What does an effective e learning video look like?
What does an effective e-
learning video look like?
● Videos are the majority of content and the most expensive
● Blended learning, credit bearing courses
● Instructor training
● Best practices
● Open research
How do we know what makes an effective online educational video so that we
can implement best practices?
How we currently make decisions about videos
● Experience of video producers and learning designers
● Film theory
● Empirical research
● Drop out rates and watch
time used as a proxy for
● Unclear if cause is length or
● Varies according to video
(Guo, Kim and Rubin, 2014)
● Traditional lecture settings are less engaging
● Intimacy trumps production values
● Lecturer comfort and decreased cognitive load increases learner engagement
(Guo, Kim and Rubin, 2014) (Chen et al, 2016)
Rate of speech
● Correlated with engagement
● Faster is generally better
● Could be about enthusiasm
● LectureSight controlled study
● Importance of face and
● Improved recognition and
● Very specific. Broader
(Wulff et al, 2013)
Edits (visual transitions)
● Viewers navigate videos to before and after edit points
● Supports chapters and interactivity
● Argument for picture in picture (Kim et al, 2014)
Picture in picture
● Controlled study
● Avoids transitions
● Learner preference
● No significant learning
● Implications for multimodality
and cognitive load
(Kizilcec, Papadopoulos, and Sritanyaratana, 2014)
Colour and highlights
● MOOC AB test
● Counter-intuitive results
● Worth further study
• Style and visual consistency
• Eye line
• Jump cuts vs multiple angles
• Correlation of video format with
• When is video appropriate?
● Educators thinking like video producers and visa versa
● Data driven video production
● More detailed AB testing
● Understanding the role and importance of aesthetics
Chen, Z., Chudzicki, C., Palumbo, D., Alexandron, G., Choi, Y.J., Zhou, Q. and Pritchard, D.E., 2016.
Researching for better instructional methods using AB experiments in MOOCs: results and challenges.
Research and Practice in Technology Enhanced Learning, 11(1), pp.1-20.
Guo, P.J., Kim, J. and Rubin, R., 2014, March. How video production affects student engagement: An
empirical study of mooc videos. In Proceedings of the first ACM conference on Learning@ scale
conference (pp. 41-50). ACM.
Hansch, A., Hillers, L., McConachie, K., Newman, C., Schildhauer, T. and Schmidt, P., 2015. Video and
online learning: Critical reflections and findings from the field
Kim, J., Guo, P.J., Seaton, D.T., Mitros, P., Gajos, K.Z. and Miller, R.C., 2014, March. Understanding in-
video dropouts and interaction peaks inonline lecture videos. In Proceedings of the first ACM conference
on Learning@ scale conference (pp. 31-40). ACM.
Kizilcec, R.F., Papadopoulos, K. and Sritanyaratana, L., 2014, April. Showing face in video instruction:
effects on information retention, visual attention, and affect. In Proceedings of the 32nd annual ACM
conference on Human factors in computing systems (pp. 2095-2102). ACM.
Pierce, M., 2015. Learning and Development: What Makes Videos Effective? Iconlogic.
Reutemann, J., 2016. Differences and Commonalities–A comparative report of video styles and course
descriptions on edX, Coursera, Futurelearn and Iversity. Proceedings of the European Stakeholder
Summit on experiences and best practices in and around MOOCs (EMOOCS 2016), p.383.
Simonite, T., 2013. As data floods in, massive open online courses evolve. Technology Review.
Wulff, B., Rupp, L., Fecke, A. and Hamborg, K.C., 2013, December. The lecturesight system in production
scenarios and its impact on learning from video recorded lectures. In Multimedia (ISM), 2013 IEEE
International Symposium on (pp. 474-479). IEEE.