Supporting Peer Help Recommendation Based on Learner-Knowledge Model

Abstract

With the development of information technology tools and the Internet, computer-supported collaborative learning has become increasingly accessible and promising. Peer help is a popular practice of collaborative learning. In this paper, we propose a way to realize intelligently mediated peer help. We obtain open learning activity data from an integrated learning platform called LEAF for modeling. First, we create a network-based knowledge model. Then, we construct learner models associated with the knowledge model. Based on the knowledge and learner modeling, we propose a method to find problems of a learner based on the order of closeness centrality of knowledge nodes. Also, the system recommends potential peer helpers who can help with these problems. We present a scenario of physics learning at the high school level to explain the practical use of this method which is aimed to enhance learners’ initiative during peer help.