Supporting Online Video Learning with Concept Map-based Recommendation of Learning Path
| Autor: | Yu-Rong Cao, Chien-Lin Tang, Ching-Ying Sung, Hao-Chuan Wang, Wen-Chieh Lin, Jingxian Liao |
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| Rok vydání: | 2020 |
| Předmět: |
Structure (mathematical logic)
Multimedia Computer science Concept map 05 social sciences 020207 software engineering 02 engineering and technology computer.software_genre Pipeline (software) Visualization Domain (software engineering) Content analysis 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences Relevance (information retrieval) computer 050107 human factors |
| Zdroj: | CHI Extended Abstracts |
| DOI: | 10.1145/3334480.3382943 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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