A Workshop Series for Effective Use of AI in Uncertain Times: Building a Physics Faculty Learning Community
Abstract
Generative AI tools are being widely taken up by students in their physics courses and beyond, often before instructors and institutions can develop policies and effective approaches for the use of these tools. Building on a framework for change in the era of AI, we developed and implemented a faculty learning community to help a university physics department address these challenges collectively. Over six biweekly sessions, faculty worked through course policies, classroom conversations about AI, AI-integrated coursework tasks, and assessment. Each session shared a common structure: we presented local data and department-sourced materials, tested them in small groups, and discussed them together, emphasizing durable pedagogical approaches over specific tools and platforms, and leading with evidence of students' own AI use. The series produced a shared, evolving repository of resources for faculty to draw on. This workshop provides an adaptable, theoretically informed model for a faculty learning community that departments can build on.
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BibTeX
@misc{perlnussbaum2026workshop,
title = {{A Workshop Series for Effective Use of AI in Uncertain Times: Building a Physics Faculty Learning Community}},
author = {David Perl-Nussbaum and Noah D. Finkelstein},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.23887},
eprint = {2609.23887},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.23887},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Workshop Series for Effective Use of AI in Uncertain Times: Building a Physics Faculty Learning Community
AU - David Perl-Nussbaum
AU - Noah D. Finkelstein
PY - 2026
DA - 2026/09/20
PB - arXiv
DO - 10.48550/arxiv.2609.23887
UR - https://arxiv.org/abs/2609.23887
AB - Generative AI tools are being widely taken up by students in their physics courses and beyond, often before instructors and institutions can develop policies and effective approaches for the use of these tools. Building on a framework for change in the era of AI, we developed and implemented a faculty learning community to help a university physics department address these challenges collectively. Over six biweekly sessions, faculty worked through course policies, classroom conversations about AI, AI-integrated coursework tasks, and assessment. Each session shared a common structure: we presented local data and department-sourced materials, tested them in small groups, and discussed them together, emphasizing durable pedagogical approaches over specific tools and platforms, and leading with evidence of students' own AI use. The series produced a shared, evolving repository of resources for faculty to draw on. This workshop provides an adaptable, theoretically informed model for a faculty learning community that departments can build on.
ER -