Difference between revisions of "At-risk/Dropout/Stopout/Graduation Prediction"
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Gardner, Brooks and Baker (2019) [[https://www.upenn.edu/learninganalytics/ryanbaker/LAK_PAPER97_CAMERA.pdf pdf]] | Gardner, Brooks and Baker (2019) [[https://www.upenn.edu/learninganalytics/ryanbaker/LAK_PAPER97_CAMERA.pdf pdf]] | ||
* Model predicting MOOC dropout | * Model predicting MOOC dropout | ||
* Some algorithms studied performed worse for female students than male students | * Some algorithms studied performed worse for female students than male students, particularly in courses with 45% or less male presence | ||
Revision as of 02:55, 24 January 2022
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
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
Gardner, Brooks and Baker (2019) [pdf]
- Model predicting MOOC dropout
- Some algorithms studied performed worse for female students than male students, particularly in courses with 45% or less male presence