How Physics Professors Use and Frame Generative AI Tools
Vidar Skogvoll, Tor Ole Odden
TL;DR
Facing rapid GenAI adoption in physics, the paper investigates how physics professors use and frame GenAI in teaching and research. The authors conducted semi-structured interviews with twelve professors at a Scandinavian university and performed inductive thematic analysis guided by epistemic framing, identifying 19 practices organized into six overlapping frames. A dominant threat frame colors other frames, while five positive frames treat GenAI as a tool for knowledge, discussion, coding, text processing, and labor-saving tasks. The findings illuminate opportunities and challenges for academic integrity, learning, and the evolving professional identity of physicists, and point to the need for AI literacy and thoughtful integration in physics education.
Abstract
Generative AI is rapidly reshaping how physicists teach, learn, and conduct research, yet little is known about how physics faculty are responding to these changes. We interviewed 12 physics professors at a major Scandinavian research university to explore their uses and perceptions of Generative AI (GenAI) in both teaching and research. Using the theoretical framework of epistemic framing, we conducted a thematic analysis that identified 19 overlapping practices, ranging from coding and literature review to assessment and feedback. From these practices, we derived six overlapping epistemic frames through which professors make sense of GenAI: as a threat to genuine learning and assessment, a source of knowledge, a discussion partner, a text-processing tool, a coding tool, and a labor-saving device. While the latter five position GenAI as a useful tool in the physicists' toolbox, the threat frame represented an overarching concern that colored all other frames. These findings reveal how GenAI is beginning to transform what it means to be a physicist, highlighting both opportunities for innovation and challenges for academic integrity and learning.