Generating Guided Map for Scaffolding Navigation Planning of Self-Directed Learning in Hyperspace

Abstract

Planning navigation process in hyperspace is an important activity for learning hypermedia-based Web resources. However, learners often fail to plan their navigation process in a self-directed way. Our approach to this issue is to provide learners with a guided map, which not only represents hyperspace but also highlights representative pages and links to be learned in the hyperspace. This paper describes the guided map generation with navigation history mining, which extracts the representative pages and links from a repository accumulating learning histories obtained from a set of learners who learned the same Web resource with the same learning goal. The number of the extracted pages and links is around the average of the ones learned by the learners. We also describe a case study with the guided map. The results indicate that it can scaffold learners’ navigation planning process.