Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review
Computers & Education - Methodological issue in researching CSCL
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
The effect of moderator's facilitative strategies on online synchronous discussions
Computers in Human Behavior
Project-Based learning with eMUSE: an experience report
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
Social network analysis for technology-enhanced learning: review and future directions
International Journal of Technology Enhanced Learning
Assessing social construction of knowledge online: A critique of the interaction analysis model
Computers in Human Behavior
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This study aims to investigate the patterns and the quality of online interaction during project-based learning (PjBL) on both micro and macro levels. To achieve this purpose, PjBL was implemented with online group activities in an undergraduate course. Social network analysis (SNA) and content analysis were employed to analyze online interaction during project work. According to the SNA results generated from the online discussion boards, the group cohesiveness of seven teams, indicated by density indices, varied considerably, from as low as 9.81 to as high as 30.00. Regarding the content analysis of two teams with high project scores (Teams F and G), team members not only shared information (Phase I), but also identified the areas of disagreement and clarified the goals and strategies (Phase II). They also conducted some negotiations (Phase III). However, team members with low project scores (Teams C and E) shared information and stated their opinions in most cases (Phase I), with not much social construction in the higher level. Although both Team C and G showed high level of group cohesiveness among the seven teams, it is notable that the high-performing Team G dedicated nearly 39.3 percent of online discussion to negotiating and co-constructing knowledge, contrary to the 5.9 percent of low-performing Team C. Based upon the findings, some implications were proposed for further research.