Date
Publisher
arXiv
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.
Study at a glance
- Question: How can teachers use AI assistants to create interactive physics experiment tools without programming skills?
- Setting and data: Not stated in the abstract
- Method: Product development using iterative prompting to build an interactive physics simulation application
Why it matters
Physics lab instruction faces common obstacles, including complex setups, unstable signals, and limited class time. At the same time, educators need to create practical teaching tools without specialized programming skills to highlight core physical ideas.
Key findings
- In physics laboratory instruction, AI assistants can help educators create practical, interactive experiment simulation tools without requiring specialized programming skills.
- The resulting application runs reliably on classroom computers, enabling step-by-step waveform visualization, adjustable wave parameters, and immediate error comparisons with an ideal reference.
- AI-assisted co-design can extend across physics topics like harmonic motion and optical interference, offering a scalable path for developing customizable instructional tools.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
