Difference between revisions of "Course Grade and GPA Prediction"

Revision as of 00:54, 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]

Model predicting undergraduate course grades and average GPA
students of several racial backgrounds were inaccurately predicted to perform worse than other students

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

@@ Line 10: / Line 10: @@
 Riazy et al. (2020) [[https://www.scitepress.org/Papers/2020/93241/93241.pdf pdf]]
-* Model predicting course outcome
+* Models predicting course outcome of students in a virtual learning environment (VLE)
-* Fairly marginal differences were found for prediction quality and in overall proportion of predicted pass between groups
+* Students with self-declared disability were predicted to pass the course with 16-23 percentage points in favor from the training and test set
-* Inconsistent in direction between algorithms