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dc.contributor.authorEl-Adawy, Shams
dc.contributor.authorLiao, Isaac
dc.contributor.authorLad, Vedang
dc.contributor.authorAbdelhafez, Mohamed
dc.contributor.authorDourmashkin, Peter
dc.date.accessioned2026-03-10T16:13:50Z
dc.date.available2026-03-10T16:13:50Z
dc.date.issued2024-10-01
dc.identifier.urihttps://hdl.handle.net/1721.1/165065
dc.description.abstractThe 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.en_US
dc.language.isoen
dc.publisherAIP Publishingen_US
dc.relation.isversionofhttps://doi.org/10.1119/5.0201458en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAIP Publishingen_US
dc.titleStreamlining Physics Problem Generation to Support Physics Teachers in Using Generative Artificial Intelligenceen_US
dc.typeArticleen_US
dc.identifier.citationShams 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.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physicsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Laboratory for Computer Scienceen_US
dc.relation.journalThe Physics Teacheren_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2026-03-10T16:05:32Z
dspace.orderedauthorsEl-Adawy, S; Liao, I; Lad, V; Abdelhafez, M; Dourmashkin, Pen_US
dspace.date.submission2026-03-10T16:05:34Z
mit.journal.volume62en_US
mit.journal.issue7en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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