Community Dynamics of Large Open Online Learning Networks (Poster 10)

• In Event: AERA Poster Session Ten
  In Poster Session: Online Teaching and Learning SIG Poster Session

Abstract

Online learning communities are becoming increasingly popular as they are known to support collaborative dialogue and knowledge building. Previous studies have typically focused on small, closed learning communities from an individual, static, and aggregated perspective. This research aims to advance our understanding of open and large online learning networks by exploring and characterizing community level dynamics and communities of performance. We mined a large open online learning network of over 30,000 students and approximately one million posts. Results found that large open online learning communities begin with a very large network having numerous small sub-communities. The overall network size gradually shrinks, as does the number of sub-communities, and these communities evolve over time for their membership formulation.

Authors

• Wanli Xing, University of Florida
  Presenting Author

• Hanxiang Du, Western Washington University
  Presenting Author