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Massive Open Online Courses (MOOCs) platforms are becoming increasinglypopular in recent years. Online learners need to watch the whole course videoon MOOC platforms to learn the underlying new knowledge, which is often tediousand time-consuming due to the lack of a quick overview of the covered knowledgeand their structures. In this paper, we propose ConceptThread, a visualanalytics approach to effectively show the concepts and the relations amongthem to facilitate effective online learning. Specifically, given that themajority of MOOC videos contain slides, we first leverage video processing andspeech analysis techniques, including shot recognition, speech recognition andtopic modeling, to extract core knowledge concepts and construct thehierarchical and temporal relations among them. Then, by using a metaphor ofthread, we present a novel visualization to intuitively display the conceptsbased on video sequential flow, and enable learners to perform interactivevisual exploration of concepts. We conducted a quantitative study, two casestudies, and a user study to extensively evaluate ConceptThread. The resultsdemonstrate the effectiveness and usability of ConceptThread in providingonline learners with a quick understanding of the knowledge content of MOOCvideos.

ConceptThread: Visualizing Threaded Concepts in MOOC Videos