Social Network Analysis of Student-Student Interaction in a Blog Activity of an Online Course

• In Event: 32.084 - Poster Session 6
  In Poster Session: 32.084-6 - Learners' Perspectives on MOOCs, Knowledge, Interactions, and Preferences

Abstract

This study explores student-student interaction patterns in a blog activity of a graduate level online course through Social Network Analysis and content analysis. The preliminary results showed averagely students interacted with about 7 peers in the blog activity. The interaction increased as time went by. Meeting the class requirement could be one of the reasons to explain the dynamic of the interaction pattern. Identifying the paths of interaction is the first step in evaluating the learning that follows. Measures of SNA can help us better understand students’ behavior over time in the online class and identify the unequal distribution of the interaction online and the reasons behind the inequality. These should be considered when designing and developing online courses.

Authors

• Jiaming Cheng, Texas Tech University

• Jing Lei, Syracuse University

• Mary Wilhelm-Chapin, Syracuse University