Evaluating Learners´ Knowledge-structure using Bayesian networks

E-learners typically check their understanding by taking end-of-unit quizzes, usually as often as they like. However, the benefits of doing this are not well understood. In this research, a "consistency index", which was defined for a series of answers from repeated attempts at quizzes, was used to classify learners into groups. The difference in the structure of the acquired knowledge for each group was clarified using Bayesian networks. As a result, learners who require additional individual counseling can be objectively detected by the index. Using networks that teachers thought to be ideal, adequate individual counseling for each learner can be provided.