The Dynamics of Learner-Learner Interaction Over Time: A Network Analysis Using Stochastic Actor-Oriented Models

• In Event: Social Networks and the Building of Learning

Abstract

Using a stochastic-actor oriented model, this study explores the mechanisms that drive learner-learner interaction over time, specifically, the patterns and evolution of learner-learner interaction in a Massive Open Online Course (MOOC). The findings contradict previous evidence that shows that MOOC networks show reciprocity and transitivity. The study also found evidence about the reinforcement of popular learners (those who receive more replies) and learners with high outdegree activity (those who post more). Understanding MOOC networks from a longitudinal perspective opens the door to examine potential parameters that could play a significant role in lowering attrition rates.

Authors

• Daniela Castellanos-Reyes, Purdue University

• Wanju Huang, Purdue University

• Jennifer C. Richardson, Purdue University