ZHANG Rui;ZHAO Hui;JIA Fei;ZHANG Jianwei;HAN Tangan;

• 1:School of Physics Science and Engineering
• 2:Tongji University
• 3:School of GuoHao
• 4:Tongji University

Abstract：

The rapid advancement of large language models(LLMs) has opened new avenues for innovation in physics teaching. This study focuses on a computational-thinking-driven methodology for creating digital and intelligent inquiry-learning scenarios with LLMs, enabling the rapid development of such scenarios for university-level smart physics courses. Using the projectile motion experiment as an example, we illustrate how AI-based inquiry learning can be employed to assess students' innovative capabilities. By mining the data generated during inquiry activities, we uncover the problem-solving strategies students adopt. Coupled with explainable AI, we can then derive scientifically grounded rubrics for evaluating their inquiry processes, thereby offering a quantifiable means of measuring innovation.

Key Words： AI-based inquiry learning;Large language model;machining learning;innovation assessment

Abstract:

Keywords:

Foundation: 上海市重点本科教改项目（4250104092/008）的支持;; 上海市基础学科拔尖学生培养计划2.0研究项目;; 同济大学2024年精品公共基础课程建设的支持（1370104330）;; 同济大学本科生教育研究与改革教育管理项目（4250104092/052）的支持

Authors: ZHANG Rui;ZHAO Hui;JIA Fei;ZHANG Jianwei;HAN Tangan;

References：

• [1]PERSSON T. Strategies for teaching students to think critically:a meta-analysis[J]. Review of Educational Research,2015(2):275-314.
• [2]THOMAS J W. A review of research on project-based learning[J]. San Rafael, CA:Autodesk, 2000.
• [3]Open AI. Open AI o3 System Card. Open AI Technical Report, 2025.
• [4]卢宇,余京蕾,陈鹏鹤,等.生成式人工智能的教育应用与展望——以Chat GPT系统为例[J].中国远程教育, 2023,43(4):24-31.LU Y, YU J L, CHEN P H, et al. Educational applications and prospects of generative artificial intelligence:A case study of the Chat GPT system[J]. Chinese Journal of Distance Education, 2023, 43(4):24-31.(in Chinese)
• [5]WING J M. Computational Thinking[J]. Communications of the ACM, 2006, 49(3):33-35.
• [6]WANG Z, ZHANG R, XIE N, et al. Evaluation of physics inquiry based on event map:A case study of projectile motion inquiry game[J]. GCCIL2024,21(3):70-74.
• [7]DING X, LI Z, LIU T, et al. Event logic graph:A survey on construction, reasoning and applications[J]. ACM Computing Surveys, 2023, 55(9):1-34.
• [8]詹泽慧,钟煊妍,邹萱萱,等.以评促教:基于事理图谱的计算思维水平评价方法[J].现代远距离教育,2024(1):45-57.ZHAN Z H, ZHONG X Y, ZOU X X, et al. Promoting teaching through assessment:A computational-thinking proficiency evaluation method based on event-logic graphs[J]. Modern Distance Education, 2024(1):45-57.(in Chinese)