Wang Li

Predicting Student Academic Performance Based on Multi-source Heterogeneous Features and Explainable Ensemble Learning

Experimental results show that the boosting models and fusion models overall outperform the linear baseline in terms of accuracy and robustness; previous academic performance, attendance participation, homework completion rate, and behavioral investment are the most stable core predictors, while psychological stress an...