Academic journal article Learning Disability Quarterly

LD Identification: It's Not Simply a Matter of Building a Better Mousetrap

Academic journal article Learning Disability Quarterly

LD Identification: It's Not Simply a Matter of Building a Better Mousetrap

Article excerpt

Historically, researchers, policy makers, and practitioners have sought improved solutions to the issues associated with LD identification decisions. Since the passage of P.L. 94-142, numerous identification methods has been proposed, implemented, and studied. While each new method has been successful, at least partially, in addressing some of the limitations of earlier methods, each new identification model is saddled with its own set of shortcomings. This article argues that factors beyond specific LD identification technology significantly influence the decision-making process and ultimately decisions about who is and who is not LD. Results from focus group discussions with six stakeholder groups (LD parents, LD teachers, general education teachers, directors of special education, school principals, and school psychologists/diagnosticians) are reported, indicating that a broad array of factors beyond a student's performance on formal and informal assessments influence ultimate decisions made about a student's eligibility for learning disability services. Thus, the search for new identification technologies should also include efforts to better understand the values and biases of critical stakeholders and how to include these factors in the overall decision-making process.

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One commonly ascribed characteristic of students with learning disabilities (LD) is underachievement. That is, students with LD demonstrate learning commensurate with estimates of their abilities in many areas, but in a specific area they show an unexplained deficit. Their deficits in learning or performance on specific tasks (e.g., reading, math calculation and reasoning, oral and written expression, and listening comprehension) are due to a presumed underlying processing delay or dysfunction.

Shortly after P.L. 94-142 was passed in the mid-1970s, the federal government published regulations detailing procedures for how to identify students with LD. The regulations gave states and local districts direction for ways to operationalize the definition of the LD construct. Those regulations indicated that students' level of underachievement could be calculated with a discrepancy formula. Even though the initial severe discrepancy formula published in the regulations was met by strong negative reactions (Hallahan & Mercer, 2002), the U.S. Department of Education stayed with the notion of an aptitude-achievement discrepancy in the regulations but did not specify a particular formula or specific criteria to be used. As a result, by the 1990s, the vast majority of states had adopted underachievement as a critical attribute of LD and an aptitude-achievement discrepancy model as a part of their LD determination framework (Kavale, 2002; Reschly, Hosp, & Schmied, 2003).

Researchers and policy makers have proposed a broad array of discrepancy formulas and criteria as a means of assessing students' underachievement and making accurate LD determination decisions. Proposed formulas have included (a) grade-level deviations whereby an expected grade level score is compared to an actual grade-level score and the discrepancy is calculated from the difference (e.g., Harris, 1971; Selz & Reitan, 1979); (b) expectancy formulas that include some combination of variables such as IQ, chronological age, mental age, years in school, and grade age (e.g., Bond & Tinker, 1973); (c) standard score methods that involve direct comparison between common metrics for intellectual ability and academic achievement (e.g., Elliot 1981; Erickson, 1975); and (d) regression methods in which measurement errors associated with IQ and achievement measures are accounted for (e.g., Reynolds, 1985). Each of these formulations was an attempt to increase the accuracy of decision making about children's school underachievement problems. Additionally, the formulas were attempts to address the shortcomings of previously proposed models (e.g. …

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