A Predictive Study of Students’ Self-regulated Learning Skills and Their Roles in the Social Network Interaction of Online Discussion Board

Abstract

Online learners' learning skills and behaviors are challenging for educators to foresee, particularly what skills may be related to certain social interaction behaviors. Selfregulated 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 played more influential roles in online discussion network. Learners with higher SRL skills tended to connect to others based on flow and distance of the connections, rather than how prominent (eigenvector) and prestigious (PageRank) of their connections were. [ABSTRACT FROM AUTHOR]