AI-DRIVEN PHYSICS RESEARCH: A TEACHING CASE ON KEPLER’S ELLIPTICAL LAW OF PLANETARY MOTION
AI-driven scientific research has made significant advancements in various fields such as physics, chemistry, and biology. Integrating AI tools into college physics education to cultivate students’ familiarity with their principles and methods is a cutting-edge topic in current educational reform. This paper takes Kepler’s law of elliptical planetary motion as an example to demonstrate the role and limitations of symbolic regression in discovering physical laws. It guides students to start from data, combine artificial intelligence tools with physical imagery, and re-derive Kepler’s laws of planetary elliptical motion. This paper demonstrates the positive role of artificial intelligence tools in scientific exploration and emphasizes the importance of physical reasoning when using AI tools. It provides valuable teaching examples for integrating AI-driven physics research into physics education.
Authors
- Lufeng ZHANG
- Jian GAO
- Wanyu Li
- Jinghua Xiao
- Zixiang YAN
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- Wuli yu gongcheng.
- Published
- 2024-10-01
- DOI
- https://doi.org/10.26599/phys.2024.9320530
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00