Bridging Over from Learning Videos to Learning Resources Through Automatic Keyword Extraction

Abstract

The presented system and approach facilitate intelligent, contextualized information access for learners based on automatic learning video analysis. The underlying workflow starts with automatically extracting keywords from learning videos followed by the generation of recommendations of learning materials. The approach has been implemented and investigated in a user study in a real-world VET setting. The study investigated the acceptance, perceived quality and relevance of automatically extracted keywords and automatically generated learning resource recommendations in the context of a set of learning videos related to chemistry and chemical engineering. The results indicate that such extracted keywords are in line with user-generated keywords and summarize the content of videos quite well. Also, they can be used as search key to find relevant learning resources.