Comparative Statistical Validation of Ensemble and Deep Learning Models for Enhanced Student Performance Prediction in Computer-Aided Learning Environments
Empirical findings conclusively demonstrate that ensemble and deep learning methods significantly surpass traditional statistical approaches in predictive accuracy and robustness in Computer-Aided Learning systems, and provide strong empirical support for integrating advanced ML models into CAL environments.