Chien-Lin Tang
Hao-Chuan Wang
ABSTRACT
People increasingly use online video platforms, e.g., YouTube, to locate educational videos to acquire knowledge or skills to meet personal learning needs. However, most of existing video platforms display video search results in generic ranked lists based on relevance to queries. These relevance-based information display does not take into account the inner structure of the knowledge domain, and may not suit the need of online learners. In this paper, we present ConceptGuide, a prototype system for learning orientations to support ad hoc online learning from unorganized video materials. ConceptGuide features a computational pipeline that performs content analysis on the transcripts of YouTube videos queried by the user and generates concept-map-based visual recommendations of conceptual and content links between videos, forming learning pathways to provide structures feasible and usable for learners to consume.
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Index Terms
- Supporting Online Video Learning with Concept Map-based Recommendation of Learning Path
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