Universal Screening May Not Be for Everyone: Using a Threshold Model as a Smarter Way to Determine Risk

Abstract.

Universal academic screening is an endeavor that many systems implement with inefficiency and error. School personnel do not consider how the data will be used and therefore fail to collect the data needed to reach the most accurate and efficient decisions. Accurate and efficient decision making requires consideration of screening accuracy in the base rate context in which the screening will be used. Decision makers can use post-test probability data to reach decisions about whether assessment is needed or instead intervention should begin without assessment. A model for determining when assessment should be conducted and when it is smarter to begin intervention without assessment is provided, and screening data in mathematics and reading are used to illustrate the decision model.

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Notes on contributors

Amanda M. VanDerHeyden

Amanda VanDerHeyden, PhD, is a private consultant and researcher who has directed and evaluated numerous school-wide intervention and reform efforts, most often in the area of mathematics. She serves as advisor to the National Center for Learning Disabilities, iSTEEP (a web-based data management system), and is a standing panel member for the Institute for Education Sciences at the U.S. Department of Education. Dr. VanDerHeyden is a frequent contributor to the literature on screening and school-wide performance improvement. Her most recent book is The RTI Approach to Evaluating Learning Disabilities co-authored with Joe Kovaleski and Edward Shapiro and published by Guilford in 2013.