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Direct linkSaleem Malik; K. Jothimani – Education and Information Technologies, 2024
Monitoring students' academic progress is vital for ensuring timely completion of their studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine learning and feature selection to gain insights into student performance. However, many feature selection algorithms lack performance forecasting systems, limiting their…
Descriptors: Algorithms, Decision Making, At Risk Students, Learning Management Systems
