Paper Info
Title
Supporting Online Video Learning with Concept Map-based Recommendation of Learning Path
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.
Year
DOI
Venue
2020
10.1145/3334480.3382943
CHI '20: CHI Conference on Human Factors in Computing Systems Honolulu HI USA April, 2020
Keywords
DocType
ISBN
Education/Learning, Information Seeking & Search, Visualization, Concept map
Conference
978-1-4503-6819-3
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Chien-Lin Tang100.34
Jingxian Liao201.01
Hao-Chuan Wang329645.80
Ching-Ying Sung4223.19
Yu-Rong Cao500.68
Wen-Chieh Lin647644.50