aceLeveraging generative artificial intelligence for simulation-based physics experiments: A new approach to virtual learning about the real world
Abstract: This study investigates the impact of a novel application of generative artificial intelligence (AI) in physics instruction: engaging students in prompting, refining, and validating AI-constructed simulations of physical phenomena. In a second-semester physics course for life science majors, we conducted a comparative study of three instructional approaches in a laboratory focused on electric p...
Science and life; Aberdeen adresses by Soddy, Frederick, 1877-1956. Public domain
As of the September 2025 publication date, researchers investigated a novel use of generative AI in physics instruction where students in a second-semester course for life science majors were asked to prompt, refine, and validate AI-constructed simulations of physical phenomena in a lab focused on electric topics, comparing three instructional approaches.
The approach matters because it shifts virtual physics learning from consuming simulations to co-constructing and checking them with AI, which could change how lab skills and conceptual understanding are taught; the supplied excerpt does not report measured learning outcomes, effect sizes, or longer-term retention, leaving the comparative impact uncertain.
- Study focused on a second-semester physics course for life science majors
- Instructional approach centered on students prompting, refining, and validating AI-constructed simulations
- Comparative study of three instructional approaches in a laboratory focused on electric p
Life-science physics students engaged in prompting, refining, and validating generative AI-constructed simulations as a new method for virtual learning about physical phenomena.
The rundown
The paper describes a laboratory intervention in a second-semester physics course for life science majors, structured as a comparative study of three instructional approaches.
The laboratory focus was on electric p phenomena, with students tasked with prompting, refining, and validating simulations built by generative AI rather than using pre-built simulations.
Sources
- Peer-reviewedSemantic Scholar–indexed venue2025-09-26
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