Streamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligence
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Shams El-Adawy
[1]
;
Isaac Liao
[1]
;
Vedang Lad
[1]
;
Mohamed Abdelhafez
[1]
;
Peter Dourmashkin
[1]
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[1] Massachusetts Institute of Technology
Massachusetts Institute of Technology
City of Cambridge, Estados Unidos
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- Localización: The Physics Teacher, ISSN 0031-921X, Vol. 62, Nº. 7, 2024, págs. 595-598
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
The rapid advancement of large language models (LLMs) presents a unique opportunity for educators to find ways to include artificial intelligence (AI) in physics course design. By critically engaging with LLMs to help with the task of generating problems, physics teachers can not only model a potentially effective way to use LLMs for other teachers, but also showcase to students ways to productively engage with LLMs. This article presents a workflow with two different starting points to generate physics problems using ChatGPT 3.5. The first initialization involves interacting with ChatGPT in a conversational manner, guiding iterative problem creation by breaking tasks into smaller tasks. The second initialization harnesses ChatGPT’s generative abilities, aligning problem generation with established problem styles by instructing the model to emulate contexts from question banks. We discuss the implications of this workflow for other physics instructors exploring productive ways to incorporate the use of AI in their own course design.
