Harvesting latent and usage-based metadata in a course management system to enrich the underlying educational digital library

Abstract

In this case study, we demonstrate how in an integrated digital library and course management system, metadata can be generated using a bootstrapping mechanism. The integration encompasses sequencing of content by teachers and deployment of content to learners. We show that taxonomy term assignments and a recommender system can be based almost solely on usage data (especially correlations on what teachers have put in the same course or assignment). In particular, we show that with minimal human intervention, taxonomy terms, quality measures, and an association ruleset can be established for a large pool of fine-granular educational assets.