Operational Definition of Patterns of Strengths and Weaknesses

Volume 18, Number 2 87 The 2004 Indviduals with Disabilities Education Improvement Act (IDEA) and subsequent regulations published in August 2006, have significantly changed the identification process for students suspected of having specific learning disabilities (SLD; Flanagan & Alfonzo, 2011; Mather & Kaufman, 2006; Schultz & Stephens, 2009a). According to the 2006 IDEA regulations (§300.307) concerning SLD, each state must adopt criteria for determining whether a child has a specific learning disability as defined by §300.8 (c)(10), requiring that states 1. Must not require the use of severe discrepancy between intellectual ability and achievement for determining whether a child has a specific learning disability as defined in §300.8 (c)(10); 2. Must permit the use of a process based on the child’s response to scientific, research-based intervention; and 3. May permit the use of other alternative researchbased procedures for determining whether a child has a specific learning disability as defined in §300.8 (c)(10); (IDEA, 20 U.S.C.§ 1414 (b)(6)(A). Since these policies have been in effect, many state education agencies have opted to allow the use alternative researchbased procedures in the context of a Response-to-Intervention (RTI) identification model (Flanagan & Alfonzo, 2011; Schultz & Stephens, 2009a; Zirkel & Thomas, 2010). Several states (e.g., Idaho, Michigan, Oregon, Texas) have allowed third-method approaches by identifying students with SLD by analyzing a pattern of strengths and weaknesses (PSW) (Flanagan, Fiorello, & Ortiz, 2010). Since states have autonomy in SLD identification methodology, the manner by which we identify a student with SLD continues to be a source of much controversy in the field (Fletcher, 2011; Fletcher, Barth, & Stuebing, 2011; Fuchs, Fuchs, & Stecker, 2010; Hale et al., 2010; Kavale, Kauffman, Bachmeier, & Lefever, 2008). As local education agencies are no longer required to use a discrepancy model when determining SLD eligibility, increased reliance is placed on the knowledge and expertise of assessment teams in the areas of learning acquisition and special education law, in addition to the selection, administration, scoring, and interpretation of multiple forms of assessment. Eligibility criteria are no longer based on a simple score difference; instead, a disability is determined through the analysis of multiple sources of data, and the identification of strengths and weaknesses which impact learning. The federal regulations state that eligibility decisions must be made using a variety of assessment tools and strategies, while states determine the types of necessary data to determine SLD. Very little guidance is provided on how to best analyze and interpret the data to make educationally and legally sounds decisions. The purpose of this paper is to (a) discuss the third method of patterns of strengths and weaknesses (PSW) approaches, (b) describe organization and data collection using a PSW approach, and (c) explain how to interpret data using sound data analysis principles.