Difference between revisions of "Course Grade and GPA Prediction"
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Yu et al. (2020) [[https://files.eric.ed.gov/fulltext/ED608066.pdf pdf]] | Yu et al. (2020) [[https://files.eric.ed.gov/fulltext/ED608066.pdf pdf]] | ||
* | * Models predicting undergraduate course grades and average GPA | ||
*students of several racial backgrounds were inaccurately predicted to perform worse than other students | *students of several racial backgrounds were inaccurately predicted to perform worse than other student | ||
* First-generation college students were inaccurately predicted to lower than class media final course grade and lower average GPA | |||
* Fairness of models improved with the inclusion of clickstream and survey data | |||
Riazy et al. (2020) [[https://www.scitepress.org/Papers/2020/93241/93241.pdf pdf]] | Riazy et al. (2020) [[https://www.scitepress.org/Papers/2020/93241/93241.pdf pdf]] | ||
Revision as of 06:00, 17 February 2022
Lee and Kizilcec (2020) [pdf]
- Model predicting college course grade of median or above
- Out-of-the-box random forest model violates demographic parity and equality of opportunity for URM (underrepresented minority: American Indian, Black, Hawaiian or Pacific Islander, Hispanic, and Multicultural) than for non-URM students (White and Asian)
Yu et al. (2020) [pdf]
- Models predicting undergraduate course grades and average GPA
- students of several racial backgrounds were inaccurately predicted to perform worse than other student
- First-generation college students were inaccurately predicted to lower than class media final course grade and lower average GPA
- Fairness of models improved with the inclusion of clickstream and survey data
Riazy et al. (2020) [pdf]
- Models predicting course outcome of students in a virtual learning environment (VLE)
- Students with self-declared disability were predicted to pass the course with 16-23 percentage points in favor from the training and test set