ARCHIVES

1. DAOZONG SUN, RONGXIN LUO, QI GUO, JIAXING XIE, “A University Student Performance Prediction Model and Experiment Based
on Multi-Feature Fusion and Attention Mechanism”, 2023
2. KOUSHIK ROY AND DEWAN MD. FARID, “An Adaptive Feature Selection Algorithm for Student Performance Prediction”, 2024
3. YONG SHI 1, FANG SUN2, HONGKUN ZUO3, AND FEI PENG1, “Analysis of Learning Behavior Characteristics and Prediction of
Learning Effect for Improving College Students’ Information Literacy Based on Machine Learning”, 2023
4. NUHA MOHAMMED ALRUWAIS, “Deep FM-Based Predictive Model for Student Dropout in Online Classes”, 2023
5. MUSTAPHA SKITTOU , MOHAMED MERROUCHI, AND TAOUFIQ GADI, “Development of an Early Warning System to Support
Educational Planning Process by Identifying At-Risk Students”, 2023
6. MUHAMMAD ADNAN, EMEL KHAN, FAHD S. ALHARITHI, AND AHMAD A. ALZAHRANI, “Earliest Possible Global and Local
Interpretation of Students’ Performance in Virtual Learning Environment by Leveraging Explainable AI”, 2022
7. ESSA ALHAZMI AND ABDULLAH SHENEAMER, “Early Predicting of Students Performance in Higher Education”, 2023
8. N. R. RAJI 1, R. MATHUSOOTHANA S. KUMAR2, AND C. L. BIJI, “Explainable Machine Learning Prediction for the Academic
Performance of Deaf Scholars”, 2024
9. MAI ABDALKAREEM AND NASRO MIN-ALLAH, “Explainable Models for Predicting Academic Pathways for High School Students in
Saudi Arabia”, 2024
10. SITI DIANAH ABDUL BUJANG1,2, ALI SELAMAT, “Imbalanced Classification Methods for Student Grade Prediction: A Systematic
Literature Review”, 2023
11. GABRIELA CZIBULA 1, GEORGE CIUBOTARIU1, MARIANA-IOANA MAIER1, “IntelliDaM: A Machine Learning-Based Framework for
Enhancing the Performance of Decision-Making Processes. A Case Study for Educational Data Mining”, 2022
12. GHAZANFAR LATIF 1,2, SHERIF E. ABDELHAMID 3, KHALED S. FAWAGREH1, “Machine Learning in Higher Education: Students’
Performance Assessment Considering Online Activity Logs”, 2023
13. AHMAD ALMADHOR 1, SIDRA ABBAS 2, (Graduate Student Member, IEEE), GABRIEL AVELINO SAMPEDRO, “Multi -Class Adaptive
Active Learning for Predicting Student Anxiety”, 202414. JIN EUN YOO1, MINJEONG RHO 1, AND YEKYUNG LEE2, “Online Students’ Learning Behaviors and Academic Success: An Analysis of
LMS Log Data from Flipped Classrooms via Regularization”, 2022
15. NAVEED ANWER BUTT 1, ZAFAR MAHMOOD1, KHAWAR SHAKEEL1, SULTAN ALFARHOOD, “Performance Prediction of Students
in Higher Education Using Multi-Model Ensemble Approach”, 2023
16. Tarik Ahajjam, Mohammed Moutaib, Haidar Aissa, Mourad Azrour, Yousef Farhaoui, and Mohammed Fattah, “Predicting Students’ Final
Performance Using Artificial Neural Networks”, 2022
17. LIDYA R. PELIMA, YUDA SUKMANA, AND YUSEP ROSMANSYAH, “Predicting University Student Graduation Using Academic
Performance and Machine Learning: A Systematic Literature Review”, 2024
18. Yuanyi Zhen, Jar-Der Luo, and Hui Chen, “Prediction of Academic Performance of Students in Online Live Classroom Interactions —an
Analysis Using Natural Language Processing and Deep Learning Methods”, 2023
19. DALIA ABDULKAREEM SHAFIQ, MOHSEN MARJANI, RIYAZ AHAMED ARIYALURAN HABEEB, AND DAVID ASIRVATHAM, “Student
Retention Using Educational Data Mining and Predictive Analytics: A Systematic Literature Review”, 2022
20. REYHAN ZEYNEP PEK 1, SIBEL TARIYAN ÖZYER2, TAREK, “The Role of Machine Learning in Identifying Students At -Risk and
Minimizing Failure”, 2023