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

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

Chase Hatcher, Edward Price, P. Sean Smith, Chandra Turpen and Eric Brewe
arXiv (Cornell University)
19 Sep 2022
DOI: https://doi.org/10.48550/arxiv.2209.09306
url
https://arxiv.org/abs/2209.09306View
Preprint (Author's original)arXiv.org - Non-exclusive license to distribute,  Open

Abstract

Physics - Physics Education
Community-based professional development initiatives have been shown to support physics faculty in their adoption of research-based instructional strategies. Hoping to better understand these initiatives' mechanisms of success, we analyze the results of two surveys administered to a faculty online learning community teaching a common physics curriculum designed primarily for pre-service elementary teachers. We use social network analysis to represent the faculty network and compare members' centrality, a family of measures that capture the prominence of individuals within a network, to their reported experience in the community. We use a principal component analysis of different centrality measures to show that closeness, a measure of how closely connected a person is with every other person in their network, is the most appropriate centrality measure for our network. We then compare regression models according to Bayes factors to find relationships between participants' closeness and their survey responses. We find that participants' self-efficacy, as well as their sense of improvement to their teaching and sense of benefitting from the community, are predictors of their closeness with other participants and thus their breadth and depth of participation in the community. Our results are consistent with other studies that have highlighted interactions among faculty as key components of successful professional development initiatives. They may also be useful for designers of similar communities as they decide how to prioritize time and resources to meet specific goals.

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