The power of Deep Learning techniques for predicting student performance in Virtual Learning Environments: A systematic literature review

Author:

Alnasyan Bayan,Basheri Mohammed,Alassafi Madini

Publisher

Elsevier BV

Reference102 articles.

1. Can we predict success from log data in vles? Classification of interactions for learning analytics and their relation with performance in vle-supported f2f and online learning;Agudo-Peregrina;Computers in Human Behavior,2014

2. The effectiveness of using deep learning algorithms in predicting students achievements;Akour;Indonesian Journal of Electrical Engineering and Computer Science,2020

3. A flexible feature selection approach for predicting students' academic performance in online courses;Al-Zawqari;Computers and Education: Artificial Intelligence,2022

4. A systematic literature review of student' performance prediction using machine learning techniques;Albreiki;Education Sciences,2021

5. Predicting student outcomes in online courses using machine learning techniques: A review;Alhothali;Sustainability,2022

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