1. Molina, M. M., Luna, J. M., Romero, C., & Ventura, S.: Meta-learning approach for automatic parameter tuning: a case of study with educational datasets. In Proceedings of the 5th international conference on educational data mining. pp. 180–183, (2012).
2. Pardos, Z. A., Wang, Q. Y., & Trivedi, S.: The real world significance of performance prediction. (2012).
3. Thai-Nghe, N., Horváth, T., & Schmidt-Thieme, L: Factorization models for forecasting student performance. In Proceedings of the 4th international conference on educational data mining. pp. 11–20, (2011).
4. B. Sen, E. Ucar, D. delen: Predicting and analyzing secondary education placement-test scores. (2012).
5. Baker, R. S. J. D., Gowda, S. M., & Corbett, A. T.: Automatically detecting a student’s preparation for future learning: Help use is key. In Proceedings of the 4th international conference on educational data mining. pp. 179–188, (2011).