Zha Haoran, Li Wenye, Wang Weihao, Xiao Jian
College of Physical Education and Health Management, Chongqing University of Education, Chongqing 400065, China.
Institute of Education, Nanjing University, Nanjing 210093, China.
Behav Sci (Basel). 2025 Feb 19;15(2):240. doi: 10.3390/bs15020240.
This study investigates why artificial intelligence (AI) may hinder rather than enhance teaching efficiency in primary school physical education (PE). Guided by socio-technical systems theory, we conducted focus group interviews with 13 PE teachers (6 from Nanjing and 7 from Chongqing, China) who had at least three years of teaching experience and two years of AI implementation experience. Participants were purposefully selected through a two-stage sampling strategy: initial screening via open-ended questionnaires to identify teachers reporting negative experiences with AI integration, followed by snowball sampling to recruit additional participants with similar perspectives. Data collection employed a dual-facilitator approach using semi-structured interviews, with one moderator guiding discussions while another observed non-verbal cues. Qualitative content analysis revealed key barriers across four dimensions: technological (interface complexity, infrastructure limitations), employee (professional identity conflicts, interpersonal tensions), task-related (real-time monitoring challenges, reduced pedagogical flexibility), and organizational (inadequate support systems, unclear implementation policies). These findings suggest that successful AI integration in PE requires a holistic approach addressing both technological and human factors, rather than focusing solely on technological advancement. The study contributes to understanding how socio-technical interactions uniquely manifest in physically active learning environments.
本研究探讨了为什么人工智能（AI）可能会阻碍而不是提高小学体育教学效率。以社会技术系统理论为指导，我们对13名体育教师（6名来自中国南京，7名来自重庆）进行了焦点小组访谈，这些教师至少有三年教学经验和两年人工智能应用经验。参与者通过两阶段抽样策略有目的地选取：首先通过开放式问卷进行初步筛选，以确定报告有人工智能整合负面经历的教师，然后通过滚雪球抽样招募其他有类似观点的参与者。数据收集采用双主持人方式，使用半结构化访谈，一名主持人引导讨论，另一名观察非语言线索。定性内容分析揭示了四个维度的关键障碍：技术方面（界面复杂性、基础设施限制）、员工方面（职业身份冲突、人际紧张关系）、任务相关方面（实时监测挑战、教学灵活性降低）和组织方面（支持系统不足、实施政策不明确）。这些发现表明，在体育教学中成功整合人工智能需要一种全面的方法，既要解决技术因素，也要解决人为因素，而不是仅仅关注技术进步。该研究有助于理解社会技术互动在体育学习环境中是如何独特地表现出来的。
