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  • Open Access

Characterizing faculty online learning community interactions using social network analysis

Emily Bolger1, Marius Nwobi1,2, and Marcos D. Caballero1,3,4

  • 1Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, Michigan 48824, USA
  • 2Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, USA
  • 3Department of Physics and Astronomy and CREATE for STEM Institute, Michigan State University, East Lansing, Michigan 48824, USA
  • 4Department of Physics and Center for Computing in Science Education, University of Oslo, 0315 Oslo, Norway

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Phys. Rev. Phys. Educ. Res. 21, 020133 – Published 21 October, 2025

DOI: https://doi.org/10.1103/n3yf-5h29

Abstract

The Partnership for Integration of Computation into Undergraduate Physics (PICUP) was founded in the mid-2010s to assist educators with the challenges of integrating computation into physics curricula. In addition to in-person trainings and hosted educational materials, PICUP uses a Slack Workspace to continue collaboration and discussion off-line. In this work, we use social network analysis (SNA) to study the communication patterns of PICUP and assess if PICUP is meeting their goals in the Slack environment. Through our analysis, we discuss PICUP’s community structure and define a conceptual framework to evaluate if the goals are being met through SNA metrics. We present a comprehensive analysis of eight channels in the Slack Workspace using various SNA metrics, identifying three distinct levels of user engagement. We conclude with implications for PICUP and provide recommendations for the community.

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Outline

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Phys. Rev. Phys. Educ. Res. 21, 020133– Published 21 October, 2025
  • Received 2 July 2024
  • Revised 3 August 2025
  • Accepted 16 September 2025
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