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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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 |
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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 |
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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. |
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ZHOU, Zhiguang YE, Li CAI, Lihong WANG, Lei WANG, Yigang WANG, Yongheng CHEN, Wei Yong WANG, |
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ZHOU, Zhiguang YE, Li CAI, Lihong WANG, Lei WANG, Yigang WANG, Yongheng CHEN, Wei Yong WANG, |
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ZHOU, Zhiguang |
title |
ConceptThread: Visualizing threaded concepts in MOOC videos |
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ConceptThread: Visualizing threaded concepts in MOOC videos |
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ConceptThread: Visualizing threaded concepts in MOOC videos |
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ConceptThread: Visualizing threaded concepts in MOOC videos |
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ConceptThread: Visualizing threaded concepts in MOOC videos |
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conceptthread: visualizing threaded concepts in mooc videos |
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Institutional Knowledge at Singapore Management University |
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2024 |
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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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