Communities of Performance & Communities of Preference

The current generation of Massive Open Online Courses (MOOCs) operate under the assumption that good students will help poor students, thus alleviating the burden on instructors and Teaching Assistants (TAs) of having thousands of students to teach. In practice, this may not be the case. In this paper, we examine social network graphs drawn from forum interactions in a MOOC to identify natural student communities and characterize them based on student performance and stated preferences. We examine the community structure of the entire course, students only, and students minus low performers and hubs. The presence of these communities and the fact that they are homogeneous with respect to grade but not motivations has important implications for planning in MOOCs.