Relative Efficacy of Teacher Rankings and Curriculum-Based Measures as Predictors of Performance on High-Stakes Tests

Abstract

Data from 403 third graders were analyzed to determine relative and combined efficacy of group-administered Curriculum-Based Measures (CBMs) and Teacher Rankings of student reading and math performance taken early in the school year to predict end-of-year achievement scores. Teacher Rankings added to the power of CBMs to predict reading ( R2change = .18) and math ( R2change = .22). Combined CBMs and Teacher Rankings predicted at-risk status in reading (82%) and math (86%), based on logistic regression, and yielded strong area under the curve (AUC) statistics, defining risk status .88 (reading) and .82 (math). Surprisingly, Teacher Rankings yielded higher correlations with end-of-year scores than CBMs. Findings support using rankings as a simple, efficient strategy to add to the predictive power of CBMs readily available within a response to intervention (RTI) context and depicts a methodology school personnel can use to determine the relative/combined predictive power of CBMs and rankings. Of note, predictions based on Teacher Rankings vary across end-of-year performance levels.