At-risk/Dropout/Stopout/Graduation Prediction

Hu and Rangwala (2020) pdf

• Models predicting if student at-risk for failing a course
• Several algorithms perform worse for African-American students

Kai et al. (2017) pdf

• Models predicting student retention in an online college program
• J48 decision trees achieved much lower Kappa and AUC for Black students than White students
• JRip decision rules achieved almost identical Kappa and AUC for Black students and White students
• J-Rip model performed moderately better for female students than male students
• J-Rip decision tree model performed more equitably than a J-48 decision tree model for both male and female students.

Anderson et al. (2019) pdf

• Models predicting six-year college graduation
• Performance for African-American students comparable to performance for students in other races.

Yu, Lee, and Kizilcec (2021)[pdf]

• Model predicting college dropout
• worse true negative rates and better recall for students who are not White or Asian, and also worse accuracy if the student is studying in person

Gardner, Brooks and Baker (2019) [pdf]

• Model predicting MOOC dropout, specifically through slicing analysis
• Some algorithms performed worse for female students than male students, particularly in courses with 45% or less male presence