Madina Yelemessova

A Multi-Model Approach to Academic Performance Prediction Using Student–Semester Educational Data

Identifying students at academic risk early calls for forecasting that respects the temporal structure of educational data and stays readable for advising staff. In this work, linear, gradient-boosted, and deep tabular models are compared under one protocol on two tasks: next-semester performance prediction and binary...