More Web Proxy on the site http://driver.im/

research-article

Video and learning: a systematic review (2007--2017)

Authors:

Oleksandra Poquet,

Negin Mirriahi,

Shane DawsonAuthors Info & Claims

LAK '18: Proceedings of the 8th International Conference on Learning Analytics and Knowledge

Pages 151 - 160

https://doi.org/10.1145/3170358.3170376

Published: 07 March 2018 Publication History

Abstract

Video materials have become an integral part of university learning and teaching practice. While empirical research concerning the use of videos for educational purposes has increased, the literature lacks an overview of the specific effects of videos on diverse learning outcomes. To address such a gap, this paper presents preliminary results of a large-scale systematic review of peer-reviewed empirical studies published from 2007-2017. The study synthesizes the trends observed through the analysis of 178 papers selected from the screening of 2531 abstracts. The findings summarize the effects of manipulating video presentation, content and tasks on learning outcomes, such as recall, transfer, academic achievement, among others. The study points out the gap between large-scale analysis of fine-grained data on video interaction and experimental findings reliant on established psychological instruments. Narrowing this gap is suggested as the future direction for the research on video-based learning.

References

[1]

Allen, I.E. and Seaman, J. 2017. Digital Learning Compass: Distance Education Enrollment Report 2017. Babson Survey Research Group, e-Literate, and WCET.

[2]

Bearman, M., Smith, C.D., Carbone, A., Slade, S., Baik, C., Hughes-Warrington, M. and Neumann, D.L. 2012. Systematic review methodology in higher education. Higher Education Research & Development. 31, 5 (2012), 625--640.

[3]

Brown, S.A., Upchurch, S.L. and Acton, G.J. 2003. A framework for developing a coding scheme for meta-analysis. Western Journal of Nursing Research. 25, 2 (2003), 205--222.

[4]

Chi, M.T., Roy, M. and Hausmann, R.G. 2008. Observing tutorial dialogues collaboratively: Insights about human tutoring effectiveness from vicarious learning. Cognitive science. 32, 2 (2008), 301--341.

[5]

Chi, M.T. and Wylie, R. 2014. The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist. 49, 4 (2014), 219--243.

[6]

Clark, R.C. and Mayer, R.E. 2016. E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. John Wiley & Sons.

Digital Library

[7]

Cohen, J. 1960. A coefficient of agreement for nominal scales. Educational and psychological measurement. 20, 1 (1960), 37--46.

[8]

D'mello, S.K. and Kory, J. 2015. A review and meta-analysis of multimodal affect detection systems. ACM Computing Surveys (CSUR). 47, 3 (2015), 43.

Digital Library

[9]

Giannakos, M.N. 2013. Exploring the video-based learning research: A review of the literature. British Journal of Educational Technology. 44, 6 (2013).

[10]

Hansch, A., Hillers, L., McConachie, K., Newman, C., Schildhauer, C. and Schmidt, P. 2015. Video and Online Learning: Critical Reflections and Findings from the Field. Technical Report #HIIG Discussion Paper Series No. 2015--02.

[11]

Höffler, T.N. and Leutner, D. 2007. Instructional animation versus static pictures: A meta-analysis. Learning and instruction. 17, 6 (2007), 722--738.

[12]

Kay, R.H. 2012. Exploring the use of video podcasts in education: A comprehensive review of the literature. Computers in Human Behavior. 28, 3 (2012), 820--831.

Digital Library

[13]

Lang, A. 2000. The limited capacity model of mediated message processing. Journal of communication. 50, 1 (2000), 46--70.

[14]

Leppink, J., Paas, F., Van der Vleuten, C.P., Van Gog, T. and Van Merriënboer, J.J. 2013. Development of an instrument for measuring different types of cognitive load. Behavior research methods. 45, 4 (2013), 1058--1072.

[15]

Li, N., Verma, H., Skevi, A., Zufferey, G., Blom, J. and Dillenbourg, P. 2014. Watching MOOCs together: Investigating co-located MOOC study groups. Distance Education. 35, 2 (2014), 217--233.

[16]

Major, L. and Watson, S. 2017. Using video to support in-service teacher professional development: the state of the field, limitations and possibilities. Technology, Pedagogy and Education. (Sep. 2017), 1--20.

[17]

Mayer, R.E. 2006. Ten research-based principles of multimedia learning. Web-based learning: Theory, research, and practice. (2006), 371--390.

[18]

Mirriahi, N. and Vigentini, L. 2017. Analytics of Learner Video Use. Handbook of Learning Analytics. Columbia University, USA, C. Lang, G. Siemens, University of Texas at Arlington, USA, A. Wise, New York University, USA, D. Gasevic, and University of Edinburgh, UK, eds. Society for Learning Analytics Research (SoLAR). 251--267.

[19]

Moreno, R. and Mayer, R. 2007. Interactive Multimodal Learning Environments. Educational Psychology Review. 19, 3 (Sep. 2007), 309--326.

[20]

O'Callaghan, F.V., Neumann, D.L., Jones, L. and Creed, P.A. 2017. The use of lecture recordings in higher education: A review of institutional, student, and lecturer issues. Education and Information Technologies. 22, 1 (2017), 399--415.

Digital Library

[21]

Papamitsiou, Z.K. and Economides, A.A. 2014. Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Educational Technology & Society. 17, 4 (2014), 49--64.

[22]

Spann, C.A., Schaeffer, J. and Siemens, G. 2017. Expanding the scope of learning analytics data: preliminary findings on attention and self-regulation using wearable technology. Proceedings of the Seventh International Learning Analytics & Knowledge Conference (2017), 203--207.

Digital Library

[23]

Witthaus, G.R. 2016. Lecture capture: what can business schools learn from the recent literature? (2016).

[24]

Yousef, A.M.F., Chatti, M.A. and Schroeder, U. 2014. Video-based learning: A critical analysis of the research published in 2003-2013 and future visions. eLmL 2014, The Sixth International Conference on Mobile, Hybrid, and On-line Learning (2014), 112--119.

Cited By

Cebrián-Robles VRaposo-Rivas MCebrián-de-la-Serna M(2024)Formación para la competencia argumentativa con anotaciones multimediaCampus Virtuales10.54988/cv.2024.1.142213:1(171)Online publication date: 31-Jan-2024
https://doi.org/10.54988/cv.2024.1.1422
Trenholm SMarmolejo-Ramos F(2024)When Video Improves Learning in Higher EducationEducation Sciences10.3390/educsci1403031114:3(311)Online publication date: 15-Mar-2024
https://doi.org/10.3390/educsci14030311
Orak CTuran Z(2024)Using artificial intelligence in digital video production: A systematic review studyJournal of Educational Technology and Online Learning10.31681/jetol.14594347:3(286-307)Online publication date: 30-Sep-2024
https://doi.org/10.31681/jetol.1459434
Show More Cited By

Index Terms

Video and learning: a systematic review (2007--2017)
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI

Recommendations

Smart environments and analytics on video-based learning
LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge

The International Workshop of Smart Environments and Analytics on Video-Based Learning (SE@VBL) aims to connect research efforts on Video-Based Learning with Smart Environments and Analytics to create synergies between these fields. The main objective ...
Improving the effectiveness of video-based flipped classrooms with question-embedding
Abstract
Although video-based flipped learning is a widely accepted pedagogical strategy, few attempts have been made to explore the design and integration of pre-class instructional videos into in-class activities to improve the effectiveness of flipped ...
Supporting Learning Engagement and Teacher Awareness in Video-Based Learning Through the Evoli Video-Annotation Tool
Technology Enhanced Learning for Inclusive and Equitable Quality Education
Abstract
The rise in popularity of video-based learning within educational models such as the flipped classroom has been remarkable. However, there are two limitations. The first is that instructors only become aware of how students have absorbed the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

LAK '18: Proceedings of the 8th International Conference on Learning Analytics and Knowledge

March 2018

489 pages

ISBN:9781450364003

DOI:10.1145/3170358

Conference Chairs:
Abelardo Pardo
The University of Sydney, AUS
,
Kathryn Bartimote-Aufflick
The University of Sydney, AUS
,
Grace Lynch
Society for Learning Analytics Research, AUS
,
Program Chairs:
Simon Buckingham Shum
University of Technology Sydney, AUS
,
Rebecca Ferguson
The Open University, UK
,
Agathe Merceron
Beuth University of Applied Sciences, GER
,
Xavier Ochoa
Escuela Superior Politécnica del Litoral, EC

Copyright © 2018 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

LAK '18

LAK '18: International Conference on Learning Analytics and Knowledge

March 7 - 9, 2018

New South Wales, Sydney, Australia

Acceptance Rates

LAK '18 Paper Acceptance Rate 35 of 115 submissions, 30%;

Overall Acceptance Rate 236 of 782 submissions, 30%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

44
Total Citations
View Citations
1,702
Total Downloads

Downloads (Last 12 months)229
Downloads (Last 6 weeks)28

Reflects downloads up to 02 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Cebrián-Robles VRaposo-Rivas MCebrián-de-la-Serna M(2024)Formación para la competencia argumentativa con anotaciones multimediaCampus Virtuales10.54988/cv.2024.1.142213:1(171)Online publication date: 31-Jan-2024
https://doi.org/10.54988/cv.2024.1.1422
Trenholm SMarmolejo-Ramos F(2024)When Video Improves Learning in Higher EducationEducation Sciences10.3390/educsci1403031114:3(311)Online publication date: 15-Mar-2024
https://doi.org/10.3390/educsci14030311
Orak CTuran Z(2024)Using artificial intelligence in digital video production: A systematic review studyJournal of Educational Technology and Online Learning10.31681/jetol.14594347:3(286-307)Online publication date: 30-Sep-2024
https://doi.org/10.31681/jetol.1459434
Liu JZhang Y(2024)Modeling Health Video Consumption Behaviors on Social Media: Activities, Challenges, and CharacteristicsProceedings of the ACM on Human-Computer Interaction10.1145/36536998:CSCW1(1-28)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3653699
Steinbeck HElhayany MMeinel C(2024)Millions of Views, But Does It Promote Learning? Analyzing Popular SciComm Production Styles Regarding Learning Success, User Behavior and PerceptionProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636861(134-144)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636861
Lang COstrow K(2024)Challenge variance: Exploiting format differences for personalized learner modelsProceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3627043.3659542(102-109)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3627043.3659542
Prawake RSrisawasdi NChaipidech P(2024)Analyzing Computational Processes in Tracking Visual Attention and Assessing Scientific Understanding within Interactive Learning Content2024 IEEE 7th Eurasian Conference on Educational Innovation (ECEI)10.1109/ECEI60433.2024.10510865(75-80)Online publication date: 26-Jan-2024
https://doi.org/10.1109/ECEI60433.2024.10510865
Danzglock MHänze M(2024)Benefits of Problem-Solving First for the Success of Cooperative Learning with VideosThe Journal of Experimental Education10.1080/00220973.2024.2379542(1-18)Online publication date: 22-Jul-2024
https://doi.org/10.1080/00220973.2024.2379542
Beege MPloetzner R(2024)Learning from interactive video: the influence of self-explanations, navigation, and cognitive loadInstructional Science10.1007/s11251-024-09693-553:1(99-119)Online publication date: 30-Nov-2024
https://doi.org/10.1007/s11251-024-09693-5
Seidel N(2024)Short, Long, and Segmented Learning Videos: From YouTube Practice to Enhanced Video PlayersTechnology, Knowledge and Learning10.1007/s10758-024-09745-229:4(1965-1991)Online publication date: 5-Jul-2024
https://doi.org/10.1007/s10758-024-09745-2
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten