Making Static Online Teaching Materials Be Flexible to Learners by Reconstructing Its Hypermedia Structures Automatically

Abstract

Many teachers and researchers put their teaching materials on the Internet for students to read in recent years. This sort of teaching materials could be seen as static because students can only follow the learning sequence made by teachers in advance. The goal of this paper is trying to develop a tool, K-Navi toolbar, to parse and rebuild teaching materials' hypermedia structures according to the concept relations and extracted rules automatically. K-Navi toolbar first uses the formal concept analysis (FCA) to parse the whole set of teaching materials and gets the embedded concept relations between each of two instructional documents; then uses the association rule methodology (ARM) to extract the rules from the concept lattices; and, finally rebuilds the hypermedia structure of the instructional document read by the student automatically. K-Navi toolbar adds related concept hyperlinks (or says links to other knowledge pieces) into the specific position on the instructional hypermedia document automatically when a student asks the document resource. A student then will be able to dig related knowledge pieces via these relevant hyperlinks.