Predicting the Academic Success of Students (PASS)

The Predicting the Academic Success of Students (PASS) project aims to improve student self-regulated learning skills by reflecting student behaviors back to individuals.  Using predictive learning analytics, models of student activity and the correlation these models have with successful outcomes will be shown to students.  These models will be based not only on traditional indicators of success (e.g. gender, background, course registrations, incoming GPA) but will be customized for students and linked to how they interact with education technology (e.g. the Canvas LMS) in their classroom.  The end result is a set of actionable insights personalized to students that they can use to improve their course outcomes.

Project Team

Christopher Brooks, School of Information

Stephanie Teasley, School of Information