Accelerating chronically unresponsive children to tier 3 instruction: what level of data is necessary to ensure selection accuracy?

Abstract

Response-to-intervention (RTI) approaches to disability identification are meant to put an end to the so-called wait-to-fail requirement associated with IQ discrepancy. However, in an unfortunate irony, there is a group of children who wait to fail in RTI frameworks. That is, they must fail both general classroom instruction (Tier 1) and small-group intervention (Tier 2) before becoming eligible for the most intensive intervention (Tier 3). The purpose of this article was to determine how to predict accurately which at-risk children will be unresponsive to Tiers 1 and 2, thereby allowing unresponsive children to move directly from Tier 1 to Tier 3. As part of an efficacy study of a multitier RTI approach to prevention and identification of reading disabilities (RD), 129 first-grade children who were unresponsive to classroom reading instruction were randomly assigned to 14 weeks of small-group, Tier 2 intervention. Nonresponders to this instruction (n = 33) were identified using local norms on first-grade word identification fluency growth linked to a distal outcome of RD at the end of second grade. Logistic regression models were used to predict membership in responder and nonresponder groups. Predictors were entered as blocks of data from least to most difficult to obtain: universal screening data, Tier 1 response data, norm referenced tests, and Tier 2 response data. Tier 2 response data were not necessary to classify students as responders and nonresponders to Tier 2 instruction, suggesting that some children can be accurately identified as eligible for Tier 3 intervention using only Tier 1 data, thereby avoiding prolonged periods of failure to instruction.