1. J. Bayer, H. Bydzovská, J. Géryk, T. Obšıvac, and L. Popelınský, “Predicting drop-out from social behaviour of students,” in Proceedings of the 5th International Conference on Educational Data Mining-EDM 2012, 2012, pp. 103-109.
2. C. Romero, P. G. Espejo, A. Zafra, J. R. Romero, and S. Ventura, “Web usage mining for predicting final marks of students that use Moodle courses,” Computer Applications in Engineering Education, vol. 21, pp. 135-146, 2013.
3. E. J. Lauría and J. Baron, “Mining Sakai to Measure Student Performance: Opportunities and Challenges in Academic Analytics.”
4. N. Thai-Nghe, L. Drumond, A. Krohn-Grimberghe, and L. Schmidt-Thieme, “Recommender system for predicting student performance,” Procedia Computer Science, vol. 1, pp. 2811-2819, 2010.
5. N. Bousbia and I. Belamri, “Which Contribution Does EDM Provide to Computer-Based Learning Environments?,” in Educational Data Mining, ed: Springer, 2014, pp. 3-28.