Developing a ChatGPT-Based Tool for Physics Experiment Teaching
Yifeng Liu, Min Li, Zhaojun Zhang, Youkang Fang, Meibao Qin

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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOnline Learning and Analytics · Artificial Intelligence in Healthcare and Education
