1. Yukselturk, E., Ozekes, S., & Turel, Y. K. (2014). Predicting dropout student: An application of data mining methods in an online education program. European Journal of Open, Distance and E-Learning., 17(1), 118–133.
2. Lin, J. J. J., Imbrie ,P. K., & Reid, K. J. (2009). Student retention modelling: An evaluation of different methods and their impact on prediction results. In 2009 Research in Engineering Education Symposium REES 2009 (January).
3. Hu, Y.-H., Lo, C.-L., & Shih, S.-P. (2014). Developing early warning systems to predict students’ online learning performance. Computers in Human Behavior, 36, 469–478.
4. Jia, P., & Maloney, T. (2015). Using predictive modelling to identify students at risk of poor university outcomes. Higher Education, 70(1), 127–149.
5. Chun-Teck, L. (2010). Predicting preuniversity students’ mathematics achievement (published conference proceedings style). In: International conference on mathematics education research, multimedia university, Malaysia (pp. 299–306).