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arXiv:2303.17012physics.ed-ph

Advances in apparent conceptual physics reasoning in GPT-4

Colin G. West

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Abstract

ChatGPT is built on a large language model trained on an enormous corpus of human text to emulate human conversation. Despite lacking any explicit programming regarding the laws of physics, recent work has demonstrated that GPT-3.5 could pass an introductory physics course at some nominal level and register something close to a minimal understanding of Newtonian Mechanics on the Force Concept Inventory. This work replicates those results and also demonstrates that the latest version, GPT-4, has reached a much higher mark in the latter context. Indeed, its responses come quite close to perfectly demonstrating expert-level competence, with a few very notable exceptions and limitations. We briefly comment on the implications of this for the future of physics education and pedagogy.

arXiv comments
5 pages, one figure one table. arXiv admin note: text overlap with arXiv:2303.01067 (longer, prior version of this project)
Journal reference
DOI
Subjects
physics.ed-phPhysics Education cs.AIArtificial Intelligence

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