A Study on Pathways for Enhancing the Teaching Competencies of Physical Education Teacher Candidates Through Artificial Intelligence
Kata Kunci:
Artificial Intelligence, Physical Education Teacher Education Students, Teacher Education Students, Teaching CompetenceAbstrak
The digital transformation of education, accelerated by artificial intelligence (AI), has profoundly reshaped pedagogical practices across disciplines. However, pre-service physical education (PE) teacher training programs face persistent structural challenges, including limited authentic teaching practice opportunities, overly subjective and untimely evaluation systems, and a lack of individualized mentoring, all of which hinder the cultivation of adaptive and reflective practitioners. Despite growing interest in educational technology, there remains a notable gap in both theoretical frameworks and practical pathways specifically tailored to integrate AI into PE teacher preparation. To address this gap, this study employs a comprehensive literature review and theoretical synthesis to construct a dual-dimensional competency framework for PE pre-service teachers, comprising "professional pedagogical competence" and "digital teaching competence." Based on this framework, the study identifies and elaborates four AI-enabled instructional pathways: (1) AI-assisted instructional design and resource generation, (2) virtual simulation for motor skill demonstration and movement analysis, (3) intelligent classroom interaction systems for real-time feedback, and (4) multidimensional, data-driven teaching assessment. These pathways collectively facilitate a paradigm shift from traditional experience-driven teaching to evidence-based, data-informed instructional decision-making. Furthermore, the research critically examines persistent barriers to implementation, including curriculum misalignment with digital competencies, insufficient digital literacy among teacher educators, and the absence of sustainable mechanisms for long-term AI integration. In response, the study proposes actionable strategies such as reforming PE curricula to embed AI literacy, establishing university-industry collaborative training platforms, enhancing faculty digital professional development, and optimizing assessment frameworks to incorporate AI-generated analytics. This research contributes both theoretically and practically by offering an original competency model and a systemic implementation roadmap for integrating AI into pre-service PE education. The findings are intended to inform policy-making, guide curriculum innovation, and support the sustainable, high-quality development of school physical education in the digital age
Referensi
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
Aleven, V., McLaughlin, E. A., Glenn, R. A., & Koedinger, K. R. (2017). Instruction based on adaptive learning technologies. In R. E. Mayer & P. A. Alexander (Eds.), Handbook of research on learning and instruction (2nd ed., pp. 522–560). Routledge.
Bai, C. J. (2025). The ideal model, actual challenges, and pathways for enhancing the professional development of physical education instructors through digital and intelligent technologies. Journal of Shenyang Sport University, 44(02), 16–22.
Central Committee of the Communist Party of China, & State Council. (2025, January 19). The Central Committee of the Communist Party of China and the State Council issue the "Outline of the Plan for Building a Strong Country in Education (2024–2035)" [Press release]. https://www.gov.cn/zhengce/202501/content_6999913.htm
Chu, H. Q. (2025). Comprehensively building a fair and high-quality basic education system: Promoting the overall optimization of all stages of basic education. Educational Research, 46(09), 4–15.
Dan, Y. F., Liu, M. Y., Jing, Y., et al. (2022). A study on the concepts, mechanisms, and pathways for collaborative training of physical education teachers in the context of sports-education integration. Journal of Shandong Institute of Physical Education, 38(04), 94–102. https://doi.org/10.14104/j.cnki.1006-2076.2022.04.011
Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute.
Davenport, T. H., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423–435. https://doi.org/10.1016/j.compedu.2012.02.001
Fullan, M. (2007). The new meaning of educational change (4th ed.). Teachers College Press.
General Administration of Sport. (2021, October 8). Notice of the General Administration of Sport on issuing the "14th Five-Year Plan for Sports Development" [Press release]. https://www.gov.cn/zhengce/zhengceku/2021-10/26/content_5644891.htm
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Graham, S., Depp, C., Lee, E. E., Nebeker, C., Tu, X., Kim, H. C., & Jeste, D. V. (2019). Artificial intelligence for mental health and mental illnesses: An overview. Current Psychiatry Reports, 21(11), 116. https://doi.org/10.1007/s11920-019-1094-0
Gu, L. J., & Wang, C. Y. (2023). A study on the optimization of demand-oriented full-time faculty supply in higher education institutions: A forecast for 2035. Chinese Higher Education Research, 2023(11), 79–87. https://doi.org/10.16298/j.cnki.1004-3667.2023.11.11
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2019). Cochrane handbook for systematic reviews of interventions (2nd ed.). John Wiley & Sons.
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Ifenthaler, D., & Yau, J. Y. K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Khowaja, K., & Salim, S. S. (2019). A systematic review of strategies and computer-based intervention (CBI) for reading comprehension of children with autism. Research in Autism Spectrum Disorders, 58, 22–34. https://doi.org/10.1016/j.rasd.2018.11.006
Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE-2007-01. Keele University and Durham University.
Koehler, M. J., Mishra, P., & Cain, W. (2013). What is technological pedagogical content knowledge (TPACK)? Journal of Education, 193(3), 13–19. https://doi.org/10.1177/002205741319300303
Lin, Z. J. (2019). School district reform: How to open the door to regional educational resource integration. People's Education, 2019(01), 44–47.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications.
Liu, D. Y., & Luo, F. (2024). Artificial intelligence empowering data processing in education and psychology research. China Examinations, 2024(03), 18–27. https://doi.org/10.19360/j.cnki.11-3303/g4.2024.03.003
Liu, D. Y., Luo, F., Tu, Z. R., et al. (2024). Current status and challenges of artificial intelligence in empowering the development of psychology. Journal of Beijing Normal University (Natural Science Edition), 60(01), 30–37.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). https://doi.org/10.1145/3313831.3376727
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
McGaghie, W. C., Issenberg, S. B., Petrusa, E. R., & Scalese, R. J. (2010). A critical review of simulation-based medical education research: 2003–2009. Medical Education, 44(1), 50–63. https://doi.org/10.1111/j.1365-2923.2009.03547.x
Ministry of Education of the People's Republic of China. (2018, April 18). Notice of the Ministry of Education on issuing the "Education Informatization 2.0 Action Plan" [Press release]. https://www.moe.gov.cn/srcsite/A16/s3342/201804/t20180425_334188.html
Ministry of Education, & Eight Other Departments. (2025, April 15). Opinions of the Ministry of Education and eight other departments on accelerating the digital transformation of education [Press release]. https://www.moe.gov.cn/srcsite/A01/s7048/202504/t20250416_1187476.html
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
OECD. (2021). OECD Digital Education Outlook 2021: Pushing the frontiers with artificial intelligence, blockchain and robots. OECD Publishing. https://doi.org/10.1787/589b283f-en
O'Sullivan, M. (2019). The future of physical education: A practice-based approach. Sport, Education and Society, 24(5), 449–462. https://doi.org/10.1080/13573322.2019.1608994
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). Sage Publications.
Qiu, J. D., Li, K., & Fu, X. Q. (2025). Digital technology empowering the inheritance of intangible cultural heritage in physical education. In Abstracts of the 7th Conference on Intangible Cultural Heritage in Sports (pp. 51–53). Chinese Society of Sports Science.
Richards, K. A. R., Templin, T. J., & Gaudreault, K. L. (2013). Understanding the realities of school life: Recommendations for the preparation of physical education teachers. Quest, 65(4), 442–457. https://doi.org/10.1080/00336297.2013.804850
Rose, D. H., & Meyer, A. (2002). Teaching every student in the digital age: Universal Design for Learning. Association for Supervision and Curriculum Development.
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.
Sen, A. (1999). Development as freedom. Oxford University Press.
Shang, L. P. (2024). How to teach students to teach: Reflections on issues and practical countermeasures in cultivating teaching competence among physical education teacher trainees. Journal of Shanghai University of Sport, 48(08), 73–81+93. https://doi.org/10.16099/j.sus.2023.10.29.0001
State Council. (2025, August 21). Opinions of the State Council on deepening the implementation of the "AI+" initiative [Press release]. https://www.gov.cn/gongbao/2025/issue_12266/202509/content_7039598.html
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45
Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners (2nd ed.). ASCD.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, C. Y., & Zhou, Y. (2023). The transformation of physical education teacher education in the digital age. Journal of Teaching in Physical Education, 42(3), 321–329.
Wang, C. Y., Gu, L. J., & Yu, Y. W. (2022). The impact of the "three-child" policy on the scale of education: A forecast toward 2035. Educational Research, 43(11), 124–135.
Wang, N. N. (2025). A theoretical and practical study on artificial intelligence empowering the professional development of physical education teachers in primary and secondary schools. Journal of Shenyang Sport University, 1–7. Advance online publication. https://link.cnki.net/urlid/21.1081.G8.20251110.1020.008
Wang, Z. Z., & Zhang, Y. (2024). A visual analysis of international research on artificial intelligence-empowered diagnosis and intervention for children with special needs over the past 20 years. Chinese Journal of Rehabilitation Theory and Practice, 30(04), 404–415.
Wei, C. C., & Liu, Q. (2025). The significance, applications, and future pathways of artificial intelligence in special education. Modern Special Education, 2025(10), 26–33.
Williamson, B. (2021). Big data in education: The digital future of learning, policy and practice. Journal of Education Policy, 36(3), 456–459. https://doi.org/10.1080/02680939.2020.1777594
Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (pp. 1–10). https://doi.org/10.1145/2601248.2601268
Wu, S. L. (2024). The application of artificial intelligence technology in special education. Chinese Journal of Multimedia and Network-Based Teaching (Mid-Month Edition), 2024(07), 25–28.
Xi, J. P. (2025). Accelerating the construction of an education powerhouse. Seeking Truth, 2025(11).
Xiao, Y., & Watson, M. (2019). Guidance on conducting a systematic literature review. Journal of Planning Education and Research, 39(1), 93–112. https://doi.org/10.1177/0739456X17723971
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0
Zeichner, K. (2012). The turn once again toward practice-based teacher education. Journal of Teacher Education, 63(5), 376–382. https://doi.org/10.1177/0022487112445789
Zhao, W. (2025). The necessity, generative logic, and educational framework for cultivating interdisciplinary teaching competence in physical education teacher candidates. Bulletin of Sports Science and Technology, 33(08), 155–159. https://doi.org/10.19379/j.cnki.issn.1005-0256.2025.08.036
Zhi, Q., & Li, H. (2025). Problems and countermeasures in soccer courses for physical education majors at teacher training institutions. Theory and Practice of Education, 45(21), 61–64.
Zhu, W. (2024). Effective integration of AR gesture interaction technology into elementary school physical education classes. Research on Primary School Teaching, 2024(24), 74–75.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
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