Contemporary Special Education Research

Syntheses of the Knowledge Base on Critical Instructional Issues

Russell Gersten, Ellen P. Schiller, Sharon R. Vaughn

• Publisher: Routledge
• Year: 2000
• eBook ISBN: 9781135680626
• Topic: Education
• Subtopic: Education General

Considerable research in the past 30 years has accumulated regarding the academic and social functioning of youngsters with disabilities. Only in the past decade has there been sufficient special education research published from which meta-analyses and syntheses can be conducted. In this volume, seven sets of authors grapple with synthesizing the knowledge base on an array of critical topics in the field of special education.

Among others, specific chapters include:
* a synthesis of what is known about effective instructional grouping practices for reading.
* an examination of the differences between students classified as learning disabled and other low-achieving students on a range of academic performance measures.
* a review of effective instruction for English-language learners.
* an examination of the research on behavioral supports for low-incidence special education populations.
* a synthesis on how technology supports literary development, across the full spectrum of disabilities categories.

These papers provide up-to-date, informative summaries of current knowledge and a base from which further venture into the critical area of instructional intervention in special education can occur.

Chapter 1

What Instruction Works for Students With Learning Disabilities? Summarizing the Results From a Meta-Analysis of Intervention Studies

H. Lee Swanson

University of California–Riverside

In this chapter, I review some of the empirical evidence collected from a comprehensive educational intervention research synthesis for students with learning disabilities (Swanson, Hoskyn, Lee, & O’Shaughnessy, 1997). The synthesis used meta-analytic techniques to aggregate the research literature on intervention. Meta-analysis is a statistical reviewing technique that provides a quantitative summary of findings across an entire body of research (Cooper & Hedges, 1994; Hedges & Olkin, 1985). The results of individual studies are converted to a standardized metric or effect size. These scores are then aggregated across the sample of studies to yield an overall estimate of effect size. Particular attention is given to the magnitude of the effect size estimate. According to Cohen (1988), .80 is considered a “large” effect size estimate, .50 a moderate estimate, and .20 a small estimate.

One of the major purposes of our (Swanson et al., 1997) meta-analysis was to identify effective instructional models that yield high effect sizes, as well as the components that make up those models. As an extension of an earlier synthesis (Swanson, Carson, & Sachse-Lee, 1996), we tested whether treatments that include components of strategy instruction (SI), direct instruction (DI), and/or both instructional models yield significant difference in effect size. Our earlier synthesis found that strategy and direct instruction models yielded higher effect size than competing models, but the instructional components that made up those models were not analyzed.

Because the terms strategy instruction and direct instruction are used in various ways by researchers and practitioners alike, further clarification of how studies were analyzed in the current synthesis as a function of treatment approach is necessary. Given the overlap between strategy and direct instruction models, we draw upon the literature to operationalize these approaches in the following manner. Components of direct instruction are reviewed by Engelmann and Carnine (1982); Kameenui, Jitendra, and Darch (1995); and several others. They suggest that direct instruction emphasizes fast-paced, well-sequenced, highly focused lessons. The lessons are delivered usually in small groups to students who are given several opportunities to respond and receive feedback about accuracy and responses. Based on these reviews and others, those activities coded that reflect direct instruction in the present synthesis were as follows: (a) breaking down a task into small steps, (b) administering probes, (c) administering feedback repeatedly, (d) providing a pictorial or diagram presentation, (e) allowing for independent practice and individually paced instruction, (f) breaking the instruction down into simpler phases, (g) instructing in a small group, (h) teacher modeling a skill, (i) providing set materials at a rapid pace, (j) providing individual child instruction, (k) teacher asking questions, and (1) teacher presenting the new (novel) materials. Any study that included a minimum of four of these codes in the treatment phase was labeled a direct instruction.

Components related to effective strategy instructional programs are reviewed elsewhere (for a review see Borkowski & Turner, 1990; Levin, 1986; Pressley & Ghatala, 1990). Some of these components include advance organizers (provide students with a type of mental scaffolding in which to build new understanding, i.e., consist of information already in the students’ minds and the new concepts that can organize this information), organization (information questions directed to students to stop from time to time to assess their understanding), elaboration (thinking about the material to be learned in a way that connects the material to information or ideas already in their mind), generative learning (learners must work to make sense out of what they are learning by summarizing the information), and general study strategies (e.g., underlining, note taking, summarizing, having students generate questions, outlining, and working in pairs to summarize sections of materials), think about and control one’s thinking process (metacognition), and attributions (evaluating the effectiveness of a strategy). Based on these reviews, we categorized studies as reflecting strategy instruction if they include at least three of the following instructional components:

1. Elaborate explanations (i.e., systematic explanations, elaborations, and/or plans to direct task performance).

2. Modeling from teachers (verbal modeling, questioning, and demonstration from teachers).

3. Reminders to use certain strategies or procedures (i.e., students are cued to use taught strategies, tactics, or procedures).

4. Step-by-step prompts or multiprocess instructions.

5. Dialogue: teacher and student talk back and forth.

6. Teacher asks questions.

7. Teacher provides only necessary assistance.

Based on these criteria, studies to be classified fell into one of four models: strategy+direct instruction (referred to as the combined model), direct instruction (Dl)-alone, strategy instruction (Sl)-alone, and non-strategy+nondirect instruction. As a validity check on our classifications, we compared our classification of the treatment conditions with that of the primary author’s general theoretical model and/or the label attached to the treatment condition. There was substantial overlap (approximately 70% of the studies) between those studies we classified as direct instruction and strategy instruction models with the primary authors’ tides or description of the independent variables. For example, frequent terms provided by the author were: strategy, cognitive intervention, monitoring, metacognition, self-instruction, and cognitive-behavior modification for the strategy model. Those that were classified as direct instruction by our criteria used such labels as: directed instruction, advanced organizers, adapting materials, or corrective feedback or direct computation. Those approaches that were below the component threshold (did not include the minimum number of components for being labeled as either direct instruction or strategy intervention) used, for example, such labels as reinforcement-only, modeling-only, or social skills training.

Although considerable attention was devoted to coding studies on instructional variables, there were two additional areas of interest related to instruction that we considered in our synthesis. One focused on whether some domains of instruction are more resistant to change as a function of treatment than others. One conceptual model that has some consensus in the field is that learning-disabled (LD) children are of normal intelligence, but suffer information-processing difficulties (e.g., Borkowski, Estrada, Milstead, & Hale, 1989; Deshler & Schumaker, 1988; Fletcher et al., 1994; Stanovich & Siegel, 1994; Swanson & Alexander, 1997). A popular assumption that has emerged in the last few years is that LD children have specific processing deficits that are localized to low-order processes, particularly phonological processing deficits (e.g., Francis, Shaywitz, Stuebing, Shaywitz, & Fletcher, 1996; Siegel, 1992; Stanovich & Siegel, 1994). Phonological processing is “the association between sounds with letters, that is, the understanding of the grapheme-phoneme conversion rules and the exceptions to these rules” (Siegel, 1993, p. 38). This assumption finds some consensus in the field because reading problems are pervasive in LD populations, and there is a plethora of research that suggests phonological coding underlies most of these problems (see Stanovich & Siegel, 1994, for a review). Although this may be true, there has been no synthesis of intervention studies to determine if specific processes or skills related to reading are more resistant to change than other academic domains.

The second area related to instruction we considered was whether variations in aptitude interact with the magnitude of treatment outcomes. More specifically, we assessed whether studies that include samples with intelligence and reading scores at various levels yield different treatment outcomes than those studies in which such levels are not specified. Reading scores at or below the 25th percentile in reading recognition (see Siegel & Ryan, 1989; Stanovich & Siegel, 1994) and standardized intelligence performance at or above 85 have been considered as critical cutoff scores for defining learning disabilities (LD; see Morrison & Siegel, 1991, for discussion of this issue). The rise in the use of cutoff scores in the experimental literature has been in response to the poor discriminant validity of discrepancy scores in defining children with LD from generally poor achieving children (see Stanovich & Siegel, 1994, for a review). The treatment validity of such a cutoff score definition, however, has not been tested as a function of treatment outcomes. That is, we assume that the face validity of a definition is enhanced if one can show that such a definition is significantly related to treatment outcomes.

Key Constructs

Three constructs were important in our synthesis of the research: LD, treatment, and outcome. First, although we took a nonjudgmental stance on the quality of the definition of LD reflected in intervention studies (e.g., operational vs. a school district definition vs. Federal Register definition), we held to a general parameter that such students must have at least normal intelligence (standardized intelligence scores at or above 85) or the study states explicitly that participants are in the normal range of intelligence. The study must also state that the participants perform poorly (as indicated by teachers and/or psychometric tests) in at least one academic (e.g., reading) and/or behavioral domain (social skills). We coded the variations of definitions reflected in the database (discrepancy vs. cutoff scores; school identified vs. research identified; specific academic difficulty vs. multiple academic difficulties) to investigate the relationship between the definitional parameters related to learning disabilities and actual treatment outcomes.

Second, the term treatment or intervention was defined as the direct manipulation by the researcher of psychological (e.g., metacognitive awareness), medical (e.g., drug) and/or educational (e.g., teaching, instruction, materials) variables for the purposes of assessing learning efficiency (e.g., rate, time), learning accuracy (e.g., percent correct), learning understanding (e.g., amount of verbal elaboration on a concept), or a combination of all three. In general, treatment was administered in the context of school as an extension of the regular classroom, special education classroom, and/or clinical services. This extension varied from three instructional sessions to several continuous instructional sessions over months or years. Because of the vastness of the topic, however, additional boundaries were necessary in our analysis. The intervention literature that focuses on administrative decisions and does not reflect a manipulation of treatment conditions (e.g., educational placement – resource room) falls outside the boundaries. Educational research based on intervention that occurs as an extension of the educational placement of children, adolescents, and adults with LD within various educational (e.g., classroom or college) placements is included. Moreover, attention is directed to only those instructional interventions that include students with LD. Excluded from the analysis, however, are interventions in which the effects of intervention on students with LD cannot be directly analyzed or partialed out in the analysis. Also, within the area of educational intervention, it was necessary to place parameters on the level or scope of intervention. At one end of a rough continuum, we distinguished between treatment techniques that include separable elements, but that do not, by themselves, reflect a free-standing treatment (e.g., teacher presents advance organizers). At the other end of this continuum are broad approaches that reflect policies and organizational arrangements (e.g., consulting-teacher model that provides help to a LD student in a regular classroom). We excluded those treatments that were at the top of the continuum. Although there are some gray areas in our selection, we have found it possible to identify instructional programs that are added to the typical instructional routine.

Finally, treatment outcomes included six general categories of information. These categories were:

1. Article or technical report identification (funding sources, citations).

2. Methodological characteristics (e.g., sampling procedure, reliability and validity of measures, internal and external validity, treatment integrity).

3. Sampling characteristics (e.g., psychometric information, chronological age, gender, ethnicity, sample size, type of definition, marker variables).

4. Parameters of intervention (e.g., domain, setting, materials, duration and length of session).

5. Components of intervention (e.g., group vs. individual instruction, number and description of steps in intervention, level of student response to instruction, maintenance and transfer).

6. Effect size (e.g., magnitude of treatment effects).

Data Collection

The PSycINFO, MEDline, and ERIC online databases were systematically scanned for studies from 1963 to 1997 that met the inclusion criteria described next. The computer search strategy used the following terms: learning disabled (disabilities), or reading disabled (disabilities), or dyslexic, or educationally handicapped, or slow learners, paired with variations of intervention or treatment or training or remediation or instruction. This search yielded approximately 3,000 abstracts that included articles, technical reports, chapters, and dissertations. We examined all the abstracts prior to study selection to eliminate those studies that clearly did not meet the inclusion criteria (e.g., articles were reviews or position papers). Because the computer search procedures excluded unpublished studies and the most recent literature, researchers (as identified by journal board affiliations with the Learning Disability Quarterly, Journal of Learning Disabilities, and Learning Disabilities Research and Practice and/or membership in the International Academy for Research in Learning Disabilities) were sent letters requesting copies of unpublished and/or ongoing intervention studies. We also hand searched the following journals for articles that did not emerge from the computer search: Journal of Learning Disabilities, Journal of Educational Psychology, Learning Disability Quarterly, Reading and Writing, Learning Disabilities Research and Practice, Exceptional Children, and the Journal of Special Education. In addition, every state department and 200 School District Directors of Educational Research were sent a letter requesting technical reports on intervention studies for children and adolescents with LD.

Data Evaluation

The pool of relevant literature (3,164 reports, abstracts, dissertations, or articles) was narrowed down to studies that utilized an experimental design in which children or adults with LD receive treatment to enhance their academic, social, and/or cognitive performance. This procedure narrowed the search to 913 databased articles (or reports) that appeared potentially acceptable for inclusion i...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Foreword
• Preface
• 1 What Instruction Works for Students With Learning Disabilities? Summarizing the Results From a Meta-Anaylsis of Intervention Studies
• 2 The Professional Knowledge Base on Instructional Practices That Support Cognitive Growth for English-Language Learners
• 3 Reading Differences Between Low-Achieving Students With and Without Learning Disabilities: A Meta-Analysis
• 4 How Reading Outcomes of Students With Disabilities Are Related to Instructional Grouping Formats: A Meta-Analytic Review
• 5 A Meta-Analysis of Positive Behavior Support
• 6 Technology, Literacy, and Disabilities: A Review of the Research
• 7 Research Syntheses: Implications for Research and Practice
• 8 The Methodology of Meta-Analysis
• 9 Policy Decisions in Special Education: The Role of Meta-Analysis
• Author Index
• Subject Index