Year: 2025
Type: conference-paper
Abstract: Reasoning models are the new generation of Large Language Models (LLMs) capable of complex problem solving.Their reliability in solving introductory physics problems was tested by evaluating a sample of n = 5 solutions generated by one such model-OpenAI's o3-mini-per each problem from 20 chapters of a standard undergraduate textbook.In total, N = 408 problems were given to the model and N × n = 2, 040 generated solutions examined.The model successfully solved 94% of the problems posed, excelling at the beginning topics in mechanics but struggling with the later ones such as waves and thermodynamics.
Authors: Amir Bralin, N. Sanjay Rebello
Institution: Purdue University West Lafayette
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Funder: National Science Foundation
OpenAlex ID: W4415600144