Brain Wave and User Profile based Learning Content Type Recom- mendation in Interactive e-Learning Environment
Kyung suk Jung, Yong Suk Choi · 2012
To date, most e-learning systems have not reflected emotion of users effectively as against off-line learning (system) that has sufficiently considered it. They might cause several problems hindering e-learning from effectiveness. Overcoming this weakness, we introduce a methodology that measures user’s brain wave and recommends learning content to user based on it. In this paper, we assume that a person would have similar tendency with someone whose brain wave patterns are like his, and use it for recommendation of learning content type. As a technique for our experiment, we use kNN-Recommendation, learning content type recommendation system, based on brain wave data that appears in studying. Our system can solve cold-start problem that occurs in typical recommendation system and we additionally propose harmony value for better accuracy of recommendation that is calculated with recommended values from preceding our profile based recommendation system. We check advanced performance using several experiments.