Abstract
In recent years, with the development of information technology, the use of Web-Based Training (WBT) and other individualized learning programs are increasingly used and are gaining attention. In individual online learning, efficient learning is possible by providing individualized learning materials based on the degree of understanding and growth characteristics of each learner. However, actually, appropriate teaching materials for each individual learner is not be provided, which reduces his/her motivation to learn and makes it difficult for him/her to learn. The reason is that it is difficut to establish a desirable relationship between an educator model on the learning support system and each learner. This paper proposes a learner classification method based on learners' growth curves using the neural networks for the purpose of providing appropriate learning support to each learner. Since a huge amount of data is required for training of the neural networks, this paper construct an “educator-learner” model based on a control engineering approach representing the interaction between learning support systems and each learner, and virtual learner data is generated. The usefulness of the proposed method is shown by numerical experiments.
