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July 13, 2026International Journal of Academic Research in Progressive Education and Development0 citationsOpen Access

The Level of AI Utilization in Teaching among Physical Education Teachers in Licheng District, Jinan City

CZCai ZhiqiangKJKhairul Azhar Jamaludin

Key Points

  • This study aims to evaluate the level of AI utilization among physical education teachers and identify barriers to its implementation.
  • Mixed-methods design including quantitative survey and qualitative interviews
  • 50 PE teachers from eight public primary and junior high schools in Licheng District
  • Data analysis using SPSS for quantitative and thematic analysis for qualitative data
  • 54% of teachers reported never using AI tools in PE teaching
  • 52% of teachers received no AI-related training
  • Teachers with AI training were significantly more likely to use AI in their teaching than those without.

Abstract

HRMARS - Artificial intelligence (AI) has become an important driver of educational digitalization, yet its application in compulsory education physical education (PE) remains uneven and insufficiently examined. This mixed-methods study investigated the current level of AI utilization, the barriers to implementation, and practical improvement strategies among 50 PE teachers from eight public primary and junior high schools in Licheng District, Jinan City, China. Quantitative data were collected through a structured questionnaire measuring AI familiarity, training exposure, usage frequency, perceived value, perceived difficulty, self-rated competence, and school support. Descriptive statistics and cross-tabulation analysis were conducted using SPSS. Qualitative data were collected through semi-structured interviews with 25 purposively selected teachers and analyzed thematically following Braun and Clarke's six-phase framework. Results showed that AI utilization was low: 54% of teachers had never used AI tools in PE teaching, and 52% had received no AI-related training. Although teachers perceived AI as useful for assessment, personalized instruction, motivation, and teaching efficiency, they also reported high levels of difficulty related to inadequate equipment, insufficient PE-specific training, limited operational skills, privacy concerns, and lack of peer examples. A cross-tabulation showed that teachers who had received AI training were much more likely to report actual AI use than those without training, indicating that the intention-behavior gap was primarily shaped by facilitating conditions rather than teacher resistance. Interpreted through the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology, the findings suggest that AI adoption in PE depends on environmental fit, practical training, and institutional support. The study recommends embedded professional learning in gymnasium settings, equitable PE technology investment, clear data governance, and school-based AI champion teachers.

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Cite This Study

Zhiqiang et al. (2026) studied this question.

synapsesocial.com/papers/6a548219475c38bf615a5bfahttps://doi.org/10.6007/ijarped/v15-i3/28550
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A289: Challenges and Strategies for PE Teachers in the AI Era2026
  2. 2A287: Innovation of School Physical Education Systems Driven by AI Technologies2026
  3. 3A119: AI-Enabled Physical Education2026
  4. 4A166: Implications of Finland’s AI-Enhanced Physical Education Model for China’s School Physical Education Reform2026
  5. 5Associations between physical education teachers' digital teaching competence and students' self-regulated physical activity in AI-augmented classes2026