A Dual-Model Framework for Early Identification of At-Risk Students Using Gradient Boosting and Logistic Regression

Early identification of academically at-risk students is a critical challenge in education, as timely intervention can significantly improve student outcomes and retention. Many existing student performance prediction approaches rely on assessment dat