Study of mining models of understanding by structuring reference history under Web learning environment

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We realized the idea of the state transition model that composed page reference relation of the learner by the node and the edge. Then by the statistical work of reference histories of more than 150 Web learners, we completed the platform that structures and extracts the state transition model. The result was published in the international conference proceedings of Global Learn Asia Pacific 2011. Based on the answers of Web learners to questionnaires about the content of support, we designed the mining models presumed learner's state of knowledge, and out of a large amount of learner's reference histories a state transition candidate that is the nearest to a current transition process of learning was retrieved, and displayed to the learner from whom the continuance of learning became difficult. We explained this result at the SITE2013 round table conference.