Application of generative AI-based programming in physics education for non-English speaking students

Abstract We explore the application of natural language programming in non-English languages to physics education using generative artificial intelligence (AI). Recent advances in generative AI have enabled students with no prior programming experience to create basic programs by interacting with AI in their native language. This article introduces an example of a data analysis program created by giving instructions in Japanese to generative AI. Using theoretical formulas, we were able to fit data that can be found in undergraduate university physics laboratory classes. By simplifying the technical aspects of data analysis, such as programming tasks, generative AI allows students to focus more on evaluating physical models based on experimental data and understanding the scientific principles behind familiar phenomena. Generative AI has the potential to enable a more accessible, approachable, and inclusive physics education for diverse learners, particularly by helping them to overcome barriers related to language proficiency and basic scientific literacy.

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Institutions

Publication Details

Journal
European Journal of Physics
Published
2025-08-15
DOI
https://doi.org/10.1088/1361-6404/adfc16
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69

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article

Application of generative AI-based programming in physics education for non-English speaking students

Yoichi Nishiwaki
1 citations
European Journal of Physics
Online Learning and Analytics
1.69
article

Application of generative AI-based programming in physics education for non-English speaking students

Yoichi Nishiwaki
article en
1 citations

Abstract

Abstract We explore the application of natural language programming in non-English languages to physics education using generative artificial intelligence (AI). Recent advances in generative AI have enabled students with no prior programming experience to create basic programs by interacting with AI in their native language. This article introduces an example of a data analysis program created by giving instructions in Japanese to generative AI. Using theoretical formulas, we were able to fit data that can be found in undergraduate university physics laboratory classes. By simplifying the technical aspects of data analysis, such as programming tasks, generative AI allows students to focus more on evaluating physical models based on experimental data and understanding the scientific principles behind familiar phenomena. Generative AI has the potential to enable a more accessible, approachable, and inclusive physics education for diverse learners, particularly by helping them to overcome barriers related to language proficiency and basic scientific literacy.

European Journal of PhysicsVol. 46(5)
Azabu University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 11%
Online Learning and Analytics
1.69
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