Magazine article National Association of School Psychologists. Communique

Applying a Response to Intervention Framework for Noncategorical Special Education Identification

Magazine article National Association of School Psychologists. Communique

Applying a Response to Intervention Framework for Noncategorical Special Education Identification

Article excerpt

There has been much recent discussion among educators on the topic of implementing a response to intervention (RTI) framework to identify special education needs for students with specific learning disabilities. There is good reason for such discussion, as all students benefit from RTI when implemented with integrity and fidelity. The result of RTI is an assurance that all students will receive instruction that is responsive to their educational progress (Batsche et al., 2006).

Since special education disability labeling is not mandated by IDEA, some local education agencies allow noncategorical special education identification. The fundamental difference between noncategorical and traditional assessment lies in the question that guides the assessment process. Traditional categorical assessment focuses on whether or not a child meets criteria for a disability category. The focus is placed on child deficits and examining what they are unable to do. In contrast, the assessment question asked in the noncategorical framework is about what the student can do (Reschly, Tilly, 8c Grimes, 1999). More specifically, noncategorical assessment focuses on specific functional academic skills and behaviors and students' rates of growth in the context of school-based interventions. Thus, the problem solving process occurs within an RTI framework to form a multitiered model of service delivery to all students. This is the foundation for noncategorical implementation.

As a model of service delivery to all students, RTI is a necessary prerequisite to engage in noncategorical special education identification. Response to intervention implementation is two-pronged: (a) it provides a data-based decision making model for guiding instruction within the context of multitiered service delivery, and (b) it is a valid means of identifying students with disabilities (Reschly, Tilly, & Grimes, 1999). The remainder of the paper will provide a rationale for noncategorical special education identification within the context of an RTI framework and discuss the present and future benefits of these practices as they are implemented in a large, urban, Midwestern school district.


Traditional standardized assessment techniques often used to determine special cation eligibility provide little when linking assessment to intervention. school psychological assessment models sought to differentiate processing strengths and weaknesses in linking assessment to intervention. Data kept on the aptitude by treatment interaction model has provided inadequate support with respect to cacy of this model when applied to educational diagnosis. Additionally, there are mented negative effects that labels have on student self-concept. The use of a lem solving decision-making process, coupled with ecological assessment, within a response to intervention framework has been proposed as a positive and manageable alternative to traditional categorical assessment models (Kavale & Forness, 1999; schly, Tilly, & Grimes, 1999; Stoiber & Vanderwood, 2008).

Pairing interventions based on profile analyses is a practice that seemingly has a high degree of face validity, yet has little research support. The use of cognitive cessing in treatment planning shows no advantages over a response to intervention framework. A limited effect size (.03) is reported on studies examining the use of cific learning strategies for either "auditory" or "visual learners." While there is much valuable research in the neuropsychological literature about brain tion, injury, etc., functional MRI studies have failed to identify reliable markers for learning disabilities and cognitive processing deficits. Despite categorical labels, ment techniques based on individual student needs and goals yield large effects on student outcomes. The effect sizes range from .70 for curriculum-based intervention with graphing and formative evaluation, .93 for functional behavior analysis; and 1. …

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