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.

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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
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article

AI-DRIVEN PHYSICS RESEARCH: A TEACHING CASE ON KEPLER’S ELLIPTICAL LAW OF PLANETARY MOTION

Lufeng ZHANG, Jian GAO, Wanyu Li, Jinghua Xiao et al.
Wuli yu gongcheng.
Artificial Intelligence in Healthcare and Education
article

AI-DRIVEN PHYSICS RESEARCH: A TEACHING CASE ON KEPLER’S ELLIPTICAL LAW OF PLANETARY MOTION

Lufeng ZHANG, Jian GAO, Wanyu Li, Jinghua Xiao, Zixiang YAN
article en

Abstract

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.

Wuli yu gongcheng.Vol. 34(5)
Beijing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 54%
Artificial Intelligence in Healthcare and Education
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AI-DRIVEN PHYSICS RESEARCH: A TEACHING CASE ON KEPLER’S ELLIPTICAL LAW OF PLANETARY MOTION — Lufeng ZHANG, Jian GAO, et al. · Wuli yu gongcheng. (2024) | TGRS Research Map | TGRS