ARCHIVES
Original Article
AI In Academia: Forecasting Student Dropouts
Dr. Deepali Y. Kirange1
Dr. Yogesh N. Chaudhari2
12Assistant Professor, KCES’s Institute of Management and Research, Jalgaon, Maharashtra, India.
Published Online: July-August 2025
Pages: 11-14
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20250504002
References
1. Lee, J., Kim, M., Kim, D., & Gil, J.-M. (2021). Evaluation of predictive models for early identification of dropout students. Journal of Information Processing Systems, 17(3), 630–644. https://doi.org/10.3745/JIPS.04.0218
2. Fernandes, J. (2023). The role of data driven decision making in effective educational leadership. Academy of Educational Leadership Journal, 27(S2), 1–3.
3. Kim, S., Yoo, E., & Kim, S. (2023). Why do students drop out? University dropout prediction and associated factor analysis using machine learning techniques (arXiv: 2310.10987). arXiv. https://doi.org/10.48550/arXiv.2310.10987
4. Alhardi, A., & Alan, S. (2024), Predicting Student Dropout in Higher Education Using Machine Learning Techniques: A Predictive Model Using XGBoost Algorithm. International Conference on Engineering Technologies (ICENTE’24).
5. Vaarma, M., & Li, H. (2024), Predicting student dropouts with machine learning: An empirical study in Finnish higher education. Technology in Society, 76, Article 102474. https://doi.org/10.1016/j.techsoc.2024.102474
6. Albugami, S., Almaghrabi, H., & Wali, A. (2024), from data to decision: Machine learning and explainable AI in student dropout prediction. Journal of e Learning and Higher Education, 2024, Article 246301. https://doi.org/10.5171/2024.246301
7. Mduma, N., Kalegele, K., & Machuve, D. (2019). A survey of machine learning approaches and techniques for student dropout prediction. Data Science Journal, 18, 1–23. https://doi.org/10.5334/dsj-2019-014
2. Fernandes, J. (2023). The role of data driven decision making in effective educational leadership. Academy of Educational Leadership Journal, 27(S2), 1–3.
3. Kim, S., Yoo, E., & Kim, S. (2023). Why do students drop out? University dropout prediction and associated factor analysis using machine learning techniques (arXiv: 2310.10987). arXiv. https://doi.org/10.48550/arXiv.2310.10987
4. Alhardi, A., & Alan, S. (2024), Predicting Student Dropout in Higher Education Using Machine Learning Techniques: A Predictive Model Using XGBoost Algorithm. International Conference on Engineering Technologies (ICENTE’24).
5. Vaarma, M., & Li, H. (2024), Predicting student dropouts with machine learning: An empirical study in Finnish higher education. Technology in Society, 76, Article 102474. https://doi.org/10.1016/j.techsoc.2024.102474
6. Albugami, S., Almaghrabi, H., & Wali, A. (2024), from data to decision: Machine learning and explainable AI in student dropout prediction. Journal of e Learning and Higher Education, 2024, Article 246301. https://doi.org/10.5171/2024.246301
7. Mduma, N., Kalegele, K., & Machuve, D. (2019). A survey of machine learning approaches and techniques for student dropout prediction. Data Science Journal, 18, 1–23. https://doi.org/10.5334/dsj-2019-014
Related Articles
2025
A Comprehensive Review on Antibiotic Resistance
2025
AI-Driven Conversational Models for Supporting Migrant Career Guidance and Labour Market Integration: A Scoping Review
2025
Cloud-Based MIS Framework for Streamlining Outcome-Based Education Evaluation in Higher Education
2025
A Scalable System Design for Real-Time Personalized Recommendation Engines in E-Commerce
2025
AI-Powered Career Advisor (A Personalized Career Guidance System)
2025
