Developing a ChatGPT-Based Tool for Physics Experiment Teaching

TL;DR

This paper demonstrates how AI can assist physics educators in creating interactive, customizable teaching tools for experiments like square-wave synthesis, reducing setup complexity and emphasizing core concepts.

Contribution

It introduces an AI-assisted workflow for developing physics teaching tools that are easy to use, adaptable, and enhance student engagement without requiring programming expertise.

Findings

AI-generated visualization tools simplify experiment setup

Interactive tools improve understanding of physical principles

Workflow is adaptable to various physics topics

Abstract

This paper examines how advanced AI assistants can help physics educators create practical teaching tools without specialized programming skills. Using the square-wave synthesis experiment as a case, we target common obstacles in laboratory instruction-complex setup, unstable signals, and limited class time-and show how AI-assisted development can shift attention from wiring and calibration to core physical ideas. To address this need, we guided an AI assistant through iterative prompts to generate a clean, runnable program that visualizes square-wave synthesis from its component sine waves. The tool supports step-by-step construction of the waveform, adjustable parameters (amplitude, frequency, and phase), and immediate comparison with an ideal reference using simple error measures. We packaged the result as a standalone application so it runs reliably on standard classroom computers, enabling pre-lab demonstrations and interactive exploration that reduce procedural friction and highlight underlying concepts. Building on this proof of concept, we argue the same workflow extends to other topics-such as simple harmonic motion and optical interference-where adjustable parameters and real-time visualization deepen understanding. We conclude that AI-assisted co-design can improve teaching efficiency, enhance student engagement with foundational principles, and provide a scalable path for developing customizable physics education tools.