Video lectures are nowadays widely used by growing numbers of learners all over the world. Nevertheless, learners’ interactions with the videos are not readily available, because online video platforms do not share them. In this paper, we present an open-source video learning analytics system, which is also available as a free service to researchers. Our system facilitates the analysis of video learning behavior by capturing learners’ interactions with the video player (e.g, seek/scrub, play, pause). In an empirical user study, we captured hundreds of user interactions with the video player by analyzing the interactions as a learner activity time series. We found that learners employed the replaying activity to retrieve the video segments that contained the answers to the survey questions. The above findings indicate the potential of video analytics to represent learner behavior. Further research, should be able to elaborate on learner behavior by collecting large-scale data. In this way, the producers of online video pedagogy will be able to understand the use of this emerging medium and proceed with the appropriate amendments to the current video-based learning systems and practices.

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Chorianopoulos, K., Giannakos, M.N., and Chrisochoides, N. 2014. Open system for video learning analytics. Proceedings of the first ACM conference on Learning @ scale conference - L@S ’14, ACM Press, 153–154.   BibTeX