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Community-based professional development initiatives have been shown tosupport physics faculty in their adoption of research-based instructionalstrategies. Hoping to better understand these initiatives' mechanisms ofsuccess, we analyze the results of two surveys administered to a faculty onlinelearning community teaching a common physics curriculum designed primarily forpre-service elementary teachers. We use social network analysis to representthe faculty network and compare members' centrality, a family of measures thatcapture the prominence of individuals within a network, to their reportedexperience in the community. We use a principal component analysis of differentcentrality measures to show that closeness, a measure of how closely connecteda person is with every other person in their network, is the most appropriatecentrality measure for our network. We then compare regression models accordingto Bayes factors to find relationships between participants' closeness andtheir survey responses. We find that participants' self-efficacy, as well astheir sense of improvement to their teaching and sense of benefitting from thecommunity, are predictors of their closeness with other participants and thustheir breadth and depth of participation in the community. Our results areconsistent with other studies that have highlighted interactions among facultyas key components of successful professional development initiatives. They mayalso be useful for designers of similar communities as they decide how toprioritize time and resources to meet specific goals.

Closeness in a physics faculty online learning community predicts impacts in self-efficacy and teaching