How video production affects student engagement: an empirical study of MOOC videos
Abstract
Videos are a widely-used kind of resource for online learning. This paper presents an empirical study of how video production decisions affect student engagement in online educational videos. To our knowledge, ours is the largest-scale study of video engagement to date, using data from 6.9 million video watching sessions across four courses on the edX MOOC platform. We measure engagement by how long students are watching each video, and whether they attempt to answer post-video assessment problems.
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Shorter videos (about 10 minutes) are more engaging compared to longer YouTube videos.
“Another criterion for choosing YouTube as a video clip is the length of the video because shorter videos (about 10 minutes) are more engaging compared to longer YouTube videos (Guo, Kim and Rubin, 2014), Thus, YouTube video clips which are used in this research was retrieved from https://www.youtube.com/watch?kuFWbA-k (accessed May 24, 2019).”
From Teaching and Learning Science Using YouTube Videos and Discovery Learning in Primary School (2020) · cites this paper as Guo, Kim and Rubin, 2014
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Müller, F. A., & Wulf, T. (2020) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-020-00226-x · Cited by 100 · see citing works
Slemmons, K. E. H., Anyanwu, K., Hames, J., Grabski, D., Mlsna, J., Simkins, E., & Cook, P. A. (2018) · Journal of Science Education and Technology · doi:10.1007/s10956-018-9736-2 · Cited by 88 · see citing works
Videos in higher education: Making the most of a good thing
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Effectiveness of online dementia caregivers training programs: A systematic review
Pleasant, M. L., Molinari, V., Dobbs, D., Meng, H., & Hyer, K. (2020) · Geriatric Nursing · doi:10.1016/j.gerinurse.2020.07.004 · Cited by 81 · see citing works
Curriculum Design of a Flipped Classroom to Enhance Haematology Learning
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The effects of video lecture viewing strategies on cognitive load
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PeakVizor: Visual Analytics of Peaks in Video Clickstreams from Massive Open Online Courses
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“Many studies have discussed how to prepare videos [38] and their impact on the dropout rate of students,”
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“medical biochemistry course [15] and from analysis of video content from massive open online courses [16].”
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The learning behaviours of dropouts in MOOCs: A collective attention network perspective
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Learning in double time: The effect of lecture video speed on immediate and delayed comprehension
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“Despite having less time to encode accompanying visually presented information at faster video speeds, the shorter durations may make it easier for participants to sustain focused attention throughout the learning period (see Guo et al., 2014).”
BackgroundFlipping the calculus classroom: an evaluative study
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Effects of sustained attention and video lecture types on learning performances
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Code, Camera, Action: How Software Developers Document and Share Program Knowledge Using YouTube
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“But screencast narrators who speak quickly may be perceived as more energetic and engaging by the audience [42].”
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- Authors
- Guo, P. J., Kim, J., & Rubin, R.
- Affiliations
- University of Rochester (US)
- MIT Computer Science and Artificial Intelligence Laboratory (US)
- edX, Cambridge, MA, USA
- Venue
- Proceedings of the first ACM conference on Learning @ scale conference
- Publisher
- ACM
- Published
- 2014-03-04
- Pages
- 41-50
- OpenAlex
- W2051525497
- Cited by
- 1,850
- References
- 10
- Citations by year
- 2026: 113 · 2025: 138 · 2024: 168 · 2023: 172 · 2022: 204 · 2021: 173 · 2020: 172 · 2019: 200 · 2018: 165 · 2017: 142 · 2016: 92 · 2015: 90 · 2014: 19
- FWCI
- 72.58
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Conference on Learning @ Scale (L@S) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Education › Innovations in Educational Methods
- Keywords
- educational videos, student engagement, online learning, MOOCs, edX, video length, learner behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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