Bias Using Maze to Predict High-Stakes Test Performance Among Hispanic and Spanish-Speaking Students

Abstract

Universal screening using curriculum-based measures allows educators to detect students who may be in need of instructional interventions. Curriculum-based measures, such as oral reading fluency and Maze, are effective at accurately and efficiently identifying reading proficiency levels for overall school populations. Nevertheless, little is currently known about whether these measures are equally predictive for the diverse populations of students in schools. The current study examined whether Maze has prediction bias for Hispanic students and for students who primarily speak Spanish at home. Slope and intercept bias were examined using hierarchical linear modeling techniques. Intercept bias was found; however, effects were small. Maze underpredicted scores on a high-stakes state language arts test for both Spanish-speaking and Hispanic students, compared to their English-speaking and Caucasian counterparts. Maze was a strong predictor of the state outcome measure and should not be ruled out as a potential universal screening measure. Implications are discussed along with suggestions for future research.