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…

Spurred by the "No Child Left Behind Act" of 2001, virtually every educational reform program now includes an accountability component that requires sound data collection and reporting (NCLB, 2002, section 101). Drawing from empirically based and theoretical literature in the field, this dissertation examines Adequate Yearly Progress…

Because of advances in psychotropic medications, psychiatric rehabilitation methods, the implementation of civil rights legislation, and empowerment movement of consumers with psychiatric disabilities, students with mental illnesses are increasingly able to access and complete higher education. Disability services offices on college campuses can…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…