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…

A long standing debate among policymakers as well as researchers is whether and how funding affects the quality of education. Often missing from the discussion is information about the costs of providing education at the school level and below, yet such information could impart a better indication of the linkages between outcomes and resources…