Student models construction by using information criteria

This paper proposes a construction method of Student models for Intelligent Tutoring Systems(ITSs) by using information criteria, This proposal provides a method to automatically construct the optimum Student model from data. The main problem when the traditional information criteria are employed to construct a model is that large amount of data, which are difficult to obtain in actual school situations, need to be obtained. This paper proposes a new criterion for using a smaller amount of data by utilizing a teacher's expert knowledge. Concretely, 1) the general predictive distribution is derived, and 2) the determination method of the hyper parameters by using a teacher's expert knowledge is proposed, Finally, some Monte Carlo experiments comparing some information criteria (ABIC, BIC, MDL, and the exact predictive distribution) are performed. The results show that the proposed method provides the best performance.