The Web has enabled one of the most visible recent developments in education-the deployment of massive open online courses. With their global reach and often staggering enrollments, MOOCs have the potential to become a major new mechanism for learning. Despite this early promise, however, MOOCs are still relatively unexplored and poorly understood. In a MOOC, each student's complete interaction with the course materials takes place on the Web, thus providing a record of learner activity of unprecedented scale and resolution. In this work, we use such trace data to develop a conceptual framework for understanding how users currently engage with MOOCs. We develop a taxonomy of individual behavior, examine the different behavioral patterns of high-and low-achieving students, and investigate how forum participation relates to other parts of the course. We also report on a large-scale deployment of badges as incentives for engagement in a MOOC, including randomized experiments in which the presentation of badges was varied across subpopulations. We find that making badges more salient produced increases in forum engagement.
In a more recent a empt REF , a taxonomy of individual learner behaviors was developed to examine the di erent behavior pa erns of high-and low-achieving students.
Engaging with Massive Online Courses
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Computer Science Physics Mathematics