Vadlya Maarif

Interpretable Machine Learning for Early Detection of Academically At-Risk Students Using Behavioral, Socio-Demographic and Learning-Related Factors

The increasing adoption of learning analytics in higher education has encouraged the development of machine learning models for the early detection of academically at-risk students. However, many predictive models emphasize accuracy while providing limited interpretability for educators and academic advisors. This stud...