Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review

• Main Authors: Abdul Bujang S.D., Selamat A., Krejcar O., Mohamed F., Cheng L.K., Chiu P.C., Fujita H.
• Other Authors: 24467381700
• Format: Review
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Subjects: education; Imbalanced classification; machine learning; prediction model; student grade prediction; systematic literature review; Classification (of information); Education computing; Forecasting; Learning systems; Grade predictions; High educations; Machine-learning; Prediction modelling; Predictive models; Student grade prediction; Student success; Students' grades; Systematic literature review; Students
• Institution: Universiti Tenaga Nasional

Student success is essential for improving the higher education system student outcome. One way to measure student success is by predicting students' performance based on their prior academic grades. Concerning the significance of this area, various predictive models are widely developed and ap...