Evaluating validity and bias for hand-calculated and automated written expression curriculum-based measurement scores

Abstract

Written expression curriculum-based measurement (WE-CBM) is a formative assessment approach for screening and progress monitoring. To extend evaluation of WE-CBM, we compared hand calculated and automated scoring approaches in relation to the number of screening samples needed per student for valid scores, the long-term predictive validity and diagnostic accuracy of scores, and predictive and diagnostic bias for underrepresented student groups. Second- to fifth-grade students (n = 609) completed five WE-CBM tasks during one academic year and a standardised writing test in fourth and seventh grade. Averaging WE-CBM scores across multiple samples improved validity. Complex hand-calculated metrics and automated tools outperformed simpler metrics for the long-term prediction of writing performance. No evidence of bias was observed between African American and Hispanic students. The study will illustrate the absence of test bias as necessary condition for fair and equitable screening procedures and the importance of future research to include comparisons with majority groups.

Michael Matta

Research Scientist in Educational Measurement

My research focuses on developing and validating computer-based methods for the assessment of academic skills and behaviors of school-aged students.