research-article

VUC: Visualizing Daily Video Utilization to Promote Student Engagement in Online Distance Education

Authors:

Guobin LiAuthors Info & Claims

CompEd '19: Proceedings of the ACM Conference on Global Computing Education

Pages 99 - 105

https://doi.org/10.1145/3300115.3309514

Published: 09 May 2019 Publication History

Abstract

Online video is widely used in various courses in online distance education (ODE). For ODE students, it is challenging to study multiple online courses and keep track of the video viewing progress each semester. In this paper, we introduce a visualization tool called video utilization calendar (VUC) for promoting student engagement with the videos of multiple online courses. VUC is designed to visualize both the current viewing progress and the daily viewing history for all the courses in a semester for students to check their viewing progress for all videos and choose any course video to view directly. To evaluate VUC, we conducted a randomized controlled trial and a survey in an ODE school. Our results demonstrate that students may spend more days online and view more course videos with the support of VUC, whereas the total video viewing time does not increase significantly. In addition, course instructors identified two patterns of video utilization, which suggests that VUC may also be of assistance to instructors in understanding how students schedule their video viewing for multiple courses.

References

[1]

Ashton Anderson, Daniel Huttenlocher, Jon Kleinberg, and Jure Leskovec. 2014. Engaging with Massive Online Courses. In Proceedings of the 23rd International Conference on World Wide Web (WWW '14). ACM, New York, NY, USA, 687--698.

Digital Library

[2]

T. Auvinen, L. Hakulinen, and L. Malmi. 2015. Increasing Students' Awareness of Their Behavior in Online Learning Environments with Visualizations and Achievement Badges. IEEE Transactions on Learning Technologies, Vol. 8, 3 (July 2015), 261--273.

Digital Library

[3]

Jiye Baek and Jesse Shore. 2016. Promoting Student Engagement in MOOCs. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale (L@S '16). ACM, New York, NY, USA, 293--296.

Digital Library

[4]

Miguel L. Bote-Lorenzo and Eduardo Gómez-Sánchez. 2017. Predicting the Decrease of Engagement Indicators in a MOOC. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (LAK '17). ACM, New York, NY, USA, 143--147.

Digital Library

[5]

Emma Brunskill, Dawn Zimmaro, and Candace Thille. 2018. Exploring the Impact of the Default Option on Student Engagement and Performance in a Statistics MOOC. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale (L@S '18). ACM, New York, NY, USA, 34:1--34:4.

Digital Library

[6]

Qing Chen, Yuanzhe Chen, Dongyu Liu, Conglei Shi, Yingcai Wu, and Huamin Qu. 2016. PeakVizor: Visual Analytics of Peaks in Video Clickstreams from Massive Open Online Courses. IEEE Transactions on Visualization and Computer Graphics, Vol. 22, 10 (Oct. 2016), 2315--2330.

Digital Library

[7]

Carleton Coffrin, Linda Corrin, Paula de Barba, and Gregor Kennedy. 2014. Visualizing Patterns of Student Engagement and Performance in MOOCs. In Proceedings of the Fourth International Conference on Learning Analytics And Knowledge (LAK '14). ACM, New York, NY, USA, 83--92.

Digital Library

[8]

R. Wes Crues, Nigel Bosch, Michelle Perry, Lawrence Angrave, Najmuddin Shaik, and Suma Bhat. 2018. Refocusing the Lens on Engagement in MOOCs. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale (L@S '18). ACM, New York, NY, USA, 11:1--11:10.

Digital Library

[9]

Paul Denny. 2013. The Effect of Virtual Achievements on Student Engagement. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). ACM, New York, NY, USA, 763--772.

Digital Library

[10]

Jennifer A Fredricks, Phyllis C Blumenfeld, and Alison H Paris. 2004. School Engagement: Potential of the Concept, State of the Evidence. Review of Educational Research, Vol. 74, 1 (March 2004), 59--109.

[11]

Philip J. Guo, Juho Kim, and Rob Rubin. 2014. How video production affects student engagement: an empirical study of MOOC videos. In Proceedings of the First (2014) ACM Conference on Learning @ Scale. ACM Press, 41--50.

Digital Library

[12]

Curtis R. Henrie, Lisa R. Halverson, and Charles R. Graham. 2015. Measuring student engagement in technology-mediated learning: A review. Computers & Education, Vol. 90 (Dec. 2015), 36--53.

Digital Library

[13]

Khe Foon Hew. 2015. Promoting engagement in online courses: What strategies can we learn from three highly rated MOOCS. British Journal of Educational Technology (2015), n/a--n/a.

[14]

Kalle Ilves, Juho Leinonen, and Arto Hellas. 2018. Supporting Self-Regulated Learning with Visualizations in Online Learning Environments. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). ACM, New York, NY, USA, 257--262.

Digital Library

[15]

Ryosuke Ishizue, Kazunori Sakamoto, Hironori Washizaki, and Yoshiaki Fukazawa. 2018. PVC: Visualizing C Programs on Web Browsers for Novices. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). ACM, New York, NY, USA, 245--250.

Digital Library

[16]

Yeonji Jung and Jeongmin Lee. 2018. Learning engagement and persistence in massive open online courses (MOOCS). Computers & Education (Feb. 2018).

[17]

Geza Kovacs. 2016. Effects of In-Video Quizzes on MOOC Lecture Viewing. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale (L@S '16). ACM, New York, NY, USA, 31--40.

Digital Library

[18]

Kyungmee Lee. 2017. Rethinking the accessibility of online higher education: A historical review. The Internet and Higher Education, Vol. 33 (April 2017), 15--23.

[19]

Deqing Li, Honghui Mei, Yi Shen, Shuang Su, Wenli Zhang, Junting Wang, Ming Zu, and Wei Chen. 2018. ECharts: A declarative framework for rapid construction of web-based visualization. Visual Informatics, Vol. 2, 2 (June 2018), 136--146.

[20]

M. Liu, R. A. Calvo, A. Pardo, and A. Martin. 2015. Measuring and Visualizing Students? Behavioral Engagement in Writing Activities. IEEE Transactions on Learning Technologies, Vol. 8, 2 (April 2015), 215--224.

[21]

Jing Ma, Xibin Han, Juan Yang, and Jiangang Cheng. 2015. Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: The role of the instructor. The Internet and Higher Education, Vol. 24 (2015), 26--34.

[22]

Trang Phan, Sara G. McNeil, and Bernard R. Robin. 2015. Students' Patterns of Engagement and Course Performance in a Massive Open Online Course. Computers & Education (Dec. 2015).

Digital Library

[23]

Vivek Singh, Balaji Padmanabhan, Triparna de Vreede, Gert-Jan de Vreede, Stephanie Andel, Paul E. Spector, Steve Benfield, and Ahmad Aslami. 2018. A Content Engagement Score for Online Learning Platforms. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale (L@S '18). ACM, New York, NY, USA, 25:1--25:4.

Digital Library

[24]

Frans Van der Sluis, Jasper Ginn, and Tim Van der Zee. 2016. Explaining Student Behavior at Scale: The Influence of Video Complexity on Student Dwelling Time. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale (L@S '16). ACM, New York, NY, USA, 51--60.

Digital Library

[25]

Jinyue Xia and David C. Wilson. 2018. Instructor Perspectives on Comparative Heatmap Visualizations of Student Engagement with Lecture Video. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). ACM, New York, NY, USA, 251--256.

Digital Library

[26]

Qian Zhao, Sashank Varma, and Joseph A. Konstan. 2017. In-Video Reuse of Discussion Threads in MOOCs. In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale (L@S '17). ACM, New York, NY, USA, 153--156.

Digital Library

Cited By

Pei BCheng YAmbrose ADziadula EXing WLu J(2024)LearningViz: a dashboard for visualizing, analyzing and closing learning performance gaps—a case study approachSmart Learning Environments10.1186/s40561-024-00346-111:1Online publication date: 3-Dec-2024
https://doi.org/10.1186/s40561-024-00346-1
Kui XZhang Mliu QWang ZHuang GZheng ZXia JZhang C(2024)TSSeer: a visual analytics approach for exploring the correlation between teachers’ multimodal emotions and students’ behaviors in massive open online coursesJournal of Visualization10.1007/s12650-024-00988-w27:4(749-764)Online publication date: 22-Apr-2024
https://doi.org/10.1007/s12650-024-00988-w
Na SPark SJun JJeong HYoo TChun MLee HLee HJung H(2023)SUV: Students’ Understanding Visualizer to Support Instructors in Synchronous Online LecturesIEEE Access10.1109/ACCESS.2023.330303011(88929-88945)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3303030
Show More Cited By

Index Terms

VUC: Visualizing Daily Video Utilization to Promote Student Engagement in Online Distance Education
1. Applied computing
  1. Education
    1. E-learning
2. Human-centered computing
  1. Visualization

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Published In

cover image ACM Conferences

CompEd '19: Proceedings of the ACM Conference on Global Computing Education

May 2019

260 pages

ISBN:9781450362597

DOI:10.1145/3300115

General Chairs:
Ming Zhang
Peking University, China
,
Bo Yang
Linyi University, China
,
Program Chairs:
Steve Cooper
University of Nebraska-Lincoln, USA
,
Andrew Luxton-Reilly
University of Auckland, New Zealand

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCSE: ACM Special Interest Group on Computer Science Education

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 May 2019

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Funding Sources

National Science Foundation of China
MOE Innovation Research Team
Project of China Knowledge Center for Engineering Science and Technology
National Key Research and Development Program of China

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CompEd '19

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SIGCSE

CompEd '19: ACM Global Computing Education Conference 2019

May 9 - 19, 2019

Chengdu,Sichuan, China

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CompEd '19 Paper Acceptance Rate 33 of 100 submissions, 33%;

Overall Acceptance Rate 33 of 100 submissions, 33%

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CompEd '25

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sigcse

ACM Global Computing Education Conference 2025

October 21 - 25, 2025

Gaborone , Botswana

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Cited By

Pei BCheng YAmbrose ADziadula EXing WLu J(2024)LearningViz: a dashboard for visualizing, analyzing and closing learning performance gaps—a case study approachSmart Learning Environments10.1186/s40561-024-00346-111:1Online publication date: 3-Dec-2024
https://doi.org/10.1186/s40561-024-00346-1
Kui XZhang Mliu QWang ZHuang GZheng ZXia JZhang C(2024)TSSeer: a visual analytics approach for exploring the correlation between teachers’ multimodal emotions and students’ behaviors in massive open online coursesJournal of Visualization10.1007/s12650-024-00988-w27:4(749-764)Online publication date: 22-Apr-2024
https://doi.org/10.1007/s12650-024-00988-w
Na SPark SJun JJeong HYoo TChun MLee HLee HJung H(2023)SUV: Students’ Understanding Visualizer to Support Instructors in Synchronous Online LecturesIEEE Access10.1109/ACCESS.2023.330303011(88929-88945)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3303030
Aldosemani TAl Khateeb A(2022)Learning Loss Recovery Dashboard: A Proposed Design to Mitigate Learning Loss Post Schools ClosureSustainability10.3390/su1410594414:10(5944)Online publication date: 13-May-2022
https://doi.org/10.3390/su14105944
Susnjak TRamaswami GMathrani A(2022)Learning analytics dashboard: a tool for providing actionable insights to learnersInternational Journal of Educational Technology in Higher Education10.1186/s41239-021-00313-719:1Online publication date: 14-Feb-2022
https://doi.org/10.1186/s41239-021-00313-7
Guo YGuo SJin ZKaul SGotz DCao N(2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TVCG.2021.3100413
Zhang GZhu ZZhu SLiang RSun G(2022)Towards a better understanding of the role of visualization in online learning: A reviewVisual Informatics10.1016/j.visinf.2022.09.0026:4(22-33)Online publication date: Dec-2022
https://doi.org/10.1016/j.visinf.2022.09.002
Kui XLiu NLiu QLiu JZeng XZhang C(2022)A survey of visual analytics techniques for online educationVisual Informatics10.1016/j.visinf.2022.07.0046:4(67-77)Online publication date: Dec-2022
https://doi.org/10.1016/j.visinf.2022.07.004

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