VideoMark: A video-based learning analytic technique for MOOCs

The massive online open course (MOOC) revolution offers opportunities for learning analytics regarding the diversity in learning activities of MOOCs. In MOOCs, video lectures represent the principal learning resource, and learners spend most of their time engaged in self-paced, independent learning. Therefore, MOOCs present an innovative form of video-based learning. How to improve this learning environment by adding additional features to video lectures represents a path for progress. Few studies have investigated the interaction between learners and the video content; however, improvement in this domain is necessary. This paper proposes a video-based learning analysis approach called VideoMark, which enables learners to judiciously review, consolidate, and clarify specific concepts introduced in MOOCs. This analytical approach can be applied to MOOC-style ShareCourse programs in Taiwan. Finally, this analytical approach is presented as a visual keyword cloud for learners to clarify specific learning concepts in the MOOC learning process.