Quantifying Context in Assessment: Capturing the Effect of Base Rates on Teacher Referral and a Problem-Solving Model of Identification

Abstract

The purpose of this article was to examine the effect of base rate occurrence of race, sex, and student achievement on the accuracy of a problem-solving model of assessment and teacher referral. All students in first and second grade (n = 182) at a participating school were exposed to four screening measures. Students who performed poorly on at least one of the screening measures participated in a more thorough assessment process including individual curriculum-based assessment with individual intervention. The predictive accuracy (e.g., sensitivity, specificity) of the problem-solving model and teacher referral was examined using the more thorough assessment process as the standard for comparison. The degree to which the problem-solving model and teacher referral correctly identified male and female children, children of minority and nonminority ethnicity, and children in high-achieving and low-achieving classrooms was specified. Further, the efficiency of the problem-solving model and teacher referral was examined by comparing identification relative to base rate occurrence of problems in the screened population.

Additional information

Notes on contributors

Amanda M. VanDerHeyden

Amanda M. VanDerHeyden, PhD, is an assistant professor in the school psychology program at the University of California at Santa Barbara. She is a member of the Journal of Early Intervention, Journal of Behavioral Education, and School Psychology Review editorial boards. Her research interests include applied behavior analysis, early intervention, teacher and parent training, and generally finding ways to help children learn.

Joseph C Witt

Joe Witt, PhD, is currently a professor of psychology at Louisiana State University. His research interests are in assessment and intervention to improve outcomes for at-risk students.