Authors: Conglei Shi, Siwei Fu, Qing Chen, Huamin Qu
Abstract: Massive Open Online Courses (MOOCs) are becoming increasingly popular and have attracted much research attention. Analyzing clickstreams on MOOC videos poses a special analytical challenge but provides a good opportunity for understanding how students interact with course videos, which in turn can help instructors and educational analysts gain insights into online learning behavior. In this poster, we develop a visual analytical system, VisMOOC, to help instructors analyze the clickstream data. VisMOOC consists of three main views: the List View to list all course videos for analysts to select the video they are interested in; the Content-based View to show how each type of click actions change along the video timeline, which enables the most viewed sections to be observed and the most interesting patterns to be discovered; The Dashboard View shows the information of the clickstream data in different aspects, including the course information, the geographic distribution, the video temporal information, the video popularity, and the animation. Furthermore, case studies made by the instructors demonstrate the usefulness of VisMOOC and helped them gaining deep insights into learning behavior for MOOCs.