Feng, M., Heffernan, N. (2010). Using Data Mining Findings to Aid Searching for Better Skill Models. In Proceedings of the 10th International Conference on Intelligent Tutoring Systems (ITS 2010), Pittsburgh, PA. 2010.
One key component of creating an intelligent tutoring system is forming a model that monitors student behavior. Researchers in machine learning area have been using automatic/semi-automatic techniques to search for skill models. One of the semi-automatic approach is learning factor analysis (LFA, Cen, Koedinger & Junker, 2006), which involves human making hypothesis and identifying difficulty factors in the related items. In this paper, we propose a hybrid approach in which we leverage findings from our previous educational data mining work to aid the search for a better skill model and thus, improve the efficiency of LFA. Preliminary results suggest that our approach can lead to significantly better fitted skill models fast.
Keywords: Data mining, transfer model, learning factor analysis.