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…

Making robust and reliable information about schools accessible is one of the most powerful ways to foster engagement and promote informed decisions that will shape our communities. Though education data is frequently collected and aggregated at the state level, data is rarely synthesized across cities. This report provides comparable information…