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http://dx.doi.org/10.9708/jksci.2011.16.7.127

A Method for Recommending Learning Contents Using Similarity and Difficulty  

Park, Jae -Wook (Dept. of Computer Science and Engineering, Dongguk University-Seoul)
Lee, Yong-Kyu (Dept. of Computer Science and Engineering, Dongguk University-Seoul)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.7, 2011 , pp. 127-135 More about this Journal
Abstract
It is required that an e-learning system has a content recommendation component which helps a learner choose an item. In order to predict items concerning learner's interest, collaborative filtering and content-based filtering methods have been most widely used. The methods recommend items for a learner based on other learner's interests without considering the knowledge level of the learner. So, the effectiveness of the recommendation can be reduced when the number of overall users are relatively small. Also, it is not easy to recommend a newly added item. In order to address the problem, we propose a content recommendation method based on the similarity and the difficulty of an item. By using a recommendation function that reflects both characteristics of items, a higher-level leaner can choose more difficult but less similar items, while a lower-level learner can select less difficult but more similar items, Thus, a learner can be presented items according to his or her level of achievement, which is irrelevant to other learner's interest.
Keywords
Learning Content; Recommendation System; Similarity; Difficulty;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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