crossrefAI2026-07-18
Predicting Student Stress Using Machine Learning Ensemble Models: A Multi-Criteria Comparison with Explainable Artificial Intelligence Analysis
Daniel Cristóbal Andrade-Girón, William Joel Marin-Rodriguez, Marcelo Gumercindo Zuñiga-Rojas, Abrahan Cesar Neri-Ayala, Edgar Tito Susanibar-Ramírez, Miguel Angel Aguilar-Luna-Victoria
Student stress is a significant mental health issue in educational settings; therefore, developing reliable, calibrated, and interpretable predictive models can support the classification of observed stress levels. This study analyzed the public Student Stress Factors dataset, co…