Mixed methods with social network analysis for networked learning

In our research we study small group interaction and meaning making in the context of a larger community of people and artifacts. Our research methodology combines social network analysis and content analysis in different ways. The primary purpose of this paper is to explore approaches and demonstrate the feasibility of mixed methods research combining network-level and content-level methods. We report our experiences from three case studies (Get Satisfaction, Canvas, r/place), which include individual variation (innovative approaches toward integration) and a common approach of “zooming in,” or shifting perspective between bird’s eye and detailed levels of interaction data during analysis (message content, dialogic structure, or visual artifact vs. patterns of users and their interactions). We show that the two sets of methods in combination can eliminate shortcomings of the separate methods used independently.