Supporting instructional change in mathematics: using social network analysis to understand online support processes...

Studies continually show benefits of active learning in college classrooms, yet it is difficult to get faculty to adopt these methods. Particularly challenging is the final step of the instructional change process, "refreezing," when after making initial changes in instructional methods, instructors decide whether to continue with new instructional methods or return to their previous methods. Though this stage is important, it is not well studied. Most available studies about ongoing support following professional development on teaching merely state that facilitators made an effort to offer support, or report how frequently participants engaged with online support mechanisms through counting postings on listservs or message boards. Such measures do not show evidence that participants actually received positive reinforcement or intellectual and emotional support, which are crucial to refreezing, nor do these frequency analyses help other professional developers learn how to create productive ongoing support mechanisms that yield high participant engagement.

This workshop for 35 college mathematics instructors used online and in-person communities to provide support to participants during the post-workshop period of "refreezing." Almost all workshop attendees participated in "e-mentoring" (94%), primarily through a productive, engaging group email listserv. By combining qualitative coding of message content with the techniques of social network analysis, we reveal how facilitators and participants on the group listserv provided intellectual and emotional support, as well as positive reinforcement through feedback loops. The analysis also shows how the facilitators made this a helpful group and maintained participant engagement through frequent encouragement, deliberate community building, and thoughtfully timed responses.

Though many professional development workshops offer online support through email listservs, there is little evidence that these listservs successfully engage and support participants. Applying the analytic approach of social network analysis allowed us to model the conversation threads in one highly engaged and supportive listserv following a mathematics professional development workshop. This method revealed the processes of ongoing support in ways that traditional frequency-based analyses cannot. This method also revealed lessons for how other professional developers can create productive, helpful online support listservs. Since this is an innovative application of social network analysis, we describe the method in detail.