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…

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…

These proceedings contain the papers of the 11th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2014), October 25-27, 2014, which has been organized by the International Association for Development of the Information Society (IADIS) and endorsed by the Japanese Society for Information and Systems in…