ConceptThread: Visualizing threaded concepts in MOOC videos

Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered...

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Main Authors: ZHOU, Zhiguang, YE, Li, CAI, Lihong, WANG, Lei, WANG, Yigang, WANG, Yongheng, CHEN, Wei, Yong WANG
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Language:English
Published: Institutional Knowledge at Singapore Management University 2024
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Online Access:https://ink.library.smu.edu.sg/sis_research/8655
https://ink.library.smu.edu.sg/context/sis_research/article/9658/viewcontent/2401.11132.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-96582024-04-18T01:28:09Z ConceptThread: Visualizing threaded concepts in MOOC videos ZHOU, Zhiguang YE, Li CAI, Lihong WANG, Lei WANG, Yigang WANG, Yongheng CHEN, Wei Yong WANG, Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered knowledge and their structures. In this paper, we propose ConceptThread , a visual analytics approach to effectively show the concepts and the relations among them to facilitate effective online learning. Specifically, given that the majority of MOOC videos contain slides, we first leverage video processing and speech analysis techniques, including shot recognition, speech recognition and topic modeling, to extract core knowledge concepts and construct the hierarchical and temporal relations among them. Then, by using a metaphor of thread, we present a novel visualization to intuitively display the concepts based on video sequential flow, and enable learners to perform interactive visual exploration of concepts. We conducted a quantitative study, two case studies, and a user study to extensively evaluate ConceptThread . The results demonstrate the effectiveness and usability of ConceptThread in providing online learners with a quick understanding of the knowledge content of MOOC videos. 2024-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8655 info:doi/10.1109/TVCG.2024.3361001 https://ink.library.smu.edu.sg/context/sis_research/article/9658/viewcontent/2401.11132.pdf http://creativecommons.org/licenses/by/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer aided instruction Concept map Data mining Data visualization Education Electronic learning MOOC summarization online learning Videos Visual analytics visualization in education Online and Distance Education Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer aided instruction
Concept map
Data mining
Data visualization
Education
Electronic learning
MOOC summarization
online learning
Videos
Visual analytics
visualization in education
Online and Distance Education
Software Engineering
spellingShingle Computer aided instruction
Concept map
Data mining
Data visualization
Education
Electronic learning
MOOC summarization
online learning
Videos
Visual analytics
visualization in education
Online and Distance Education
Software Engineering
ZHOU, Zhiguang
YE, Li
CAI, Lihong
WANG, Lei
WANG, Yigang
WANG, Yongheng
CHEN, Wei
Yong WANG,
ConceptThread: Visualizing threaded concepts in MOOC videos
description Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered knowledge and their structures. In this paper, we propose ConceptThread , a visual analytics approach to effectively show the concepts and the relations among them to facilitate effective online learning. Specifically, given that the majority of MOOC videos contain slides, we first leverage video processing and speech analysis techniques, including shot recognition, speech recognition and topic modeling, to extract core knowledge concepts and construct the hierarchical and temporal relations among them. Then, by using a metaphor of thread, we present a novel visualization to intuitively display the concepts based on video sequential flow, and enable learners to perform interactive visual exploration of concepts. We conducted a quantitative study, two case studies, and a user study to extensively evaluate ConceptThread . The results demonstrate the effectiveness and usability of ConceptThread in providing online learners with a quick understanding of the knowledge content of MOOC videos.
format text
author ZHOU, Zhiguang
YE, Li
CAI, Lihong
WANG, Lei
WANG, Yigang
WANG, Yongheng
CHEN, Wei
Yong WANG,
author_facet ZHOU, Zhiguang
YE, Li
CAI, Lihong
WANG, Lei
WANG, Yigang
WANG, Yongheng
CHEN, Wei
Yong WANG,
author_sort ZHOU, Zhiguang
title ConceptThread: Visualizing threaded concepts in MOOC videos
title_short ConceptThread: Visualizing threaded concepts in MOOC videos
title_full ConceptThread: Visualizing threaded concepts in MOOC videos
title_fullStr ConceptThread: Visualizing threaded concepts in MOOC videos
title_full_unstemmed ConceptThread: Visualizing threaded concepts in MOOC videos
title_sort conceptthread: visualizing threaded concepts in mooc videos
publisher Institutional Knowledge at Singapore Management University
publishDate 2024
url https://ink.library.smu.edu.sg/sis_research/8655
https://ink.library.smu.edu.sg/context/sis_research/article/9658/viewcontent/2401.11132.pdf
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