using these materials difficult. Background and implications of mandated assessments and the inclusion movement is provided. A review of intervention strategy research concludes with a discussion on the implications for instruction. 夽 This

chapter has been refined and expanded from sections of the author’s doctoral dissertation.


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Suggestions on how to embed strategies into ongoing daily instruction are provided.

INTRODUCTION The purpose of this chapter is to explore and synthesize intervention research in social studies content that has been conducted with middle or high school students. To provide context certain issues related to current practice, materials, and societal change have been addressed.

RATIONALE: VALUE OF THE CONTENT AND INSTRUCTIONAL CONCERNS The July/August 1998 issue of The Social Studies was devoted to inclusion. In the introduction “Inclusion – Where Social Studies Teachers Need Help!” (Pahl, 1998, p. 149), editor Ron J. Pahl comes out strongly for the importance of social studies education, as a basis for responsible citizenship for all students and alludes to the possibility that this has not always been the case. In the same vein he states that, “The exclusion of certain students from such an education is not acceptable” (Pahl, 1998, p. 149). Sound instruction in social studies content, a synthesis of geography, economics, culture(s), history, and government is expected to result in competent, thoughtful, responsible citizens (Brophy, 1990; Patton et al., 1987). The considered importance of social studies content is reflected in achievement testing. Almost half of the 50 states have mandated social studies assessment in middle school, high school, or both, assuring the position of social studies instruction in the hierarchy of public education (Orlofsky & Olson, 2001). Social studies education is considered crucial for all students, including those who do not learn at the same rate, or in the same manner as their peers. Aspects of the instructional dilemma include, but are not limited to: (a) characteristics of the at risk population; (b) current trends in legislation resulting in changing demographics in U.S. classrooms; (c) materials and methods of instruction; and (d) the push for educational standards which has resulted in the proliferation of high stakes testing.

Characteristics of Students with Learning Disabilities The number of students identified with learning disabilities (LD) has increased steadily (Lerner, 2000; Zigmond et al., 1995). They form a heterogeneous group,

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but, several factors which affect the learning of social studies may be considered intrinsic in varying degrees in various circumstances to students with LD. These include: (a) a high incidence of language and reading difficulties (Lerner, 2000; Lyon, 1985); (b) problems with memory (Ceci et al., 1981; O’Shaughnessy & Swanson, 1998; Swanson, 1994; Swanson & Trahan, 1990); (c) difficulties with thinking, drawing conclusions and the recall, selection and use of effective strategies (Mastropieri & Scruggs, 2000); (d) information processing deficits (Scanlon et al., 1996; Swanson, 1987); (e) lack of prior knowledge (Pressley et al., 1987); and (f) lack of basic skills and/or strategies (Maheady et al., 1988a, b). Another student-centered factor not limited to students with LD and pervasive in content classes is inexperience with expository prose in general (Harniss et al., 1994; Stetson & Williams, 1992). These students, in spite of language and reading difficulties that identify them as at risk (Mastropieri & Scruggs, 2000), are, in response to the inclusion movement more likely to be placed in regular education classrooms for content instruction and are then expected to meet the same specific academic competency levels as their peers. The impact of the inclusion movement and student placement is discussed next.

Current Trends in Legislation: Inclusion and Student Placement In 1986, under the guidance of Madeline Will, a policy statement was issued by the Office of Special Education and Rehabilitative Services of the U.S. Department of Education (OSERS) which inspired the concept of inclusion (Lerner, 2000). Part of a general desire to reform special education, this Regular Education Initiative (REI) supports the concept that every child belongs in a regular classroom first and special services are ancillary. It is the driving force behind the inclusion movement (Mastropieri & Scruggs, 2000; Semmel et al., 1995). The definition of inclusion varies among districts and even among schools within a district. “Inclusion means different things to people who want different things from it” (Fuchs & Fuchs, 1994, p. 299). The 1997 revision of IDEA reaffirmed the federal commitment to educating children with disabilities within the context of current educational reform. A greater emphasis was placed on outcomes, educational results, with the requirement that students with disabilities be included in state and district-wide assessments with or without accommodations as appropriate. In keeping with the inclusion movement, the 1997 amendments also require that a student’s Individualized Educational Program (IEP) address how the student will access the general education curriculum (OSEP, 2000). For the student with LD the setting and levels of primary and related services vary by student age and disability; however, an

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increasing number of these students are receiving instruction in general education settings in inclusion classrooms (OSEP, 1999, 2000). Access to the curriculum may result in access to assessment including state mandated proficiency testing.

Current/Common Practice in Social Studies Instruction Research suggests that basal textbooks used for social studies instruction may often be inappropriate for their targeted population because of specific readability issues and lack of instructional strategy suggestions for teachers. Within texts, expository patterns of writing may vary to the extent that comprehension is impeded. Poor organization and the over-estimation of student prior knowledge contribute to the difficulties students may encounter as they attempt to read for meaning. According to Harniss et al. (1994), “Social studies textbooks appear to be among the most difficult reading material students encounter” (p. 237). Stetson and Williams (1992) noted that social studies textbooks (grade levels were not specified) are more difficult to read than textbooks in other disciplines citing a wide range of readability levels within one text, unique vocabulary, and the quantity of information students were called upon to process and learn. Kinder et al. (1992) examined ten, 8th grade social studies textbooks found on the state adoption lists of Texas and California. The Fry Readability Formula used by these authors revealed a mean readability level of 10.9 with a range of 9th grade to college levels for these 8th grade textbooks, thus challenging for many students. While readability scales provide some insight into the difficulty level of a text, the use and presentation of new vocabulary influences the level of ease a student will experience with a text. Harmon et al. (2000) investigated the nature of vocabulary instruction in teacher’s editions of social studies textbooks for grades 4–8 which were on the Texas state adoption list. The authors identified a gap between vocabulary instruction and what is expected of the students when writing assignments were related to social studies content. They noted that although publishers include some vocabulary teaching strategies, lower level association activities such as matching and fill in the blank assignments were most common. All textbooks highlighted what were considered to be key vocabulary, but none included pronunciations. Beck and McKeown (1991) synthesized research on social studies textbooks. They identified three major areas of deficiency. A lack of consistent framework for the reader to use to organize and relate information was the first deficiency noted. The authors identified several patterns used to present information: cause/effect, comparison/contrast, problem/solution, and description. This integration of the styles was determined to result in unpredictable text. Secondly, a lack of


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coherence in textbook presentations contributed to the level of difficulty of textbooks. Finally, the authors criticized textbook publishers for overestimating students’ prior knowledge. In their suggestions for teachers the authors stressed the need for in-depth instruction and the importance of assisting students to make connections. Results of an examination into the effects of prior knowledge on students’ ability to cope with poorly constructed textbooks (McKeown et al., 1992) supported the earlier advice of Beck and McKeown (1991). In this investigation, students participated in lessons aimed at improving their background knowledge before reading revised or original text. It was concluded that background knowledge is most effective if the textbook is constructed with coherence. More recently Jitendra et al. (2001) evaluated four middle school geography textbooks for readability and other instructional elements in relationship to the needs of diverse learners. Readability continues to be above the targeted grade level. The books were judged to be fact laden, but lacking in concepts or principles. Only one publisher provided suggestions for diverse learners. Some critical aspects related to instructional materials have been established. How teachers use or adapt these materials is also a critical issue. Bean et al. (1994) investigated teacher’s use of social studies textbooks, their perceptions about the strengths and weakness of those books, and adaptations they made to accommodate students experiencing difficulty in social studies. Twenty-two classroom teachers, in grades 1–7 from a variety of rural, suburban, and urban schools were interviewed. Ninety-one percent of the teachers in this sample reported that they used a single basal social studies text as their primary source for preparing instruction. They appreciated the organizational framework basal programs provided. The majority of teachers in this study complained about the readability level of the textbooks and several criticized vocabulary instruction techniques used by textbook publishers. Reported adaptations included activating prior knowledge, oral guided reading, tapes, teacher read aloud, discussion, additional textbooks, projects, and workbooks. Almost half provided some sort of study guide. It was observed that although teachers were concerned about the difficulty level of the textbooks, they continued to use them as the primary source of instruction. Tyson and Woodward (1989), speaking to textbook use in general, reported that 75–90% of classroom instruction is defined by the scope and sequence of textbooks. Teacher dependency on poorly conceived basal texts may be further exacerbated by false notions of student proficiency. In spite of their perceptions of textbook inadequacies, many teachers continue to rely upon basal textbooks to drive instruction. There appears to be an over-reliance on inherently deficient instructional materials coupled with a lack of experience with expository prose among students in general (Bean et al., 1994; Harniss et al.,

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1994; Stetson & Williams, 1992). Consider the plight of the teacher faced with an increasing number students with mild disabilities who do not possess adequate skills to read grade-level texts, and/or have not developed sufficient work-study habits to offset skill deficits (Maheady et al., 1988a, b). These students are also more likely to be included in state mandated high stakes testing.

Mandated Assessments IDEA (1997) reaffirmed the Federal commitment to educating children with disabilities within the context of current educational reform. A greater emphasis was placed on outcomes and students with disabilities are to be included in state and district-wide assessments with or without accommodations as appropriate (OSEP, 2000). No Child Left Behind (NCLB) Act of 2001 requires that states applying for a grant must satisfy the requirements of the statute and also coordinate with IDEA (CEC, 2002). The statute specifically refers to Section 612(a)(17)(A) of the IDEA, which requires that students with disabilities participate in general state and district-wide assessments with or without accommodations (NCLB, 2001). The law includes all public elementary and secondary school students. Those with disabilities are not excepted (CEC, 2002). It is notable that by 2001, forty-seven states had established academic standards in all four core subjects (Orlofsky & Olson, 2001). The same authors reported that: (a) all 50 states test their students; (b) forty-five states require “school report cards”; (c) twenty-seven states either rate all of their schools or identify low-performing ones; (d) twenty-seven offer assistance to low-performing schools; and (e) fourteen states have the authority to close down, completely re-staff, or overhaul schools which fail chronically. As a content area, social studies is assessed by almost half of the 50 states, and students with mild disabilities are expected to participate in these assessments. Change in instructional philosophy (inclusion movement) coupled with high stakes testing for all students requires that educators implement the most effective means of instruction.

A REVIEW OF INTERVENTION RESEARCH IN SOCIAL STUDIES CONTENT WITH STUDENTS WITH LD AND MILD DISABILITIES For the purposes of this review, intervention research in social studies for students with mild disabilities has been divided into three categories: (a) instructional delivery routines; (b) strategies for organization of information; and (c) interventions


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with mnemonic strategies to facilitate the memorization of targeted information. Instructional delivery routines include peer tutoring, technology supported projects, and routines that incorporate multi-strategy applications. Organizers include an array of formats with or without visual displays used to activate prior knowledge, facilitate notetaking, or guide study. Mnemonics studies include those which compared or measured the efficacy of the keyword, keyword/pegwords, and/or elaborative reconstructions against other methods. Although the focus of this chapter on interventions with middle or high school students, studies with elementary school students may be noted for the readers benefit. Subheadings occur under each of the three broad categories. The following are commonalities among the studies synthesized in this section. Studies or applications were published between 1985 and the present; Studies are quantitative; Several designs are represented including within subject crossover, multiple baseline, pretest-posttest, experimental vs. control or no treatment control, and A vs. B; The number of participants in the studies varied, but all included studies had a minimum of 3 participants; Student participants were enrolled in, middle, or high schools; Participants represent a variety racial and ethnic minorities (data analysis procedures did not address race or ethnicity as covariates); Participants represent populations labeled as LD, ED, mild disability, MMR, and nondisabled students; With the exception of several studies that integrated social studies and science content, literature reviewed within the instructional delivery routines and strategies for organization category focus on social studies content; Mnemonic studies include those related to social studies content only; Articles were located through a variety of keyword and author searches of PsycINFO, ERIC and Dissertation Abstracts electronic databases as well as through ancestry searches and a hand search of selected journals; Studies or applications appeared in peer-reviewed journals, ERIC documents, or are dissertations.

Instructional Delivery Routines Studies have been grouped under three subheadings: (a) class-wide peer tutoring (CWPT); (b) technology supported projects; and (c) teacher directed routines with strategy applications. Historical or general overviews introduce each subsection.

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Class-Wide Peer Tutoring The roots of this instructional method has been traced to the system of cross-aged tutoring defined by Andrew Bell in the late 1700s and has gained in popular support with modern educators only in the last 20 years (Byrd, 1990). In its modern form, peer tutoring or class-wide student tutoring teams (CSTT) were developed at the Juniper Gardens Children’s Project in Kansas City, Kansas, with the specific goal of improving instruction for students who were disadvantaged, members of minority groups, or designated as LD (Byrd, 1990). Several models of peer tutoring exist: (a) Greenwood and colleagues (CWPT); (b) Fuchs and Fuchs and colleagues, Peer Assisted Learning Strategies (PALS); and (c) Maheady and colleagues. A recent literature synthesis of research on students with disabilities as tutors from 1982 to 2000 (Mastropieri et al., 2000) was comprised of 35 studies indicating the current level of interest in peer tutoring as a viable strategy for students with mild disabilities. Studies designed to measure the effects of peer tutoring models on social studies achievement for students with mild disabilities receiving services in resource rooms (Maheady et al., 1988a, b; Mastropieri et al., 2003; Spencer, 2001) and in general education classrooms that include students with mild disabilities (Maheady et al., 1988a, b) had varying results. Maheady et al. (1988a, b) investigated the effects of class-wide peer tutoring on the academic performance in social studies of 20 students in grades 9–12. Students were identified as, mildly handicapped (MH). The population included students in two resource room classes identified as learning disabled, behavior disordered, or educable mentally retarded. The school was described as urban with a racially and ethnically diverse population. An ABAB withdrawal of treatment design was implemented across two settings and two curricula. Settings were two social studies resource classes, one for students in grade 9 and the other for students in grades 10–12. The intervention lasted 20 weeks. The number of 30-minute sessions varied weekly. Academic measures consisted of weekly social studies quizzes. Baseline materials included lecture, discussion and study guides. After 4 weeks the intervention was added to the routine. Students were randomly assigned to competitive teams and then teacher paired for the procedure. Students were taught a tutoring process that included questioning, correction, and practice. Each acted as a tutor or tutee for 15 minutes of each 30-minute session. Authors reported that social studies test performance was significantly improved. Surveys indicate that students responded positively to the intervention procedures. Maheady et al. (1988a, b) replicated their previous work and expanded the application into three regular education 10th grade social studies classes. They collected data on 14 students designated as learning disabled and 36 nondisabled


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students. Following similar procedures, materials and measures of the previous investigation, the 20 week intervention included 3, twenty minute and 2, thirty minute sessions each week. The authors credit classwide peer tutoring for the general average increase of 21 points on weekly tests. Students with learning disabilities gained an average of 23.15 points on weekly tests with scores that sometimes exceeded those of the general education students. Spencer et al. (2003) studied the effects of peer tutoring with questioning and summarization strategies on social studies achievement. Participants included thirty 7th and 8th grade students enrolled in a middle school for students with emotional or behavioral disorders. The school, located in a suburban community, has an ethnically and economically diverse population. Students were distributed among four classes (2 at each grade level). A crossover design allowed each student to participate in each condition. In the treatment condition students served as peer tutors via repeated readings with cued summarization and additional questioning. The 35 minute peer tutoring sessions occurred daily for 2 weeks. The alternate or traditional condition was a continuation of instruction as usual which consisted of review with warm up questions, lecture and activities related to the content for the day. The teachers provided an assortment of guided notes and worksheets. Measures included criterion reference weekly tests and delayed posttests. A student satisfaction survey consisted of 7 Likert-style questions and one open ended question. These were administered individually and read aloud. Teachers were interviewed to determine their response to the intervention. Results showed a statistically significant difference favoring the peer tutoring condition. Students in the peer tutoring condition scored higher on content tests and on-task behavior. Qualitative data indicates that students enjoyed the peer tutoring relative the traditional approach and would like to use the procedure in the future. Teachers agreed that the intervention enhanced student performance. Mastropieri et al. (2003) compared a CWPT intervention (cloze format guided notes, partner reading, questioning, and summarization) with a guided notes condition in a high school self-contained class. Sixteen students designated as LD, ED or MR. Participated in a 9 week application of 1 of the 2 conditions. Quantitative measures included reading fluency, comprehension and immediate and delayed content recall assessments. Results indicated that students in the tutoring condition outperformed their counterparts in the content assessments and were better able to independently use a reading comprehension strategy. Students responded positively to the tutoring procedures and to the guided notes. Applications of CWPT to social studies instruction for students with mild disabilities are limited, but, the literature on CWPT systems is extensive. An example is a synthesis of 35 studies published from 1980 to 2000 in which students with disabilities acted as tutors. It was found that academic gains measured

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by criterion reference assessments were reported consistently across subjects with students with LD, ED, MMR, and attention deficit hyperactivity disorder. Academic gains were higher for tutees than for tutors (Mastropieri et al., 2000). An overall effect size of 0.49, considered educationally significant, was reported. In general, research suggests that CWPT in its various combinations of tutors and tutees supports student achievement. Research measuring student achievement in CWPT models supports the use of CWPT for social studies content. Another scenario employing cooperative learning format is the use of student group projects. The following section is a review of inquiries into the effects of instruction in social studies with technology supported projects. Technology Supported Projects Research on the use of computer technology to support instruction in social studies is a relatively recent phenomena. As computers and software increase in sophistication it is expected that teachers and students will become more adept at using these tools. Participants in these studies are in upper elementary grades. The research has been included in this review at the author’s discretion as examples of technology supported projects available at the time of publication and are additionally relevant because of the variance in the middle school grade designations among school divisions. A series of studies investigated the use of student group projects supported by multimedia technology. To create projects, students in the experimental group had an array of multi-media equipment while control groups had access to word processing tools only (Okolo & Ferritti, 1996b). Two studies (Okolo & Ferritti, 1996a, b) were carried out in a resource room or university lab, respectively. Two others (Ferritti et al., 2001; Okolo & Ferritti, 2001) were conducted in inclusion classrooms. Dependent measures included knowledge tests, videotapes to determine student on/off task behaviors, and information gathered from students and teachers relative to motivation to learn and attitudes toward social studies. Quantitative data that compared student achievement with and without technology support was available for only one study (Okolo & Ferritti, 1996b). A test score difference of 2.4 points between treatment groups on posttest knowledge scores was recorded. It was generally concluded by the researchers that multimedia-supported, project-based learning promoted gains in knowledge for students with and without mild disabilities. It would seem that the projects accomplished in collaborative groups with teacher coaching and support via materials and questioning was at least somewhat accountable for the increase in student knowledge and that the effects of each cannot be disaggregated. Difficulties with the project-technology combination included the need to teach the technology and class management issues.


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Teacher Directed Routines with Strategy Applications This section is concerned with several studies (Bulgren et al., 1988, 1994; Hudson, 1996, 1997; Kinder & Bursuck, 1993; Wong et al., 1986) which support the use of strategy instruction with overt teacher-directed structure or routines to teach social studies to middle or high school students. Variance in methods and procedures require that each study be addressed individually. Bulgren et al. (1988) measured teacher ability to create and use concept diagrams and student performance relative to the implementation of the instructional strategy. The use of diagrams, a synthesis of advanced organizers and web-style graphic organizers, followed a strict 14-step routine. Steps included the use of advance and review graphic organizers, keyword instruction, comparison and contrast, and examples or non-examples of concepts to be learned. Participants included 475 students in grades 9–11 (mean grade level 9.8) enrolled in 23 classes taught by 7 teachers. Thirty-two students with LD who were distributed among the classes. A subgroup of 32 non-LD students were randomly selected from pool of students of similar gender, age and grade to serve as a comparison group. A multiple baseline across groups of students design was used. Measures of student knowledge acquisition included unit and chapter tests. Concept acquisition and notetaking was also evaluated. High school students with and without LD achieved significantly higher scores on the regularly scheduled unit and chapter tests and on concept acquisition tests during the concept/review condition than during the baseline condition, or concept training alone. In a later study with forty-one 7th and 8th grade students, Bulgren et al. (1994) incorporated mnemonic devices into a recall enhancement routine to teach the history of journalism in two team taught social studies classes. Eighteen students with LD and 23 non-disabled students were randomly assigned to an experimental or control group. Students in the experimental group were introduced to acronyms, visual images and keywords to enhance recall of prioritized content. These menemonics were part of a structured routine that included cues lectures (You need to remember this . . ., p. 5) and cued notetaking. Lecture and discussion scripts differed by condition. The control condition experienced only lecture and review. A 40 item multiple choice test evaluated student recall. Performance on reviewed and non-reviewed facts were compared. The authors reported that students with and without LD in the experimental group recalled more of the reviewed information that those in the control condition. This also resulted in an increase in grades that were considered passing for that group. A multiple baseline design was used to measure the effectiveness of strategy instruction for 24 junior high school students with behavior disorders (Kinder & Bursuck, 1993). Data were collected for 6, 4, or 3 weeks in each of three classes. Students were taught to analyze history using a problem-solution-effect

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approach. Instruction was scripted and brisk. Students took notes, made timelines, were introduced to vocabulary, and engaged in reciprocal questioning. Section tests were administered after each 4 days of instruction. The authors reported that students in each class made, “immediate and educationally significant improvement” (Kinder & Bursuck, 1993, p. 324). Student and teacher post-study interviews were generally positive about the process and components of the strategies implemented during the intervention. Hudson (1996) measured the effects of an integrated set of prelesson activities prior to lecture presentations on student performance. Twenty students (final sample) with LD were randomly assigned to the experimental or control condition. The experimental group began each day’s lesson with a teacher-delivered cumulative review. New information was presented and independent practice followed. Students were introduced to facts and causes in sequence prior to lecture on the topic. A causal, or organizing relationship was stated once by the teacher. The control group participated in a scripted lecture with transparencies to display specific facts. These students reviewed notes silently each day, previewed the day’s lesson using the notetaking guide, and took notes during the lecture. Students in both conditions had outline-style notetaking guides. Authors reported that the treatment group performed significantly better on immediate and delayed posttests, supporting the need for lesson structure and teacher direction for students with LD. In a second study, 18 (final sample) 7th and 8th grade students with LD were randomly assigned to the treatment or control group. Hudson (1997) broke the lecture segment of instruction into mini-lessons each followed by interactive teacher guided practice (TGP) consisting of oral questions. TGP facilitated teacher monitoring of student understanding. All students had notetaking guides to use during lectures. TGP for students in the control condition consisted of silent independent study. Students in the experimental group significantly outperformed those in the control group on immediate and delayed posttests. Initial and replica studies with 7th grade students and 8th grade students designated either as LD or underachievers measured the effects of a summarization/self-questioning strategy (Wong et al., 1986). In study 1, a multiple baseline design across 5 subjects was employed to determine the feasibility of teaching summarization strategies to adolescents. In 3 phases, students were taught to identify main ideas and summarize paragraph content using a web-style graphic organizer and then to use a self-questioning/summarization strategy to complete an outline template or “summarization grid” (Wong et al., 1986, p. 25). After extensive instruction they applied the strategy to social studies materials. Measures of both summarization and recall indicated that students learned and transferred the summarization and self-questioning strategies to improve their academic achievement.


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In study 2 (Wong et al., 1986) one male with LD and 2 females designated as underachievers participated in a replica of study 1. Based upon their data, authors reported that the self-questioning summarization strategy used in these 2 studies was an effective reading study strategy. Summary Three types of instructional delivery routines introduced to students with a variety of mild disabilities have been reviewed. Class-wide peer tutoring appears to be a strategy that could be used with positive effects on student achievement in social studies for middle and high school students with and without disabilities. The use of multimedia support for projects is inconclusive partly due to the difficulty of assessing the effects of the integrated independent variables, projects, and technology. The use of collaborative projects appears to increase time on task and have some influence on student achievement. Individual configurations of routines and strategy applications show promise. Taken as a group, the results of the series of studies characterized by teacher directed routines and the application of several integrated strategies into those routines indicated the positive effects of well planned systematic instruction rather than the influence of a specific intervention.

Strategies to Facilitate the Organization of Information Interventions that imposed charts or tables as advanced organizers, semantic mapping matrices, web-style graphic organizers with or without visual displays, and study guides or notetaking applications to improve student academic achievement in social studies are reviewed. A series of studies that applied computer applications of study guides and/or notetaking support are included in this section. The concept of graphic organizers (GOs) is an application of schema theory (Anderson & Ausubel, 1965) which suggests that the acquisition of knowledge is not necessarily linear and may be assisted when information is arranged in a nonlinear visual fashion (Crank & Bulgren, 1993). Ausubel’s advanced organizer (AO) was designed to activate students’ prior knowledge by providing students with links to new information. These organizers consisted of prose statements presented to students before they read from their textbooks (Robinson, 1998). The structured overview (SO) was developed to provide diagrams of relationships among key vocabulary words (Robinson, 1998). The evolution of the strategy continued with “mapping,” defined by Hanf (1971) as a technique for translating reading into thinking. “It is a verbal picture of ideas which are organized and symbolized by the reader . . . an exercise in critical thinking . . .” (Hanf, 1971,

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p. 225). Hanf described a hierarchical organizer with two applications: its construction and its use for review or study. More recently, GOs have come to refer to diagrams, flow charts, webs, and an almost endless array of visual displays. A survey of several textbooks written by experts in the field of content literacy for teacher education in literacy reveals that the GO is considered a reasonable strategy for content instruction in mainstream content classes (Fontana, 2000). GOs in a variety of forms have been used to counteract common academic difficulties including basic reading deficits, memory, organizational, and notetaking difficulties experienced by students with LD (Crank & Bulgren, 1993). Since study guides and notetaking products may be mutually supportive, studies have been organized by format or author’s label rather than by purpose. Advance Organizers and Matrices A comparison of the effectiveness of outlines used as AOs to supplement instruction to prereading activities modeled after strategies used in basal reading series (Darch & Gersten, 1986) suggested a significant positive effect in academic achievement in related science/social studies units for high school students using the outline/AO. In this investigation 24 students with LD were randomly assigned to 1 of 2 conditions. Those in the experimental group were taught from an outline overview of important facts which was also used to guide systematic rehearsal. Students in the control condition received lecture style instruction with discussion. Measures included a pre-test to guide instruction, a unit test and a delayed posttest. Darch and Carnine (1986) used a quasi outline hierarchial display with illustration to teach science and social studies content to middle and high school students. In 3 interrelated studies, participants were described as LD, remedial or regular. The authors concluded that graphic organizers whether teacher directed, student directed with text references or student directed with cues were significantly more effective than independent self-study. They noted significant positive effects for students using their organizers. Lenz et al. (1987) taught teachers to use AOs to manage behavior and to organize and deliver their instruction. A multiple baseline across teachers design was used to track teacher implementation as well as student outcomes before and after they were trained to use an AO to track information statements. Seven high school students with LD participated in the multiple baseline across students design. Instruction occurred in regular secondary classrooms. Student measures were an analysis of the number of items students were able to verbally relate to an interviewer. When teachers used the AO’s to teach, but had not yet taught students to construct them, there was little change from the baseline in student outcomes. Students in general retained more information after being trained to use the AOs.


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Bos et al. (1989) investigated the effectiveness of a matrix presentation of ideas and related vocabulary on social studies achievement of 50 high school students with LD. Intact social studies and English classes were randomly assigned to the Semantic Feature Analysis (SFA) or a dictionary approach. The experimental group used a matrix which illustrated relationships between items to be learned and prior knowledge or discussion cues. The control group was directed to look up the terms. Authors report that the SFA strategy proved to be significantly more effective than the traditional dictionary method for both immediate and delayed retention of content information. Graphic Organizers for Study or Notetaking There are several formats or designs for ordering and connecting information included in this subgroup. They have been compared to each other, to different methods entirely, or to no treatment controls. Study guides come in a variety of styles including computer applications, in narrative and/or quasi-outline formats. They may use questions or prompts designed to assist students in the identification and ordering of important information. Often designed to assist students in taking notes during lecture, they also become a tool for review. Study guides have been used effectively to augment instruction in social studies and science with middle and high school students with LD (Horton & Lovitt, 1989; Horton et al., 1991). Three separate but interrelated experiments conducted by Horton et al. (1990) demonstrated positive effects for organized notetaking formats to teach social studies and science. Doyle (1999) focused on notetaking, comparing the effects of three types of GO’s: (a) problem solution matrices; (b) hierarchical trees demonstrating sequential/cause effect; and (c) central webs to traditional linear note-taking. Posttests revealed a 22 point difference between the means by condition favoring the GO treatment over lecture and linear notetaking. Incarcerated adolescents with learning and behavior issues participated in a study to explore the effects of guided notetaking on social studies achievement. When measures of strategy application and social studies quiz scores were used to compare the effects of open-ended student generated notes vs. cloze notetaking guides, researchers (Hamilton et al., 2000) concluded that the variability of the quiz scores did not demonstrate a clear correlation between the strategy and scores. Computer assisted instruction (CAI) with study guides to support learning for students with LD has been the focus of several studies by Horton and several colleagues. Horton et al. (1989) investigated the effectiveness of a computerized study guide in comparison with a more traditional notetaking condition. They concluded that for both groups the computerized study guides resulted in significantly higher scores than undirected notetaking.

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The use of hypertext study guides to improve student achievement in social studies has been investigated. Higgins and Boone (1990, experiment 1) defined three student types, LD, remedial, and regular, and assigned students to one of three conditions, lecture, lecture/computer study guide, and computer study guide alone. Overall, data revealed no significant effects for treatment condition, but performance on daily quizzes indicated that hypertext study guides were as effective as lecture with study guide and that both were more effective than lecture with undirected student notetaking. The effects varied by group. Students with LD benefited the most, followed by remedial and then regular students. In a follow-up study, Higgins and Boone (1990, experiment 2) selected five students with the lowest test scores from the initial study to determine if computerized study guides were a useful tool to boost academic achievement of lower achieving students. Although variable, daily quiz scores were higher during the intervention phase and decreased in the return to baseline phase. Retention scores varied considerably by student, but the authors maintained that hypertext computer study guides: (a) enabled lower achieving students receive a passing grade on daily quizzes; (b) resulted in increased performance from pretest measures; and (c) resulted in little loss of knowledge from posttest to retention measures. Four students with LD receiving remedial instruction in social studies were trained to use hypertext study guides. The guides contained textbook information presented on a computer screen. Students responded to computer-generated questions. Four levels of cuing were employed as needed based upon student responses to the questioning (Horton et al., 1990). Efficacy of the procedure was determined by comparing students’ immediate and delayed test performance on questions reviewed via the hypertext strategy, or not reviewed. Students performed better on the questions that had been covered during hypertext instruction. Ninth grade students who had been designated as LD or remedial were directed to study with a computerized tutorial, or with an atlas to learn the locations of Asian cities (Horton et al., 1988). Posttests administered at the end of each session indicated that the computerized map tutorial produced significantly higher performance than the atlas condition. Summary Students with LD and others with mild disabilities characteristically encounter difficulty with drawing conclusions and selecting and using strategies (Maheady et al., 1988a, b; Mastropieri & Scruggs, 2000). Organizational strategies including charts and matrices, linear outlines, and complex illustrated graphic designs have been investigated as means to enhance comprehension as well as to facilitate both notetaking and study of social studies content. The studies included here support the use of teacher-directed strategies to assist students in organizing


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information for learning. Specificity within this data set is not clear because of the limited number of studies and because in several instances (Bos & Anders, 1989; Horton & Lovitt, 1990; Horton et al., 1991) the intervention was pitted against methods such as dictionary use, lecture, or student-generated notes, which because of student performance, were already perceived as ineffective. Doyle (1999) was somewhat of an exception in a comparison of student outcomes with lecture and GOs vs. lecture and linear notetaking. Studies with CAI strategies frequently offered a similar set of comparisons (Higgins & Boone, 1990; Horton & Lovitt, 1989; Horton et al., 1989, 1990). In conclusion, the results of this limited sample support the use of both teacher directed organizational strategies and computer study guides which impose organization on student review to improve the academic performance of students with mild disabilities in social studies. Organization of information is considered conducive to the recall of information. In the last group of studies the structure imposed upon relevant information was comprehensive yet not as finite in focus as the investigations into the efficacy of complex mnemonic strategies. These require the identification of specific important facts and direct instruction using combinations of acoustically similar words and interactive illustrations to link the new with the known.

Mnemonic Strategies This section is a review and synthesis of the literature on mnemonic interventions with students with mild disabilities. An introduction provides a brief historical perspective on the strategy and definitions of three types of mnemonic strategies. Studies with high school students are presented first followed by those with middle school participants. Mnemonics refers to an instructional model in which a “specific reconstruction of target content intended to tie new information more closely to the learners existing knowledge base and, therefore, facilitate retrieval” (Scruggs & Mastropieri, 1990, pp. 271–272). Mnemonic strategy instruction is based upon the premise that concrete information that is meaningful or familiar may be elaborated and made easier to learn than abstract and seemingly unrelated information (Scruggs & Mastropieri, 1990). The use of memory enhancing techniques dates back over 2000 years to the ancient Greeks (Higbee, 1979; Scruggs & Mastropieri, 1990). Over time, interest in their use as an instructional strategy has fluctuated. As a topic of research, mnemonics has been traced back to the 1800s and is associated historically with the burgeoning field of psychology. Interest waned somewhat in the 1930s with the advent of the behaviorist period (Higbee, 1979; Scruggs & Mastropieri, 1990).

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Atkinson (1975), who used the keyword method to teach Russian vocabulary, is credited with the most recent resurgence in mnemonics. Research on mnemonic strategies for students with mild to moderate disabilities has been conducted systematically over the past 20 years and continues to be an area of interest particularly to special educators. Three classifications of strategies are most commonly implemented. These are keywords, keyword/pegword combinations and elaborative constructions. Keyword strategies are the simplest form in this series of mnemonic applications. They are constructed by transforming new or unfamiliar words into words that are familiar, concrete, and acoustically similar. Keywords with interactive illustrations reconstruct new information into an acoustically similar term, a rhyme or alliteration, which is known by the learner. To retrieve information the learner first remembers the keyword; next, recalls the interactive illustration; and finally states the correct response (Mastropieri & Scruggs, 2000). For example, to learn that Eddie Rickenbacker was a flying ace during World War I, the student was provided with the keyword linebacker for Rickenbacker and a picture of a linebacker shooting down German airplanes over a football field. Students were taught to associate linebacker with Rickenbacker and then recall the picture for relevant information (Mastropieri & Scruggs, 1988). Pegwords are rhyming proxies for numbers (e.g. one is bun, two is shoe, three is tree, etc.) (Scruggs & Mastropieri, 2000). As such they are used to facilitate the learning of information in which order or degree is part of the target content. Pegwords are often combined with keywords to increase the power of the mnemonic. For example to recall the names of the presidents in order the mnemonic representation of Franklin Pierce, the 14th president, consisted of a purse (for Pierce) with a fork sticking in it (14 is forking) (Mastropieri et al., 1997). Reconstructive elaborations use combinations of mimetic acoustic, symbolic, and first letter mnemonics to ease the recall of factual information (Mastropieri & Scruggs, 1989b). According to Mastropieri and Scruggs, new content information in history textbooks can be classified as: (a) meaningful/concrete; (b) meaningful/abstract; or (c) non-meaningful, thus for the student neither concrete nor abstract. Unfamiliar terms and pertinent factual information may be shown via interaction between the keyword and event information. Mastropieri et al. (1992) used dual keywords and events interactive illustrations to teach states and capitals in forward (capital) or backward (state) order (e.g. state keyword: New Hampshire = hamster; capital keyword: Concord = Concorde; illustration = a hamster flying a Concorde jet). Another example developed by Mastropieri and Scruggs is an illustration of a burning “Allied” moving van with the word FIRE to depict the first letters of the Allied powers in World War I (France, Italy, Russia, and England) (Mastropieri & Scruggs, 1989a).


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Mnemonic Strategies with High School Students To date the vast majority of empirical work on mnemonic strategies with students with mild to moderate disabilities with older students has been accomplished in middle or junior high schools with small groups or 1:1 instruction with a researcher or special education teacher as intervenor. Studies conducted with high school students will be discussed first. Three studies were located that included students in high school. In the first, thirty mildly handicapped adolescents in grades 8–10 were stratified by grade level and randomly assigned to 1 of 2 treatment conditions (Scruggs & Mastropieri, 1989b). One on one instruction employed a combination of keywords, with and without pegwords and elaborated mnemonics to teach history facts and concepts of the early 20th century. With the exception of condition specific mnemonics, materials were comparable across conditions. Measures included immediate and delayed posttests and differences by condition were considered statistically meaningful. Although the researcher does not identify, or exclude special education students, this study (Bednarz, 1995) had been included at the author’s discretion because of its unique status as an early example of classwide application of mnemonic strategy instruction. Bednarz (1995) compared variations of mnemonic instruction (keywords, keywords and test-like practice, keywords in a cooperative framework) and the presentation of text information without mnemonic enhancements to teach place geography. The population of 307 students in grades 6, 9, and 10 were enrolled in two school districts. Classes were randomly assigned within districts to 1 of 4 treatments. The control group read from the text and pointed out the targeted areas. Treatment condition 1, added keywords to the control procedure. Treatment condition 2 added test like practice and treatment condition 3 had students in cooperative groups. Immediate and delayed retention was measured. Data suggests that traditional instruction consisting of reading the text and pointing to geographical areas was the least effective. Keywords and test-like practice was the most effective. More recently, Fontana (2003) investigated the effects of mnemonic strategy instruction with fifty-nine students enrolled in four inclusive world history classes. A within subjects design was used to compare effects of mnemonic strategies and direct instruction on academic performance. High school teachers using keywords with interactive illustrations and alternately, direct instruction of definitions taught 2 units to 10th and 11th grade students. Academic outcomes were measured with unit tests and a delayed cumulative posttest. Students were given strategy use and satisfaction surveys. Time sampling was used to measure student time on task by condition. Teachers’ attitudes and satisfaction were surveyed.

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Three student categories, general education, special education and students whose first language was not English (ESL) were defined. Analysis yielded mixed results on delayed cumulative tests. Significant main effects were noted for condition and category favoring mnemonic instruction particularly for the ESL students. Mnemonic strategies created for the study were most effective with the ESL students, somewhat effective for the general education population and appeared to have little impact on the performance of the special education students. Additional analysis by delayed recall interval indicate that mnemonic instruction yielded statistically stronger recall over direct instruction on a 12-day delay. There was a significant correlation between strategy use and performance for unit 1 was noted. Percent of time on task was significantly greater during mnemonic instruction. Survey responses indicate that the majority of students preferred, would like to continue with, and felt they learned more with mnemonic strategies. Teacher attitudes varied, but generally favored mnemonic instruction. Mnemonic Strategies with Middle School Students Of four studies conducted with middle or junior high school students two, (Brigham et al., 1995; Scruggs et al., 1992) involved 1:1 instruction, 4 (Mastropieri & Scruggs, 1988; Mastropieri et al., 1992, 1997; Scruggs & Mastropieri, 1989a) involved small group instruction. Scruggs et al. (1992) used keywords and color-coded maps to teach names, locations and victors of Revolutionary War battles. The controls used color-coded maps without the keywords with illustrations. Thirty-nine 7th and 8th graders were stratified by grade and randomly assigned to 1 of 2 treatments for one session of 1:1 instruction. Student performance on 1:1 test of the information shoe that students in the mnemonic condition scored significantly higher that the controls on location and victor content. Brigham et al. (1995) measured the effect mnemonic maps with elaborative text and illustrations to teach outcomes of battles of the American Revolution. Seventy-two students with LD were randomly assigned to 1 of 3 conditions for 1:1 instruction. Instruction in the elaborative condition prompted visualization of concrete keywords (deer for Deerfield) and to associate events with the battle. The mnemonic condition used keywords prompted visualization but associated facts were not linked to the keyword of picture. In the control condition there were pictures to mark the location of a battle, but information was merely presented, not connected to prior knowledge of concrete cues to support recall. Data analysis indicated that although students in the elaborative and mnemonic condition did not have significant differences in performance both differed positively and significantly from the control group.


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The remaining 4 studies used a within subject design and instruction was delivered to small groups of students in special education settings. These are discussed in turn. Twenty-seven (complete data available for 19) 7th and 8th grade students with LD received traditional and mnemonic instruction in counterbalanced order (Mastropieri & Scruggs, 1988). Lessons modeling effective classroom instruction were scripted for both conditions. Students had access to textbooks, worksheets and notes in both conditions. Traditional instruction was textbook based with teachers pointing out important information. Keywords with interactive illustrations were used in the mnemonic condition. Measures included four multiple choice chapter tests and a delayed cumulative recall test. Analysis of chapter tests showed significant positive effects for the mnemonic condition. On the cumulative unit test students scored significantly higher on items taught mnemonically. Surveys indicate that both students and teachers preferred mnemonic instruction and found them motivating. States and capitals were taught to 29, 7th and 8th grade students with LD (Mastropieri et al., 1992). Students had access to worksheets and condition specific workbooks in both conditions. The traditional or control condition used labeled outline maps of states and their capitals. Materials in the mnemonic condition consisted of keywords for states and capitals with interactive illustrations that linked the two. Measures consisted of weekly tests. It was reported that students in the mnemonic condition significantly outperformed their control in immediate and delayed posttests. Students’ perceptions suggested that they spent more time on task in the mnemonic condition. Names and order of U.S. presidents’ were taught to 11 (final sample) middle school students with LD. Students in the experimental condition were presented with keyword/pegword mnemonics. The keyword provided an acoustic reminder of the president’s name, e.g. purse for Franklin Pierce. The pegword, a fork for 14 gave the order. An interactive illustration pictured a fork piercing a purse. Worksheets provided practice. In the control condition students were presented transparencies with the presidents’ names and their order of tenure. Measures included immediate weekly assessments and a delayed cumulative posttest 2 weeks after the last day of instruction. Data from the cumulative posttests demonstrated that although performance did not differ significantly, every student scored higher on items taught mnemonically. Scruggs and Mastropieri (1989a) used a within subject design across 3 classes to investigate the performance of 20 (final sample) 7th and 8th grade students with LD. Textbooks, worksheets and notes were available for students in both conditions. Scripted mnemonics materials included keywords and pictures, some with dialogue. These were created around the content of the textbooks’

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presentation of WWI and the great depression. The same content was presented in the control condition with no mnemonic enhancements. Measures included 4 chapter tests administered immediately after 2 weeks of instruction in a chapters’ content. Overall students in the mnemonic condition scored higher than those in the control. Both teachers and students enjoyed the mnemonic materials and instruction. Teachers reported that students were more engaged in instruction during the mnemonic condition. Summary A synthesis of the results and discussions of the mnemonic research presented here reveals that when compared to other methods such as direct instruction, rehearsal, or free study, mnemonic instruction was more effective for short and long term recall of social studies terms, concepts, events, people, and places. A variety of middle, and high school students who were considered academically at-risk appeared to benefit when their instruction incorporated mnemonic strategies. Researchers, classroom teachers, and students have the ability to create meaningful effective keyword mnemonics. When questioned about the strategy both students and teachers have responded positively.

COMPREHENSIVE SUMMARY Students and Materials Three factors compel the quest for effective teaching strategies for students with mild disabilities: (a) student issues: poor reading skills and memory deficits; (b) the inclusion movement which has resulted in an increasing number of students with special needs receiving instruction in general education settings; and (c) the proliferation of high stakes testing which all students are expected to participate in with or without accommodations. Instructional materials compound the issue. Research on basal textbooks used to teach social studies indicates that they may be inappropriate for their targeted population because of specific readability issues and lack of instructional strategies suggestions for teachers. Within texts, expository patterns of writing are varied to the extent that comprehension may be impeded. Poor organization and the overestimation of student prior knowledge contribute to the difficulties students may encounter as they attempt to read for meaning. Studies of teachers use of basal materials indicate that many continue to rely upon basal textbooks to drive instruction. There appears to be an over-reliance on inherently deficient instructional materials coupled with a lack of experience


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with expository prose among students in general (Harniss et al., 1994; Stetson & Williams, 1992). Bean et al. (1994) reported that teacher adaptations included activating prior knowledge, oral guided reading, tapes, teacher read aloud, discussion, additional textbooks, and projects workbooks. Almost half of the teachers questions provided some sort of study guide.

Instructional Methods and Strategies The body of research that focuses upon social studies instruction was organized into three categories. Instructional delivery routines included: (a) class-wide peer tutoring; (b) technology-supported projects; and (c) teacher-directed routines with integrated strategy applications. Strategies designed to facilitate the organization of information included: (a) interventions that imposed charts or tables as advance organizers or semantic mapping matrices; (b) web-style graphic organizers with and without visual displays; (c) the use of study guide notetaking applications. The last included computer applications to study guides; and (d) mnemonic strategy instruction. Taken as a whole, the body of research concerned with social studies instruction indicates that instructional delivery routines and organizational strategies have positive effects on student performance and as such reconfirm the need for systematic direct instruction for students with mild disabilities. Study guides (Bean et al., 1994) and various formats of organizers (Fontana, 2000) appear to have become somewhat common in the classroom. The focus of routines and organizational tools may be considered to be related to enabling students to access and/or organize information and as such are valuable to the students. Mnemonics strategies directly focus upon the remembrance of targeted factual information and the considerable body of research included in this review indicates that mnemonic strategies should be considered a viable instructional method, particularly for small group or one on one instruction.

CONTENT AND COGNITION IN SOCIAL STUDIES INSTRUCTION The mission statement of the National Council for the Social Studies (NCSS) defines the role of social studies educators. The challenge is to, “teach students the content knowledge, intellectual skills, and civic values necessary for fulfilling the duties of citizenship in a participatory democracy” (NCSS, 2001). Although undefined in the mission statement, the term intellectual skills would seem to

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correlate with Brophy’s emphasis on the necessity of, “teaching for understanding and higher order thinking applications of content,” described as, “conceptual understanding, critical thinking, decision making and giving students control over accessible and usable knowledge” (Brophy, 1990, p. 351). In his seminal taxonomy of educational objectives, Bloom (1956) used the terms remembering, recall, thinking, problem solving, and creating to define cognition. Accordingly, six classes of cognition arranged in what is commonly considered hierarchical order were identified. They are knowledge, comprehension, application, analysis, synthesis, and evaluation. Knowledge is defined as the remembering of an idea or phenomenon in a form similar to how it was originally presented. Continuing his explanation, Bloom noted a range from simple concrete knowledge of specifics to complex abstract knowledge of theories and structures, thus noting the status of factual recall as a prerequisite to higher levels of cognition. Memory function is the demonstration of the basic level of cognition (Alberto & Troutman, 2003). Memory and structure of knowledge has been identified as one of five themes contributing to changes in how learning is understood (Bransford et al., 1999). Donovan et al. (1999) concluded that learning differs across disciplines due to the demands and structure of the content, but that the nature of learning is constant, meaning that students learn by using their prior knowledge to construct new knowledge. Current theories of cognitive psychology maintain that knowledge is organized into structures called schemata, or schemes. These are mental structures that represent related knowledge. Schema theory also holds that new knowledge is shaped, in that it is assimilated in a subject specific or unique manner according to one’s prior knowledge. Schema, then, may be considered as simultaneously a store of prior knowledge as well as a receiver of new information which once discriminated, will be sorted into the appropriate mental structure. These “. . . networks of connected knowledge structured around powerful ideas can be learned with understanding and retained in forms that make them accessible for application” (Brophy, 2001, p. 11). It is supposed that to become competent in any area students must: (a) have a deep foundation of factual knowledge; (b) understand facts and ideas in the context of a conceptual framework; and (c) be able to discriminate and organize knowledge in ways that facilitate its retrieval and application (Donovan et al., 1999). A difficulty inherent in social studies instruction is that the scope and array of content may preclude in-depth coverage which counters the student’s ability to organize information (Bransford et al., 1994). To demonstrate their academic proficiency in social studies, students are required to remember general information plus a collection of names, places, events, and dates. They must be able to discriminate details and link new information in meaningful ways (Martorella, 1991). Schema theory supports the idea of a symbiotic relationship among


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facts, concepts, and retrieval. Therefore, strategies designed to improve recall information are appropriate and important. Recall is enhanced by fluency. Automatic and fluent retrieval of information denotes expertise (Bransford et al., 1994). Fluency is a combination of speed and effortless processing which places fewer demands on attention. Fluency refers to associative tasks, or those which may be accomplished in tandem with other associative (automatic) tasks. Instructional strategies which result in fluent, accurate retrieval of factual knowledge fall within the realm of current cognitive theory in that they support the acquisition of information into increasingly complex links of schemata. Mnemonics, or memory enhancing strategies, address the need for a broad base of factual knowledge that can be accessed automatically. Accordingly, Matorella (1991) discussed specific memory enhancing strategies, including keyword mnemonics and their place in knowledge and concept development. The idea that basic content specific vocabulary is important in the development of fluency and sophisticated expertise is supported by Bloom’s taxonomy and the current theories of cognition that hold with the formation of schema, those cognitive webs or networks of interrelated information. Remembrance of the conglomeration of factual information is the foundation for application, analysis, and synthesis, those skills of the intellect alluded to in the mission statement of the NCSS.

IMPLICATIONS FOR INSTRUCTION: RESEARCH TO PRACTICE This body of research on instructional approaches and strategies supports the current thoughts on cognition and social studies content. It consistently demonstrates that the more engaged a student is in working with the content the better his/her performance. In study after study we saw that when reading the text, looking up words and lecture were supplanted or supplemented by activities or strategies that required students to rehearse, discuss and critique, summarize, visualize or organize information student performance improved. When students were provided a structure for increased or more thoughtful exposure to the content their academic performance was enhanced. The challenge to all teachers is to design instruction that maximizes student engagement. Well orchestrated lessons review, connect, develop content and assess. Learning is not passive. It is linking new information to prior knowledge via analogies. It is sorting and categorizing and sometimes changing categories. Some students, most particularly those designated as LD benefit from direct instruction in how and when to employ strategies and strategy instruction should be embedded into content lessons (Fig. 1).

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Fig. 1. Suggestions for Embedding Strategies into a Basic Lesson Plan.

In the literature reviewed, teacher induced strategies have demonstrated their effectiveness. However, the goal should be to create independent learners. Students need to know how to and when to use these various approaches to learning. In order to transfer these learning tools students should be taught that they can function in any content. There are 5 issues to remember when teaching students to use strategies. These 5 R’s include: Respect the learner: Tell them what the strategy is, what it is for and why, or how you expect it to help them.


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Required: You are teaching a new habit and perhaps breaking an old one. Require that the strategy be used. Reiterated: Model it often. Use the I do, we do, you do approach. Redundant: Provide practice. Rewarded: Positive feedback for effort. Connect strategy use with academic performance. If we accept the premises that for a variety of reasons including lack of organizational skills and memory deficits, lack of prior knowledge, unsophisticated, or even deficient reading skills many of our students will find the textbooks difficult or confusing. We must also acknowledge that simply assigning readings and superficial fact questions will not accomplish the breadth or depth of learning required to pass many state assessments let alone produce responsible citizens.

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HOW CAN A STUDENT’S DEPRESSIVE ATTITUDE INTERFERE WITH THE USE OF GOOD SELF-REGULATION SKILLS? Angelica Moè, Cesare Cornoldi, Rossana De Beni and Luisa Veronese ABSTRACT Self-regulation skills, such as organisation, self-evaluation, personal elaboration, metacognitive attitude and strategic awareness are very important predictors of academic achievement. However, research has not studied in depth the factors that facilitate the use of good self-regulatory skills. The present research was intended to study the role of some factors that could affect these self-regulation skills, in particular depressive attitude and motivational beliefs. A group of 246 adolescents, aged between 14 and 18, were administered self-report questionnaires devised to test aspects underlying self-regulation. A preliminary factor analysis confirmed the centrality of the three-hypothesised aspects: motivational beliefs, depressive attitude, and self-regulation-skills. A path analysis revealed that there are important links between motivational beliefs and self-regulation and between depressive attitude and motivational beliefs. Some educational implications are discussed. In higher education, students frequently have been seen to fail dramatically, despite good basic cognitive skills. Research has been carried out to investigate the


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possible causes of students’ low achievement in the attempt to predict and prevent dropout. A number of factors has been identified (e.g. De Beni et al., 2003; Pressley et al., 1997) and has demonstrated the fundamental role of self-regulation skills (Hofer et al., 1998; Wolters, 1998), i.e. skills by which the student controls and monitors the learning process. Examples of critical self-regulatory skills are organization (Moè & De Beni, 2000), self-evaluation of preparation (Drew & Watkins, 1998) and the deliberate use of strategies for increasing the elaboration of the to-bestudied text (Ley & Young, 1998). Students with learning difficulties also tend to be less flexible in choosing different strategies (Wood et al., 1998) and to lack “strategic coherence” (De Beni & Moè, 1997; Moè et al., 2001). In a recent study, we (Cornoldi et al., 2003) presented an assessment device intended to obtain an overall measure of the self-regulatory ability of a student involved in higher education, and we found that this measure was a powerful predictor of the student’s achievement. Given the importance of self-regulation skills, a very interesting question concerns which factors could foster these skills. The intention of the present investigation was to examine how motivational and interfaced depressive components can affect the development and the use of good self-regulatory ability. In fact, recent research on study skills has stressed the importance of the psychological state, in particular of affective and personality factors, such as cognitive learning style (Drysdale et al., 2001), perfectionism (Mills & Blankstein, 2000), emotions in learning contexts (Hareli & Weiner, 2002), social abilities (Bogler & Somech, 2002) and the feeling of integration in the school context (Hu & Kuh, 2002). It was observed that differences in emotional and personal factors among individuals could explain and predict future academic achievement. Since academic achievement is strictly related to self-regulation, it may be expected that also some of these affective measures can affect and correlate with self-regulation. In the present investigation, we focused on some motivational factors, which in one respect appeared particularly closely associated with self-regulation (Cornoldi et al., 2003), but also seemed related to the presence/absence of depressive symptoms. In particular, we considered the following important beliefs to be associated with the learning process (see Dweck, 1999): attributions, self-esteem, and naive theory of intelligence. In fact, previous research demonstrated the predictive power on academic achievement of an attributional style centred on personal effort (Sinkavich, 1994) of positive self-esteem (Leondari et al., 1998), and of the tendency to focus on mastery rather than performance goals (Archer, 1994; Dweck, 1999) Strictly tied to these motivational beliefs and self-perceptions of one’s own abilities are some aspects we could consider to be depressive symptoms. In fact, research has indicated that some motivational patterns are strictly closed to a depressive attitude. This is the case of a psychological state characterised by a

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perception of absence of control on negative events, called learned helplessness (Abramson et al., 1978) or learned hopelessness (Abramson et al., 1989). In such a state, there is the tendency not to use effective coping strategies (Sonoda & Tonan, 1999) and effortful and attention strategies for the purpose of avoiding an overload of the cognitive, emotive and motivational systems (Kofka & Sedek, 1998). Among the different motivational beliefs, attributional style is one of the most crucial for depression. In fact, depression is generally associated with the tendency to attribute failures to a lack of ability (Hareli & Weiner, 2002). The kind of attributional style can exacerbate some relationships, for instance the link between perfectionism and depressive symptoms (Chang & Sanna, 2001). Research has also been carried out demonstrating the effects of depression on cognitive and metacognitive skills (Kizilbash et al., 2002; Slife & Weaver, 1992; Terreni & Campiotti, 1999) and revealing that a wider range of depressive symptoms tends to correspond to lower levels of strategy use, strategic attitude, self-monitoring ability, motivation and attribution to effort (Palladino et al., 2000). Within this perspective, it seems possible to find a deeper psychological description of the often-mentioned relationship between depression and learning failure. In fact, epidemiological researches have reported impressive data concerning the relationship, in pre-puberty children, between depression and learning difficulties (for a review, see Heath, 2001), suggesting that the relationship can be in the two directions, increasing depressive symptoms in students who fail in school, but also leading students with deeper pre-existing depressive symptoms into school failure. It is rather intuitive that a severely depressed student may have problems in meeting the demands of life, including demands of school. However, the relationship can be less clear for students who present only slight depressive symptoms and seem apparently able to have a normal life. Furthermore, it appears important to develop a plausible description of the main aspects that create in a student an articulated cognitive, motivational and affective psychological pattern, producing low selfregulation and then low school achievement. Palladino et al. (2000) demonstrated that this pattern could be well described within a metacognitive perspective as the one proposed by Borkowski and co-authors (e.g. Borkowski et al., 1990). Palladino et al. (2000) found that pre-adolescents with learning disabilities (LD) had lower attributions to effort, less effective self-regulatory skills and a wider range of depressive symptoms than did students without LD. Within this perspective, a modest inclination to the development and use of self-regulatory skills could be produced by a student who combines some basic traits of state-depression with low confidence in himself as a student and with a poor attributional belief system. In fact, his/her attributional system should be characterised, as has been typically shown in individuals with learning difficulties, by attributions of high-frequency failures to lack of ability, and of low-frequency failures to a lack of effort. This attributional


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system would operate both in increasing a depressive attitude and in producing a motivational attitude that is related to a naive theory of intelligence as a static entity that cannot be modified by effort (as Dweck has repeatedly demonstrated, e.g. Dweck, 1999). In order to better examine these issues, in the present investigation, we decided to test adolescent students, since the relationship between depression and learning failures has been less intensively studied in adolescence. As Heath (2001, p. 6) summarized in her review, there appears to be some early evidence that pre-puberty children with learning disabilities are more at-risk than non-LD peers for self-reported depressive symptomatology and that girls with LD may be particularly at risk. In studies of post-puberty or adolescent samples the relationship between learning disabilities and depression becomes more tentative.

At the same time, adolescence is characterised by instability and a change in self-representation that put in evidence, more frequently than later or before in the development, depressive symptoms. These surely affect personal life and well being, as previous research has shown (e.g. Huntington & Bender, 1993), but could, as we hypothesise, affect even motivational and strategic attitude and consequently self-regulation abilities and academic achievement.

METHOD Participants Participants were 246 students (105 males, 141 females), aged between 14 and 18 years. Mean age was 15.43, standard deviation 1.37. They were attending the first (41 males and 31 females), the second (26 males and 32 females), the third (25 males and 36 females), and the fourth (13 males and 42 females) years of a technical high school.

Materials We administered to the students a series of questionnaires which were collected into a single booklet composed of the Children’s Depression Inventory (Kovacs, 1992), the Attributional Style Questionnaire (De Beni & Moè, 1995) and three questionnaires from a set of instruments called AMOS (Ability and Motivation to Study: Evaluation and Vocational Tests) of De Beni et al. (2003). The first was the Study Strategy Questionnaire (SSQ) to test student attitudes about a series of 39

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study strategies. The student is required to rate on a 7-point Likert-type scale the grade by which he/she uses each of them. The second was the Approach to Study Questionnaire (ASQ) for the measure of self-regulation during study (see Cornoldi et al., 2003). The student is required to rate, on a 5-point Likert type scale, how much he/she uses 50 study approaches pertaining to 5 fundamental areas characterising the self-regulated student, i.e. organization, elaboration, self-evaluation, strategic awareness and metacognitive attitude. The third instrument, the Beliefs Questionnaire (BQ) measures some emotive-motivational aspects, particularly beliefs about oneself and one’s own learning and confidence. It is divided into five parts in which the student is invited to describe respectively his own intelligence and personality theories, confidence in his own intelligence and personality, and perception of his own ability. In the Appendix we have included one example item for each of the dimensions considered.

RESULTS Preliminarily, we looked at the differences due to age and we found that the sample was rather homogeneous. Twelve separate one-way analyses of variance (ANOVAs) comparing the four age groups for each of the considered dimensions did not yield significant differences, except for organization, F(3, 242) = 3.87, p = 0.010, and ability perception, F(3, 242) = 2.76, p = 0.043. Post-hoc analyses revealed that first year students perceived themselves as more organized (mean score was 37.99 vs. 35.01 for the other age groups) and having a superior ability perception (mean score was 19.04 vs. 17.91 for the older students) than all the other groups. Considering the slight age differences, all the subsequent analyses were carried out on the entire group.

What Distinguishes Depressed from Non-Depressed Students? Students were distinguished on the basis of the Children’s Depression Inventory (CDI) in depressed and non-depressed students. A student was included in the depressed group (10 males, 21 females) if his/her score at the CDI was equal or greater to 19 (the typical cut-off proposed for the CDI, see Kovacs, 1992). The control group was formed selecting the 10 lowest scores for males and the 21 lowest scores for females. Research has in fact demonstrated the importance of comparing the pathological group with a group proportional with respect to gender.


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Table 1. Mean Scores Obtained by Depressed and Non-Depressed Students in the Variables Considered. Variable Organization Self-evaluation Strategic awareness Lack of ability attribution Ability perception Incremental theory Confidence

Depressed

Non-Depressed

F (1, 48)

30.77 (7.13) 35.65 (3.68) 29.52 (4.80) 14.26 (5.88) 16.42 (2.95) 23.44 (6.57) 8.58 (2.51)

38.48 (6.03) 37.29 (5.01) 34.10 (4.69) 11.03 (5.64) 19.42 (2.28) 27.23 (5.74) 12.84 (1.78)

19.85, p < 0.001 4.38, p = 0.041 13.68, p < 0.001 4.66, p = 0.035 19.04, p < 0.001 4.62, p = 0.036 55.30, p < 0.001

Since the depressive attitude tends to produce different behavioral effects in males and females, gender was included in the comparison between depressed and non-depressed students. A 2 (depressed vs. non-depressed) × 2 (males vs. females) ANOVA was conducted on all the aspects measured. We found an overall main effect for depression, F(1, 48) = 7.34, p < 0.001. Individual comparisons are shown in Table 1, together with the mean scores (standard deviations in parentheses) obtained by the two groups. Only the significant comparisons are shown. However, all the others are in the expected direction: a better score for the non-depressed students. This confirms that the variables we had selected are critically related to the presence of a depressive trait. No significant difference due to gender was found nor interaction of gender by depression, except for confidence, F(1, 48) = 4.03, p = 0.049: females (M = 10.33, S.D. = 3.12) are less confident than males (M = 11.50, S.D. = 2.97). As can be seen in Table 1, a great difference has been found for the ability perception and confidence confirming the literature showing a tendency for depressed people to lack self-esteem. Slight, but significant differences also have been found for lack of ability attribution and for incremental theory. Concerning strategic and self-regulational aspects, substantial differences were found in organization and strategic awareness.

What Are the Underlying Factors? In order to have a better description of the relationships between the variables included in the Study we ran a factor analysis with a Varimax rotation and a hypothesis of three main factors: Self-regulation skills, Depressive Attitude and Motivational beliefs.

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Table 2. The Three Factors Underlying the Considered Dimensions. Variable

Factor 1: SelfRegulation Skills 28% Variance Explained

Organization Elaboration Self-evaluation Strategic awareness Metacognitive attitude Strategy use Ability perception Depression Lack of ability attribution Lack of confidence Lack of effort attribution Incremental theory

Factor 2: Depressive Attitude 12% Variance Explained

Factor 3: Motivational Beliefs 10% Variance Explained

0.629 0.617 0.357 0.802 0.598 0.633 0.600 0.709 0.606 0.785 0.559 0.739

The factor analysis (see Table 2) revealed three factors (total explained variance = 50%), which substantially confirmed the existence of the three hypothesised factors, from Factor 1 to Factor 3, respectively: (a) Self-regulation skills; (b) Depressive attitude; and (c) Motivational beliefs. Confidence was transformed, here and in the following analysis, into lack of confidence to facilitate understanding (i.e. to avoid negative relationships). The only partially unexpected loading concerned perception of ability. This perception involves a self-regulatory aspect, as the student must rate how competent he/she feels himself/herself in a variety of self-regulation processes, but it also involves depressive and motivational components: in fact, the student must rate how able and how motivated he/she perceives himself/herself. In the present factor analysis “ability perception” mainly loaded on the first factor (self-regulation skills).

What Are the Relationships Among the Three Factors? In order to better understand the relationships between the variables, we tested the causal model assuming that depressive attitude and motivational beliefs may interact and affect self-regulation skills, by developing a structural equation model using the LISREL program (Jöreskog & Sörbom, 1996). A preliminary examination of the variables controlled whether the different measures had normal distribution. Effort attribution for successes was excluded because it was not symmetrical (−0.977), but lack of effort was considered to have a

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normal distribution. Furthermore, incremental theory of intelligence (−0.318) and of personality (0.113) and confidence (−0.369 and 0.377 respectively for intelligence and personality) were summed because they had opposite asymmetry. All the other factors had a normal or near-normal distribution (asymmetry under 0.300), except for depression (asymmetry was 0.791). The depression measure was retained both because it was critical for the study, and because this corresponded to the expectation that depression is a psychopathological trait shared only by a minority of the students. In fact, the instrument (CDI) is devised to individuate the tendency to pathology. It must be noted that the number of subjects was high enough to include a relatively high number of students who could be described as at risk of depression. Figure 1 presents the model we obtained. In model three, main latent variables were considered: depressive attitude, motivational beliefs and self-regulation skills. Depressive attitude was measured by three variables: depression, lack of confidence and lack of ability attribution. Motivational beliefs was given by three measures: incremental theory, lack of effort attribution and ability perception. Finally, the following measures were assumed to represent the self-regulation skills latent variable: strategy use, organization, elaboration, self-evaluation, strategic awareness and metacognitive attitude.

Fig. 1. The Model Explaining the Relationships Between the Considered Dimensions and the Underlying Factors.

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In order to better compare the regression indexes, giving that all the estimates depend on the metric used and that this is different from one to the other measure, we obtained the standardized solutions. In general, greater values of the index correspond to stronger relationships. All the indexes written near each arrow are significant except for the index representing the relationship between depressive attitude and self-regulation. The model had a sufficiently good solution (Bollen, 1989) compared with other models combining in different ways the variables (␹2 = 124.34, df = 52, p < 0.001, RMSEA = 0.08, NNFI = 0.82). A bi-directional (and negative) relationship was hypothesised and confirmed between motivational beliefs and depressive attitude. As can be seen in Fig. 1, greater depression is related with more modest student motivational beliefs. Motivational beliefs affect self-regulation skills to a great extent. This latter is unaffected by depressive attitude (0.04 is not significant). All the measured indexes pertain significantly to a less or more significant way to the hypothesised underlying factors (latent variables). In particular, depressive attitude is well represented by depression measured by the CDI and by the lack of confidence. Motivational beliefs are given primarily by the ability perception measure. Self-regulation skills are well represented by metacognitive attitude, organization, elaboration and strategy use.

DISCUSSION AND CONCLUSIONS Our study was based on the students’ self-ratings on a series of psychological dimensions. Therefore, each conclusion must be cautious and take into consideration the various biases involved in self-rating procedures, for example the lack of correspondence between ratings and actual variables or the mutual influences between different ratings. Despite this, our results offer a general description of the interaction between a series of important factors. Self-regulation has been repeatedly seen to be critical for an effective student carrier. Self-regulation has been differently defined. In the present study, we took advantage of a previous study (Cornoldi et al., 2003), which had validated a questionnaire including, in a self-regulation dimension, the student’s abilities to organize, implement elaboration strategies, and develop awareness concerning study. All these aspects clearly loaded on the self-regulation skills factor. Despite the fact that the factor analysis revealed a lower loading for the self-evaluation subscale, the path analysis included it in the self-regulation dimension. The self-regulation dimension also included scores obtained at the questionnaire on the strategies suggesting that a self-regulated student also use a higher number of strategies.

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In the present investigation, we wanted to examine the role of non-cognitive variables, such as a depressive attitude and a poor motivational system, on the use of good self-regulatory skills. The causal model we obtained offers an interesting description on how these variables may interact and affect self-regulation. In fact, it revealed that both dimensions are the result of a series of variables, which, in the present study, were selected on the basis of a metacognitive model. A depressive attitude (having consequences for self-regulation) is described not only by a high score in a specific scale devised in order to measure depression in children, but also by a low confidence the student has in his own intelligence and personality and by an ability attribution, particularly in face of failure. The motivational system here considered included the perception of one’s own ability (notice that this aspect has a high loading on the self-regulation factor), the naive theory of intelligence (is it static or can it be modified?) and an effort attribution. The two attributions, which our analyses associated with two different dimensions, are obviously part of a general interactive attributional system and make evident the relationship between the two dimensions we studied, i.e. the depressive attitude and the motivational beliefs, which in fact the causal model described as strictly related. The model also showed how the two dimensions could affect the implementation of self-regulatory skills. Showing that a depressive attitude and a motivational pattern may affect the student’s self-regulation, we have put in evidence how the self-regulatory behavior does not only depend on adequate basic abilities and experiences, but also depends on the student’s inclination to implement skills, which probably are already available to him. By consequence school appropriate instructional procedures should move in two main different directions. First, they should increase the student’s study skills and strategies (see Hattie et al., 1996; Simpson et al., 1997) and his/her knowledge and competence in the components of self-regulation. Second, school should pay attention that the student is aware of the utility of these skills and is really willing to use them. For this reason it is important that school changes the motivational pattern of the student. However, we have seen that also the emotionally depressed status of the student can affect self-regulation. In particular, a depressed individual could be inclined to escape from challenging situations and to not use skills he/she has. In principle, depression seems a basic characteristic of the individual more resistant to school action. However, research has shown that various elements inducing a depressive attitude (for example a poor attributional pattern) can be modified through experience and appropriate instructional procedures. This could be an attack point for initiating a pathway directed to increase the student’s tendency to behave in a more self-regulated way.

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APPENDIX In the appendix, we have included one example item for each of the considered dimensions. Depression Chose one of the following phrases, thinking to your feelings and ideas in the last two weeks. “I am sad sometimes” “Very often I am sad” “I am always sad” Attributions Image the following situation and chose three out of five causal explanations “You have done your homework and made a lot of mistakes? Why?” I have not put enough effort (lack of effort attribution) I received no help It was difficult I was unlucky I am not able to do this task well (lack of ability attribution) (The Attributional Style Questionnaire comprises 24 hypothetical situations, 12 describing success and 12 describing failure pertaining to learning, memory and everyday settings) Strategy Use To what extent do you “Create schemas or diagrams” when you study? ASQ Organization “At the beginning of the afternoon, I get a look to all the homework I have to do”


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Elaboration “When I read, I try to question myself about the content of the passage” Self-Evaluation “I succeed in knowing when I have studied enough” Strategic Awareness “When the professors give exams at the end, I pay a lot of attention to understand what they require” Metacognitive Attitude “I like to think about the mental functioning”

Incremental Theory “No matter how intelligent you are, you can always improve your intelligence” (subjects are required to rate their agreement on a 6-point Likert-type scale)

Confidence Chose the item that better describes you Usually, “I think to be intelligent” or “I wonder about my intelligence” Now state how much it describes you “very well” “enough” or “quite a lot”

Ability Perception “Your ability to study” (subjects are required to rate each of the proposed dimensions using a 5-point Likert-type scale)

PRELIMINARY WORK IN DETERMINING WHETHER DYNAMIC ASSESSMENT OF WORKING MEMORY HELPS IN THE CLASSIFICATION OF STUDENTS WITH READING DISABILITIES Crystal B. Howard and H. Lee Swanson ABSTRACT This chapter reviews some of our most recent research as to whether the cognitive performance of reading disabled and poor readers can be separated under dynamic assessment procedures. We describe results related to junior high school students (mean chronological age of 12 years) with reading disabilities, poor readers, and skilled readers. Students were administered intelligence, reading and math tests, and working memory (WM) measures (presented under static and dynamic testing conditions). The results thus far show that: (1) dynamic assessment measures (maintenance scores) contributed unique variance to predicting reading; and (2) poor readers and skilled readers were more likely to change and maintain gains under the dynamic testing conditions than students with reading disabilities. Some discussion was given to developing a valid classification of reading disabilities.


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CRYSTAL B. HOWARD AND H. LEE SWANSON

The notion of potential has played a critical role in defining learning disabilities since the inception of the field (e.g. see Bateman, 1992, for review). Typically, differences between IQ and achievement on standardized tests are viewed as a prototype for representing differences between potential and actual performance (Fletcher et al., 1992; Shepherd et al., 1983). A review of the literature suggests, however, that such procedures are invalid for classification purposes (e.g. Fletcher et al., 1992; Hoskyn & Swanson, 2000; Stuebing et al., 2002). For example, the relevance of standardized intelligence measures (e.g. WISC-III) in the diagnostic classification of reading disabilities (RD) has been criticized because reading achievement within learning disabled samples is not predicted by variations (high vs. low) in IQ (e.g. Fletcher et al., 2002; Hoskyn & Swanson, 2000; Siegel, 1989, 1992; Stanovich & Siegel, 1994; Stuebing et al., 2002). Further, several authors (e.g. Brown & Ferrara, 1999; Campbell & Carlson, 1995; Campione, 1989; Embretson, 1992) have suggested that traditional intelligence tests (i.e. tests that measure unassisted performance on global measures of academic aptitude) provide a poor estimate of general ability. Oakland and Cunningham (1999) note that traditional assessment strategies “assess outcomes or products, focus evaluation on past and present, test to inform professionals, and diagnose and label permanent barriers that restrict attainment” (p. 49). These authors argue that because static or traditional approaches to assessment typically provide little feedback or practice prior to testing, failure often reflects the child’s misunderstanding of instructions more that their ability to perform the task. Thus, a conceptual problem exists as to whether “potential” in students with RD is adequately captured on traditional IQ measures. One possible alternative or supplement to traditional assessment is to measure a child’s gain in performance when given examiner assistance. Thus, “potential” for learning new information (or accessing previously presented information) is measured in terms of the distance, difference between, and/or change from unassisted performance to a performance level with assistance. Procedures that attempt to modify performance, via examiner assistance, in an effort to understand learning potential are called dynamic assessment (e.g. see Grigorenko & Sternberg, 1998; Swanson & Lussier, 2001). Although dynamic assessment is a term used to characterize a number of distinct approaches (see Grigorenko & Sternberg, 1998; Swanson & Lussier, 2001, for a review) two critical features are: to determine the learner’s potential for change when given assistance, and to provide a prospective measure of performance change independent of assistance (Embretson, 1987). Unlike traditional testing procedures, score changes due to examiner intervention are not viewed as threatening task validity. In fact, some authors argue that construct validity increases (e.g. Carlson & Wiedl, 1979; Elliott & Lauchlan, 1997; Lidz, 1996; Swanson, 1992). Such innovative assessment strategies, such as dynamic

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assessment, “assess the process used to achieve the product, focus evaluation on present and future, test to inform students, and identify (without labeling) temporary and improvable barriers to attainment” (Oakland & Cunningham, 1999, p. 49). Although dynamic assessment has been suggested as an alternative to traditional assessment (e.g. Day et al., 1997; Jitendra & Kameenui, 1993; Lidz, 1996), there are no published data, to the authors’ knowledge, on whether students with RD are more sensitive than other ability groups to such procedures. Thus, a number of questions need to be addressed if such procedures are to be used to assess RD. For example, can students with RD, when given instructional support on processing tasks, be differentiated in performance from poor as well as average readers? This question is important because assessment practices that rely heavily on psychometric tests for classification of students with RD have not provided, to date, systematic procedures to separate those students who primarily have reading problems related to inadequate or weak instructional support from those students who experience information processing deficits (Torgesen, 2002). Related to this issue is the finding that the cognitive profile of students with RD cannot always be discriminated from generally low achieving students when using static or traditional assessment (Hoskyn & Swanson, 2000; Stuebing et al., 2002).

PURPOSE OF STUDY The study briefly reported in this chapter has two purposes. First, a determination is made as to whether processing “potential,” via dynamic assessment, is related to reading achievement. Processing potential is defined as the score obtained with examiner assistance (i.e. gain score) and sustained performance without assistance (i.e. maintenance score). In statistical terms, the question is whether gain and maintenance scores contribute unique variance to reading achievement beyond what is already contributed by a traditional intelligence measure. Second, it was of interest to determine whether students with RD can be discriminated, via dynamic assessment, from those students who are poor readers. This is important to determine because several studies (see synthesis of the literature by Hoskyn & Swanson, 2000; Stuebing et al., 2002) indicate that there are no clear psychometric and processing distinctions that exist between poor readers and students with RD. Thus, we examine whether a child’s response to assisted performance provides a frame of reference for separating students who are poor readers from those students who are RD. Although not related to dynamic assessment, a comprehensive synthesis of the treatment intervention literature indicated that the magnitude of treatment outcomes (effect size) for students with RD was smaller

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(i.e. they were less responsive) than poor readers (see Swanson & Hoskyn, 1998, p. 307 for discussion). Based on these findings, it is possible that poor readers will be more responsive to measures of change than students with RD.

PARTICIPANTS AND DEFINITIONAL CRITERIA The pilot sample consisted of 70 students (39 females and 31 males). Thirty five percent of the standardization sample was low income, and 65% was middle income. The mean intelligence and reading scores, and chronological age for each group are shown in Table 1. No significant differences emerged between ability groups in terms of gender, ethnicity, or chronological age. Students with RD were selected from clinic and special education classroom samples. Classification of RD followed the “cut off” scores detailed by Fletcher et al. (1992, 1994) and Siegel (1989; Siegel & Ryan, 1989). Operational criteria included a Verbal Scale IQ score > 85 and word recognition score on the WRAT-R below the 16th perentile and math score greater than the 25th percentile (e.g. Siegel & Ryan, 1989). Verbal IQ was selected as a classification measure because a comprehensive meta-analysis comparing RD and poor readers found these scores (in contrast to Full Scale scores) moderated differences between the two groups (Hoskyn & Swanson, 2000). A cutoff score in reading rather than a 15 point discrepancy score between reading and IQ was selected because the latter scores have been found to have weak discriminant validity in separating the cognitive performance of children with RD from that poor readers (Fletcher et al., 1992; Hoskyn & Swanson, 2000; Stuebing et al., 2002). All students with RD were administered the reading and math subtests from the Wide Range Achievement Test, Revised (WRAT-R, Jastak & Wilkinson, 1984). Intelligence scores were measured on the Wechsler Intelligence Scale for Children, Third Edition (WISC-III, Wechsler, 1991). All standard verbal IQ scores for each subject were above 85. Students classified as poor readers (n = 14) followed the operational definition outlined by Hoskyn and Swanson (2000, p. 105). Criteria for poor readers were defined as students with verbal intelligence scores below a standard score of 96, but above 70, and word recognition and arithmetic scores below the 40 percentile. Students classified as skilled readers had reading, math, and Verbal scale IQ scores above a standard score of 90.

MEASURES AND PROCEDURES Four working memory subtests (two verbal and two visual-spatial) from a standardized battery of 11 of the S-CPT (Swanson, 1995a, b) were selected because

Ability Level

Variables Total Readers (n = 70) M

S.D.

Poor Readers (n = 14) M

Skilled Readers (n = 30)

S.D.

M

S.D.

Reading Disabled (n = 26) M

F Ratio

Post Hoc

S.D.

108.02 86.19 11.93

14.42 28.20 2.29

89.71 68.03 12.26

3.29 13.31 2.49

118.00 114.01 12.41

11.04 14.16 3.76

106.38 63.86 11.18

10.81 16.22 1.82

39.34** 97.21** 1.38

1 < 2 = 3a 1=31>3 2>1=3 –

Gain Rhyming Visual matrix Digit/sentence Mapping directions

3.21 6.27 3.90 3.72

1.08 1.19 1.62 2.11

2.78 5.98 3.00 3.92

0.69 1.77 1.03 2.12

3.63 6.80 4.60 3.53

1.35 2.03 1.81 2.41

2.96 5.84 3.57 3.84

0.72 1.75 1.33 1.78

4.40* 2.08 6.27** 0.22

2>1=3 – 2>3>1 –

Maintenance Rhyming Visual matrix Digit/sentence Mapping directions

2.51 5.35 2.84 3.20

1.45 1.82 1.54 1.98

2.07 5.28 2.28 3.85

1.14 1.97 0.99 2.17

3.20 5.63 3.79 3.06

1.51 1.90 1.60 2.14

1.96 5.07 2.15 3.00

1.21 1.67 1.25 1.67

6.88** 0.65 10.25** 0.96

2>1=3 – 2>1=3 –

Probe Rhyming Visual matrix Digit/sentence Mapping directions

3.57 4.00 2.89 3.17

2.30 2.88 3.05 2.96

3.42 4.21 2.21 3.71

1.60 3.59 2.45 3.64

3.56 4.26 3.63 2.16

2.48 2.87 3.14 2.82

3.80 3.70 2.40 4.20

2.41 2.47 3.16 2.32

0.13 0.27 1.58 3.74

– – – 2 0.05. In general, the results show clear performance advantage was found for skilled readers on verbal WM tasks when compared to poor readers and students with RD. In contrast, no consistant advantage was found between students with RD and poor readers.

Effect Size To determine if probe procedures influenced performance, effect sizes were calculated between the gain and initial condition. Mean effect sizes [(gain span score – initial span score)/SD of initial score)] were calculated across the four tasks. The mean effect size was comparable between poor and RD students (0.77 and 0.78, respectively), but these effect sizes were smaller in magnitude when compared to those of skilled readers (M = 1.30). Cohen (1988) considered effect sizes that approximate 0.80 as substantial. Thus, all three ability groups improved substantially on the gain condition.

Hierarchical Regression The subsequent analysis determined if intelligence and the WM measures contributed unique variance to reading performance. Standard scores on the WRAT-R measure served as the criterion measure. Because ability group differences were primarily isolated to the verbal WM tasks, and to simplify the analysis, composite scores on those tasks were the measures entered into the regression analysis. These

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composite scores were the sum of z-scores for the rhyming and Digit/Sentence tasks within each of the testing conditions (i.e. initial, gain, maintenance, and probe scores). z-Scores were based on the total sample. Hierarchical regression analyses determined the amount of variance accounted for in reading scores by the gain, maintenance, and probe scores of the dynamic measure after initial scores and verbal IQ scores were partialed out. Because the order of entry is known to influence the outcome of regression analyses, six subsequent models varied the entry of gain, maintenance, and probe scores. More specifically, we varied the entry of the dynamic measures as follows: gain, main, and probe scores (Model 1), gain, probe, and main scores (Model 2), main, probe, and gain scores (Model 3), main, gain, and probe scores (Model 4), probe, gain, and main scores (Model 5), and probe, main, and gain scores (Model 6). We also entered intelligence scores last in the equation (Model 7) to determine if WM scores partialed out the influence of intelligence on reading. In the following regression analysis tables, the cumulative R2 associated with the variables entered into the regression equation is presented in the second column. The increment in R2 associated with each variable appears in the third column. The F statistics related to the squared partial correlations appear in the fourth column. The results of the regression analysis, assessing which dynamic measures best predicted reading scores, are presented in Table 2. IQ scores were entered first, followed by initial dynamic measure subtest scores. Table 3 showed that IQ scores accounted for 31% of the variance in reading scores when entered first, and 11% when enter last in the regression models. Regardless of entry, maintenance scores were a significant predictor for models. Maintenance scores accounted for 22% of variance in reading when entered first, and 3% of the variance when entered last in the regression models. The influence of gain scores on reading, however, was sensitive to presentation order. Gain scores accounted for an additional 9% of the variance in reading scores when entered after IQ and initial scores (Model 2), and an additional 6% when entered fourth after probe (Model 3). However, entry of maintenance scores into the regression partialed out the contribution of gain scores to reading.

Discriminant and Change Analysis A discriminant analysis was carried out with group membership (skilled, reading disabled, and poor readers) as the dependent variable and the four verbal WM composite scores (measures from the initial, gain, probe and maintenance condition) as the independent variables. The discriminant function permitted prediction of group membership above the chance level, Wilks’ = 0.65, F(4, 67) = 7.75, p < 0.0001. Of the four predictor variables in the discriminant function, only the


235

Table 2. Hierarchical Regression Analysis for Reading Scores. Predictive Measures

Reading R2

Increment R2

F

Model 1 IQ Initial Gain Main Probe

0.31 0.31 0.40 0.43 0.43

– – 0.09 0.03 –

35.49*** 0.02 9.29** 3.97* 0.03

Model 2 IQ Initial Gain Probe Main

0.31 0.31 0.40 0.40 0.43

– – 0.09 – 0.03

35.49*** 0.02 9.29** 0.30 3.70*

Model 3 IQ Initial Main Probe Gain

0.31 0.31 0.42 0.42 0.43

– – 0.09 – 0.01

35.49*** 0.02 10.95** 1.45 0.89

Model 4 IQ Initial Main Gain Probe

0.31 0.31 0.42 0.43 0.43

– – 0.11 0.01 –

35.49*** 0.02 10.95** 2.31 0.03

Model 5 IQ Initial Probe Gain Main

0.31 0.31 0.33 0.39 0.43

– – 0.03 0.06 0.04

35.49*** 0.02 2.51 7.08** 3.70*

Model 6 IQ Initial Probe Main Gain

0.31 0.31 0.33 0.42 0.43

– – 0.02 0.09 –

35.49*** 0.02 2.51 9.89** 0.89

Model 7 Main Initial Probe Gain IQ

0.22 0.26 0.29 0.31 0.43

– 0.04 0.03 0.03 0.12

14.22*** 5.56* 3.04 2.21 13.78***

∗

p < 0.05. p < 0.01. ∗∗∗ p < 0.001. ∗∗

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Table 3. Percentage of Participants Who Demonstrated Change from Initial to Maintenance Condition Across the Four S-CPT Tasks. Change Score Poor readers Skilled readers Reading disabled

0

1

2

3

4

7.14 20.00 3.85

14.29 26.67 46.15

35.71 26.67 46.15

42.68 23.33 3.85

0 3.33 0

Note: Maximum score = 4. Total Sample X 2 (8, N = 70) = 16.81, p < 0.05; RD vs. skilled reader, X 2 (4, N = 56) = 10.43, p < 0.05; RD vs. poor reader, X 2 (3, N = 40) = 10.98, p < 0.05; poor reader vs. skilled reader, X 2 (4, n = 44) = 3.59, p > 0.05.

maintenance measure made a significant contribution to the accuracy of classification prediction, partial Wilks’ = 0.72, F-to-remove (1, 67) = 13.20, p < 0.001. The other measures fell short of significance (p > 0.05). When comparing only students with RD and poor readers in performance, none of the measures predicted group membership (all ps > 0.05). Because performance stability and change were a major focus of this analysis, the results were analyzed to determine those participants who were able to yield a maintenance score higher than their initial scores. Maintenance scores were used as the criterion for change because the hierarchical regression analysis showed that this measure contributed unique variance to reading performance. Participants who demonstrated change achieved maintenance scores higher than their initial scores. Participants whose maintenance scores were higher than their initial score were assigned a score of 1 and those participants whose maintenance scores matched their initial scores were assigned a score of 0. Performance on all four tasks was used in this analysis. Because there were four tasks, scores of 4 (1 point for each task) reflected a consistent positive change across all tasks. Table 3 shows the distribution of scores. As shown in Table 3, those participants who frequently showed the greatest amount of change across the four tasks were poor readers. Approximately 43% of these students received a change score of 3 when compared to skilled readers (24%) and students with RD (4%). Chi-square tests between groups indicated that poor readers yielded significantly higher change scores than students with RD, X 2 (3, n = 40) = 10.98, p < 0.01. However, poor reader’s change scores were comparable to skilled readers, X 2 (4, n = 44) = 3.59, p > 0.05. A further analysis was done focusing only on the two verbal (Rhyming, Digit/Sentence) tasks. For the two verbal tasks, approximately 60% of the students with RD received a 0 change score when compared to 21% for poor readers and 37% for skilled readers. Thus, changes in performance for the maintenance condition were less likely to occur in students with RD than in the other two reading groups.


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A discriminant analysis was also computed to determine the percentage of students correctly classified based on IQ and reading scores as a function of change scores. When the dependent measures were change scores (0 vs. 1) across the four tasks, the percentage of students correctly classified was 50% for poor readers, 60% for skilled readers and 57.69% for students with RD. These results indicated that group membership was correctly classified in approximately 50–60% of the students. For the RD students, only 15.38% were misclassified as skilled readers and 26.92% were misclassified as poor readers. When dependent measures included only verbal WM tasks, the percentage of students correctly classified based on change scores were 64.29% for poor readers, 53.33% for skilled readers, and 69.23% for RD students. For students with RD, only 7.69% of the students were misclassified as skilled readers and 23.08% were misclassified as poor readers. Taken together, these results show that of the dynamic measures, specifically maintenance scores, predicted group membership. When change scores on verbal measures were analyzed, approximately 70% of the students with RD were correctly classified. However, the results also showed that the cognitive performance of students with RD was distinct from those classified as poor readers. That is, performance changes across all four tasks were more likely to occur in poor and skilled readers when compared to students with RD.

GENERAL FINDINGS AND DISCUSSION The results yield two general findings. First, the results support the hypothesis that dynamic assessment adds significant variance in predicting reading achievement. That is, maintenance scores are better predictors of reading than initial scores. The results also suggest that dynamic assessment contributes unique variance to predicting reading, beyond what is attributed to verbal IQ. Maintenance scores contributed significant variance to reading even after verbal IQ and initial scores were partialed in the analysis. Thus, the results support the notion that a “testingthe-limits” procedure (e.g. Carlson & Wiedl, 1979; Swanson, 1992) appears to be tapping different mental constructs than static assessment procedures (e.g. WISCIII). Further, these constructs appear to be independent of information gleaned from a traditional intelligence measure. Second, ability group differences were primarily isolated to the verbal WM tasks. As expected, skilled readers outperformed poor readers and students with RD. The results further found that poor readers and RD students generally perform in the same low range on verbal WM tasks. Thus, the results coincide with others’ findings that poor readers and students with RD are difficult to separate on cognitive measures (e.g. Siegel, 1992; see Hoskyn & Swanson, 2000,

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for a review). However, these findings must be qualified because differences were found between the two groups in terms of changes in performance. The results clearly showed that poor readers were more likely to change and maintain their WM score from initial testing conditions than RD students. No significant differences were found between poor readers and skilled readers in changes from the initial to the maintenance condition. In contrast, students with RD were more likely to return to their initial score performance after presentation of probes (feedback) had been stopped. More specifically, approximately 70% of the students with RD on the verbal measures failed to maintain their performance. This occurred even though all groups were statistically comparable in the number of probes necessary to obtain an asymptotic level of performance.

PRACTICAL IMPLICATIONS The practical implication of the above findings is that approximately 30% of the RD sample were incorrectly diagnosed when change scores were taken into consideration. Stated differently, 70% of the RD sample were unresponsive to dynamic testing conditions. This finding coincides with recent classification studies attributing treatment resistance to some students with RD (e.g. Fuchs & Fuchs, 1998; Torgesen, 2000). Further, treatment resistance is becoming a key indicator of in the accurate classification of students with learning disabilities (Fuchs & Fuchs, 1998). Although it is unclear from our findings whether “treatment resisters” under dynamic testing conditions match those who have difficulties over an extended period of intervention time (e.g. 2 years of intervention), the results clearly show that WM deficits related to the verbal system are less changeable for students with RD when compared to poor readers and skilled readers. Thus, it may be possible in the early stages of assessment to identify students at risk for RD in terms of their responsiveness to feedback. The present study raises a number of interesting questions. For example, the results raise the question as to why both maintenance and verbal IQ scores predicted reading. We assume that the results reflect distinct testing conditions. Static assessment reflects two states: unaided success and failure, whereas dynamic assessment reflects some “in between” state. In the first condition, the child either answers the question correctly, without prompts or cues from the examiner, or the child is considered to fail the item. In the second condition, the child may be somewhere in between these two states: unable to perform the task independently but able to succeed with minimal assistance. For example, two students can earn the same low score on the S-CPT. With minimal intervention, however, one child experiences significant growth in performance, whereas the other child shows


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little improvement. Although the two students received the same score initially, a different degree of future success may be predicted for the two students. The above interpretation of the findings, however, must be viewed as tentative. This is because the poor performance on either verbal IQ or reading measures might indicate difficulty in responding to items, understanding task instructions, or a host of other factors. Further, the achievement measures reflect basic word recognition that may share a common memory construct with WM (see Swanson & Siegel, 2001, for a review). In addition, because poor readers with low verbal IQs were in the sample, the relationship between recall of words and recall on S-CPT items may have been heightened. Regardless of these alternative explanations, the results clearly suggest that maintenance scores contribute significant variance to the prediction of reading even when verbal IQ is partialed from the analysis. The results raise an important question as to why dynamic assessment procedures are able to separate out poor readers from those students operationally defined as RD given that performance on the majority of WM measures was statistically comparable between the two groups. A related question is why were students with RD generally inferior in performance to average readers under dynamic testing conditions. To answer these questions, let’s consider the goals of dynamic assessment. Embretson (1987; also see Grigorenko & Sternberg, 1998, for a review) described three goals of dynamic assessment “(a) improving ability estimates; (b) assessing new constructs; and (c) improving true ability.” (p. 167). These assumptions may be plausible in evaluating the sensitivity of dynamic assessment measures in predicting performance in students with RD from those who are poor readers. Given these goals we consider three explanations for the findings. The first explanation is that the dynamic assessment measures simply provide a better indicator of ability group differences than the initial testing conditions. As shown, the dynamic assessment measures were simply a more sensitive indicator of reading achievement than the initial WM score, and therefore the ability group differences reflect true differences. An alternative explanation, however, is that the performance differences were an artifact of spreading out the scores. It is unlikely, however, that the ability group differences were simply an artifact of inducing variance. For example, maintenance scores for those readers operationally defined as RD were not that different from initial scores. Likewise, a significant number of skilled readers improved on gain conditions, whereas some students with RD did not. Therefore, instead of inducing variance or spreading out the scores, the measures were sensitive indicators of processing potential in some students and not in others. The second explanation was that dynamic assessment measures tap new abilities: modified performance. A consideration of effect size sheds some light on whether performance was influenced by the feedback instructions provided

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in the gain condition. The effect size for raw scores averaged approximately 3/4 standard deviations for gain conditions for all three-ability groups. These findings suggest that responsiveness to probes was not simply an artifact of “reading ability,” thereby suggesting that some “temporal” modifications in processing performance occurred for all ability groups. We emphasize “temporal” because the readminstration of the WM tasks under maintenance conditions were more detrimental in some groups (students with RD) than others. Finally, dynamic assessment influenced students’s information processing ability. That is, dynamic-testing procedures were expected to produce changes in ability group classification because it is assumed that many psychological entities are not static (e.g. Carlson & Wiedl, 1979). The results clearly support the notion that changes in processing ability occurred across some ability groups. For example, the results indicate that some generally “inefficient” information processors (such as poor readers) were influenced by procedures that facilitate access to previously stored information. Further, some dynamic assessment measures were more likely to yield high R2 values than the initial scores in discriminating among ability group classifications, suggesting that new abilities were being tapped. In summary, the preliminary results of this study support the validity of using the dynamic assessment measures to facilitate in the correct classification of students with RD. No doubt other measures of processing must be developed to capture the subtle processing differences between ability groups. The study demonstrates, however, the applicability of the dynamic assessment to the measurement of learning potential and provides further evidence regarding the relationship between performance on information processing tasks and the classification of RD.

REFERENCES Bateman, B. (1992). Learning disabilities: The changing landscape. Journal of Learning Disabilities, 25, 29–37. Brown, A. L., & Ferrara, R. A. (1999). Diagnosing zones of proximal development. In: P. Lloyd (Ed.), L. Vygotsky: Critical Assessments: The Zones of Proximal Development (Vol. III, pp. 225–256). NY: Routledge. Brown, A. L., & French, L. A. (1979). The zone of potential development: Implications for intelligence testing in the year 2000a. Intelligence, 3, 255–273. Campbell, C., & Carlson, J. S. (1995). The dynamic assessment of mental abilities. In: J. S. Carlson (Ed.), Advances in Cognition and Educational Practice: Vol. 3, European Contributions to Dynamic Assessment. London: JAI Press. Campione, J. C. (1989). Assisted assessment: A taxonomy of approaches and an outline of strengths and weaknesses. Journal of Learning Disabilities, 22, 151–165. Campione, J. C., & Brown, A. L. (1987). Linking dynamic testing with school achievement. In: C. S. Lidz (Ed.), Dynamic Testing (pp. 82–115). New York: Guilford Press.


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Carlson, J. S., & Wiedl, K. H. (1979). Toward a differential testing approach: Testing the limits employing the Raven matrices. Intelligence, 3, 323–344. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Academic Press. Day, J. D., Engelhardt, J. L., Maxwell, S. E., & Bolig, E. E. (1997). Comparison of static and dynamic assessment procedures and their relation to independent performance. Journal of Educational Psychology, 89(2), 358–368. Elliott, J., & Lauchlan, F. (1997). Assessing potential – the search for the philosopher’s stone? Educational and Child Psychology, 14, 6–16. Embretson, S. E. (1987). Toward development of a psychometric approach. In: C. Lidz (Ed.), Dynamic Assessment: Foundations and Fundamentals (pp. 141–172). New York: Guilford. Embretson, S. E. (1992). Measuring and validating cognitive modifiability as an ability: A study in the spatial domain. Journal of Educational Measurement, 29, 25–50. Fletcher, J. M., Francis, D. J., Rourke, B. P., Shaywitz, S. E., & Shaywitz, B. A. (1992). The validity of discrepancy-based definitions of reading disabilities. Journal of Learning Disabilities, 25, 555–561. Fletcher, J. M., Lyon, G. R., Barnes, M., Stuebing, K. K., Francis, D. J., Olson, R. K., Shaywitz, S. E., & Shaywitz, B. A. (2002). Classification of learning disabilities: An evidenced-based evaluation. In: R. Bradley, L. Danielson & D. Hallahan (Eds), Identification of Learning Disabilities: Research to Practice (pp. 185–239). Mahwah, NJ: Erlbaum. Fletcher, J. M., Shaywitz, S. E., Shankweiler, D. P., Katz, L., Liberman, I. Y., Stuebing, K. K., Francis, D. J., Fowler, B., & Shaywitz, B. A. (1994). Cognitive profiles of reading disability: Comparisons of discrepancy and low achievement definitions. Journal of Educational Psychology, 86, 6–23. Fuchs, L. S., & Fuchs, D. (1998). Treatment validity: A unifying concept for reconceptualizing identification of learning disabilities. Learning Disabilities Research & Practice, 13, 204–219. Grigorenko, E. L., & Sternberg, R. J. (1998). Dynamic testing. Psychological Bulletin, 124(1), 75–111. Hoskyn, M., & Swanson, H. L. (2000). Cognitive processing of low achievers and children with reading disabilities: A selective meta-analytic review of the published literature. The School Psychology Review, 29, 102–119. Jastak, S., & Wilkinson, G. S. (1984). Manual: The wide range achievement tests-revised. Wilmington, DE: Jastak Associates. Jitendra, A. K., & Kameenui, E. J. (1993). Dynamic testing as a compensatory testing approach: A description and analysis. RASE: Remedial and Special Education, l4, 6–18. Lidz, C. S. (1996). Dynamic assessment approaches. In: D. P. Flanagan, J. L. Genshaft & P. L. Harrison (Eds), Contemporary Intellectual Assessment: Theories, Tests, and Issues. New York: Guilford Press. Oakland, T. D., & Cunningham, J. (1999). The futures of school psychology: Conceptual models for its development and examples of their applications. In: C. R. Reynolds & T. B. Gutkin (Eds), The Handbook of School Psychology (3rd ed., pp. 34–53). Shepherd, L. A., Smith, M. L., & Vojir, C. P. (1983). Characteristics of pupils identified as learning disabled. American Educational Research Journal, 20, 309–331. Siegel, L. S. (1989). IQ is irrelevant to the definition of learning disabilities. Journal of Learning Disabilities, 22, 469–478. Siegel, L. S. (1992). An evaluation of the discrepancy definition of dyslexia. Journal of Learning Disabilities, 25, 618–629.

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Siegel, L. S., & Ryan, E. B. (1989). The development of working memory in normally achieving and subtypes of learning disabled. Child Development, 60, 973–980. Stanovich, K., & Siegel, L. S. (1994). Phenotypic performance profile of children with reading disabilities: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86, 24–53. Stuebing, K. K., Fletcher, J. M., LeDoux, J. M., Lyon, G. R., Shaywitz, S. E., & Shaywitz, B. A. (2002). Validity of IQ-discrepancy classifications of reading disabilities: A meta-analysis. American Educational Research Journal, 39, 469–518. Swanson, H. L. (1992). Generality and modifiability of working memory among skilled and less skilled readers. Journal of Educational Psychology, 84, 473–488. Swanson, H. L. (1993). Working memory in learning disability subgroups. Journal of Experimental Child Psychology, 56, 87–114. Swanson, H. L. (1995a). Swanson-cognitive processing test: A dynamic testing measure (S-CPT). Austin, TX: PRO-ED. Swanson, H. L. (1995b). Using the cognitive processing test to assess ability: Development of a dynamic measure. School Psychology Review, 24, 672–693. Swanson, H. L., & Hoskyn, M. (1998). Experimental intervention research on students with learning disabilities: A meta-analysis of treatment outcomes. Review of Educational Research, 68, 277–321. Swanson, H. L., & Lussier, C. (2001). A selective synthesis of the experimental literature on dynamic assessment. Review of Educational Research, 71, 321–363. Swanson, H. L., & Siegel, L. (2001). Learning disabilities as a working memory deficit. Issues in Education: Contributions from Educational Psychology, 7, 1–48. Torgesen, J. K. (2000). Individual differences in response to early interventions in reading: The lingering problem of treatment resisters. Learning Disabilities Research and Practice, 15, 55–64. Torgesen, J. K. (2002). Empirical and theoretical support for direct diagnosis of learning disabilities by assessment of intrinsic processing weaknesses. In: R. Bradley, L. Danielson & D. Hallahan (Eds), Identification of Learning Disabilities: Research to Practice (pp. 565–603). Mahwah, NJ: Erlbaum. Vygotsky, L. S. (1978). Interaction between learning and development. In: M. Cole, V. John-Steiner, S. Scribner & E. Souberman (Eds), Mind in Society: The Development of Higher Psychological Processes (pp. 79–91). Cambridge, MA: Harvard University Press. (Original work published 1935.) Wechsler, D. (1991). Manual: Wechsler intelligence scale for children (3rd ed.). New York, NY: Harcourt Brace Jovanovich.

RECENT RESEARCH IN SECONDARY CONTENT AREAS FOR STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Thomas E. Scruggs and Margo A. Mastropieri ABSTRACT In this chapter, recent research applications in secondary content-area instruction for students with learning or behavioral disabilities are reviewed. Included are research studies in the areas of English, SAT vocabulary, world history, algebra, social studies, and chemistry. Generally, instructional strategies that have included strategy instruction, peer mediation, as well as mnemonics and other verbal elaborations, have been effective in substantially improving learning performance. Implications for practice and future research are discussed.

INTRODUCTION Students with learning or behavioral disabilities begin to encounter particular challenges as they make the transition from elementary to secondary education programs (Deshler et al., 1996). In addition to the fact that adolescence may be the single most difficult and challenging developmental stage, a number of additional elements of secondary school instruction may interact negatively with


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adolescents with learning or behavioral disabilities to make instruction at this level particularly challenging (Scruggs, 2003). A primary concern is that at secondary levels, a substantial amount of expected learning is based on adopted textbooks. Students who do not easily read and comprehend at the reading levels of these textbooks (which often exceed the grade level at which they are assigned) are particularly at risk for learning failure. In addition to the reading level, many content area textbooks are “unfriendly,” in that they present subject matter that does not lend itself to easy comprehension (e.g. Armbruster & Anderson, 1988). Students who are already experiencing difficulty reading the words in the text may find comprehension particularly troublesome when text is unfriendly. Another difficulty encountered by students with learning or behavioral disabilities is the need for strategic information on procedures needed to comprehend and recall text. Such strategies are rarely identified in textbooks themselves, and are not common in general education classroom content area instruction. In addition, content area textbooks typically contain a vast amount of content area information presented verbally. Following is a sample of content from a high school chemistry textbook: In most polymers, like polyethylene and cellulose, the monomers are all identical. In other cases, such as proteins, different monomers may be combined. Although the amino acid monomers that make up proteins appear to be very different, each one has an amino functional group and an organic acid functional group, so the monomers all link in the same way, forming a “backbone” of carbon, nitrogen, and oxygen atoms. A polymer with three amino acids is called a tripeptide (Tocci & Viehland, 1996, p. 257).

Not only is the text remarkably dense, but also the cited passage represents only 15% of the space of one page of an 848-page book. Although the passage might not be representative of the density of the entire text, passages such as this embedded within such a large book can make the task of reading, comprehending, and remembering content seem discouragingly difficult for struggling readers (Scruggs et al., 2003). In American secondary schools, introduction of very large amounts of verbal information is the rule rather than the exception. In order to cover this content within the normal academic year, a very rapid pace of instruction, and an emphasis on broad, shallow knowledge is required. Unfortunately, such instruction is not optimal for students with learning disabilities, many of whom appear to benefit from more in-depth information, presented over a longer period of time, and the use of visual-pictorial and experiential materials in addition to text learning. Further, many students with behavioral disabilities (many of whom are belowaverage readers) may not have the attentional or motivational resources to addend

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to text for long periods of time (Mastropieri & Scruggs, 2004). Nevertheless, in an age of inclusive instruction, access to the general education curriculum, and high-stakes testing, it is necessary to identify means to help students with special learning needs to succeed in contemporary learning environments. In this chapter, we report on the results of several recently conducted investigations in secondary content area learning with students with learning and behavioral disorders. These investigations included students with learning and behavioral disorders in special education and inclusive settings, in middle schools and high schools, and across a variety of content areas, including English, science, and social studies. Some investigations were more successful in promoting positive learning outcomes than were others; however, considered together, the results of these investigations provide important information about secondary content area learning for students with learning and behavioral disorders.

REVIEW OF RECENT RESEARCH SAT Vocabulary Terrill et al. (2004) described the use of the keyword method to improve vocabulary recall of a group of high school students with learning disabilities studying to take their SAT exams. The classroom teacher had expressed concerns that traditional textbook methods of teaching SAT vocabulary were not producing sufficient learning. As a result of consultation between the teacher and university researchers, the partners agreed to implement the keyword method (Mastropieri & Scruggs, 2004) and evaluate its effectiveness. The keyword method is a type of mnemonic, or memory-enhancing strategy, involving a multi-step process for improving the link between known and unknown information. In the first step, a familiar, acoustically similar word (the keyword) for the new word is created. For example, a good keyword for “martinet,” meaning “a strict disciplinarian,” would be Martian, since Martian sounds like martinet and is easy to picture (e.g. as a space alien). In the next step, an interactive picture is created in which the keyword and the meaning of “martinet” are combined. For example, a picture could be created of a Martian acting as a strict disciplinarian. In the last stage, when students are asked the meaning of “martinet,” learners are prompted to think of the keyword (Martian) think of the picture with the Martian in it, remember what else was happening in the picture (the Martian is being a strict disciplinarian), and retrieve the answer, that is, that martinet means a strict disciplinarian. Although the keyword method had been demonstrated to be effective in previous vocabulary learning research with younger students with learning

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disabilities (e.g. Mastropieri et al., 1985, 1990), the value of the keyword method in facilitating SAT vocabulary learning with high school students with learning disabilities had not been previously evaluated. Terrill et al. (2004) implemented the investigation over a period of six weeks in a 10th grade special education class. Eight 10th grade students with learning disabilities from a public high school in a Mid-Atlantic suburban community participated. The high school had a total enrollment of over 1900, with a history of high achievement (over 95% of the students typically enter four-year colleges upon graduation). Over 70% of the students scored above the 74th percentile on standardized tests in the ninth grade, and over 80% of students passed statewide tests at the proficient or advanced levels. Of the students in the Terrill, Scruggs, and Mastropieri investigation, all had been classified as learning disabled based upon federal and state criteria. The students in the study included seven boys and one girl, and they ranged in age from 15 years, 11 months, to 16 years, 6 months, with a mean age of 16 years, 1 month. Their scores on the Wechsler Intelligence Scale for Children III (WISC-III) ranged from 76 to 107 with a mean of 84. The school practiced block scheduling, in which they met Monday, Tuesday, and Thursday for 90-minute periods. The vocabulary words to be taught were selected from published classroom materials for teaching SAT vocabulary, and included such words as altruistic, benefactor, diffident, implicate, turbulent, and vociferous. The teacher selected 10 words each from units 5 to 10 for this investigation. Units 5, 7, and 9 were taught using the mnemonic keyword method, while units 6, 8, and 10 were taught using the traditional classroom materials. Mnemonic condition materials were developed by the teacher. Keywords were developed for each of the ten words per unit, and an illustration to connect the new word with the keyword was obtained from clip art obtained from commercial software, or from the internet. Each picture displayed the new vocabulary word, the keyword in parentheses, the meaning of the word, and in interactive picture of the keyword representing the meaning. For example, for “martinet,” the keyword Martian was provided, along with the definition, and an illustration was shown depicting a Martian as a strict disciplinarian. On Monday, the teacher presented all words on an overhead projector, and practiced them with the class. Later in the week, students studied the words and completed worksheet activities in which they filled in keywords and definitions for the new vocabulary words. In the traditional instruction condition, the teacher also presented the words and definitions on the overhead projector and practiced the meanings with the class. Later in the week, students practiced the meaning of the words on worksheet activities. The activities in these materials included fill-in-the blank definitions,

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sentence completion activities, and synonyms. Directions for the activities were provided in the materials. Following is an example of a sentence completion activity item (Shostak, 1996, p. 42): (2) What a(n) time to ask Milt for help, just when he was having trouble with his own car! [answer: inopportune]

Following is an example for a synonym activity item (Shostak, 1996, p. 43): (1) distinct, forthright, unambiguous

[answer: explicit]

In both conditions, practice activities continued into Tuesday and on Thursday, when the students worked on independent practice worksheets specific to their instructional condition. Students took a test on the words on the following Monday, four days after the last day of practice. Students received one week of mnemonic instruction, followed by one week of traditional instruction, in alternating fashion, until the last unit was covered. Analysis of post-test scores revealed that the students, overall, scored 49% correct on vocabulary words taught traditionally, but 92% correct on words taught mnemonically. These differences were statistically significant, as well as substantial in magnitude. When examined across weekly tests, it was found that students scored 88, 91, and 96% correct on weeks when vocabulary instruction was delivered mnemonically, while the same students scored 43, 51, and 53% correct when instruction was delivered traditionally. Although it is possible that the vocabulary words happened to be more difficult on weeks 6, 8, and 10 (this is not apparent from a visual examination of the words), the great likelihood is that the mnemonic instruction was responsible for the substantial increase in SAT vocabulary learning. Such results, combined with the results of previous mnemonic strategy research, suggest strongly that the mnemonic keyword method can a very useful component of vocabulary learning in secondary schools (Figs 1 and 2).

Middle School English Mastropieri et al. (2001) used classwide peer tutoring practices to attempt to increase reading comprehension strategy use, reading fluency, and achievement in middle school English classes of students with learning disabilities and mild mental retardation. As in the vocabulary investigation, classwide peer tutoring has been seen to be effective in promoting learning of literacy skills in the primary grades (e.g. Fuchs et al., 1997), the effectiveness of classwide peer tutoring has been

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Fig. 1. Student Performance: Mnemonic vs. Traditional.

less thoroughly studied in the secondary grades. In the present instance, students studied English content using classwide peer tutoring procedures with reading comprehension strategy instruction, or using traditional instructional techniques. Participants were from two special education classrooms in a middle school in a small Midwestern city, and included 24 students with learning disabilities (n = 20) or mild mental retardation (n = 4). All students were currently enrolled in 7th grade special education classes. Seventeen of the total were males, and

Fig. 2. Weekly Scores on Vocabulary Tests.

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seven were females; 21 Caucasian, 2 Hispanic American, and 1 African American student were included. Students with learning disabilities had an average age of 12 years, 9 months, while the average age of the students with mild mental retardation was 13 years, 0 months. IQ scores of the students with learning disabilities ranged from 81 to 113, with a mean of 84, while the mean IQ score of the students with mild mental retardation was 64. Mean reading comprehension grade equivalent for students with learning disabilities was 3.1, while the mean reading comprehension grade equivalent for students with mild mental retardation was 2.8. Reading materials were the same in both conditions, and included high interest, low vocabulary materials within the reading range for the students. Materials included trade books that ranged in readability from 2nd to 4th grade, and provides mystery stories, and narrative and expository stories about animals. Students were assigned to dyads, where the No. 1 reader was paired with the No. 13 reader, the No. 2 reader with the No. 14 reader, and so on. Dyads were then assigned at random to one of the two classes. Classes met and read the materials over 50-minute daily sessions, over a period of five weeks (Fig. 2). In the traditional condition, students received whole-class instruction, teacher questioning, oral reading, silent reading, and worksheet practice activities. Students took turns reading aloud during oral reading. Teachers employed directions for teachers listend in the teacher materials, and included activating prior knowledge and making predictions. Students discussed titles and cover illustrations, and discussed possible meanings of the title. Comprehension activity sheets were also included for use before, during, and after reading activities. These activity sheets covered building vocabulary, understanding what was read, and extensions to life skills. For example, building vocabulary activities included sentence completion activities, such as “How much damage did the robbers on the neighborhood?” with inflict included among the answer choices. Students were provided instructions for using context in comprehending the meaning of text. In the tutoring condition, students were instructed in the tutoring roles, rules, and materials on the first day, and students practiced the partner reading, and how to correct reading errors. Review and practice were provided on the second and third days. Rules for interacting appropriately with tutor partners were also discussed. These included speaking in a quiet voice, cooperating with partners, and doing the best possible work. Students were provided with tutoring materials in folders which included rules for tutoring, procedures for partner reading, for correcting errors, and for introducing the summarization strategies. Checklists for appropriate questioning were included. Overall, the traditional condition contained many important “teacher effectiveness” variables, including appropriate use of engaged time on task, teacher questioning, and content coverage (Mastropieri & Scruggs, 2002, 2004).

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During partner reading in the tutoring condition, the first reader read for five minutes, after which a timer went off and the next reader would read the same passage for five minutes. During partner reading the tutoring partners provided corrective feedback. After the partner reading followed the summarization strategy. Students asked their partners, “What was the first thing you learned?” followed by, “What was the next thing you learned?” until the story was restated. For summarization strategies, students asked their partners, “What is the most important who or what in the text?”, followed by “What is the most important thing about the who or what in the text?”, followed by “What is the summary sentence?” For this last question, students were asked to answer in 10 words or less. Teachers moved around the class and provided assistance where necessary. After five weeks of the intervention, students were given posttests. Although the two instructional groups did not differ in comprehension skills, they differed significantly on posttest. Tutoring condition students scored 82% correct on the reading comprehension measure, while traditional condition students scored only 63% correct. Observations and interviews with teachers and students revealed that tutoring was very positively received, with students indicating they enjoyed tutoring (83%) and would like to use it in other classes (75%). Among the concerns about tutoring were decoding difficulties, comprehension difficulties, and problems with partners. Reading passages twice was also less popular with students. Nevertheless, the comprehension advantages obtained by the students in the tutoring condition seemed to justify any concerns that arose concerning the tutoring.

Middle School Social Studies Spencer et al. (2003) employed strategies similar to those of Mastropieri et al. (2001) in middle school classes of students with emotional or behavioral disorders studying social studies. Although such students are typically referred to receive services to help them improve their social or emotional functioning, academic achievement is frequently a secondary problem. Students with emotional or behavioral disorders have IQ scores that are often lower than normal, although average or above IQ scores are also noted (Kauffman et al., 1987). In addition, students with emotional or behavioral disorders have been seen to function one or more years below grade level in academic skill areas such as reading, math, writing, and spelling (Kauffman, 2001; Scruggs & Mastropieri, 1986), and unfortunately, low achievement and behavior problems often accompany each other. To help students improve social and academic functioning, peer tutoring has been recommended (Spencer et al., 2003).

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Thirty students in four social studies classes completed all aspects of the investigation. Twenty-one of these students were male, about 70% were Caucasian, the others being African-American, Hispanic, and Asian. The mean age of the seventh graders was 13.2 years, and the mean age of the eighth graders was 14.1. The seventh graders had a mean IQ of 94 and a mean reading standard score of 98. The eighth graders had a mean IQ of 101 and a mean reading standard score of 107. Seventh grade students studied a U.S. History text, while eighth grade students studied a Civics test. This investigation employed a crossover design in which all students received instruction under both traditional and tutoring conditions, and each students’ score under one condition was compared with that same student’s score in the other condition. Introduction of tutoring or traditional instructional conditions was counterbalanced so that treatment was not associated with instructional unit. Seventh grade materials in the traditional instruction condition included teacher-made guided notes and accompanying textbook materials, in addition to materials from other sources (e.g. a handout on fads from the twenties, “Marathon Dancing”). Instructional materials consisted of worksheets and information sheets relevant to the topics of discussion. In the eighth grade traditional instruction, materials were similar and consisted of teacher-made guided notes, review questions at the end of the chapter, and articles from the newspaper that the teacher considered relevant to the civics topic. Teaching methods employed in this condition included round-robin reading of the textbook chapter, teacher-led discussions, and use of supplemental videos. Each student also received a pocket folder. The students used their folders to keep their daily class work, project information, and class handouts. Experimental materials from the Mastropieri et al. (2001, 2003) investigations were modified and adapted for the tutoring condition of this investigation. Teacher materials included four types of lesson plans. These included lesson plans for introducing the rules and procedures for peer tutoring, for partner reading and identifying and correcting oral reading errors, for using the summarization strategies, and for using review sheet activities. Each student received a folder that included four 30 × 50 laminated cards. These cards stated the rules for peer tutoring, identifying oral reading errors, correcting oral reading errors, and questions included on the summarization sheets, similar to those of previous investigations. Posters of this information also were displayed in the classroom during the peer tutoring sessions. Blank summarization strategy sheets and the review sheet for the upcoming week were included in the folder along with a peer tutoring checklist that students completed at the end of each peer tutoring session which allowed the students to monitor their own behavior. Review sheets contained important facts taken from each chapter, and presented in a

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list format for practice with the tutoring partners. For example, the review sheet for the seventh grade unit on the Roaring Twenties included items such as the following: Nineteenth Amendment Teapot Dome Scandal

gave all American women the right to vote. during Harding’s term, the Secretary of the Interior sold oil rights to government land.

During the traditional instruction condition in the seventh grade classes, the teacher began each class with a brief class discussion of the “warm-up” questions. Following this, the classroom activities included round-robin oral reading of the chapter, teacher-led discussions, and the independent completion of teacher-made guided notes or worksheets from the textbook. Occasional use was made of supplemental videos. The teacher assigned student projects as homework. During the traditional instruction condition in the eighth grade classes, the received “daily agenda” on their desks, upon entering the class. The agenda included homework assignments, information on projects, and activities that had been planned for the day. The students were expected to write the homework assignment in their agenda notebooks, and the teacher or instructional aide was to initial it before putting it away. In these classes, classroom instruction consisted of teacher-led discussions using outside resources such as newspaper articles that the teacher considered relevant to the civics topic. Teacher-made guided notes were sometimes given to complete independently; on some occasions, students were assigned the review questions at the end of the chapter. Round-robin reading of the chapter and supplemental videos were also used on occasion. Student projects or worksheets were assigned as homework. Instruction was implemented for four weeks, during which each class received one two-week unit using traditional instruction, and one two-week unit using peer tutoring. Treatment order was counterbalanced across classes. Results indicated that students, when in the tutoring condition, scored higher on weekly quizzes, on multiple choice unit posttests, and received higher (but not significantly higher) scores on open-ended unit tests (a smaller N for this analysis may have contributed to the negative finding). Students were not observed to have improved over pretest scores in reading comprehension. In addition, observational data revealed the students exhibited a higher degree of on-task behavior when in the tutoring condition. Interviews of teachers and students indicated that the tutoring intervention was received positively overall, and generally was thought to contribute to higher academic and social outcomes. Students were less positive, as before, with re-reading passages during partner reading.

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High School World History Guided Notes vs. Peer Tutoring Mastropieri et al. (2003) developed and implemented classwide peer tutoring materials to facilitate learning in high school social studies classes, focusing on a unit on the World Wars. Specifically, they evaluated the effectiveness of a peer tutoring procedure that included strategy questioning, as compared with the effectiveness of a guided notes strategy in the study of high school world history. Sixteen students in two classrooms participated in the investigation, including 15 students with learning disabilities, and 1 student with mild mental retardation. Thirteen of the students were males and three were females; the sample included six Caucasian, four Hispanic American, four African-American, and two Asian-American students. All students were in the 10th grade with the exception of a single 12th grader who was repeating the class. The average age of the sample was 15 years, 8 months. Students in the two conditions, although not assigned at random, were virtually identical; for example, students in the tutoring condition scored an average of 81.8 in Broad Reading, while students in the guided notes condition scored an average of 81.7. However, students in the guided notes condition scored higher on Performance and Full Scale IQ. Using a procedure similar to that employed by Mastropieri et al. (2001) in English classes, students in the tutoring condition were assigned to pairs of students referred to individually as “admirals” or “generals.” At the beginning of each tutoring session, the admirals read one paragraph while generals listened, and then students reversed roles, with the generals reading while the admirals listened. Following the oral reading session, students used summarization strategies to promote reading comprehension, similar to those used by Mastropieri et al. (2001). After reading each paragraph twice, students asked each other, “What is the most important what or who in the text?”; followed by “What is the most important thing about the what or who in the text?”; and, finally, “What is the summary sentence?” For each paragraph, students worked together with their partners to develop answers to each of the questions; however, each student wrote the answers to the questions separately on his or her own worksheet. After the reading was completed, the teacher implemented a whole class review session. In this session, a blank summarization sheet was placed on the overhead projector, while students were asked to supply their responses to the questions. When answers differed, these were discussed, and students were directed to alter their own responses based on the class discussion.

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In the guided notes condition, the teacher employed whole-class lecture and discussion, and provided students were provided with guided notes. The guided notes were developed by the teacher, and included the title of the chapter and relevant text sections, with fill-in-the-blank items interspersed throughout the set of notes taken from the text materials. Following reading of the text, guided notes based on the day’s readings were distributed. Students completed the activities by inserting the appropriate words in the blank spaces, while the teachers circulated around the room, providing assistance to individual students as needed. After this, the teacher reviewed the guided notes with the class as a whole by placing a copy on the overhead projector, and asking students to volunteer writing answers on the overhead transparency. As this activity progressed, students were directed to correct their own guided notes worksheets. Students participated in the investigation over a period of eight weeks. All students received a pretest of open-ended items (e.g. “What was the League of Nations?”). In addition, students received three chapter tests, consisting of open ended items and multiple choice items. After the end of the eight-week unit, students were given both a cumulative test with open-ended questions, and a cumulative test with multiple choice questions. In addition, a cumulative final exam that was administered at the end of the year was employed to evaluate the effectiveness of the tutoring intervention. Analysis of test scores revealed that students performed similarly at pretest, but students in the tutoring condition significantly outperformed guided notes condition students on each of the chapter tests, and on each of the cumulative tests. A significant condition-by-type of test interaction revealed that the performance advantage of the tutoring condition students was even greater on the multiple choice cumulative test. Performance was also evaluated on the end-of-year cumulative test. It was found that students in both conditions did not differ on items that were not covered in the World Wars unit, but students in the tutoring condition significantly outperformed students in the guided notes condition on items that were covered in the World Wars unit. Students in both conditions rated the interventions similarly when asked if they enjoyed the instructional method; however, students in the tutoring condition responded significantly more positively when asked whether they thought the method helped them learn and remember content information, and when asked whether they would like to use the method in other classes. Mnemonic Strategies Fontana et al. (2003) investigated whether mnemonic strategies would facilitate learning of world history content in inclusive 10th grade world history classes. Mnemonic strategies had been employed successfully in a number of previous

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investigations of content area learning (e.g. Mastropieri & Scruggs, 1989a), including history classes (e.g. Mastropieri & Scruggs, 1989b). However, mnemonic instruction in inclusive high school social studies classes had not been previously investigated. The investigation took place in four world history classes in a suburban high school in a Mid-Atlantic area. The classes included 59 students, of whom 56 were in the 10th grade, and 3 were in the 11th grade. The sample included 27 males and 43 females, and thirteen of the students had identified learning disabilities. In addition, 14 of the students spoke English as a second language, and the remaining 32 were general education students. These four classes included 33 Causasian, 10 African American, 11 Hispanic, 4 Asian/Pacific Islander, and 1 multi-racial student. Similar to the Spencer et al. (2003) investigation, the investigation employed a crossover design in which students received instruction in both mnemonic and traditional conditions in a counterbalanced order across units of instruction. The classes employed a world history text with a readability level of grade 14. The mnemonic condition materials included overhead transparencies of content which included mnemonic keyword strategies, worksheets, notecards, notetaking templates, and a guided practice table. The traditional instruction condition materials were developed to parallel as closely as possible the mnemonic instructional condition, and included non-mnemonic transparencies, worksheets, notecards, notetaking templates, and a guided practice table. For example, for the item “anarchist,” defined as “opposed to all forms of government,” the mnemonic condition material consisted of the word, keyword (ant), and definition on top of the transparency, and below a pictorial depiction of the keyword interacting with the meaning. In this case, “ants” were depicted pushing over the government. In the traditional instruction condition, the mnemonic information was not included on the transparency. Following is an example of teacher dialogue in the mnemonic condition: Teacher (T): Anarchist, An anarchist is against all forms of government. What is an anarchist? (S Answers) T: Good! The keyword for anarchist is ant. What is the keyword for anarchist? (S: Ant) T: Good! To remember that anarchist are against all forms of government recall this strategy of the ants pushing over the capitol or government building. When I ask you what an anarchist is, think of the keyword, ant, and what is happening in the picture. What is the keyword for anarchist? SR: Ant. T: Good! What is the strategy/picture?

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SR: T: SR: T:

The ants are pushing over the government building. What is an anarchist? An anarchist is against all forms of government. Great!

All students were taught 2 history units, one mnemonic and one traditional, in a crossover design where experimental treatment was counterbalanced. Two classes were received traditional instruction for Unit 1, and mnemonic instruction for Unit 2. The remaining two classes received mnemonic instruction for Unit 1, and traditional instruction for Unit 2. All students received unit pretests, unit posttests, delayed posttests, and strategy use surveys. In addition, time-on-task was measured for both conditions, and students and teachers were given attitude surveys. Instruction took place over four weeks, including two weeks for each unit. The school participated in block scheduling in which three classes were provided one week, followed by two classes the following week. Each class period was 90 minutes in length. Students studied the content in four classes per unit, then received the unit test on the last class of the second week. After students received posttesting on Unit 1, all classes alternated conditions for Unit 2. Results revealed a condition by type-of-learner interaction, in which students with learning disabilities and normally achieving students did not appear to benefit from mnemonic instruction, while the students for whom English was a second language scored significantly higher in the mnemonic condition. These results were surprising, since students with learning disabilities had consistently benefited from mnemonic instruction in numerous previous investigations (Scruggs & Mastropieri, 2000). One possibility is that, since the students with learning disabilities in the present investigation were unusually high functioning, scoring at approximately the same level as the normally achieving students, they received less benefit from the mnemonic strategies, particularly as they were provided in a large class environment. On the other hand, students for whom English was a second language apparently benefited from the additional verbal support provided by the mnemonic strategies.

Algebra Lang et al. (2004) investigated the effects of strategy training in algebra problem solving in inclusive urban classrooms. Although similar problem solving strategies have been applied successfully with elementary school students, only a few studies have been identified that specifically addressed secondary level students with learning disabilities and students and algebra (e.g. Hutchinson, 1993; Maccini

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& Ruhl, 2000; Mastropieri et al., in press). Other researchers have addressed the teaching of algebra by implementing practice activities using peer tutors (e.g. Allsopp, 1997). The Lang et al. investigation employed 74 students in four classes, and included 45 males and 29 females. Two students were 2 Caucasian, 28 were Hispanic, 26 were African-American, 1 was Pacific Islander, and 17 belonged to other racial or ethnic groups. The classes contained eight 9th graders, fifty-seven 10th graders, and nine 11th graders. Seventeen of the students had been identified as having learning disabilities, 20 were considered “at-risk,” and 37 students spoke English as a second language. The four classes were divided into two classes for the traditional condition and two classes for the self-instruction condition. Students were assessed on pretest and two posttests (immediate and delayed). In addition, students were administered a pre- and post-attitudinal questionnaire, and a pre- and post-strategy usage questionnaire. Each class received a two-week unit of instruction for each condition. Materials included the Algebra I textbook being used for all classrooms, along with scripted lessons for each condition. Student folders were also developed that included notebook paper, word problem worksheets, pencils, and self-instruction strategy steps (for the self-instruction only). The practice worksheets included 8 worksheets containing 10 word problems each. In the strategy instruction condition, students received strategy step worksheets and practice worksheets. In the traditional instruction condition, students received practice worksheets only. Students in both conditions received questionnaires on attitude and strategy use. In the strategy condition, students were taught to use the following problem solving strategy: If I use this strategy I will be successful; Read the problem; What is known? What is not known? Represent the knowns; Represent the unknowns; Do I need more than one equation? What is the equation? Substitute the knowns into the equation; Solve the equation; and Have I checked my answer? Examples of problems similar to those studied in the experimental and control conditions included the following:

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Suppose you are riding in a car that maintains a constant speed of 60 km per hr for 1 1 hr. How far will you travel? Find 2the perimeter of a rectangular field 121 feet long and 218 feet wide. A windbreaker normally costs $48. You buy it on sale and save $12. What is the percent discount? What is the area of a circle with a radius of 9 cm? All students received intensive instruction in algebra problem solving, from the same teacher, over the two-week unit. The essential difference between the two treatments was the instruction in the algebra problem solving strategy in the experimental condition. After instruction was delivered, all students were administered posttests, and two-weeks later were administered a delayed posttest. It was found that students in both conditions made significant gains from pretest to posttest (141%), and to delayed posttest (181%). Further, it was found that all types of students, including students with learning disabilities, at-risk students, and students who spoke English as a second language, made similar gains. Outcomes did not vary by experimental condition, indicating that students in the strategy condition did not perform higher as a group than students in the traditional condition. However, it was determined that strategy use was significantly correlated with performance, and that strategy condition students outperformed control students on strategy use. Although the performance differences were not significantly different across groups, the observed relation between strategy use and performance suggests that future variations of this strategy, perhaps applied over a longer time period, could result in more positive outcomes for the strategy.

Chemistry Mastropieri et al. (2003) employed peer tutoring and learning strategies to improve learning in inclusive 10th grade chemistry classes, including 39 students with and without learning disabilities. Strategies and procedures were developed to emphasize verbal recall and concept acquisition, and were presented in a peer tutoring format. Participants included 39 students, 15 of whom had disabilities. Fourteen had learning disabilities, while one student had been identified with emotional disabilities/Asperger’s syndrome. Approximately seven or eight students with disabilities attended each class. Students were taught by co-teaching teams of one chemistry teacher and one special education teacher. In the control condition, students studied from the chemistry textbook, completed worksheet and lab activities, and participated in class lecture and

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discussion. In the experimental condition, students participated in these same activities, but for about 20 minutes per class period, participated in a classwide tutoring activity in which students questioned each other on important unit content. The content for the nine-week chemistry included the following content: Core electrons; Valence electrons; Covalent bonding; Ionic bonding; Polyatomic effect; Pauli exclusion principle; Alkali metals; Metalloids; Halogens; Noble gases. All tutoring materials were placed in a number of student folders that were distributed for the tutoring activity. Students alternated tutor and tutee roles. Each tutor asked the tutee about important content (e.g. “What is the periodic table of elements?”). If the tutee could correctly answer, the tutor asked additional questions (e.g. “What else is important about the periodic table?”). If the tutee could not correctly answer, the tutor stated the answer and provided a strategy from the tutoring materials to facilitate recall of the content. For example, to remember that Mendeleev was the Russian scientist who developed the periodic table in 1872, the tutor displayed a picture of “men dealing” cards on a table, as a keyword for Mendeleev. Tutors were directed to think of the men dealing cards on a table, to remember Mendeleev developed the periodic table of elements. Further questioning by the tutor helped refine the important information associated with Mendeleev. After the nine-week unit was completed, students took posttests of content knowledge. Results indicated that students in the tutoring condition statistically outperformed students in the traditional instruction condition. However, students with disabilities benefited more from tutoring. Normally achieving students in the tutoring condition outperformed normally achieving students in the traditional instruction condition by 16%, while students with disabilities in the tutoring condition outperformed students with disabilities in the traditional condition by 43%. Overall, students reported that they enjoyed using the materials. The higher achieving students did not need to rely on the strategies included within the materials as frequently as did the lower-achieving students. Students with disabilities appeared to benefit greatly from the tutoring, and in fact might have benefited from even more time with tutoring materials that was allocated within the general education chemistry class.

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The teachers also felt that tutoring was beneficial, particularly for the lowerachieving students. However, teachers also felt pressure to proceed through the content at rapid pace in order to complete all the material by the end of the year. Consequently, at times they did not wish to allocate precious class time to use of materials to strengthen learning of chemistry content. Future research could consider ways to increase practice with new material while continuing to move through curriculum at a pace appropriate for high-stakes tests.

GENERAL DISCUSSION The investigations described in this review were conducted in different grade levels from middle school to high school, in different environments from urban to suburban to small town, in different settings from special education to general education, and across a variety of content areas, including English, science, and social studies. Students with disabilities were included in all investigations, and although learning disabilities was the disability area most commonly represented, students in these investigations also were identified as having emotional disturbance or behavioral disorders, Asperger’s syndrome, and mild mental retardation. Some of the methods investigated were more successful at increasing learning than other methods. Nevertheless, these efforts have a number of elements in common. All investigations were intended to improve learning outcomes for students with learning or behavioral disorders, and these students may or may not have been in the company of general education students. Further, all investigations focused on secondary level content area learning, rather than acquisition of basic skills such as reading and arithmetic. There were also commonalities in these investigations with respect to the interventions. These commonalities were consistent with the conclusions drawn by Swanson and Hoskyn (2000), who summarized a great volume of intervention research in learning disabilities, and concluded that combinations of direct instruction and strategy instruction were particularly effective. Some of the variables that have been consistently been associated with positive outcomes in our research, and reported by Scruggs and Mastropieri (2003), include the following (see also Mastropieri & Scruggs, 2002, 2004): (1) Clearly specified instructional objectives. Although many different treatments have been evaluated, our research in this area has involved instruction directed toward specific instructional objectives. Teaching to specific objectives is a critical factor in effective instruction. (2) Maximized engagement. In all of our investigations, we have made specific efforts to maximize academic engagement. In fact, one very specific advantage

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commonly imputed to peer tutoring is its utility in maximizing opportunities to respond (e.g. Greenwood et al., 1984). Our tutoring interventions reviewed in this chapter had maximizing opportunities as a major objective. (3) Concreteness and meaningfulness. Using pictures and mnemonic instructional strategies, we have found that increasing concreteness and meaningfulness have led to generally positive outcomes, on verbal as well as nonverbal levels (e.g. Mastropieri & Scruggs, 1998). (4) Active thinking. In the research reviewed in this chapter, we have promoted active thinking on the part of students with learning disabilities. In the investigations reviewed, this thinking has included actively thinking about academic content, thinking through the steps of a problem solving strategy, and actively retrieving steps of a mnemonic strategy. Generally, when active thinking is encouraged and carefully supported, learning outcomes are positive. (5) Explicit provision of learning strategies. Students with learning disabilities frequently demonstrate problems in both creating and applying effective learning strategies. When specific, task-relevant learning strategies are explicitly demonstrated, practiced, and prompted, however, significant learning gains often have been realized. Although all outcomes of this research were not positive, none was negative, and in all cases, experimental students performed at least as well as controls. One possible explanation for the less-than-positive outcomes may be due to the fact that in these investigations, rigorous control or comparison conditions were employed. Thus, in the Lang et al. (2004) investigation, instruction in the control condition consisted of many of the teacher effectiveness variables was also being employed. The only difference between the two conditions was the specific problem solving strategy employed – and this strategy was seen to be related to academic achievement. In the Fontana et al. (2003) investigation, outcomes were positive for students with English as a second language. That the students with learning disabilities did not appear to benefit from the mnemonic strategies was unusual, and may be related to the fact that these students with learning disabilities were particularly high functioning. In related research, it has been seen that learning and memory strategies have benefited the lower achieving students more than higher achieving students (e.g. Mastropieri et al., 2000, 2003; Uberti et al., 2003). If this is the case, a strong argument can be made for the differential effects of strategy instruction as applied in inclusive classrooms. However, with higher functioning students apparently benefiting less, the incentive for general education teachers to employ strategies may be reduced. Taken as a whole, the results presented here lend support to the model of effective instruction widely promoted in special education (see Mastropieri & Scruggs, 2002, 2004). This model incorporates careful task analysis and specification with a

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variety of strategies – for learning, comprehension, problem solving, and memory – intended to promote collaborative engagement, active thinking, and strategic learning. These instructional components appear to interact very favorably with the characteristics of learning disabilities and behavioral disorders, and may in some cases help compensate for present challenges in secondary content area learning.

REFERENCES Allsopp, D. (1997). Using class wide peer tutoring to teach beginning heterogeneous classrooms. Remedial and Special Education, 18, 367–379. Armbruster, B. B., & Anderson, T. H. (1988). On selecting considerate content area textbooks. Remedial and Special Education, 9(1), 47–52. Deshler, D. D., Ellis, E. S., & Lenz, B. K. (1996). Teaching adolescents with learning disabilities (2nd ed.). Denver, CO: Love. Fontana, J., Mastropieri, M. A., & Scruggs, T. E. (2003). The effect of mnemonic strategy instruction on world history learning in inclusive high school classes. Fairfax, VA: George Mason University, Graduate School of Education. Fuchs, D., Fuchs, L. S., Mathes, P. G., & Simmons, D. C. (1997). Peer-assisted learning strategies: Making classrooms more responsive to diversity. American Educational Research Journal, 34, 174–206. Greenwood, C. R., Delquadri, J. C., & Hall, R. V. (1984). Opportunity to respond and student academic performance. In: W. Heward, T. Heron, D. Hill & J. Trap-Porter (Eds), Behavior Analysis in Education (pp. 58–88). Columbus, OH: Merrill. Hutchinson, N. L. (1993). Effects of cognitive strategy instruction on algebra problem solving of adolescents with learning disabilities. Learning Disability Quarterly, 16, 34–63. Kauffman, J. M. (2001). Characteristics of emotional and behavioral disorders of children and youth (7th ed.). Upper Saddle River, NJ: Merrill/Prentice-Hall. Kauffman, J. M., Cullinan, D., & Epstein, M. (1987). Characteristics of students placed in special programs for the seriously emotionally disturbed. Behavioral Disorders, 12, 175–184. Lang, C., Mastropieri, M. A., Scruggs, T. E., & Porter, M. (2004). The effects of self-instructional strategies on problem solving in algebra for students with special needs. In: T. E. Scruggs & M. A. Mastropieri (Eds), Advances in Learning and Behavioral Disabilities: Research in Secondary Schools (Vol. 17, pp. 29–55). Oxford, UK: Elsevier/JAI Press. Maccini, P., & Ruhl, K. L. (2000). Effects of a graduated instructional sequence on the algebraic subtraction of integers by secondary students with learning disabilities. Education & Treatment of Children, 23, 465–470. Mastropieri, M. A., & Scruggs, T. E. (1989a). Constructing more meaningful relationships: Mnemonic instruction for special populations. Educational Psychology Review, 1, 83–111. Mastropieri, M. A., & Scruggs, T. E. (1989b). Mnemonic social studies instruction: Classroom applications. Remedial and Special Education, 10(3), 40–46. Mastropieri, M. A., & Scruggs, T. E. (1998). Constructing more meaningful relationships in the classroom: Mnemonic research into practice. Learning Disabilities Research & Practice, 13, 138–145. Mastropieri, M. A., & Scruggs, T. E. (2002). Effective instruction for special education (3rd ed.). Austin, TX: Pro-Ed.

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Mastropieri, M. A., & Scruggs, T. E. (2004). The inclusive classroom: Strategies for effective instruction (2nd ed.). Columbus, OH: Prentice-Hall/Merrill. Mastropieri, M. A., Scruggs, T. E., Davidson, T., & Rana, R. (in press). Instructional interventions in mathematics for students with learning disabilities. In: B. Y. L. Wong (Ed.), Learning About Learning Disabilities (3rd ed.). San Diego, CA: Academic Press. Mastropieri, M. A., Scruggs, T. E., & Fulk, B. J. M. (1990). Teaching abstract vocabulary with the keyword method: Effects on recall and comprehension. Journal of Learning Disabilities, 23, 92–96. Mastropieri, M. A., Scruggs, T. E., & Graetz, J. E. (2003, April). Effects of classwide peer tutoring on learning in inclusive high school chemistry classes. Paper presented at the annual meeting of the American Educational Research Association, Chicago. Mastropieri, M. A., Scruggs, T. E., Levin, J. R., Gaffney, J., & McLoone, B. (1985). Mnemonic vocabulary instruction for learning disabled students. Learning Disability Quarterly, 8, 57–63. Mastropieri, M. A., Scruggs, T. E., Mohler, L. J., Beranek, M. L., Spencer, V., Boon, R. T., & Talbott, E. (2001). Can middle school students with serious reading difficulties help each other and learn anything? Learning Disabilities Research and Practice, 16, 18–27. Mastropieri, M. A., Scruggs, T. E., Spencer, V., & Fontana, J. (2003). Promoting success in high school world history: Peer tutoring vs. guided notes. Learning Disabilities Research and Practice, 18, 52–65. Mastropieri, M. A., Sweda, J., & Scruggs, T. E. (2000). Putting mnemonic strategies to work in an inclusive classroom. Learning Disabilities Research and Practice, 15, 69–74. Scruggs, T. E. (2003, October). Recent research in secondary content area learning: English, math, social studies, and science. Paper presented at the annual meeting of the Council for Learning Disabilities, Bellvue, WA. Scruggs, T. E., & Mastropieri, M. A. (1986). Academic characteristics of behaviorally disordered and learning disabled children. Behavioral Disorders, 11, 184–190. Scruggs, T. E., & Mastropieri, M. A. (2000). The effectiveness of mnemonic instruction for students with learning and behavior problems: An update and research synthesis. Journal of Behavioral Education, 10, 163–173. Scruggs, T. E., & Mastropieri, M. A. (2003). Science and social studies. In: H. L. Swanson, K. Harris & S. Graham (Eds), Handbook of Learning Disabilities (pp. 364–379). New York: Guilford. Scruggs, T. E., Mastropieri, M. A., & Graetz, J. (2003, April). Effects of classwide peer tutoring on learning in inclusive high school chemistry classes. Paper presented at the annual meeting of the American Educational Research Association, Chicago. Shostak, J. (1996). Vocabulary workshop: Level E. New York: William H. Sadlier. Spencer, V., Scruggs, T. E., & Mastropieri, M. A. (2003). Content area learning in middle school social studies classrooms and students with emotional or behavioral disorders: A comparison of strategies. Behavioral Disorders, 28, 77–93. Swanson, H. L., & Hoskyn, M. (2000). Intervention research for students with learning disabilities: A comprehensive meta-analysis of group design studies. In: T. E. Scruggs & M. A. Mastropieri (Eds), Educational Interventions: Advances in Learning and Behavioral Disabilities (Vol. 14, pp. 1–153). Oxford, UK: Elsevier/JAI Press. Terrill, C., Scruggs, T. E., & Mastropieri, M. A. (2004). SAT vocabulary instruction for high school students with learning disabilities. Intervention in School and Clinic, 39, 288–294. Tocci, S., & Viehland, C. (1996). Holt chemistry: Visualizing matter. New York: Holt, Rinehart & Winston. Uberti, H. Z., Scruggs, T. E., & Mastropieri, M. A. (2003). Keywords make the difference! Mnemonic instruction in inclusive classrooms. Teaching Exceptional Children, 35(3), 56–61.


TECHNOLOGY AND STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES Nicole S. Ofiesh ABSTRACT This chapter presents “what we know” about the application of technology to instruction for students with learning and behavioral disabilities. Information is presented on research-based effective practices in technological interventions for teaching specific academic skills, delivering content at the secondary level and using technology as a tool for assessment. The chapter concludes with a discussion on Universal Design for Learning and the promises this paradigm holds for educating not only students with special needs, but all learners. The chapter begins where parents and teachers typically begin: the consideration of technology. For people without disabilities, technology makes things convenient, whereas for people with disabilities, technology makes things possible. Judith Heumann, Assistant Secretary for the Office of Special Education and Rehabilitative Services (OSERS) at the Microsoft Summit on Disability, February 19, 1998.

For most of us, it seems like only yesterday that the words “software,” and “computers” emerged as promising educational interventions for students with learning and behavioral disabilities. Yesterday’s child is about 23 years old now and


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as that child has grown, so have the many expectations and realities of technology in schools. Today, even more than two decades ago, public school systems are expected to prepare all students to use technology, especially those with special needs. This preparation is expected to ready our students in ways that will allow them to compete in an increasingly complex and technologically based world (Hasselbring & Williams Glaser, 2000). Not only has the use of technology in our everyday lives demanded its presence in the schools, over the past several years, federal legislation has also served to underscore its importance, and in some cases mandate technology use. Part G of the Education for All Handicapped Children Act, authorized the Technology, Educational Media, and Materials Program for Individuals with Disabilities to conduct research and develop technological tools for students with disabilities (Hauser & Malouf, 1996). The Technology-Related Assistance for Individuals with Disabilities Act of 1988 (PL-100-407), commonly known as the Tech Act, was designed to ensure technological access in work, school, and community settings for persons with disabilities. In the last reauthorization of the Individuals with Disabilities Education Act (IDEA) technology use was again deemed a critical component in the educational planning of students with special needs. IDEA (1997) mandated that Individualized Education Plan (IEP) teams consider the technological needs for children with disabilities, including those with mild to moderate disabilities. Together, these laws have been critical in promoting the use of technology for students with special needs. In addition, reviews of empirical research examining the effectiveness of computer-based instruction and software indicate that technology can enhance a student’s acquisition of skills and content knowledge when the computer is used to deliver well-designed, and well-managed instruction (Hasselbring & Williams Glaser, 2000; Hudson et al., 1993; Hughes & Maccini, 1997; Maccini et al., 2002; Woodward & Rieth, 1997). Despite this seemingly overwhelming support for technology, preparing students for a technological world which changes rapidly from year to year is challenging. The understanding of how to use technology as an educational tool can be particularly difficult for educators to keep up with. Dave Edyburn, who writes an annual synthesis of the special education technology literature states, “the pace of change in the technology marketplace challenges scholars and practitioners to maintain their currency in the discipline of special education technology” (Edyburn, 2000a, p. 6). While twenty years ago we were investigating the effectiveness of drill and practice software, the very near future may require educators to become routinely adept at using digital format in several different ways.

Technology and Students with Learning and Behavioral Disabilities

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CONSIDERATION OF TECHNOLOGY Children with learning and behavioral disabilities vary with respect to the type and manifestation of their disabilities. Three students with behavioral disabilities may all have a co-existing Attention Deficit Hyperactivity Disorder, but have completely different Individualized Education Programs (IEPs). Moreover, the placement of these students may range from a self-contained classroom to a general education classroom. Therefore, not all students with a learning or behavioral disorder will need or benefit from the same type of technology. How do IEP teams decide what is the best technology for a student or if technology is needed at all? What factors should be considered? How do teachers decide which technological applications can be used as part of whole class or individual instruction effectively? And how do teachers stay open to new ideas while staying mindful of the “seductive power of new technologies” (Lewis, 2000)? In this section we provide methods to answer these questions. Assistive technology service is defined by IDEA as “any service that directly assists an individual with a disability in the selection, acquisition, and use of an assistive technology device” [20 U.S.C. Chapter 33, Section 1401 (25)]. Specifically, the components of this service must include: (a) evaluating an individual’s assistive technology needs; (b) purchasing, leasing, or providing for acquisition of devices; (c) selecting, designing, adapting, maintaining, repairing, or replacing devices; (d) coordinating therapies, interventions, or services; (e) training and technical assistance for the individual and/or family; and (f) training and technical assistance for professionals (Olson & Platt, 2000). To provide the necessary support to carry out these requirements, each state is required to have a designated State Assistive Technology contact. Since inadequate training and ongoing technical support as well as cost remain barriers to effective technology use (Hasselbring & Williams Glaser, 2000), it is critical that IEP teams stay cognizant of these components. Personnel at State Assistive Technology centers use a variety of assessment tools to help teachers, IEP teams, and families evaluate whether the use of technology would provide a student with greater access to the curriculum or other related educational services to a meaningful degree. It is clear by the content of these technology assessments that effective technology use goes beyond consideration of the characteristics of the student and the technological device. The environment (i.e. setting) as well as the nature of the tasks in the student’s IEP or typical curriculum must also be considered. In short, each evaluation instrument acts as an ecological or ecobehavioral assessment (heretofore ecobehavioral) analyzing the student’s total learning environment (Overton, 2003). The specific

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purpose of an ecobehavioral assessment is to probe how different environments influence the student’s performance (Pierangelo & Giuliano, 2002). Increasingly, ecobehavioral assessment is being used to develop and validate specific instructional procedures, improve understanding of the components of effective instruction (including the identification of instructional risk factors), and provide a better understanding of how the quality of instructional implementation affects student outcomes (Greenwood et al., 1991; Salvia & Ysseldyke, 2000). Currently, little empirical research has been conducted on the service delivery systems used by schools and state education agencies to provide special education technology (Edyburn, 2001). Even less is known about the relationship between assessments for technology use and the eventual effectiveness of the technology. As a result there are still many unanswered questions about how technology is ultimately implemented among students with learning and behavioral disabilities. However, grounding the consideration of technology at the onset with theoretically driven effective practice is vital. Two assessment tools and principles for effective use are examined below.

The SETT Framework The SETT (Student, Environments, Tasks, Tools) framework was developed by leading assistive technology practitioner and professional developer, Zabala (1995) as a tool for IEP teams to consider technology. The framework is widely used by State Assistive Technology centers as it offers a systematic approach to making decisions regarding the provision of assistive technology to students with disabilities. Zabala states that though the needs and abilities of the student and the features of the devices may appear to be well-matched, tools are frequently selected with insufficient up-front attention to the environment(s) in which the student is expected to use the assistive technology tools, and to the tasks in which the students is expected to participate within the identified environments. Beginning with the student, the IEP team answers questions about the student, environment, tasks, and tools. Zabala (personal interview in Bryant & Bryant, 2003) explains that these questions are designed to help the team focus on strengths and challenges facing the student and those living and working with him or her. Furthermore, in keeping with a good ecobehavioral assessment, families play a critical role in assistive technology decision making as part of the IEP team. After consideration of the environment and tasks, the last questions, “Tools” are answered. At this stage a variety of technological devices is considered. The range includes “no tech” options which may be simple adaptations that have nothing to do with electronics or devices and “low tech” options such as Velcro or sticky notes.


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Zabala suggests that the information needed to answer the questions posed by the SETT framework should be gathered through observations of the student involved in ordinary tasks presented in the natural settings in which the student operates; discussions with the significant people who share those settings with the student; and, possibly, a review of other strategies and tools that have been tried with student. Finally, Zabala (1995) underscores that the SETT framework is a valuable part of the technology assessment process, but that assessment and intervention are continual on-going processes that require follow-up to be effective.

Functional Evaluation for Assistive Technology (FEAT) Raskind and Bryant (2002) designed the Functional Evaluation for Assistive Technology (FEAT). FEAT is a series of rating scales to be used by teachers to gather data to help make decisions about the use of technological devices with a particular student. The rating scales are used by teachers and IEP teams to evaluate the interplay among: (a) the user’s specific strengths, weaknesses, special abilities, prior experience/knowledge, and interests; (b) the specific tasks to be performed; (c) specific device qualities (e.g. reliability, operational ease, technical support, cost); and (d) the specific contexts of interaction (across settings – school, home, and work) (Bryant & Bryant, 2003). One tool not discussed above, but that bears recognition is The Adaptations Framework by Bryant and Bryant (1998). The Adaptations Framework is an evaluation tool used to assess whether or not an individual can benefit from a wide variety of adaptations, not limited to, but including technology. Because Bryant and Bryant clearly organize their assessment with respect to the components of an ecobehavioral assessment, and technology is often considered an adaptation or accommodation, the Framework is another useful assessment tool. For more information on The Adaptations Framework see Bryant and Bryant (2003).

Case Illustration To illustrate how both the SETT framework and FEAT could be used, consider Raymond a tenth grader with a reading-based learning disability. Raymond reads at approximately the third-grade level but attends social studies and science in a general education classroom. He attends a special education resource room for language arts and math where he receives direct instruction in reading and math. When it comes time to consider technology as part of his educational program, Raymond’s IEP team needs to evaluate the demands of each classroom

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environment, each content area teacher, and the demands of the special education classroom and teacher. Raymond’s social studies teacher may be making accommodations without anyone being aware of it except Raymond. The science teacher may be at a loss for how to make the textbook accessible to Raymond so instead, he simply does not hold Raymond accountable for the reading. The IEP team considers what the reading demands are for both teachers while upholding the same content requirements for all other students (i.e. to gain knowledge through text). Raymond and his mother underscore to the IEP team that he would stay interested in the class lectures if he could keep on top of the reading material. Raymond’s special education teachers contribute information about the types and effectiveness of accommodations, modifications, and compensatory strategies that have been implemented such as cognitive learning strategies. Through collaboration and the assessment of additional factors, the team decides that a recorded textbook would be an appropriate instructional tool to provide Raymond greater access to the reading requirements for both courses and ultimately the general education curriculum. The special education teacher takes responsibility for providing instruction in the technology and his general education teachers agree to provide copies of the texts to be recorded by a student volunteer until a professional copy can be obtained. The team then considers all other reading materials in all other classes, as well as materials that Raymond may need as part of his transition plan. It is agreed that there are numerous other materials, such as his driver’s license test study booklet, that he is unable to read independently. To meet these reading demands, the district assistive technology specialist suggests a free software program that can be downloaded onto a computer in the library that will read aloud any basic text he has digitally scanned onto a CD. The librarian, in collaboration with the special education teacher and Raymond, agree to take responsibility for identifying these materials that need to be scanned. In this scenario, technology is used as an accommodation to help Raymond meet the needs of his high school reading material with a well below high school reading level. Of critical importance is the observation that the IEP has not used technology as a substitute for reading instruction. Raymond will still receive an appropriate reading intervention designed to improve his reading skills while the technology helps him to perform successfully in the same environment as his peers. Moreover, the team appropriately discussed responsibility for training of the technological device. One conclusion that has emerged from several literature reviews on technology is that technology in and of itself is not effective without principles of effective instruction embedded in the presentation and/or training of the device (Forness et al., 1987; Hudson et al., 1993; Lewis, 2000; MacArthur et al., 2001; Maccini et al., 2002). These principles include: (a) planning for


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instruction; (b) creating a learning set; (c) presenting content and guided practice; (d) providing independent student practice; and (e) assessing student knowledge.

Principles for Effective Use In keeping with sound educational practice, ongoing evaluation is a critical part of the assessment for technology effectiveness (Raskind & Bryant, 2002; Zabala, 1995). After a decision is made to include technology into the IEP, effectiveness can be derailed without attention to usability. One factor that could potentially derail effective use of a selected device is the availability of technical support for a product. Without technical support there is a high likelihood that the technology will be abandoned (Phillips, 1991). A second factor is the prerequisite skills that may be necessary to use a selected device. For example, speech recognition seems to hold great promise for both reading and writing skills among students with learning and behavioral disorders (Higgins & Raskind, 2000; MacArthur, 1999; Raskind & Higgins, 1999). At present however, research is inconclusive on the impact that speech recognition systems have on the improvement of a student’s written expression (Faris-Cole & Lewis, 2001; Higgins & Raskind, 1995); there appears to be greater support for its use in reading and spelling (Higgins & Raskind, 2000; Raskind & Higgins, 1999). One problem with the use of speech recognition systems is that to train the system to recognize speech, students must spend a considerable amount of time reading text into a microphone in order for the system to recognize his or her voice. Students who cannot read have great difficulty training these devices and, even if the device works with some degree of accuracy, the nonreader cannot proof what he or she has written (Lewis, 2000). Thus, an IEP that does not consider the prerequisite skills necessary to implement a device may be setting a student up for failure. Because technology specialists are typically aware of the requirements to use particular devices the IEP team should include at least one person who is familiar with the device(s) being considered.

An Alternative to Technology as an IEP Consideration Clearly the process of adopting technological devices in the classroom for students with learning and behavioral disabilities is driven by legislation. The mere fact that it is part of a federal mandate (i.e. IDEA) to consider technology may create more of barrier for technology use, than a support. Edyburn (2000b) states, “the current system of assistive technology assessment and service delivery does not

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seem adequate for meeting the demands that will be required of it [the system] as students with high-incidence disabilities need access to services and devices” (p. 8). Furthermore, he explains that the process individuals must undergo to adopt technology is a near replication of the rigorous process we use to determine students eligibility for special education. Just as the United States faces a critical teacher shortage in special education, there is a critical shortage of personnel trained in assistive technology. Edyburn (2000b) continues, “The shortage is so significant that most school districts are unlikely to have even one full-time assistive technology specialist to support the needs of all students receiving special education” (p. 8). As an alternative to this process, Edyburn recommends that the assistive technology service delivery system be redesigned around a series of “technology toolkits.” Toolkits are essentially a few technology tools that every general and special education teacher would have as a routine part of classroom materials. An example of a core toolkit might include a word processor, word prediction software, a text to speech scanner, and speech output software (Edyburn, 2000b). Toolkits can be developed for different persons (e.g. students or teachers) and reasons (e.g. class management, learner productivity). This alternative approach to service delivery for technology use holds great potential for meeting the needs of a larger number of students with high incidence disabilities.

SPECIFIC SKILL INSTRUCTION The effective use of technology to enhance or provide greater access to the core curriculum: reading, writing, and mathematics, is important across all grade levels not just in elementary school. Data from the 1998 National Assessment of Educational Progress (NAEP) show that 41% of fourth-grade boys and 35% of fourth-grade girls read below the basic level. It also reveals that at middle school, a time when the setting demands change dramatically, 32% of boys and 19% of girls cannot read at the basic level. This gap does not appear to lessen substantially by twelfth grade, when 30% of boys and 17% of girls still cannot read at the basic level. Even more disturbing is that these figures are for all students, not just students with learning and behavioral disabilities. For students in these high incidence categories, research suggests they typically score below the 8th-grade proficiency level in reading, while in high school (deBettencourt et al., 1989). In writing, studies indicate that students with learning disabilities score much lower in writing on state competency exams and in the classroom than do students without learning disabilities (Graham et al., 1993; Thurlow et al., 2000). Writing performance achievement differences between students with and without disabilities are similar to reading and math achievement. National performance


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data on state assessments across states and grades, suggests that 10–69% of students with disabilities are passing state writing standards. Narrowing the scope to 8th grade writing assessments, the differences in passing rates of students with disabilities and all students ranged from 25 to 44 percentage points (Thurlow et al., 2000). Although reading and writing are cited most often as the primary academic deficits of students with learning and behavioral disabilities, low mathematics performance is as serious a problem (Bryant & Rivera, 1997; Mastropieri et al., 1991). Not only do these findings suggest that instruction in basic skills needs to continue for many students beyond elementary school, it underscores the importance of providing appropriate intervention services during the elementary years. Research on the effectiveness of technological devices and computer software programs is limited, but several programs and devices that have resulted in mild to moderate effect sizes for students with learning and behavioral disabilities. MacArthur et al. (2001) remind us that, “The effects of technology on the literacy of students with disabilities will continue to defy a simple synthesis [of the literature]. Its effects will depend on the characteristics of the design, the instruction that accompanies it, the ways in which it is used, and the characteristics of the students who use it” (p. 298). The same understanding can be applied to research on technology and math.

Reading MacArthur et al. (2001) have provided the most substantive review to date of the research concerning technology and literacy. Their review covers an analysis of 15 years of empirical studies. In the researchers’ discussion of reading, technology is categorized into two areas: technology and word-identification and technology and text comprehension. Technology and word-identification includes: (a) computer-assisted instruction (CAI) in phonological awareness and decoding and (b) computer software that delivers speech feedback to students as they read. Technology and text comprehension covers analysis of literature designed to promote comprehension through the use of electronic text (e.g. speech synthesis, definitions, graphics, and supplementary text). The prevailing perspective in studies that are designed to promote comprehension through the enhancement of text is that they allow students to make progress in the general curriculum despite below grade level word identification and analysis skills. For many middle and high school students with reading disabilities and attentional problems, this compensatory approach is a worthwhile goal that may provide the avenue for success in content classes (see Mastropieri et al., 2003 for more information on reading comprehension strategies for secondary students with learning disabilities).

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According to Royer et al. (2001) the most common type of academic challenge experienced by children with attentional deficits and behavior disorders is reading. The direction of the relationship between behavior and reading is not clear at this time. Some speculate that oppositional behavior interferes with a student’s ability to attend to reading; while others speculate problems with reading tend to contribute and worsen the behavior of students who are predisposed to emotional problems, conduct disorders, and attention deficit disorder (Hinshaw, 1992; Silva, 1987; Stevenson, 1984). MacArthur et al.’s (2001) findings and the findings of two other research studies are described below. Word-Identification: CAI in Phonological Awareness and Decoding Computer assisted instruction (CAI) and practice in reading can help students with learning problems learn to read more effectively by helping them to develop accurate and fluent word identification skills (Torgesen & Barker, 1995). Several studies of CAI (Barker & Torgesen, 1995; Foster et al., 1994; Jones et al., 1987; Roth & Beck, 1987; Torgesen et al., 1990) appear to show qualified support for the use of efficacy of CAI for the improvement of phonological awareness and word identification (MacArthur et al., 2001). It is important to note however, that the four commercially developed software programs evaluated in these studies (e.g. Hint and Hunt, Daisy Quest) were designed for elementary grades and all of the participants in the studies were 10 years of age or younger. Little information is available regarding the effectiveness of CAI to improve the decoding skills of middle and high school students. Developmentally appropriate programs for older students who have little word-identifications skills are only recently being developed. As with many children with word identification problems, problems often remain with automatic and fluent reading even when remediation has resolved word identification problems (Shaywitz, 2003). Subsequently, when reading is slow, many students lose their ability to comprehend text (Stanovich, 1990). In order to strengthen automaticity, several researchers have turned to technology to provide CAI through repeated readings, while measuring student progress. While several of these programs have been developed, the effectiveness of these programs is being investigated. Two studies not reviewed by MacArthur et al. (2001) focused on reading automaticity training (Royer et al., 2001; Wolf et al., 2000). In the Royer et al. study, nine students with attention deficit disorder completed an 8-week intervention program Computer-based Academic Assessment System (CAAS), that focused on increasing the speed and accuracy of various reading tasks. Each student was provided with four pages of forty words at a level assigned through a pretest, at least five days per week. A graph was provided that could be used to record the average reading time per page (in seconds) on a daily basis. All students began the study with below grade level reading and ended the


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study with general improvement in the ability to: (a) identify words; (b) identify nonwords; (c) activate the meaning of words; and (d) process and understand sentences. Two students did not make a gain on each task. Two other studies by Royer and colleagues (Cisero et al., 1997; Royer, 1997) suggested similar findings with CAAS, though Royer et al. (2001) report that the application of the CAI program to students with attention deficit disorder has been difficult due to the challenge of keeping this population interested and engaged. Wolf and colleagues have researched another program RAVE-O (Retrieval, Automaticity, Vocabulary Elaboration, Orthography) (Wolf et al., 2000) designed to improve reading fluency. RAVE-O was developed for elementary age students with developmental reading disabilities. The program attempts to address multiple sources of dysfluency in readers with disabilities and involves comprehensive emphases on fluency in word attack, word identification, comprehension, and automaticity (Deeney et al., 2001; Wolf et al., 2000). One important aspect of the program uses a computerized set of games called Speed Wizards to facilitate orthographic pattern recognition. Early studies of the RAVE-O program have suggested significant program effectiveness, but it is still uncertain if the gains made from the program will generalize to standardized reading measures (Deeney et al., 2001). Word-Identification: Speech Feedback As technology has developed over the past ten years, researchers have begun to investigate speech synthesis and feedback as an educational tool. The main hypotheses, with some variation(s), are that students can develop word-recognition skills by practicing reading words in meaningful text with a computer providing the feedback through artificial speech. Either digitized (recorded) or synthesized speech can be used to provide feedback at the level of the whole word or of word segments, such as syllables, onset-rime, or phonemes (MacArthur et al., 2001). Nine studies were identified by MacArthur et al. (2001) that involved variations of speech feedback (e.g. “d-ish” vs. “dish”) and combinations of technology (e.g. speech feedback with or without CAI). The findings in these studies have been inconsistent and there is little evidence that positive findings generalize to other reading measures. At present some evidence suggests that speech feedback improves students’ decoding and word identification skills (Olson & Wise, 1992; Wise, 1992; Wise et al., 1989, 1990), however, MacArthur et al. explain that their findings must be interpreted with caution because the control group did not receive a reading intervention. Similar to studies on the effectiveness of CAI, the majority of participants in these studies were elementary ages. Only one study, Wise and Olson (1992) included students at the elementary level (i.e. ages 7–9) and the middle school level (i.e. ages 10–14). In this study a significant

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difference existed in spelling and pseudoword reading in the first week of the study, for the older group but that finding was not replicated in the second week. Text Comprehension: Speech Synthesis Speech synthesis is defined as, “the process of producing sounds similar to human speech via a computer or other device” (Bryant & Bryant, 2003, p. 226). All of the students in the MacArthur et al. review regarding text comprehension and speech synthesis involved middle or high school students. Overall findings are mixed. Two studies reported comprehension gains for students with learning disabilities from the use of screen reading programs (Elkind et al., 1993; Montali & Lewandowski, 1996), but the results from the Elkind et al. study (1993) did not generalize to an English class where literature was read from a screen reading program. Leong’s (1992) findings differed from the two later studies, but this could have been due to differences in the population (i.e. poor readers vs. readers with learning disabilities). Farmer et al. (1992) investigated student’s use of a screen reader to provide unknown words. In this study no difference was found on comprehension questions answered immediately after reading, but the researchers noted that the students requested speech synthesis on only a few words. Text Comprehension: Electronic Enhancements Several studies were evaluated to determine the overall effectiveness of electronic enhancements, also know as hypertext and hypermedia, on text comprehension. Hypertext and hypermedia software differ from typical CAI in that they allow learners to interact with information in a non-linear fashion (Horton et al., 1988). Hypermedia programs include text enhancements not typically part of a hypertext program such as graphics, digital videos, and sound enhancements (Maccini et al., 2002). Both of these technologies allow the learner to make the decision about what happens next through multiple access points to content (Jeffs, 2001; Lewis, 1998b). Unlike typical software programs, this branching feature provides the learner an opportunity to engage and take charge of his/her own learning experiences (Jeffs, 2001, p. 65). In two studies researchers added four types of enhancements to electronic passages: (a) definitions of difficult vocabulary words; (b) passage paraphrases with lower readability levels; (c) supplemental background information in the form of additional text or illustrations; and (d) a statement of the main ideas of the passage. Both studies suggested that electronic enhancements increased text comprehension, but the effectiveness appeared to be enhanced by students’ familiarity with computers (Reinking, 1988; Reinking & Shriner, 1985). The findings of a subsequent study that also included definitions and descriptions of main ideas as text enhancements, did not suggest that enhancements were effective at improving comprehension of text for a group of


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high school students (Feldmann & Fish, 1991). Similar findings suggesting the ineffectiveness of electronic enhancements were reported by Swanson and Trahan (1992). One later study (MacArthur & Haynes, 1995) included four additional types of enhancement: (a) a word processing feature for notetaking; (b) an on-line glossary; (c) links between questions and text; and (d) highlighted main ideas and supplementary questions. High school students with learning disabilities obtained significantly higher scores for the chapter studied with the enhanced version. A series of studies developed by Higgins and colleagues (Higgins & Boone, 1990; Higgins et al., 1996) examined the effects of electronic study guides with text enhancements. They found no significant differences among the treatment conditions on the outcome measure (i.e. varying quizzes). In a three year longitudinal study that took place from kindergarten through third grade (Boone & Higgins, 1993; Higgins & Boone, 1991), electronic versions of texts from a basal series were enhanced though a variety of ways, and the enhancements were introduced during different phases of the study. These results were inconclusive. Presently the findings regarding electronic enhancements on the comprehension of text are mixed at the elementary level. Research on the use of hypertext and hypermedia software at the secondary level has also been variable for hypertext but more promising for hypermedia. Horton et al. (1990) investigated the effects of a hypertext program to teach social studies content to four high school students with learning disabilities using a pretest-posttest design. The program provided self-paced study guides with differing amounts of information. The software adapted the amount of information presented to a student based on his/her correct answers to questions. The program included four effective teaching principles: (a) computerized feedback and corrections; (b) three self-paced study guide lessons; (c) access to definitions via enhancements; and (d) positive feedback as part of the corrections (e.g. computer replied, “that was correct”) (Maccini et al., 2002, p. 255). Significant treatment gains from pretest assessment to posttest assessment were observed. A similar study was conducted by Higgins and Boone (1990) with secondary students with (n = 10) and without learning disabilities (n = 30). The main difference between this study and the Horton et al. study was one group had no interaction with text. For this group, the material was presented in solely lecture format with the opportunity for notetaking, followed by a short reading passage, a review via worksheet, and a quiz. The second group differed from the first in that the review was administered through the software program. The third group differed from groups 1 and 2 in that the participants only used the computer-based study guide 30 min before the quiz. As with the Horton et al. study, the social studies information was controlled through “layers” of text enhancements: cues starting with original text, followed by definitions, tutorial strategies, and graphics. Results

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indicated that the students in computer-use groups performed as well as those in the non-computer group. The students in the computer-only study guide group scored the highest mean average posttest score. Students with learning disabilities however, did not perform to the established criterion level of 80% regardless of group assignment. In a continuing study, Higgins et al. (1996) replicated the treatment conditions from the Higgins and Boone (1990) study using hypermedia instead of hypertest with social studies content. The study involved 25 students identified as learning disabled (n = 13) and remedial (n = 12). The hypermedia software in this study allowed students: (a) greater opportunity for practice and relearning; (b) electronic definitions and the option for alternate words in text; (c) reconnection with specific parts of the text upon selection of an incorrect response; and (d) advancement in the text following a correct response. The researchers also coded the answers to the quizzes in three ways: (a) factual; (b) inferential; or (c) those answers that corresponded to the information presented in a pop-up text feature. The findings indicated that “students who had access to the hypermedia study guides exhibited better information retention than students who used alternative support and did not use the hypermedia study guides” (Higgins et al., 1996, p. 410).

Spelling, Handwriting, and Written Expression The process of writing integrates, visual, motor, conceptual and attentional abilities and is a major means through which students demonstrate their knowledge of advanced academic subjects (Mercer & Mercer, 2001; Stevenson et al., 1993). For students with learning and behavioral disabilities, these physical and cognitive requirements place great demands on precisely the areas their disabilities affect most often. The National Center on Educational Statistics indicated that the average writing scores of fourth graders was 205 on a 500-point scale (NCES, 2001). Ineffective writing not only has huge implications for a student’s ability to pass state competency exams, but it also prevents students from using one of society’s most important channels of communication. Robyn, a college freshman with attention deficit disorder and a learning disability, explains this frustrating situation: “I had a really hard time preparing for my state’s exit exam from high school, and used a lot of accommodations, like a spellchecker and word processor. I was lucky that my special education teacher taught me how to type in eighth grade . . . a lot of kids didn’t know how to do that and that really slowed them down. But even now there’s so much I want to write, but if I don’t know how to spell the words . . . which is all the time . . . I’ll just write something really


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dumb . . . and then I can never seem to say what I want. I know more than I can write . . . and I don’t send birthday cards to anyone!” Spelling and handwriting fluency are important in order to become a good writer. Unfortunately, two of the characteristics of struggling writers with mild to moderate disabilities are poor spelling and handwriting (Graham et al., 1991; McNaughton et al., 1994). These aspects of mechanical writing skills account for a substantial amount of the variance in writing quality (Graham et al., 1997). Many students detect the problems in their writing, but do not know how to correct those errors (Graham & Harris, 1993; Graham et al., 1991). The performance of students with disabilities on written expression tasks is especially poor (Schumaker & Deshler, 2003). As in the case of Robyn, many students sacrifice written expression because of their poor basic writing skills (Gregg & Mather, 2002). Moreover, Graham et al. (1991) report that students typically write with little or no planning, and frequently have no strategy for written composition. This lack of planning may explain the limited content and poor organization in their writing (MacArthur, 2000). Graham et al. (2001), note that an array of technological devices, many of them electronic provide new options for minimizing the writing difficulties experienced by students with LD, allowing them to circumvent some problems and obtain support in overcoming others. As with the example of Raymond’s use of recorded texts to compensate for below grade level reading, technological devices for spelling and handwriting should not replace good writing instruction but rather supplement good instruction (Englert et al., 1995; Graham et al., 2001). In their review of the literature on technology and writing, MacArthur et al. (2001) use the categories of “technology and word processing” and “technology and spelling.” The category of technology and word processing includes analyses of research regarding word processors, spelling checkers, graphics and multimedia, word prediction and speech recognition. The category of technology and spelling focuses on the specific area of CAI in spelling. Technology and Word Processing The appeal of word processors for students with writing difficulties is not much different from the appeal these devices offer for most individuals. Word processors offer the opportunity to easily revise and correct papers and, generate professional looking documents. For students with writing difficulties however, word processors can also alleviate writing fluency problems caused by slow and labored letter and sentence formation. With this burden gone, students may be more likely to revise and edit papers as part of the writing process and increase the length of their compositions. One assumption embedded in the idea of word processors is that students will easily pick up keyboarding skills. Without

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repeated keyboarding experience however, students may be just as dysfluent at word processing as without (Lewis, 1998b; MacArthur & Graham, 1987). Three studies have compared handwritten composition vs. word processing (MacArthur & Graham, 1987; MacArthur et al., 1995; Vacc, 1987). The results of all three studies suggest that word processing alone does not improve writing fluency, and in some instances students actually wrote less (Vacc, 1987). To evaluate the combined effectiveness of instruction and word processing four studies have been conducted (Graham & MacArthur, 1988; MacArthur et al., 1991, 1995; Stoddard & MacArthur, 1992). In general, students with disabilities made substantial gains in written expression when combined with writing instruction. These findings once again underscore the importance of aligning effective instruction with technological interventions, as well as the caution that classroom computer use should not be an independent activity (Graham et al., 2001; Lewis, 2000). In the Enhancing Writing Skills Project Lewis (1998a), examined the effects of various word processing tools on the writing performance of students with learning disabilities. Lewis and her colleagues (Lewis, 1998a; Lewis et al., 1999) came to the following conclusions: (a) students showed the greatest gains in writing speed when using Co-Writer (1990) word prediction software, but handwriting remained faster; and (b) spell checkers were found to be the only effective word processing tool for students with learning difficulties (i.e. as compared to grammar checkers, synthesized speech). In one study related to the Project, spell checkers were able to offer accurate suggestions for misspellings 50% of the time. This rate was similar to the results of a study with middle school students who had moderate to severe spelling problems (MacArthur et al., 1996). In that study students ultimately corrected 37% of the errors in their work as opposed to the 9% error correction rate of students who did not use spell checkers. In a second Project-related study Lewis et al. (1999) found the spellchecker in the word processor program Write:Outloud (1990) provided correct suggestions 70% of the time. Based on the components of cognitive strategy instruction (Deshler & Schumaker, 1988; Ellis et al., 1991), McNaughton et al. (1997) studied the effectiveness of an integrated proofreading and spelling strategy on the proofreading performance of students with learning disabilities. A multiple baseline design across three students was employed. In order to increase the error correction rate of previous studies, students were taught how to pick correct alternative spellings and generate new spelling suggestions. At the end of the study, all students produced written texts with final spelling error rates that fell within the performance range of peers without disabilities. Clearly, different spell checkers vary in their error detection rate and in their ability to supply a correct word, which strongly suggests spell checkers should not replace spelling instruction at this time. Furthermore, effective instruction should accompany the implementation of


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spell checkers as part of an educational program in writing (Graham et al., 2001; Schumaker & Deshler, 2003). Two studies have been published addressing the impact of speech recognition software on the written expression and fluency of students with learning disabilities. The results of these studies suggest that speech recognition has a variable impact on written expression depending on the age and characteristics of the users. Higgins and Raskind (1995) designed a study where university students with learning disabilities (n = 29) wrote essays on a word processor, or using a scribe, or a speech recognition system. The researchers found the students received significantly higher holistic scores when using a speech recognition system as compared to the word processor. However, quality ratings were approximately the same between speech recognition and the use of a scribe. In a second study, four intermediate grade students with learning and behavioral disorders were taught how to use two types of speech recognition software; one with discrete speech and one with continuous speech (Faris-Cole & Lewis, 2001). The results indicated extreme variability (i.e. 49–87%) in the recognition accuracy rates of students’ speech. Ultimately, in this study handwriting and type were faster than speech input because of the amount of error correction associated required by the students when using the software. Likely due to the variability in speech recognition performance, there was little improvement across all students in terms of written expression. However, one student showed substantial improvement in written expression and number of words using speech recogntion. Technology and CAI in Spelling MacArthur et al. (2001) reviewed four studies that were conducted to evaluate the effectiveness of CAI on spelling (Berninger et al., 1998; Cunningham & Stanovich, 1990; MacArthur et al., 1990; Vaughn et al., 1992). In general, only students in the Berninger et al. study, which taught orthographic spelling patterns, and the MacArthur, Haynes et al. study made gains in spelling. MacArthur et al. (2001) state, “research is needed on the design of CAI that teaches spelling as a process learning orthographic and phonological representations” (p. 296). Hasselbring and Goin (1991) suggest that for CAI in spelling to be effective, software programs should: (a) require students with disabilities to use long term memory; (b) limit in the size of the practice set of words; (c) require practice spread over several different times; and (d) emphasize speed as well as accuracy. In their review of the literature on spelling interventions for students with mild disabilities, Gordon et al. (1993) found that CAI in spelling can increase motivation and engagement in spelling, promote study strategies, and enhance spelling performance when a time delay procedure is involved.

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Math Students with learning disabilities and behavior disorders exhibit several common academic and behavioral characteristics that often affect success in mathematics (Fuchs & Fuchs, 2002; Maccini & Hughes, 1997; Scruggs & Mastropieri, 1986). These characteristics, affecting performance for both groups, include: (a) difficulty attending to the most relevant aspects of tasks (e.g. excluding irrelevant information from a story problem) (Kaufmann, 2001; Parmar et al., 1996) and (b) applying metacognitive strategies. In particular, students with behavioral and emotional disabilities possess characteristics that differentiate them from peers without disabilities, and to a lesser extent, from students with learning disabilities (Maccini & Hughes, 2002). These students often exhibit a general lack of attention, persistence, concentration, and have difficulties with independent class work (Batchelor et al., 1990; Carpenter, 1985; Carr & Punzo, 1993). For students with learning disabilities, problems have been noted such as cognitive inflexibility (Russell & Ginsberg, 1984), difficulty with spatial concepts (Homan, 1970; Kosc, 1981; Rourke, 1993); problems understanding mathematical language (e.g. greater than or equal to) (Homan, 1970; Rourke, 1993), and math application and reasoning (Cawley & Miller, 1989). One often cited report suggests the prevalence rate of students with math-based disabilities in the general population is between 6 and 7% (Gross-Tsur et al., 1996). Studies suggest that these students lag approximately two grade levels behind their peers without disabilities (Wagner, 1995), progress about one year for every two years of school attendance (Cawley & Miller, 1989), and typically plateau in math skills at about seventh grade (Warner et al., 1980). More recently, data from the National Center for Educational Statistics (1996) indicates that eight grade and 12th grade students in the United States scored below the international average in math. Like other areas of the core curriculum, technology is often suggested as an instructional intervention. Calculators The most commonly thought of technological device to aid in mathematics across grade levels is the electronic calculator (Hembree, 1986; Thompson et al., 2002). However, in the early grades, researchers suggest that calculator use be taught alongside paper-and-pencil activities for conceptual understanding of math calculation, not as a replacement for instruction (Suydam, 1980). For some students with learning and behavioral problems, use of a calculator can remove disability-related barriers such as problems with attention, cognitive flexibility, and short-term memory. This allows students to concentrate more on problem solving (Fleischner et al., 1987) and can help with the understanding of place value, reversibility,


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relationships among numbers, operations, and mathematical estimates (Heddens & Speer, 1997). In an extensive review of 79 studies involving calculator use, Hembree (1986) found that when calculators were integrated into instruction, they: (a) promoted the acquisition of basic calculation skills until fourth grade, when the effect tends become a hindrance; (b) resulted in higher test scores when used as an accommodation for application and reasoning types of math problems; and (c) improved students’ attitudes and motivation toward mathematics. CAI and Math Technology offers a variety of activities for math instruction including CAI drill and practice software, and interactive videodisc programs to facilitate the acquisition to of basic skills, math reasoning, and mathematical application. Lewis (1998b) writes, “in the 1980s more software was developed for math than for any other academic skill” (p. 22). Several studies have been conducted to assess the effectiveness of CAI in math. Hughes and Maccini (1997) reviewed 21 research studies on CAI in mathematics with students having learning disabilities. The results of these studies suggest that CAI instruction appears to be effective in the acquisition of basic math skills when effective instructional design principles (Maccini & Hughes, 1997; Mastropieri et al., 1991) were employed in the program (Gleason et al., 1990; Woodward & Carnine, 1993). Moreover, substantial evidence indicates that CAI has a positive impact on students’ attitudes and motivation toward math and this impact is not because of the game-like features (Christensen & Gerber, 1990; Okolo, 1992; Watkins, 1989). For instance, Christensen and Gerber (1990) found that a straightforward drill was actually more effective than a game-like format in their student of students with and without learning disabilities. While CAI software programs are still used in classrooms, more recently technological advances have allowed for the application of videodisc technology in teaching math skills. Videodiscs and Math As technology has evolved, video-disc instruction has attracted interest among researchers and teachers as an alternative to conventional CAI. Two distinct features differentiate videodiscs from microcomputers. One is the enhanced graphic capabilities, and the other is that teachers can operate a videodisc in the same fashion as a video cassette recorder, facilitating group instruction if desired (Woodward & Gersten, 1992). Three studies were identified that directly investigated the use of videodisc technology among students with learning and behavioral problems (Bottge & Hasselbring, 1993; Kelly et al., 1986; Woodward & Gersten, 1992). In the Kelly et al. study (1986), a highly controlled videodisc program was effectively used to teach basic fractions to secondary students in remedial

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and special education classes. Scores on a criterion-referenced posttest indicated superior performance over pretest scores, and the effects were maintained over several weeks. In a follow-up to this study, Woodward and Gersten (1992) found that using 80% as an acceptable level of performance, almost two thirds of the students (64%) reached or exceeded criterion performance on the posttest. An important aspect of this study is its application to students with behavioral problems. Students were successful in their independent seatwork and on-task in academic activities at a reasonable rate. A third study used videodisc technology to teach mathematical problem solving skills (Bottge & Hasselbring, 1993). Bottge and Hasslebring investigated the effects of teaching contextualized word problems via videodisc instruction vs. teaching word problems via teacher-directed instruction. The researchers found that practice solving problems in real-life contexts (i.e. the contextualized condition) had a greater impact on students’ math performance than did the teacher-directed guided instruction condition. Bottge and Hassbring noted that this type of “anchored instruction” helped students transfer skills to new problem solving situations. Research on videodisc technology is still emerging and earlier studies offered conflicting results in terms of effectiveness. For example, Hasselbring et al. (1986) suggested that videodisc technology was no more effective than a well-trained teacher using effective instruction (as cited in Kelly et al., 1990). Moreover, Kelly et al. (1990), echo the voices of many technology researchers in stressing the importance of curriculum design in the development of technology. Current analyses of studies however, suggest that videodisc instruction involving contextualized learning appears to be promising in educating students with learning disabilities (Maccini et al., 2002). As with CAI, videodisc programs appear to also enhance student motivation and improve their attitude toward math (Woodward & Gersten, 1992). Also like CAI, principles of effective instruction should be applied to the development and utilization of videodisc technology (Hofmeister, 1986). In summary, research has helped us to determine which types of technology appear to be the most effective educational interventions for helping students with learning and behavioral disabilities meet the requirements of the core curriculum. The one underlying notion about technology in all of the academic areas that has been reviewed thus far is that principles of effective instruction must accompany technology as either part of the instruction embedded in the technology, or the teacher-directed instruction that accompanies how to use the technology, or both. Repeatedly this message appears in special education regarding the effectiveness of new and emerging technologies and instructional techniques. In short, most technological devices are as good as the instruction that accompanies them, and thus it behooves researchers to always evaluate the differential effects of good instruction vs. the technological device.


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TECHNOLOGY AND CONTENT INSTRUCTION AT THE SECONDARY LEVEL The first section of this chapter focused on the use of technology to improve or enhance basic academic skills among students with learning and behavioral disabilities. While skill improvement is undeniably a worthwhile goal, the reality is that many of these students reach the secondary level having received little effective instruction. Alternatively, some of these students may have received effective instruction but still have difficulty meeting the demands of the general education classroom. For example, in a recent study second grade children identified as “at risk” and who benefited from a research-based reading intervention, still had difficulty maintaining acceptable reading performance once back in the general education classroom (Vaughn et al., 2003). A substantial body of literature continues to suggest the fluent application of basic skills lags behind, and is difficult to remediate in students with learning and behavioral disabilities at the secondary level. Warner et al. (1980) found that the skill level of secondary students is typically between the 5th and 7th grade levels in high school and that these levels have not changed over the past twenty years (Edgar, 1987; Rock et al., 1995; Wagner & Blackorby, 1996). Moreover, as the task and setting demands change from skill-based to content-based (Sabornie & deBettencourt, 1997) there are few opportunities for students with disabilities to be able to make up these skills and students are expected to be fluent in reading, writing, and mathematics. Additionally, with the requirements of IDEA (1997) to move students with disabilities toward the requirements of the general curriculum, the presence of standards-based assessment, and limited instructional time, special educators are unfortunately being driven to abandon notions of basic skill remediation and focus on compensatory strategies and accommodations (Cartledge & Johnson, 1996). As we have seen, technology offers students at all levels, including secondary, a variety of approaches for basic skill development such as learning fractions through videodisc instruction. In a review of the literature for students with learning disabilities, Maccini et al. (2002) reported that technology also offers students at the secondary level the opportunity to acquire content knowledge and develop important skills through: (a) hypertext and hypermedia software programs; (b) multimedia software; and as discussed earlier (c) videodisc instruction involving contextualized learning. The emphasis of their review was on students with learning disabilities; however some of the studies included a small number of students with behavior disorders. As mentioned previously, hypertext and hypermedia have been shown to have a positive impact on secondary students with disabilities in learning social studies content. One other study involving students

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with both learning and behavior disorders provides additional support for interactive hypermedia software (Lancaster et al., 2002). Research on recorded texts is variable, and the results of research by Torgesen et al. (1987) are discussed below. These studies involved effective practices for teaching compensatory skills and content-based subjects.

Hypermedia to Teach a Self-Advocacy Strategy The use of hypermedia was recently applied in a study to teach students with learning and behavioral disabilities, as well as those with other health impairments, a self advocacy strategy (Lancaster et al., 2002). The goal of the strategy was to provide secondary-level special educators with a validated option for teaching students with high incidence disabilities to participate actively in the IEP and transition-planning meetings. In this study, Lancaster et al. interfaced the previously validated Self-Advocacy Strategy (Van Reusen et al., 1994) into a hypermedia environment. The strategy was taught in two treatments conditions: (a) via live teacher directed instruction; and (b) via a hypermedia platform. A third group of students received no self advocacy instruction served as a control. Upon completion of instruction, each student lead his or her own IEP conference. In general results showed that the hypermedia program was as effective as live instruction. The researchers suggested that the inherent value in these results is that the hypermedia program can provide a time-efficient method of providing critical skills to students with learning and behavioral disabilities.

Multimedia Multimedia is defined as “the combination of various medias for integration into a computer document or presentation” (Bryant & Bryant, 2003, p. 225). Several researchers have suggested that multimedia software has the potential to be a powerful tool to engage secondary students in inclusive classroom instruction (Jeffs, 2001; Maccini et al., 2002; Quenneville, 2001). However, little research has been conducted in this area and only with elementary aged children (Dauite & Morse, 1994). One important quality of multimedia use in written expression is that it enables learners to connect writing assignments, personal experiences, and a variety of ways of expression beyond the written word (Dauite & Morse, 1994; Jeffs, 2001).


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Verbatim Text Recordings Torgesen et al. (1987) conducted a series of three studies on the effects of verbatim text recordings on the comprehension of history or health topics. In all three studies the conditions were essentially the same. The students: (a) read selected content from a text; (b) read selected content and listened to it from an audiotape; and (c) listened to a selected passage from an audiotape. In experiment three, additional supports such as worksheets and highlighted portions of text were added. In general, the text recordings did produce performance gains on a comprehension test, especially when used with the worksheet compared to the read only condition. However, the overall mean test performance over the three studies ranged from 36 to 51.4%, well below the 80% criterion that was established for acceptable performance. A high correlation between IQ and the read and listen condition (0.7), suggested that effectiveness was also influenced by IQ. At present recorded texts appear to be a good supplementary intervention for secondary students who are reading well below grade level, but they should not be used as a substitute for reading instruction or without additional support to learn content area information (Torgesen et al., 1987).

Graphic Organizers One popular software program, Inspiration (2000) has recently been investigated by two groups of researchers with different questions. Sturm and Rankin-Erickson (2002) used Inspiration in a study that evaluated the effects of hand-drawn and computer-generated concept mapping on the expository writing of middle school students with learning disabilities. Three treatment conditions were used in a within-subjects repeated measures design: (a) no-map support; (b) handwritten map; and (c) computer map support. All students received instruction on mapping, but in the no-map support conditions students were not required to map as part of the writing process. Results indicated that the essays of students in all three conditions significantly improved in terms of number of words, number of T-units and holistically, over baseline data. The fact that some students in the no-mapping condition improved suggests that there was some carry over effect from the writing instruction thus it is difficult to determine the effects that were specifically a result of the software program. The researchers stated that the students’ attitudes were significantly more positive about writing when using the computer-mapping conditions than when writing in other conditions. In another study, Inspiration was used to organize world history textbook content into a graphic, spatially oriented template (Mastropieri et al., 2002, 2003). Two

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groups of tenth-grade students with learning disabilities were assessed on their content knowledge, after one group used their spatial organizers to take notes and the other group received traditional instruction without any spatial organizer. Results indicated that students learned significantly more world history content when using the spatial organizer. These studies provide initial support for a software program that allows students to create spatial organizers for both writing and learning content at the secondary level in ways that will help them progress toward general education standards.

TECHNOLOGY AS A TOOL FOR ASSESSMENT In this era of standards-based reform much of the emphasis in education is on assessment of student progress. Assessments are no longer just a part of classroom instruction, but an integral part of IEP monitoring and state and federal accountability measures. Moreover, curriculum based assessment (Deno, 1985) may become a key tool for determining eligibility for special education for students with learning disabilities (Vaughn & Fuchs, 2003). In this section the reader is introduced to the role technology is playing in these various assessments.

Computer Based Testing With the deluge of tests that teachers and administrators are required to process, coupled with the permanent arrival of advanced electronic technology it is no surprise that many test developers are changing test formats from paper-pencil to computer. Computer based testing provides the medium to resolve many issues related to large scale tests. These include more efficient test administrations, the availability of immediate results, student preferences for this type of testing (i.e. instead of paper-pencil tests), and the possibility for built in accommodations (Thompson et al., 2003). Thompson et al. (2003) however, describe numerous concerns regarding computer based test formats. These include, but are not limited to: (a) more demands on computer related skills such as typing and mouse navigation; (b) the possibility of fatigue related to reading from a computer screen for long periods of time; (c) concerns with unfamiliarity with computer based test taking; and (d) basic research questions related to whether the medium (computer vs. paper-pencil) of test presentation affects the comparability of the tasks students are being asked to complete. Research is just beginning to emerge in this area. One study compared the test performance of 72 middle and high school students on computer-based vs.


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pencil-paper tests (Horton & Lovitt, 1994). The participants included 13 students with learning disabilities, 16 remedial students, and 43 normally achieving students in science and social studies classes. The researchers determined that overall there were no differences between the students’ performance on the two types of assessments, though some students performed better when answering factual questions on the computer. Additionally there were no differences on the two assessments between students with and without learning disabilities. Keene and Davey (1987) assessed the differential effects of computer-displayed text vs. reading from a printed page on the reading comprehension of 52 high school students with learning disabilities. Other outcome measures included strategic behaviors, attitudes toward reading, and task-completion time. The results indicated there were no differences in students’ comprehension of material based on the reading conditions. However, students who took the reading comprehension test on the computer tended to look back at test items more frequently than non-computer users. The area of testing and persons with disabilities is rapidly emerging and over the next few years we will likely continue to see numerous studies to assist test developers in creating tests that are thoughtfully designed with respect to the differences among test takers and the nuances of computer-based testing.

Curriculum-Based Assessment (CBA) Establishing acceptable criteria for learning disabilities identification historically has been the single most controversial issue in the field of learning disabilities (Vaughn & Fuchs, 2003). Presently, the field is questioning the efficacy of how we identify students with learning disabilities, and as an alternative considering how a student responds to instruction and intervention as the key factor (Fuchs & Fuchs, 1998). Curriculum-based assessment has been determined to be the best method to measure response to treatment and intervention under this new framework for learning disabilities identification (Vaughn & Fuchs, 2003). While researchers have tried for years to bring CBA into classrooms with the purpose of measuring progress toward IEP goals, general education curriculum, and effectiveness of everyday instruction, this new framework has catapulted CBA into the forefront of special education assessment (Deno, 1985; Good & Jefferson, 1998; Hamilton & Shinn, 2003; Marsten, 1989). It is possible that the notion of daily or weekly assessments was unfathomable to special teachers and this is what has kept this form of assessment out of many special education classrooms for years despite substantial research regarding its utility and validity (Good & Jefferson, 1998; Hamilton & Shinn, 2003). Recently

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however, many on-line products and services have been developed to assist teachers in implementing CBA in a simple and efficient manner. One program, AIMSWEB (www.aimsweb.com) was designed by Mark Shinn, to measure and monitor early literacy measures, reading, and spelling through on-line CBA. The website provides tests, results, graphs, and continuous formative assessments via on-line data collection. Another example of a well-developed web-based program for teachers to implement CBA allows an individual to enter any student’s probe data and make progress monitoring graphs (www.interventioncentral.org). Probes are available on-line for reading and math in Spanish and English. New technological tools such as these will likely enhance the feasibility of using CBA on a regular basis in both general and special education classrooms.

UNIVERSAL DESIGN FOR LEARNING Universal Design is a concept that emerged out of architecture from the desire to create space that would be accessible to all individuals (Mace, 1988). Mace underscored that the principle of Universal Design was not to design for individuals with disabilities per se, but for a wide range of individuals who might benefit from the same types of access. For example a woman with a baby stroller might need to use the same curb cut that a wheelchair user needs. Universal Design for Learning (UDL) is the design of instructional materials and activities that allow the learning goals to be achievable by individuals with wide variation in their abilities to see, hear, speak, move, read, write, understand English, attend, organize, and remember (Orkwis & McLane, 1998). The primary premise behind UDL is injecting flexibility into the materials and methods used in the classroom since no single representation of information is ideal, or even accessible, to all learners (Rose & Meyer, 2000). Universal design for learning encourages educators and textbook developers to build flexibility into the instructional design of textbooks, software programs, and all curricular materials at the onset rather than retrofitting. For example, instead of districts ordering textbooks and then locating sources to have the books put onto tapes or CDs, textbook developers should provide alternative options to the text from the onset. Universal Design for Learning encourages educators to consider the electronic flexibility of the materials and methods used in an educational environment at the planning stage of every school year (Rose & Meyer, 2000). According to the Center for Applied Special Technology (CAST), digital format is the most flexible means for presenting curricular materials because it is


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easily changed from one medium to another, customizable for individual needs, and is recordable. Representatives of CAST espouse three essential qualities of UDL. These are that the curriculum provides multiple means of representation and presentation; expression, and engagement. Interestingly, UDL is not solely a technological paradigm but because of the tremendous contribution electronic technology makes to the flexibility of text, there is a strong focus of technology in UDL. Universal Design for Learning is important to students with learning and behavioral disabilities in at least two ways. For one, as it gains in popularity, UDL has the potential to influence academic publishers to provide more options for students to access text. For many students this may open new doors to achievement. Secondly, the paradigm encourages both general and special educators to look beyond limitations related to disability and to consider how instruction might be adapted to benefit the wide range of diverse learners in today’s classroom. Already, principles of universal design have started to be applied to test development in an effort to reduce test bias for diverse learners (Thompson & Thurlow, 2002). Thompson and Thurlow (2002) explain, “Universal design is based on the same ethics of equity and inclusiveness that are expected for people with disabilities and others in schools, communities, and on the job – an ethic that values differences in age, ability, culture, and lifestyle” (p. 2).

SUMMARY The application of technology to improve the quality of life and educational outcomes for students with learning and behavioral disabilities has progressed a long way in the past twenty years. Perhaps the biggest benefit of technology in the lives of students with disabilities and the teachers that work with them is that practically everyday technology gives us the opportunity to take the principles of effective instruction and embed them into more efficient delivery systems. Ultimately this gives us a greater number of methods with which to meet the academic needs of students who do not learn easily. Researchers in the field of special education have provided us with many studies to draw upon when making educational decisions, and numerous opportunities exist for more studies as technology evolves. Specifically a dire need exists to include more students with behavioral disabilities in studies on technological interventions. In light of the fact that students with behavioral disabilities are a high incidence disability, it is disturbing that more studies do not include these children and adolescents. The characteristics of students with learning and behavioral disabilities do not overlap entirely, and there is a paucity of literature on how technology can help students with behavioral problems.

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On a larger scale, UDL encourages us to continue to evaluate the effectiveness of technology with a larger and diverse population of learners. The value of this paradigm among a population that is only increasing in heterogeneity is clear. Still we must guard against the appeal of moving into an educational approach before research confirms its efficacy. Continued research in technology can help us evaluate and choose the next steps. Presently, various technologies have helped students achieve and enjoy the learning process. We have learned a great deal about “what works” for students with learning and behavioral disabilities since technology has entered the classroom.

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THE EFFECTS OF TEACHER LICENSURE ON TEACHERS’ PEDAGOGICAL COMPETENCE: IMPLICATIONS FOR ELEMENTARY AND SECONDARY TEACHERS OF STUDENTS WITH LEARNING AND BEHAVIORAL DISABILITIES André A. Nougaret, Thomas E. Scruggs and Margo A. Mastropieri ABSTRACT This chapter provides a comprehensive review of research literature on teacher licensure and teacher competence. Since little research is available on teachers of students with learning and behavioral disabilities, a review of the general education literature is undertaken to provide implications for research in special education. Finally, a review of a recent study of special education teachers is provided. Implications are drawn for both elementary and secondary teachers of students with learning and behavioral disabilities.


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A severe national teacher shortage is predicted for the upcoming decade. According to June 1998 figures from the National Center for Educational Statistics, the nation’s public school teaching force will grow from 2.7 million in 1998 to more than 3 million in 2008. Most new teachers – roughly five out of six – will be needed to replace retiring teachers hired during the baby boom school years. It is estimated that between 150,000 and 200,000 teachers a year may be leaving the profession, further exacerbating the projected teacher shortage (Hardy, 1998). The fall 1997 back-to-school report on demographic trends from the U.S. Department of Education projected that to keep pace with increased teacher demand, two million new elementary and secondary teachers will be needed in the next decade (Hardy, 1998). That fewer and fewer teachers are graduating from traditional teacher preparation programs compounds the problem. For example, Dr. Jo Lynne Demary, Virginia Superintendent of Public Instruction, recently stated that the projected number of new teachers needed for Virginia schools for 2000–2001 was 7,604. Significantly, however, Virginia colleges and universities were projected to graduate fewer than 4,000 teachers from their teacher preparation programs in 2000, down from 4,249 in 1996. As noted by Dr. Demary, all of those graduates will not be available to teach in Virginia since many return home to teach or decline to start a teaching career immediately (“Report on Supply,” 2000). The need for more teachers is also driven by increasing student populations. According to demographer predictions, the peak will come by 2006 when U.S. schools are expected to enroll more than 54 million children, a dramatic increase since the mid-eighties when enrollments were around 38 million (Walters, 1998). The task of recruiting such large numbers of teachers is even more challenging in the field of special education. More than five million children have been identified as having a specific disability, including autism, mental retardation, cerebral palsy, or a learning disability that requires specialized instruction (Crutchfield, 1997). In order to address the special needs of these children, schools and parents rely upon specially trained individuals to help them. In the daily lives of children with disabilities, special educators play a key and indispensable role (Mastropieri & Scruggs, 2000). Boc et al. (1998) investigated the licensure status of nearly 50,000 special and general education teachers and documented a chronic annual shortage of fully licensed teachers in special education, a level that was almost twice the number in general education. The fact that record numbers of licensed special education teachers are leaving the field exacerbates the problem (Brownell & Smith, 1992). According to remarks from teachers and administrators, excessive paper work, difficulty keeping up with changing laws, and emotional and behavioral problems of students are “driving thousands of special education teachers to transfer into

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regular education or leave the profession altogether” (Sack, 1999, p. 14). The pressures of the job of a special education teacher can drain even the most dedicated teachers (Carter & Scruggs, 2001). According to Sack (1999), “grappling with complicated federal mandates, conflicts with parents, overcrowded classrooms, and paper work take away time needed for instruction and lesson planning, contribute to teacher burnout, and are becoming major disincentives for those considering the special education field as a career” (Sack, 1999, p. 14). The teacher shortage has many states considering alternative routes to licensure to help insure that each classroom will have a “qualified” teacher, with most states now implementing some type of alternative certification (Bradshaw, 1998, p. 10).

ALTERNATIVE LICENSURE Much has been made in the last fifteen years of the need for more and better qualified teachers. During this same time, alarms have sounded signaling concern over the shortage of teachers in our public schools. The teacher shortage initially predicted in the mid-1980s has become a reality. Alternative means of bringing individuals into the teaching profession is a growing phenomenon designed, in part, to address the teacher shortage issue. There are, the argument goes, a great number of potentially good teachers who did not earn teacher certification as undergraduates but now as more mature adults want to teach. Military retirees, second-career seekers, empty-nest housewives, downsized professionals, and recent college graduates are viewed as untapped resources (Zumwalt, 1996, p. 40; see also Paige, 2002).

By law, all teachers within the United States must have a license in order to teach. The responsibility for licensing teachers is the prerogative of each state. Each state has licensing requirements for teaching each subject area and grade level. “The role of teacher certification is to ensure for the benefit of the public that candidates for teaching are adequately prepared and safe to practice the profession” (Williamson et al., 1984, p. 3). Rozycki (1999) concluded, “licensure procedures and the consequent restricted access to jobs are the price the public pays for confidence that some pre-selection process is weeding out the most grossly incompetent and unsuited” (p. 11). Given present problems with teacher shortages, teacher attrition, and insufficient numbers of graduates from teacher education programs, alternative routes to licensing teachers is perceived as a way of getting more teachers licensed more quickly. McKibbin and Ray (1994) defined alternative licensure as “. . . any systematic teacher preparation program that departs from the traditional foundationspedagogy-student teaching model” (p. 201). Stoddart and Floden (1995) explained,

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alternative routes do not involve enrollment in a college-based program. Typically developed and administered by state departments of education or school districts, these alternate route programs give college graduates a short period of preservice training, then provide continued training and support during their first year on the job (p. 6).

Adelman (1986) defined alternative licensure programs as “those teacher education programs that enroll unlicensed individuals with at least a bachelor’s degree offering shortcuts, special assistance, or unique curricula leading to eligibility for a standard teaching credential” (p. 2). One form of alternative licensure that has been prevalent in almost every state is known as “emergency” licensure. This practice allows school districts to hire unlicensed individuals for a defined period of years. Fiestritzer (1993) noted that, “emergency certification usually involves teaching right away, with no orientation or instructional support, while taking education courses at night and during the summer” (p. 20). This lack of preservice training of any kind separates emergency licensure from most other alternative licensure programs. With the increase of identified special education students and a documented decrease in the number of special education teachers available, it is no wonder that states are seeking alternative means to attract potential special education teachers. Nevertheless, the degree of competence demonstrated by teachers with no pre-service training is necessarily a matter of concern. The most extreme view of alternative licensure was recently expressed by Secretary of Education Rod Paige, when he suggested that little more was required of new teachers than high verbal skills and solid content knowledge (Paige, 2002). According to this view, pedagogical knowledge of the type conveyed in traditional teacher education programs would be of little or no value; therefore, teachers on emergency provisional licensure might be expected to perform as well or better than traditionally licensed teachers (see also Walsh, 2001).

PREVIOUS INVESTIGATIONS OF ALTERNATIVE LICENSURE COMPARATIVE STUDIES Earlier Comparative Studies of Alternative Licensure Several early studies that took place in the 1960s and 1970s compared the effectiveness of provisionally licensed and regularly licensed teachers. Greenberg (1983) provided an overview of these early studies. Beery (1960) conducted a direct comparison study, involving a sample of 76 pairs of emergency and regularly licensed teachers. Trained observers were used to compare teaching performances. Beery (1960) concluded that the fully licensed beginning teachers were consistently rated to be more effective than the provisionally certified teachers.


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Bledsoe et al. (1967) investigated five groups of randomly selected beginning teachers in both licensure categories, and concluded that certified teachers were more competent in general, and specifically more competent in several skill and behavior areas. Copley (1975) compared stratified samples of three groups of beginning teachers: teachers with liberal arts degrees and no education training, teachers with some education courses but no student teaching, and teachers who had completed a degree in education including student teaching. Teachers in the fully trained group were rated higher by principals using a common instrument in six areas, including effective communication skill use, classroom management, fairness in relations with pupils, and effective teaching results. Evertson et al. (1985) also discussed these earlier comparative studies. They described these early observational studies as being somewhat weak in design in that they did not account for background and/or context variables possibly accountable for differences in teacher effectiveness as reported. The weaknesses in the research, however, did not overshadow the pervasive findings which revealed the positive results of formal teacher preparation. In all but two of the studies, regularly certified teachers rank higher in effectiveness than teachers with less formal training (p. 3).

Although expressing some concern for the “staying power” of strategies developed and learned within teacher education programs, the authors concluded that “teachers who participate in preservice teacher preparation programs are more likely to be (or to be perceived by administrators as) more effective than teachers who have little or no formal training” (Evertson et al., 1985, p. 4).

More Recent Comparative Research Hawk and Schmidt (1989) examined the differences between science and math teachers prepared through either a traditional teacher preparation curriculum or a lateral entry (alternative) licensure (LEP) program, which involved a year of academic and field-based study. LEP participants had prior academic preparation in one or more of the basic sciences or math and had no prior teaching experience. All but one of the five functions on observational ratings favored the traditionally prepared teacher candidates. The “instructional monitoring” function displayed the greatest percentage difference. Twenty-three percent more LEP participants than traditionally prepared teachers obtained an above standards rating. In an earlier study, Hawk et al. (1985) examined the differences between 36 secondary mathematics teachers who held teacher licensure in mathematics (“in-field”), or who held some other licensure (“out-of-field”). In this study, all participants had some form of teaching licensure; however, the out-of-field

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teachers were not licensed in mathematics. It was reported that in-field teachers scored significantly higher on the “instructional presentation” portion of the observational instrument. In addition, students of in-field teachers scored higher in math achievement. Hutton et al. (1990) compared the classroom performance of 98 alternatively licensed interns with that of 62 traditionally licensed first-year teachers. The alternatively licensed group had at least a bachelor’s degree, a 2.8 GPA, successful completion of a 150-word essay, and a successful interview; but did not have teaching credentials. After involvement in an intensive one-month training program, interns assumed the role of teacher. Each intern was assigned a teacher advisor who served as a mentor and worked in cooperation with supervising teachers who were assigned by the building principal. Traditionally licensed teachers were not observed, so direct comparisons of teacher behavior were not possible. Teacher advisors did, however, compare interns to traditional first-year teachers by completing a rating form, comprised 50 performance-related items. Results revealed that all but one alternatively licensed intern were rated “satisfactory” or above, and the majority of the interns (62%) were rated as “exceptional” or “clearly outstanding.” The interns compared favorably to traditional first-year teachers on all 50 items, receiving “superior” or “very superior” on many of the items. Hutton, Lutz, and Williamson concluded, “Almost all (91%) were rated to perform as well as, superior to, or very superior to the typical first-year teacher. Almost half of the interns were rated as superior or very superior” (Hutton et al., 1990, p. 46). Sandlin et al. (1993) explored the differences between 66 beginning teachers and 58 intern teachers during their first year of teaching at the elementary level. All of the beginning teachers had just recently completed a traditional teacher preparation program. Intern teachers were involved in a formal alternative licensure program, which involved a prior two-year paid field experience, with continued training and support while in a salaried classroom teaching position. Reviewers with experience in the supervision of teachers visited the subjects’ school sites and conducted on-site observations during the school year (fall, winter, and spring). There were several statistically significant differences noted in the performance of the two groups at the beginning of the school year, which favored the interns. However, the end of the school year assessment yielded no classroom management or instructional differences between the two groups. The fact that intern teachers started the year with an advantage in experience may have influenced the study results. Miller et al. (1998) conducted an observational study of 82 alternatively and traditionally licensed teachers. The alternative teachers all had bachelor’s degrees and had been placed in the classroom after having completed 9–15 semester hours


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of teacher preparation course work. All continued to take course work toward licensure while teaching. Each of the teachers had been teaching for three years. Two licensed teachers served as observers, and observed each teacher on one occasion. An analysis of variance revealed that the two groups did not significantly differ on any of the teaching dimensions surveyed. Alternative licensure did not lead to inferior practice among teachers evaluated three years into their careers. Guyton et al. (1991) investigated the attitudes and self-efficacy of 23 alternatively licensed and 26 traditionally licensed beginning teachers over the course of a school year. In addition, the teachers were evaluated by an administrator or a mentor using a form comprising 15 items, including use of classroom time, enthusiasm, and an overall rating of teacher performance. Findings revealed no significant differences between scores for the two groups of teachers at any point in the school year. Teaching performance at the beginning and end of the year was not significantly different for the two groups, nor were there differences in their own perceptions of their teaching and problems faced during their first year. Guyton et al. (1991), concluded, “findings from this study generally support the contention that condensed pedagogical preparation and a supervised internship are a reasonable alternative to traditional teacher preparation” (p. 7). Most recently, Laczko-Kerr and Berliner (2002) studied 293 teachers in grades 3–8. Half of the sample held traditional licensure, while the other half held emergency or alternative licensure, including Teach for America participants. Teachers were matched for school district, grade level, and years of teaching experience. Results indicated that students of traditionally licensed teachers scored about 20% better on tests than students of teachers who did not hold traditional licensure. Some general conclusions can be drawn from research which compares traditionally and alternatively licensed teachers. Although some alternative pedagogical preparation programs, which included systematic pedagogical coursework and supervised teaching experiences, have resulted in teacher ratings not statistically different from those of teachers from traditional licensure programs, traditionally licensed teachers have generally outperformed teachers with little or no systematic alternative preparation (see also Darling-Hammond, 2001).

Studies Conducting Analyses of Pre-existing Data Sources Some investigations have examined pre-existing data sources. Monk (1994) examined data from 2,829 students from the Longitudinal Study of American Youth, and noted that coursework in teachers’ subject area is positively related to student achievement in mathematics and science. However, Monk concluded that the relationship is curvilinear, in that student achievement peaks after a threshold level

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of teacher preparation (e.g. five courses in mathematics). It was also reported that teacher education courses were also associated with student learning in mathematics, greater than additional subject area preparation. Goldhaber and Brewer (2002) examined data from the National Educational Longitudinal Study of 1988 on 12th grade math and science teachers. Using regression procedures to account for the fact that uncertified teachers had students with lower SES, lower test scores, and more single-parent households, Goldhaber and Brewer concluded that students of teachers holding some sort of in-field certification outperformed students of teachers not certified in their subject area (cf. Hawk et al., 1985). It was also concluded that students of teachers with out-of-field certification did not outperform students of teachers with emergency certification. Druva and Anderson (1983) conducted a meta-analysis of 65 studies investigating relationships between teacher characteristics and teacher behaviors on student achievement in science. They reported that principal and student ratings of teachers were most strongly related to number of education courses. In addition, teacher effectiveness was found to be associated with both preparation in science and coursework in education.

Studies Employing Interview or Questionnaire Data The remaining studies presented data derived from an interview or questionnaire. McDiarmid and Wilson (1991) investigated the subject matter knowledge and pedagogical content knowledge of alternatively licensed beginning math teachers. All 55 study participants had an undergraduate degree in mathematics and had not participated in any form of teacher preparation training. The researchers gathered data through the use of a comprehensive questionnaire and a highly structured interview. The interview was designed to complement the questionnaire and consisted of a series of teaching scenarios. The results of the study suggested that many of the participating alternatively licensed teachers could not make connections within the subject matter. These teachers appeared to rely on an older view of mathematical competence that depended on memorization and a mastery of rules. When asked to explain “why” or the reasons behind the rules they were often unable to do so. The authors concluded that “subject matter knowledge is not sufficient, because teaching requires that teachers transform the content into representations that help students develop understanding” (McDiarmid & Wilson, 1991, p. 101). These conclusions were supported more recently by a dissertation by Critchfield (2001). In that investigation, 40 algebra teachers were administered a test in algebra skills and


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knowledge, and results were compared with student achievement in algebra. No relation between teacher knowledge of algebra and student achievement in algebra was observed across the sample of teachers. Jelmberg (1996) conducted a comparative investigation of traditionally prepared and alternatively prepared elementary and secondary teachers (N = 236). Both groups of teachers had been teaching for at least two years. The alternatively prepared teachers had an average of three years’ more teaching experience. On principals’ surveys in areas related to pedagogical competence, the traditionally prepared teachers were rated significantly higher in instructional skills and instructional planning. Almost without exception, principals rated teachers from teacher education programs more favorably in all areas. Jelmberg (1996) concluded, “these findings suggest that experienced teachers who have undergone preparation through college-based teacher education programs are better performers than experienced teachers from state-sponsored alternative programs” (p. 63). Houston et al. (1993) conducted a two-year study of first-year teachers, which included an analysis of the perceptions of first-year teachers who had completed a traditional teacher education program (CETS, n = 69) and those who were being prepared in an alternative licensure program (ACTS, n = 162). Study participants completed a questionnaire in November, after two months of teaching, and again in April, after eight months in the classroom. The questionnaire was designed to address three areas: problems encountered, assistance received, and level of confidence and satisfaction. The area of “problems encountered” was particularly relevant. Results revealed that after two months of teaching, “the mean rating of problems encountered by alternatively certified elementary teachers was greater in all 14 areas than those of the certified elementary teachers. ACTS perceived significantly greater problems than CETS in student motivation, managing teacher time, the amount of paperwork, school administration, lack of personal time, and grading students” (Houston et al., 1993, p. 81). It was interesting to note that six months later, after eight months of teaching, the differences between the two groups in the perceived importance of problems had virtually disappeared. Similarly, traditionally and alternatively licensed special education teachers rated their administrative needs similarly in a survey by Balfour (2001). Knight et al. (1991) investigated the perceptions of 338 elementary and middle school students of their classroom learning environment and student outcomes. Students completed a classroom inventory that addressed 11 specific areas: satisfaction, friction, difficulty, cohesiveness, competitiveness, cooperation, lower-level thought processes, higher-level thought processes, pacing, parent involvement, and assignment of homework. Significant differences were observed for five of the eleven individual classroom environment scales. Knight et al. (1991) concluded,

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Students in classes of traditionally certified teachers perceived significantly more instruction and opportunities to engage in higher thought processes than students in alternatively certified classes. Furthermore, students in traditional licensure classes perceived that their teachers moved them through classwork at a significantly more appropriate pace than students in classes of teachers certified in alternative programs. In addition, students in classes of traditional licensure teachers also perceived significantly more group cohesiveness and cooperation among students, while students in classes of alternative licensure teachers reported significantly more friction (p. 32).

Martin and Shoho (1999) investigated the differences in classroom management practice/style among traditionally prepared teachers and alternatively prepared teachers. An instrument designed to measure teachers’ perceptions of their classroom management beliefs and practices, was administered to 228 teachers. The majority of the teachers (approximately 62%) were enrolled in an alternative licensure program. Few statistical differences were observed between alternative licensure teachers and those prepared by traditional methods in regard to the facets of classroom management. Alternatively licensed teachers scored significantly more interventionist (controlling) on the scale than their traditional counterparts.

SUMMARY OF PREVIOUS RESEARCH Over the years, a number of studies have investigated the relative effects of traditional and alternative teacher licensure, using a variety of methods, including direct observation, student achievement, surveys, interviews, and administrator ratings. A wide variety of alternative programs was investigated, from little or no preparation to systematic and rigorous alternatives. A review of this research suggests that, overall, traditional licensure programs exert a positive influence in teacher performance, particularly when teachers from traditional licensure programs are compared with teachers with little or no alterative preparation (see also Darling-Hammond, 2000a, b, 2001, 2002; Darling-Hammond, Wise & Klein, 1999). This view, however, has been contested. A recent review sponsored by the Abell Foundation (Walsh, 2001) reviewed research on the effects of teacher certification. This review went to great lengths to criticize existing research in the area, suggesting that virtually all studies providing evidence for the value of traditional teacher licensure were flawed. These flaws were said to include the lack of currency of some studies, methodological problems, failure to use student achievement as a dependent variable, and inclusion of doctoral dissertations. Interestingly, in a review clearly slanted against traditional preparation teacher education programs, the focus was on identifying flaws with existing research in support of teacher licensure, rather than on identifying strong


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support from the literature for alternatives. Instead, Walsh cited research from other fields suggesting that verbal ability was the most important variable in effective teaching. This review was critiqued by Darling-Hammond (2002), who maintained that many inaccuracies and misinterpretations of research can be found in the report, and restates the general finding of the positive effects of teacher licensure. Nevertheless, there is a need for further research to evaluate the effects of traditional and alternative licensure programs in a variety of contexts. To the point of the present review, research is needed to compare the performance of traditionally and alternatively licensed special education teachers. Until recently, such research had not been identified. Research on special education teacher education programs is of interest because of the absence of a specific academic “content” domain in special education, and because of the specific pedagogical skills that are typically covered in licensure programs (Mastropieri & Scruggs, 2000). Such research is also important because of the significant national need for special education teachers and the number of limited or emergency licenses that are presently being awarded.

RESEARCH ON SPECIAL EDUCATION TEACHER PREPARATION PROGRAMS In contrast to a relatively substantial amount of research on the effectiveness of teacher licensure programs in general education, there has been a more limited amount of research relevant to special education licensure programs. Lyon et al. (1989) surveyed elementary grade general and special educators, and concluded that most teachers reported their licensure programs had not provided effective instruction, either in didactic or practicum settings. Tingey-Michaelis (1985) reviewed literature related to training of intervention agents in early intervention programs as part of a larger literature review on effectiveness of early intervention (Casto & Mastropieri, 1986). Tingey-Michaelis (1985) concluded that programs with certified intervenors were significantly more effective, with respect to student progress, than programs without certified intervenors. However, it was not always clear what was meant by certification in the studies reviewed. Balfour (2002) surveyed first year special education teachers with or without traditional special education teacher licensure regarding their expectations of administrative support in light of support they actually received. Licensed and unlicensed (or holding emergency licensure) special education teachers did not differ significantly on perceptions of administrative support, suggesting unlicensed teachers did not perceive a need for more administrative support than did first year teachers holding traditional teacher licensure. However, both groups

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reported receiving significantly less administrative support than they perceived they needed. Perhaps most directly relevant to the issue of the effectiveness of special education teacher licensure programs is a recent study by Nougaret, Scruggs & Mastropieri (in press), which is reviewed in detail here. Nougaret et al. compared the pedagogical skills of two groups of first-year special education teachers. One group of teachers had recently completed a formal teacher preparation program, while the other group of first-year special education teachers had not completed a traditional teacher preparation program, and were teaching while undertaking traditional licensure programs. As the alternatively licensed teachers in this investigation had been granted emergency provisional licensure, and had had only limited exposure to traditional teacher education, Nougaret et al. (in press) also provided insights on the value of traditional teacher education, compared with teachers with little or no formal training. A sample of 40 beginning special education teachers hired for the 2000–2001 school year was selected for this investigation. Twenty teachers were traditionally licensed had successfully completed a state-approved college or university special education teacher education program, including student teaching. Twenty other first year special education teachers had completed a bachelor’s degree in an area other than education, and had been granted emergency provisional licensure by the state. These teachers were currently enrolled in a licensure program, having completed no more than two classes (6 credit hours) toward licensure. Fifteen teachers were selected from elementary schools, while, 16 teachers were selected from middle schools, and nine teachers were selected from high schools. Thirty-six of these teachers were working with students with either learning disabilities or emotional disturbance. Additionally two teachers were working with early childhood special education students, and two teachers were working with students with mental retardation. Traditionally licensed and alternatively licensed teacher groups did not differ significantly in relative proportion of disability categories taught or age levels. Nougaret (2002) employed observational ratings of teacher performance in several domains in his investigation, rather than measures of academic achievement. However, in this case measures of achievement may have been meaningless since the special education teachers taught students from a variety of age and grade levels, in a variety of subjects, and from a variety of disability areas. Rather, students were evaluated by an outside observer unaware of licensure status using a highly reliable and valid measure of teacher competence (Danielson, 1996). It was felt that direct observational measures of teacher performance would be more closely related to teacher education programs, and could not be influenced by students’ learning histories. The measures that were employed were derived from The


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Framework for Professional Practice developed by Charlotte Danielson (1996), and evaluated teacher behavior known to be associated with student achievement in both general education (e.g. Brophy & Good, 1986) and special education (e.g. Mastropieri & Scruggs, 2002). The teachers were observed by a retired administrator with extensive experience observing and evaluating teachers, who was unaware of licensure status of the teachers. In all cases, teachers were observed teaching a primary content (e.g. math, science, English/reading, social studies) or developmental area (e.g. fine/gross motor, language, cognitive). Data were collected in special education classroom settings, ranging from five to eight students in size. The observer visited each teacher twice during instructional periods, and recorded all behaviors/activities as displayed by the teacher while in the classroom during both visits. The observer recorded only those teacher behaviors/actions observed. The observer also reviewed students’ artifacts and the teacher’s planning document. Review of such artifacts and planning documents were important in assessing specific components. When the two classroom observations had been completed, the observer reviewed and analyzed all scripted notes and completed an observation protocol representative of each teacher participant. A number score (1 – Unsatisfactory, 2 – Basic, 3 – Proficient, 4 – Distinguished) was assigned to each element of the rating scale. Each teacher participant also was asked to complete a survey, in which they rated themselves on the same variables being evaluated by the observer. Results indicated that traditionally licensed teachers statistically (and substantially) outperformed teachers with emergency licensure on each of the three observational measures, planning and preparation, classroom atmosphere, and instruction. The effect sizes associated with these outcomes ranged from 1.57 to 1.68 standard deviation units, revealing a striking difference between the groups of teachers, such that an average (50th percentile) traditionally-licensed teacher would have scored at around the 90th percentile of the alternatively-licensed group on each of the measures of teacher effectiveness. This strong advantage for the traditionally licensed teachers was evidenced on both the elementary and secondary levels. In sharp contrast to the observational ratings, teachers in both groups rated themselves similarly. This finding suggests that alternatively licensed teachers were not aware of their own pedagogical shortcomings, which seems likely since this group had not formally studied pedagogical methods. These findings support earlier studies that reported that traditionally licensed and alternatively licensed teachers evaluated themselves as similarly competent (Balfour, 2001; Houston et al., 1993; Martin & Shoho, 1999), although external ratings may reveal sharp differences.


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DISCUSSION A statement was recently made by Secretary of Education Rod Paige that suggested that traditional teacher education programs may be unnecessary, maintaining that, “we now have concrete evidence that smart teachers with solid content knowledge have the greatest effect on student achievement” (Paige, 2002). This argument leaves several issues unaddressed, however. First, the argument suggests there is no demonstrated relationship between teacher pedagogical behavior and student achievement (e.g. Brophy & Good, 1986; Rosenshine & Stevens, 1986), that was the basis of Danielson’s (1996) Framework for Professional Practice. Such pedagogical behavior, demonstrably important for effective teaching, is not taught in subject matter classes, but rather is the domain of teacher education programs. Additionally, in its emphasis on “solid content knowledge,” the argument does not acknowledge that research has failed to demonstrate a consistent relation between teacher content knowledge and student achievement (e.g. Monk, 1994). Hawk et al. (1985) reported that student mathematics achievement was higher with teachers licensed in mathematics; however, both groups of teachers had been through teacher licensure programs. Critchfield (2001) found no relationship between teacher knowledge of algebra and student achievement in algebra, in a sample of 40 algebra teachers (see also Darling-Hammond, 2002, for a discussion). It could well be that “content knowledge” bears a curvilinear relationship with teacher effectiveness; that is, a certain degree of content knowledge is necessary for effective teaching, but extensive knowledge going well beyond what students are expected to learn is not necessary, and may be less important than significant pedagogical skills. Finally, and most relevant to the present discussion, Paige’s argument does not specify the “content” of which special education teachers are expected to have solid knowledge. For most special education teachers, instilling basic skills, basic content knowledge, and appropriate social behavior in their students are the most important “content.” However, the greatest challenge often resides in identifying and employing the most effective instructional methods for improving student performance in these areas. When first year teachers were observed for these effective instructional methods, Nougaret et al. (in press) reported that licensed teachers greatly outperformed teachers on emergency licensure, on observational ratings of planning and preparation, classroom environment, and instruction. In sharp contrast to observational ratings, teachers in both groups rated themselves similarly. Several implications from the present review seem relevant to schools developing strategic plans to support first year special education teachers. First, beginning special education teachers holding alternative licensure may be at


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a great disadvantage relevant to pedagogical competencies. This conclusion is drawn from the research literature in general education, and specifically from the study by Nougaret et al. (in press), in which it was also found that teachers did not rate themselves differently. The areas evaluated in that investigation, planning and preparation, classroom atmosphere, and instruction, are covered by the Council for Exceptional Children’s standards for teacher education, and are components of most traditional special education teacher education programs accredited by the National Council for the Accreditation of Teacher Education (NCATE). On the other hand, alternatively licensed teachers, who have not encountered these standards, may be less aware of the competencies needed for effective teaching. These alternatively licensed teachers may not be able to assess teaching abilities that they do not know should exist. The results of the present review underscores the tangible value of teacher education programs in promoting effective teaching practices, and call into question the competence of beginning teachers with no formal teacher training. Although it does appear that systematic alternatives to teacher licensure – which contain systematic instruction in pedagogical skills and applied practicum experiences – may be valuable, most research agrees that traditional teacher education is preferable to little or no systematic training. With respect to special education, training also must include techniques for identification, assessment and measurement; characteristics of various disability conditions and implications for instruction and treatment; and study of legal and foundational aspects of special education. When these are combined with training in curriculum and instructional methods and supervised teaching experiences, it seems clear that any alternative licensure programs, to be effective, must be very much like traditional programs. The present review suggests that teacher licensure is an important requirement for effective instruction (although it does not guarantee effective teaching), on both the elementary and secondary levels, for both general and special education teachers. Although demands differ in elementary and secondary programs, and in general and special education, all teachers appear to require appropriate training in instructional methods. Hawk et al. (1985) provided evidence that specific licensure may be needed for specific secondary subjects (e.g. math); however, all teachers appear to benefit from instruction in general teacher effectiveness. Since the present teacher shortage shows little sign of abating in the near future, it may be necessary to continue to employ unlicensed, or alternatively licensed teachers in order to simply provide an adequate number of teachers in existing elementary and secondary classrooms. However, the results of this review suggest that there is a substantial price to be paid for this practice. In light of the high rate of turnover of special education teachers, undertrained teachers may become a

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larger and more permanent component of the teaching force. It seems clear, then, that states, the federal government, and local school districts should do everything possible to promote high quality teacher education to ensure our most qualified people are given responsibility for educating the nation’s children.

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SUBJECT INDEX Academic skills, 14, 17, 78, 265, 285 Active thinking, 261, 262 Adaptations framework, 269 Adequate yearly progress, 57 Adolescents, 1, 3, 5, 6, 13, 22, 24, 25, 31, 82, 123–128, 134, 136–138, 140, 141 Advance organizers (AO), 155, 170, 188, 197 African American students, 34 Algebra, 29–39, 45–48, 51, 52, 243, 256–258, 308, 309, 314 Alternative licensure, 303, 304, 306, 307, 309–311, 314, 315 A Nation At- risk (book title), 80 Anchored instruction, 284 Anchoring table, 162, 163 Anxiety, 123, 127, 129, 130 Asian/Pacific students, 33, 34 Asperger syndrome, 124, 125, 127, 139 Assignment Completion Strategy (PROJECT Strategy), 83, 91, 92, 94 Assistive technology, 135, 267–272 At-risk students, 43, 258 Attention deficit hyperactivity disorder, 184, 267 Attributions, 208, 209, 216, 219 Autism spectrum disorders (ASD), 123–140 Automaticity training, 274 Behavioral disorders (BD), 1, 14, 79, 81, 97, 106, 107, 119, 135, 183, 245, 250, 260, 262, 271, 281 Behavioral self-management (BSM), 1–6, 13–25 Block scheduling, 124, 126, 130, 134, 137, 138, 246, 256

Calculators, 282, 283 Caucasian students, 34 Challenging behaviors, 2 Chemistry, 243, 244, 258–260 Class-wide peer tutoring, 181, 182, 187, 197 Communication problems, 108–110, 112, 116, 117 Comparison table, 165, 166 Computer based instruction, 266 Computer based testing, 288, 289 Computer software, 135, 273 Computer-assisted instruction (CAI), 191, 273–276, 281, 283, 284 Concept diagram, 162, 164–167 Constructivism, 149, 151, 157, 172 Consultant teaching, 60 Content area instruction, 147, 243, 244 Content area learning, 245, 255, 260, 262 Content enhancement, 147, 153, 154–158, 160, 162, 165–172 Contingency contracting, 87, 88, 93 Cooperative homework teams, 77, 83, 85, 86, 92, 93 Cooperative learning, 86, 184 Co-teacher, 55, 63, 65, 66, 71, 72 Co-teaching, 55, 57–64, 72–74, 258 Covert behaviors, 2 Curriculum based assessment, 288, 289 overlapping, 133 parallel, 58, 133, 149 Decoding, 250, 273–275 Deficits in information processing, 177, 223 Depression, 81, 196, 209–216, 219 Depressive attitude, 207, 208, 211–216 319

320 Diagnostic and Statistical Manual of Mental Disorders (DSM IV), 126 Digit sentence task, 227, 229, 234, 236 Direct instruction, 83, 84, 191, 193, 194, 197, 199, 260, 269 Discrete trials, 124 Distractibility, 3, 106, 107 Diversity, 55, 56, 119, 147, 151, 153, 157 Dynamic assessment, 221–223, 231, 237–240 Ecobehavioral assessment, 267–269 Ecological assessment, 267 Effect size, 5, 184, 223, 233, 239, 240, 273, 313 Effective instruction, 260, 261, 268, 270, 280, 283–285, 291, 311, 314 Electronic enhancements, 276, 277 Elementary students, 84, 98, 119 Emotional disabilities, 77, 79, 82, 85, 103, 104, 108, 109, 111, 113, 118, 119, 258, 282 Emotional disorders, 98 English, 29, 30, 32–34, 60, 64–66, 68–73, 189, 194, 243, 245, 247, 248, 253, 255–258, 260, 261, 276, 290, 313 English as a Second Language (ESL), 29, 34, 35, 43, 48, 49, 194, 255, 257, 258, 261 Fidelity of implementation, 40 Free or reduced lunch, 33 Functional evaluation for assistive technology (FEAT), 269 General education teachers (GET), 72, 94–97, 104–107, 109–111, 113–115, 117, 118, 131, 140, 151, 261, 270, 302 Generalization, 1, 2, 5, 7, 10, 19, 20, 24, 155, 158, 165–167 Goal setting, 2, 10, 12, 15, 25, 77, 83, 87, 88, 90, 93 Graphic organizers (GO), 133, 135, 137, 153–156, 158, 160, 162, 165, 170, 185, 187–189, 287 Guided notes, 183, 251–254

SUBJECT INDEX High school, 29, 30, 32, 35, 46, 55, 59, 71–74, 78, 94–98, 106, 108, 109, 113–115, 123–131, 134–136, 138–140, 148, 175, 176, 181, 183, 185, 187–189, 191, 193, 194, 196, 210, 221, 244, 246, 247, 253, 255, 260, 270, 272–274, 276, 277, 278, 285, 288, 289, 312 Hispanic students, 34 History, 64–68, 176, 185, 192, 193, 243, 246, 251, 253–256, 287, 288 Home-based self-management program, 90 Home-school communication, 77, 108, 112–114, 116–118, 219, 252 Homework, 4, 11, 12, 14, 64, 65, 77–119, 134, 309 Homework planner, 90 Homework teams, 77, 83, 85–87, 92, 93 Hypermedia, 276–278, 285, 286 Hypertext, 190, 276, 277, 285 Impulsivity, 3 Inclusion, 6, 22, 56, 60, 74, 77, 79, 103, 147, 149, 151, 152, 175–178, 184, 196, 310 Inclusive classroom, 7, 96, 286 Individual Educational Program (IEP), 83, 177, 267 Individual support, 67 Individual with Disabilities Education Act (IDEA), 56, 132 Information processing, 127, 177, 223, 240 Intelligence quotient (IQ), 23 Interviews, 96, 101, 104, 114, 186, 250, 252, 310 Junior high, 94, 95, 97, 98, 152, 185, 193, 194, 221 Keyboarding, 279, 280 Keyword method, 192, 245–247 Language arts, 97, 98, 148, 269 Learning disabilities (LD), 1 Lesson plans, 35, 52, 85, 251

Subject Index Mainstreaming, 56, 60 Maintenance, 1, 5, 7, 19, 20, 24, 31, 48, 87, 92, 104, 114, 221, 223, 225, 231, 233, 234, 236–240 Math, 9, 20, 29–35, 47, 48, 50, 53, 60, 65, 68, 71–73, 83–86, 88–90, 92, 97, 98, 103, 133, 221, 224, 250, 269, 272, 273, 282–284, 290, 305, 306, 308, 313, 315 Maximized engagement, 139, 260 Memory, 51, 73, 129, 133, 152, 177, 188, 191, 196, 198, 199, 201, 219, 221, 224, 232, 239, 261, 281, 282 Metacognitive attitude, 207, 211, 213–215, 220 Middle school, 31, 78, 92, 94–97, 101, 103, 104, 113, 115, 125, 126, 128, 130, 131, 140, 176, 179, 183, 184, 191, 194, 195, 247, 248, 250, 260, 272, 275, 280, 287, 309 Mnemonic strategies, 181, 191–194, 196, 197, 254, 256, 261 Mnemonics, 30, 181, 191–193, 195–197, 199, 243 Modifications, 37, 83, 132, 240, 270 Motivation, 2, 103, 104, 106, 107, 125, 152, 184, 209, 210, 219, 281, 283, 284, 309 Motivational beliefs, 207–209, 212–215 Multimedia, 184, 187, 279, 285, 286 Narrative notes, 60, 61, 63, 67, 68, 74 National Assessment of Educational Progress (NAEP), 272 National Council of Teachers of Mathematics (NCTM), 30, 35 National Research Council (NRC), 148 Native American students, 33 Naturalistic observation, 55, 59 No Child Left Behind (NCLB), 57, 151, 180 Note-taking, 67, 189 Organizational skills, 126 Parents, 33, 77, 78, 82, 84, 88–91, 93, 94, 96, 99, 100, 102, 104–119, 125, 130, 151, 265, 302, 303

321 Partner reading, 183, 249–252 Peer mediation, 134, 136, 243 Peer tutors, 30, 113, 183, 257 Pegwords, 181, 192, 193 Percentage of nonoverlapping data (PND), 1, 6, 7 Personal elaboration, 207 Phonological awareness, 273, 274 Poor readers, 221, 223–225, 230, 233, 234, 236–240, 276 Prior knowledge, 151, 152, 156, 158, 162, 165, 171, 177–179, 181, 187, 189, 194, 196–199, 201 Problem solving, 2, 12, 14, 15, 17, 21, 22, 29–35, 37–39, 42, 43, 45–47, 50–52, 80, 129, 150, 158, 166, 198, 256–258, 261, 262, 282, 284 Processing difficulties, 129, 134 Prompting, 3 Protocol, 41, 47, 51, 60, 313 Question exploration guide, 167, 169 Questionnaire, 29, 35, 37, 38, 40, 41, 43–46, 51, 88, 94, 101, 207, 210, 211, 215, 219, 257, 308, 309 Reading achievement, 222, 223, 237, 239 Reading comprehension, 183, 247–250, 252, 253, 273, 289 Reading disabilities (RD), 222 Reading fluency, 183, 247, 275 Reconstructive elaborations, 192 Regular Education Initiative (REI), 151, 177 Relationship chart, 154 Reliability, 41, 60, 63, 230, 269 Resource room (RR), 56, 94, 97, 98, 162, 182, 184, 269 Rhyming, 192, 225–228, 234, 236 Sameness, desire for, 127–129 Science, 60, 65–67, 71–73, 91, 94, 97, 98, 130, 132, 133, 147–153, 156, 160, 181, 188, 189, 245, 260, 269, 270, 289, 305, 307, 308, 313 Secondary schools, 57, 59, 125, 244, 247 Self contained classes, 103 Self-administration of consequences, 3, 6

322 Self-advocacy, 25, 286 Self-control, 3 Self-delivery of consequences, 4 Self-efficacy, 152, 307 Self-esteem, 152, 208, 212 Self-evaluation, 1, 3, 4, 6–9, 14–16, 21, 25, 88, 207, 208, 211–215, 220 Self-graphing, 87, 88 Self-instruction, 1, 3, 4, 6, 7, 9, 11, 14–16, 22, 29, 32, 33–39, 42–46, 48, 50, 51–52, 54, 90, 257 Self-management, 1, 2, 3, 5–8, 10, 12–16, 20, 22, 24, 25, 77, 83, 86–88, 90, 93 Self-monitoring, 1–8, 10–16, 18, 19, 21–23, 25, 30, 87, 88, 90, 93, 136, 209 Self-punishment, 4, 6 Self-regulation, 207–210, 212–216 Self-reinforcement, 1, 4, 6, 12, 15, 16, 90 Semantic feature analysis, 154, 189 Semantic webs, 154 SETT (Student, environment, tasks, tools) framework, 268, 269 Skilled readers, 221, 224, 225, 233, 236–239 Small group support, 67 SMARTER strategy, 157, 158 Social behaviors, 124, 127–129, 136 Social interactions, 14, 21, 123, 128, 136, 137, 140 Social scripts, 123 Social skills, 3, 31, 124, 135, 136 Social stories, 123, 134, 136, 137 Social studies textbooks, 175, 178, 179 Social validity, 13, 21 Socialization, 125, 126, 135 Special education teachers (SET), 55, 89, 94, 96, 109–115, 117, 118, 131, 151, 152, 270, 301, 302, 304, 311, 312, 314, 315 Speech feedback, 273, 275 Speech recognition, 271, 279, 281 Speech synthesis, 273, 275, 276 Spelling, 9, 11, 20, 84, 89, 90, 92, 97, 98, 152, 250, 271, 276, 278–280, 290 Standards-based reform, 57, 150, 288 STAR cognitive strategy, 32

SUBJECT INDEX State assistive technology centers, 267, 268 Strategic awareness, 207, 211–215, 220 Strategy checklist, 35, 36 Stress, 80, 126, 130 Students with disabilities, 5, 30, 55–58, 60, 73, 74, 77, 79, 82, 83, 85, 93, 95, 96, 106, 108–112, 115–119, 131–133, 139, 140, 162, 172, 175, 177, 180, 182, 183, 258–260, 266, 268, 273, 279, 280, 285, 291 Study skills, 100, 208, 216 Summarization strategies, 183, 186, 249, 251, 253 Survey, 82, 94, 95, 97–101, 106–118, 183, 188, 194, 309, 313 Teacher licensure, 301, 305, 310–312, 314, 315 Teacher preparation, 52, 302, 303, 305–308, 311, 312 Teacher shortage, 272, 302, 303, 315 Teacher training, 131, 315 Team teaching, 58, 61, 63, 69–72, 74, 138 Technology, 60, 64, 112, 114, 118, 123, 134, 135, 150, 181, 184, 187, 197, 265–292 Text recordings, 287 Textbooks, 35, 37, 69, 160, 175, 178, 179, 187, 188, 192, 195–197, 201, 244, 290 Traditional instruction, 29, 33, 34, 36, 39, 40, 42–46, 50, 193, 195, 246, 247, 251, 252, 255–257, 259, 288 Transfer, 22, 32, 48, 51, 200, 284, 302 Transition, 31, 123, 124, 130, 131, 243, 270, 286 Transition team, 130 Unit organizer, 160, 161 Universal design, 132, 133, 265, 290, 291 Value added, 55, 59, 73 Verbal elaborations, 245 Video modeling, 135 Videodisc technology, 283, 284 Views of students, parents and teachers with respect to homework, 104–108

Subject Index Visual spatial working memory, 224, 228 Visual supports, 123, 131, 133, 134 Vocabulary, 65, 84, 154, 178, 179, 186, 187, 192, 199, 230, 243, 245–249, 275, 276 Word identification, 273–275 Word problems, 31, 32, 36–39, 41, 46, 48, 50, 51, 53, 257, 284

323 Word processing, 66, 67, 184, 277, 279, 280 Working memory, 129, 152, 221, 224 Writing, 66, 68–70, 133, 152, 162, 178, 196, 250, 254, 271–273, 278–281, 285–288 Written expression, 20, 271, 278–281, 286 Zone of potential, 230, 231


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