M. Namba (Japan)
Estimation, Understanding level, Tri-valued Output Cellular Neural Network for Associative Memory
In self-directed e-learning, it is important to diagnose learner’s understanding level and give feedback to him. This study aims to construct an ITS which has a function that diagnoses learner’s understanding level and gives ap propriate feedback to him. This paper describes a new es timation system of understanding level with a Tri-valued Output Cellular Neural Network(T-CNN) for Associative Memory. In first experiment, T-CNN could classify all par ticipants into expected understanding levels. We confirmed that the result is valid by consideration of accuracy and an swer time. In second experiment, we compared estimation ability of T-CNN with that of linear function(conventional method) in accordance with precision. The results provide us that an effectiveness of T-CNN estimation.
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