Reconstructing Learning Resource with Collective Knowledge

Abstract

There currently exist a lot of Web resources, which are useful for learning. However, it is hard for learners to learn these learning resources since the hyperspace is not always well-structured. Our approach to this issue is to mine collective knowledge from a group of learners who learned these resources to reconstruct the hyperspace, which consists of useful pages and links to be learned. This paper proposes a collective knowledge mining method that can extract these useful pages and links from learning histories gathered from the group of learners. The results of the analysis with case data indicate the possibility that this method extracts valid pages and links as collective knowledge.