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…

Millions of American children reach 4th grade without learning to read proficiently. The shortfall is especially pronounced among low-income children. Reading proficiently by the end of 3rd grade is a crucial marker in a child's educational development. Failure to read proficiently is linked to higher rates of school dropout, which suppresses…

Data from a population-based repository in Manitoba showed that students who are male, young for grade, and in Grades 1, 2, 7, and 8 were the most likely to be retained. After controlling for key student factors including socioeconomic status, school changes, and key school characteristics including stability of the student body, retention was a…