Online learners’ learning skills and behaviors are challenging for educators to foresee, particularly what skills may be related to certain social interaction behaviors. Self-regulated learning (SRL) skills are critical to online learning. It is unclear how SRL skills may predict social network interaction. This study empirically investigated: How will SRL skills predict students’ network roles (i.e., in-degree, out-degree, betweenness centrality, closeness centrality, eigenvector centrality, reciprocated vertex pair ratio, & PageRank) in the social network discussions of discussion board within online courses? The predictive utility of SRL skills for betweenness and closeness centralities was supported. Learners with greater SRL skills play more influential roles in online discussion network. Learners with higher SRL skills tend to connect to others based on flow and distance of the connections, rather than how prominent (eigenvector) and prestigious (PageRank) of their connections.
Yen, Cherng-Jyh; Bozkurt, Aras; Tu, Chih-Hsiung; Sujo-Montes, Laura; Rodas, Claudia; Harati, Hoda; and Lockwood, Adam B.
"A Predictive Study of Students’ Self-regulated Learning Skills and Their Roles in the Social Network Interaction of Online Discussion Board,"
Journal of Educational Technology Development and Exchange (JETDE): Vol. 11
, Article 2.
Available at: https://aquila.usm.edu/jetde/vol11/iss1/2