Survey of 90 STEM faculty finds AI pedagogical orientation strongly predicts AI adoption across research and teaching, beyond general attitudes or institutional factors.
On the Prevalence and Nature of Computational Instruction in Undergraduate Physics Programs across the United States
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abstract
A national survey of physics faculty was conducted to investigate the prevalence and nature of computational instruction in physics courses across the United States. 1246 faculty from 357 unique institutions responded to the survey. The results suggest that more faculty have some form of computational teaching experience than a decade ago, but it appears that this experience does not necessarily translate to computational instruction in undergraduate students' formal course work. Further, we find that formal programs in computational physics are absent from most departments. A majority of faculty do report using computation on homework and in projects, but few report using computation with interactive engagement methods in the classroom or on exams. Specific factors that underlie these results are the subject of future work, but we do find that there is a variation on the reported experience with computation and the highest degree that students can earn at the surveyed institutions.
fields
physics.ed-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Faculty Orientations Shape Adoption of AI in Research and Teaching
Survey of 90 STEM faculty finds AI pedagogical orientation strongly predicts AI adoption across research and teaching, beyond general attitudes or institutional factors.