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Learners’ engagement with different types of MOOC videos

Wednesday 3 July: Conference day one, 11:30am – 12:00pm parallel session



Room 2 – 303-G14, Sem



Dr LilyMin Zeng
The University of Hong Kong, Hong Kong

Dr Chi-Un Lei
The University of Hong Kong, Hong Kong

Attin Cheng
The University of Hong Kong, Hong Kong

Yuqian Chai
The University of Hong Kong, Hong Kong



MOOC has become phenomenal. Although it suffers from low completion rates, it did make higher education educators more aware of an alternative way of content sharing and delivery for the engagement with students. Based on cognitive load theories, engaging videos should include signaling (reducing extraneous load), segmenting (managing intrinsic load), and interactive elements (enhancing germane load) (deKoning, Tabbers, Rikers, & Paas, 2009; Guo, Kim, & Robin, 2014; Ibrahim, Antonenko, Greenwood, & Wheeler, 2012; Mayer & Moreno, 2003; Zhang, Zhou, Briggs, & Nunamaker, 2006). This presentation will report on learners’ engagement with MOOC videos which incorporated such elements.


The Practice

This MOOC targets at early career academics and final year PhD students who want to become university teachers. It includes a combination of the elements mentioned above in the video design to manage the cognitive load for the engagement of learners.



Ethical approval was obtained prior to the study. The data were collected through the MOOC platform from the first cohort of learners who registered with this MOOC (N=612). Using the time learners spent in watching the specific video materials as the indicator of their engagement, we analyzed and compared learners’ engagement with different types of videos. The study also explored the correlations between learners’ engagement with different types of videos and their engagement with and results in the assessment tasks such as practice quizzes, participations in the discussion forums, the assessment scores in their first attempt, and their completion of the assignment.


Evidence of effectiveness

The data showed that, in this MOOC context, different designs of the videos were correlated with different levels of engagement among the learners. Correlation patterns were also observed between learners’ engagement with the videos and their engagement with the assessment tasks.  Based upon the findings, we compiled a list of recommendations for the design of educational videos in MOOC context.



deKoning, B., Tabbers, H., Rikers, R., & Paas, F. (2009). Towards a framework for attention cueing in instructional animations: Guidelines for research and design. Educational Psychology Review, 21, 113-140.
Guo, P. J., Kim, J. Y., & Robin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos. Paper presented at the ACM Conference on Learning at Scale (L@S 2014), Atlanta, Georgia, USA.
Ibrahim, M., Antonenko, P. D., Greenwood, C. M., & Wheeler, D. (2012). Effects of segmenting, signaling, and weeding on learning from educational video. Learning, Media and Technology, 37, 220-235.
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43-52.
Zhang, D., Zhou, L., Briggs, R. O., & Nunamaker, J. F. J. (2006). Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management, 43, 15-27.


Presentation topic

Academic – Academic Development

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