Abstract. 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. The system captures learners’ interactions with the video player (e.g, pause, replay, forward) and at the same time it collects information about their performance (e.g., cognitive tests) and/or attitudes (e.g., surveys). We have already validated the system and we are working on learner modeling and personalization through large scale data analysis. The tool is a freely available open source project for anyone to try and to improve.
Chorianopoulos, K., Giannakos, M.N., 2013. Merging learner performance with browsing behavior in video lectures. In: WAVe 2013 The Workshop on Analytics on Video-Based Learning. pp. 38–42.