Streamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligence
Name
595_1_5.0201458.pdf
Description
Published version
Size
2.54 MB
Format
Adobe PDF
Checksum (MD5)
163aa114f066ce89f6dd546590f53a05
Author(s)
El-Adawy, Shams
Liao, Isaac
Lad, Vedang
Abdelhafez, Mohamed
Dourmashkin, Peter
Date Issued
October 1, 2024
Journal
The Physics Teacher
Publisher
AIP Publishing
Citation
Shams El-Adawy, Isaac Liao, Vedang Lad, Mohamed Abdelhafez, Peter Dourmashkin; Streamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligence. Phys. Teach. 1 October 2024; 62 (7): 595–598.
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Massachusetts Institute of Technology. Laboratory for Computer Science
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1119/5.0201458
