Formal concept analysis for an e-learning semantic web

We capture student interactions in an e-learning community to construct a semantic web (SW) to create a collective meta-knowledge structure guiding students as they search the existing knowledge corpus. We use formal concept analysis (FCA) as a knowledge acquisition tool to process the students virtual surfing trails to express and exploit the dependencies between web-pages to yield subsequent and more effective focused search results. We mirror social navigation and bypass the cumbersome manual annotation of webpages and at the same time paralleling social navigation for knowledge. We present our system KAPUST2 (Keeper and Processor of User Surfing Trails) which constructs from captured students trails a conceptual lattice guiding student queries. We use KAPUST as an e-learning software for an undergraduate class over two semesters. We show how the lattice evolved over the two semesters, improving its performance by exploring the relationship between 'kinds' of research assignments and the e-learning semantic web development. Course instructors monitored the evolution of the lattice with interesting positive pedagogical consequences. These are reported as well in this paper.