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…

The Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011), is collecting information about the early educational experiences of a nationally representative sample of children who were in kindergarten or who were of kindergarten age in ungraded classrooms or schools in the 2010-11 school year. The data collection began in…

Schools and communities across Montana are working hard to ensure that students receive the best education and graduate ready for college and careers. One of the most important components in this effort involves understanding where students are and how schools and communities can best help them achieve at the highest levels. Data is an invaluable…