A team of students lead by ECE faculty member Genevieve Lipp will use mastery learning data from a graduate programming course to develop a tool for predicting student performance and inform beneficial course policies. Given the grade, timeliness, and number of submissions for each autograded programming assignment, the team will develop a model for data trends that can predict a student will struggle before there are other indications, such as test grades. Identifying this model will help instructors of the course set policies that help students succeed and reach out early when a student may need extra help.
Project Lead: Genevieve Lipp, Duke ECE
Project Manager: Rafael Davila Bugarin
