A Test Theory Using Probabilistic Network.

This paper aims at estimation of the state of the knowledge (understanding) of the individual learner by executing a test composed of a small number of items. The following approach is proposed: (1) a teacher model is introduced, and the inference process for the understanding state of the learner is represented using the Bayesian network; (2) as the network information of the items based on the teacher model, EVINI (expected value of item network information) is proposed. As the test information, EVTIN (expected value of test information with network) is proposed; and (3) a strategy for item selection based on EVINI is proposed. The following advantages are realized in practice: (1) only a small amount of data is required to construct the model; (2) the goal of inference is to know the understanding state of the individual learner, and the result provides the feedback from an educational viewpoint; (3) the knowledge of the teacher about the domain can be utilized in the inference process, which helps to improve the prediction efficiency; and (4) it is easy to add or modify the knowledge of the teacher model. In this paper, the proposed technique is applied to the real data, as the inference example of the method. The strategy for presenting the items is compared to item response theory, and discussions are made from the theoretical viewpoint. [ABSTRACT FROM AUTHOR]