Reading Differences Between Low-Achieving Students With and Without Learning Disabilities: A Meta-Analysis

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NICHCY’s Structured Abstract 14 describes the following:

Title | Reading Differences Between Low-Achieving Students With and Without Learning Disabilities: A Meta-Analysis

Authors | Fuchs, D., Fuchs, L.S., Mathes, PG., & Lipsey, M.W.

Source | In R. Gersten, E.P. Schiller, & S. Vaughn (Eds.), Contemporary Special Education Research: Syntheses of the Knowledge Base on Critical Instruction Issues (pp.81 – 105). Mahwah, NJ: Erlbaum.

Year Published | 2000

Abstract
Only since the late 1980s has there been sufficient special education research published that 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. Anyone who has attempted a meta-analysis or a comprehensive research synthesis is aware of how formidable a task it is. Issues that seem relatively easy or straightforward when described in a textbook are usually extraordinarily intricate and perplexing when put into practice. Every decision, from defining the target population to exclusion criteria for studies, invariably opens up a can of worms. Where one expects many studies, often there are few. And where relatively few are expected, there are often far too many to be able to synthesize properly.

Each of these chapters represents years of work and, often, struggle. We believe the effort and the occasional agonies are reflected in the depth of insight provided in each of the chapters. Four of the research teams use meta-analysis as their major analytic tool. Three of the meta-analyses deal with learning disabilities. Batya Elbaum, Sharon Vaughn, Marie Hughes, Sally Watson Moody, and Jeanne Shay Schumm synthesize what we now know about effective instructional grouping practices for reading. Doug Fuchs, Lynn S. Fuchs, Patricia G. Mathes, and Mark W. Lipsey examine differences between students classified as learning disabled and other low-achieving students on a range of academic performance measures. They also discuss policy implications. H. Lee Swanson reviews the entire corpus of instructional research on learning disabilities in order to discern underlying principles of effective teaching and instructional design. (From the Preface of Contemporary Special Education Research)

Background
In the two decades between the mid 1970’s and the mid 1990’s, the number of children classified as having learning disabilities (LD) nearly tripled. Students with learning disabilities became the largest single category of children served under special education, accounting for nearly half of all the children receiving special education services.

Despite the growing number of children receiving special education under the category of “specific learning disability,” there was no widely accepted definition of what a learning disability was. There was even debate about whether learning disabilities really existed as a problem that differed from simple low academic achievement. Some people argued that underachieving students were the same whether they had the LD label or not. Others suggested that underachieving LD and non-LD students over-lapped in some respects. While a third group claimed that not only were students with LD distinguishable from their low-achieving peers, but they had different educational needs. This meta-analysis explores the differences and similarities between students with LD and their low-achieving peers.

Research Questions

  1. Does the reading achievement of students with LD differ from that of their non-disabled or low-achieving peers? And, if so, in what ways does it differ?
  2. What are the differences in the effect sizes associated with timed versus untimed tests?
  3. Are the same students determined to have LD using objective data (e.g. aptitude or achievement tests) as are selected by an individual or team?

Research Design
Meta-Analysis

  • Number of Studies Included | 86
  • Number of Subjects | N/A
  • Years Spanned | 1979-1997

Research Subjects
Students who labeled learning disabled (LD), low-achieving, or non-disabled in kindergarten through 12th grade.

Age/Grade of Subjects
K-12

Specified Disability
Learning Disabilities (LD) in reading.

Intervention
Reading interventions and untimed tests.

Duration of Intervention
N/A

Findings

  1. The reading achievement of students with LD differs significantly from that of their low-achieving peers.
  2. The effect sizes associated with timed tests were larger than those for untimed tests.
  3. Different students are selected as LD using objective data (e.g. aptitude or achievement tests) than by an individual or team. Students determined to be LD using objective data differed significantly from children who were low-achieving, but children determined to be LD by an individual’s or team’s opinion were more likely to over-lap with the low-achieving group.

Combined Effects Size

  1. The mean effect size across all the variations in the studies was 0.61.
  2. The effect size for timed measurements was over 1.00.

Note: Effect size is a statistical calculation, often represented as ES or d, that measures the impact of an intervention. An effect size below d = 0.20 suggests that a treatment did not have a significant effect. An effect size of d = 0.20 is considered small or low; an effect size of d = 0.50 is considered moderate; an effect size of d = 0.80 or above is large.

Conclusion/Recommendations

  1. This meta-analysis found school personnel correctly identify those with severe reading problems as learning disabled, and students identified as LD had significantly greater reading difficulties than children labeled low-achieving. The authors suggest that more intensive reading interventions should be provided to students with LD, since the magnitude of their difficulties is far more severe than the average low-achieving student.
  2. Students who had been identified as LD through a series of objective tests were more accurately separated from their low-achieving, non-LD peers than students grouped based on individual or team opinion of whether or not they were LD. Objective data, such as standardized tests, sorted students with LD and students who were low-achieving into distinct groups, while people using their own observations and opinions of students without objective data were more likely to place children due to their behavior than the nature of their learning difficulties.
  3. Students with LD were much more likely to struggle on timed tasks than other children, and the authors suggest that this finding may have implications for both assessment and interventions for students with LD. First, they suggest that the evaluation to determine if a child has LD should include some timed tests, such as rapid-naming tasks, since these tasks often dramatically display a primary area of weakness in students with LD. The authors also suggest that once students have been identified as LD they should be provided with interventions which focus on increasing their capacity for automatic word reading. Finally, they suggest that the effectiveness of interventions for students with LD should be judged in part by whether they increase students’ performance on timed tasks.

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