Interpretable Student Academic Performance Analysis Using Hybrid Feature Selection and Explainable Artificial Intelligence

We used hybride feature selection method. There were three feature selection methods: Mutual Information, RFE, and Random Forest. These methods helped us reduce 40 features to 15 important features. Ridge Regression gave the best result with an R² of 0.7353. We also used SHAP to understand which factors most affect student performance.