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Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course
ARTICLE

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IRRODL Volume 16, Number 1, ISSN 1492-3831 Publisher: Athabasca University Press

Abstract

Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views) and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices.

Citation

Giannakos, M.N., Chorianopoulos, K. & Chrisochoides, N. (2015). Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course. The International Review of Research in Open and Distributed Learning, 16(1), 260-283. Athabasca University Press. Retrieved August 10, 2024 from .

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