人工智能在物理教育中的应用：基于Web of Science核心库的文献计量分析（2021-2025）
Physics Education under the Application of Artificial Intelligence: Bibliometric Analysis Based on Web of Science Core Library (2021-2025)
AI总结：
本研究通过文献计量分析，探讨人工智能在物理教育中的应用发展，揭示了该领域从传统方法向智能化转变的趋势及未来研究方向。
摘要：
人工智能技术的快速发展正在推动物理教育从传统模型向智能化和数据驱动型方法转变。为探索该领域的发展演变及前沿热点，本研究利用VOSViewer和CiteSpace对2021至2025年间发表的138篇核心文献进行了系统性的文献计量分析，基于Web of Science核心收藏数据库。研究显示，相关文献数量将从2023年起呈指数级增长，美国、中国和德国是主要研究力量。研究重点迅速从早期的机器学习辅助数据分析转向生成式人工智能在教学中的应用，物理信息神经网络在计算物理课程中的整合，以及智能医学物理教育的探索。目前，该领域正处于爆炸性增长的初期阶段，表现出显著的跨学科特征。未来研究应聚焦于构建适应性学习生态系统，重构评估体系，并培养学生的AI伦理和物理直觉。
英文摘要：
The rapid development of artificial intelligence technology is driving the transformation of physics education from traditional models to intelligent and data-driven approaches. To explore the evolution and cutting-edge hotspots in this field, this study conducted a systematic bibliometric analysis of 138 core literature published between 2021 and 2025 using VOSViewer and CiteSpace, based on the Web of Science Core Collection database. Research shows that the number of related publications will increase exponentially from 2023, with the United States, China, and Germany being the main research forces. The research focus has rapidly evolved from early machine learning assisted data analysis to the application of generative AI in teaching, the integration of physics information neural networks in computational physics courses, and the exploration of intelligent medical physics education. At present, this field is in the early stages of explosive growth and exhibits significant interdisciplinary characteristics. Future research should focus on building an adaptive learning ecosystem, reconstructing evaluation systems, and cultivating students' AI ethics and physical intuition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
