Studying Achievement Gap Using a Large-Scale Assessment: A Quantile Regression Approach

• In Event: 43.050 - WITHDRAWN: New Research Methods for Large-Scale Assessments

Abstract

In order to assess progress towards achieving parity among students subgroups by Grade 3, this study reports the achievement gap patterns on the Common Core State Standards-aligned English language Arts Smarter Balanced Assessment adopted by the Hawaii Department of Education. The dataset included over 14,000 third-graders from the 2017-18 cohort. Using ordinary least squares regression and quantile regression methods, results indicate that the mean achievement gaps adequately represents most subgroup differences, however, for the English language learners and students with disabilities, their gaps tend to be larger at the upper levels of the outcome distribution, while for male and female students the gap tends to diminish at those levels. Policy and pedagogical considerations about the findings are discussed.

Authors

• Hugh H. Dunn, University of Hawaii

• Malkeet Singh, Wake County Public School System