Paper Info
Title
ConceptGuide: Supporting Online Video Learning with Concept Map-based Recommendation of Learning Path
Abstract
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. The design of relevance-oriented 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 retrieved for a topic, and generates concept-map-based visual recommendations of inter-concept and inter-video links, forming learning pathways as structures for learners to consume. We evaluated ConceptGuide by comparing the design to the general-purpose interface of YouTube in learning experiences and behaviors. ConceptuGuide was found to improve the efficiency of video learning and helped learners explore the knowledge of interest in many constructive ways.
Year
DOI
Venue
2021
10.1145/3442381.3449808
International World Wide Web Conference
Keywords
DocType
Citations 
Education/Learning, Information Seeking & Search, Visualization, Concept Map
Conference
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Chien-Lin Tang100.34
Jingxian Liao201.01
Hao-Chuan Wang329645.80
Ching-Ying Sung4223.19
Wen-Chieh Lin547644.50