增强或替代:大语言模型在体育教育中的定义作用
Huijun Yang1, Bingyi Huang1, Xu Li1
1School of Physical Education, Collaborative Innovation Team for the Study and Interpretation of Xi Jinping's Important Discourses on Cyberspace Governance, Chongqing University of Posts and Telecommunications, Chongqing, China.
Frontiers in sports and active living
|November 28, 2025
概括
大型语言模型 (LLM) 在体育教育方面表现有前途,但与教师的协作方法产生了更好的结果. 最好将LLM作为辅助工具来增强教学,而不是取代人类教育工作者.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 体育教育的体育教育
背景情况:
- 人工智能 (AI) 和大型语言模型 (LLM) 在教育中的快速整合带来了机遇和挑战.
- 在体育教育中,LLM显示出个性化教学的潜力,但存在关于安全性,准确性和适当性的担忧.
- 本研究调查了LLM在体育教育环境中的作用和适用性.
研究的目的:
- 用LLMs评估体育教学课程计划和教师响应的不同生成方法的有效性.
- 为了比较LLM生成的计划 (独立与资源增强与协作) 并评估LLM在模拟场景中的反应.
- 确定LLM作为辅助工具的适用性,而不是在体育教育中替代人教的潜在替代品.
主要方法:
- 进行了基于问卷的评估,比较了三个LLM驱动的课程计划生成方法.
- 每种方法的可行性,实用性,安全性,适应性和内容质量都被评估.
- 在体育教育场景中,LLM生成的响应被评估为准确性,安全性,清晰性,适应性,指导性,学习者接受性和效率影响.
主要成果:
- 由教师和LLM创建的协作课程计划显著超过独立的LLM生成的计划.
- 在体育教育场景中的LLM响应在清晰度,指导,适应性和效率支持方面获得了高评分.
- 在增加教学设计和响应性方面,LLM 证明了其价值.
结论:
- 大型语言模型是优化体育教学实践的有价值的辅助工具.
- 目前,LLM并不能取代人类教练的基本教学判断,上下文意识和安全监督.
- 在体育教育中LLM的最佳作用是支持和增强,而不是取代人类教学.
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