The Nature and Level of Learner-Learner Interaction in a Chemistry Massive Open Online Course (MOOC)
Andrew A. Tawfik, Todd D. Reeves, Amy E. Stich, Anila Gill, Chenda Hong, Joseph McDade, Venkata Sai Pillutla, Xiaoshu Zhou, Philippe J. Giabbanelli
Journal of Computing in Higher Education Volume 29, Number 3, ISSN 1042-1726
Similar to other online courses, massive open online courses (MOOCs) often rely on learner-learner interaction as a mechanism to promote learning. However, little is known at present about learner-learner interaction in these nascent informal learning environments. While some studies have explored MOOC participant perceptions of learner-learner interactions, research is still lacking regarding the content and level of such interactions. Using the interaction analysis model (IAM) as a theoretical framework and social network analysis methods, the present study investigates the nature and level of learner-learner interaction within a popular Chemistry MOOC from Coursera. Findings suggest that learner-learner interaction: was limited to lower phases of the IAM framework (e.g., sharing and comparing information); changed (decreased) over time; and was heavily dependent on a few highly-engaged learners. Potential implications for the design of future MOOCs are discussed.
Tawfik, A.A., Reeves, T.D., Stich, A.E., Gill, A., Hong, C., McDade, J., Pillutla, V.S., Zhou, X. & Giabbanelli, P.J. (2017). The Nature and Level of Learner-Learner Interaction in a Chemistry Massive Open Online Course (MOOC). Journal of Computing in Higher Education, 29(3), 411-431.