Cognitive Processing Deficits and Students with Specific Learning Disabilities: A Selective Meta-Analysis of the Literature

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Abstract. Many practitioners and state education agency staff would likely agree that the accuracy and consistency of specific learning disability (SLD) eligibility decisions is in need of improvement. One component of the SLD definition particularly controversial in the identification procedures is the evaluation of cognitive processes, primarily due to a lack of information about the role they might play in informing an SLD diagnosis and eligibility for special education services. A meta-analysis of 32 studies was conducted to examine the cognitive processing differences between students with SLD and typically achieving peers. The analysis found moderately large to large effect sizes in cognitive processing differences between groups of students with SLD and typically achieving students. These differences are of sufficient magnitude to justify including measures of cognitive processing ability in the evaluation and identification of SLD.


Ideally, diagnosis of a specific learning disability (SLD) should consist of a three-step process: (a) categorical diagnosis, (b) explanatory diagnosis, and (c) treatment planning (Witteman, Harries, Bekker, & VanAarle, 2007). As currently practiced, however, SLD diagnosis places nearly exclusive emphasis on treatment planning.

This is problematic on several levels. Most directly for the student, this can lead to treatment planning that does not appropriately address an individual student's needs (Swanson, 2009). Over time, the emphasis on treatment without first ensuring accurate classification erodes our understanding, treatment, research, and prevention of specific learning disabilities. The criteria for diagnosing an SLD are outlined in federal regulations (IDEA, 2004) as well as in clinical references such as the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (American Psychiatric Association [APA], 1994), but these criteria have neither been easily nor consistently applied in practice.

Research on practitioners' assessment of SLD confirms that the outcomes of this approach have been less than optimal (Gerber, 1988, 2005; Hallahan & Mercer, 2002; MacMillan & Siperstein, 2002; Ysseldyke, Algozzine, Richey, & Graden, 1982). The poor application of the diagnostic process can be attributed to a lack of clarity of both the environmental information about students and the relevant, scientifically established knowledge (Witteman et al., 2007).

Factors Contributing to Problems with SLD Identification

The factors identified as contributing to problems with SLD identification generally fall into three main categories: (a) resources, (b) stakeholder values, and (c) measurement issues (Johnson, Mellard, & Byrd, 2006). Constraints on resources have a significant impact on SLD eligibility decisions. At the classroom level, resource constraints are primarily related to a teacher's ability to adequately meet the needs of all the students in the room. A teacher without a broad range of instructional strategies is less likely to be successful in reaching all students and, therefore, more students in his or her class may be identified as having an SLD (Gerber, 2005). At the school level, low-achieving students may be identified as having an SLD because resources to provide services to other categories of struggling learners are not available (MacMillan, Gresham, & Bocian, 1998).

Stakeholder values also impact identification procedures. The role that stakeholder values play is clearly demonstrated in research examining differences between researcher- vs. school-identified populations (Mellard, Deshler, & Barth, 2004; MacMillan & Siperstein, 2002). This is further evidenced in the current debate over using a response to intervention (RTI) approach or a cognitive hypothesis testing approach to eligibility decisions (see, e.g., Hisock & Kinsbourne, 2009).

Finally, measurement issues are evident across the four stages of SLD determination: prereferral, referral, evaluation, and eligibility determination. …


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