Problem posing, a pedagogical practice that asks students to generate novel problems or meaningful variations to problems encountered, supports transfer of learning and strengthens problem-solving skills in physics. However, generating physics problems can be challenging, particularly for novice learners. This study in...
This study investigated the use of Large Language Models to analyze students' explanations of computational physics problems on a pre- and post- semester survey and found significant growth in Data Practices and Computational Problem-Solving Practices.
S. Savage, Anand Shanker, Grace Michlitsch et al.· 0 citations
This study examines Artificial Intelligence-generated physics solutions from two connected perspectives: how prompt design shapes these solutions and how students can be prepared to critique them, and how AI-generated solutions can ground both model-reasoning benchmarks and improved student critique of that reasoning t...
N. Borse, Amir Bralin, S. Savage et al.· 0 citations
The results show that state-of-the-art LLMs can solve much of the standard introductory physics problems, but that their performance remains uneven and constrained by problem modality and problem difficulty.
A description of the discourse PER researchers can expect to encounter when students work with an AI tutor of this design, including a striking prevalence of meta-procedural turns in which students cede strategic control to the tutor.
S. Hashmi, N. Rebello· 0 citations
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