Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

In this study, we use the US nationally representative Early Childhood Longitudinal Study-Kindergarten Cohort to examine inequalities in opportunities to learn mathematics. Specifically, we examine the characteristics of US students' elementary school math teachers and the instruction they provide. While our findings are consistent with previous…