Using Reinforcement Learning with Multi-Group Fairness to Predict Students' Algebra I Performance

• In Event: Using Reinforcement Learning with Multi-Group Fairness to Predict Students' Algebra I Performance

Short Description

Learning analytics techniques, including machine learning (ML), have been widely used in educational research to address various issues. However, little attention has been paid to the problem of algorithmic bias in ML. While some attempts have been made to mitigate bias in educational settings, most have focused on debiasing ML models for single group membership. This study aimed to propose an algorithmic strategy to mitigate bias in a multi-group context.

Authors

• Contributor: Fan Zhang, University of Florida

• Contributor: Wanli Xing, University of Florida

• Contributor: Chenglu Li, University of Florida