A review of methodological applications of social network analysis in computer-supported collaborative learning

Social network analysis (SNA) is a promising research method for analyzing relational ties in computer-supported collaborative learning (CSCL) activities in which learners interact towards a common learning goal with the aid of computers because they share the same underlying assumption that learning and behavior are influenced by one's relations. This methodological review examines whether CSCL research (n = 89) (1) reflects the diversity of actors (learners and artifacts) and relational ties that are important in CSCL environments; and (2) relates these relational ties as measured by SNA indices to CSCL learning outcomes. The results suggest that SNA applications in CSCL (1) do not reflect this diversity of CSCL actors and relational ties, investigating only one-mode networks of learners connected by communication-based relational ties; and (2) are limited to a descriptive reporting of SNA results. Future directions for CSCL are focused on filling these gaps by (1) integrating technical, instructional and knowledge artifacts as SNA actors, and (2) relating SNA findings to cognitive, social and motivational CSCL outcomes using statistical analysis. (C) 2017 Elsevier Ltd. All rights reserved.