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Student-Created Generative Artificial Intelligence (GenAI) Physics Simulations: A Build, Refine and Learn (BRaL) Framework for Conceptual Understanding

Student-Created Generative Artificial Intelligence (GenAI) Physics Simulations: A Build, Refine and Learn (BRaL) Framework for Conceptual Understanding
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Author(s): Dimitrios Sotiropoulos (University of Thessaly, Greece)
Copyright: 2026
Pages: 36
Source title: Harnessing Generative Artificial Intelligence for Science Education
Source Author(s)/Editor(s): Michail Kalogiannakis (University of Thessaly, Greece)and Dimitrios Sotiropoulos (University of Thessaly, Greece)
DOI: 10.4018/979-8-3373-2913-0.ch002

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Abstract

This chapter presents a pedagogical framework that aims to enhance physics teaching method from high school level to early college by enabling students to create interactive simulations with the help of generative AI tools which are large language models-powered. The BRaL framework recognizes learners as model builders who can develop and refine simulations without programming skills. This framework ensures students learn physics instead of merely remembering it. They create their own models, then take a break to reflect on what they're thinking, and test their arguments against theory and data. The framework has three stages and it includes educators and AI guidance to students on how to design diagrams, conduct virtual experimentation, and identify errors with clear assumptions. Hooke's law simulation as a case study presented in the chapter and depicts how students transition from simple idealized problems to harder, more complex ones.

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