Stealth assessment has been successfully embedded in educational games to measure students' learning in an unobtrusive and supportive way. This study explored the possibility of applying stealth assessment in a digital reading platform and sought to identify potential in-system indicators of students' digital learning outcomes. Utilizing the user…

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…