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

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

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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...

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Bibliographic Details
Main Authors: Siti Dianah Abdul Bujang, Ali Selamat, Ondrej Krejcar, Farhan Mohamed, Lim Kok Cheng, Po Chan Chiu, Hamido Fujita
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Imbalanced classification
prediction model
machine learning
student grade prediction
education
systematic literature review
Online Access:https://ieeexplore.ieee.org/document/9965398/

Internet

https://ieeexplore.ieee.org/document/9965398/

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