Exploring the use of Artificial Intelligence and Augmented Reality tools to improve interactivity in Physical Education teaching and training methods

Authors

  • Shirinkyz Shekerbekova Abai Kazakh National Pedagogical University
  • Guldina Kamalova Abai Kazakh National Pedagogical University
  • Makpal Iskakova Abai Kazakh national Pedagogical University https://orcid.org/0000-0001-7368-7518
  • Aigul Aldabergenova Zhetysu University named after I. Zhansugurov
  • Elmira Abdykerimova Caspian university of technology and engineering named after Sh.Yessenov https://orcid.org/0000-0002-1447-4077
  • Karlygash Shetiyeva Zhetysu University named after I. Zhansugurov

DOI:

https://doi.org/10.47197/retos.v66.113540

Keywords:

physical education, student motivation, injury prevention, immersive learning, AR, AI

Abstract

Introduction: The advent of AI and augmented reality revolutionizes physical education by offering engaging, interactive methods and immersive experiences that boost student motivation and learning outcomes.

Objective: The study rigorously evaluated AI and AR technologies' impact on student motivation, injury prevention, and pose estimation accuracy in physical education. It aimed to substantiate the educational benefits and practical implications of integrating these cutting-edge technologies into educational settings.

Methodology: A controlled experimental design involved two student groups: one engaged with AI and AR-enhanced learning environments, the other with traditional methods. Data on motivation, injury incidents, and pose estimation accuracy were analyzed using t-tests, chi-square tests, and ANOVA to compare the groups.

Results: The results revealed that students using AI and AR technologies reported significantly higher motivation and lower injury rates compared to those who participated in traditional physical education. additionally, the technology-enhanced methods demonstrated superior accuracy in pose estimation compared to conventional observation techniques.

Discussion: These outcomes align with previous studies underscoring technology's positive impact in education, enhancing engagement and learning experiences. Additionally, the reduction in injury rates and improved pose estimation accuracy highlight AI and AR's potential to make physical education safer and more effective.

Conclusions: The findings confirm that AI and AR technologies significantly enhance physical education by boosting student motivation, reducing injury risks, and improving assessment accuracy. This study advocates for their broader integration into educational curricula, highlighting the importance of addressing accessibility and teacher training challenges.

References

Wang, F. J., Choi, S. M., & Lu, Y. C. (2024). The relationship between physical literacy and quality of life among university students: The role of motivation as a mediator. Journal of Exercise Science & Fitness, 22(1), 31-38. https://doi.org/10.1016/j.jesf.2023.10.002

Artiluhung, R. R., Mahendra, A., Yulianto, A. G., & Aman, M. S. (2024). Systematic literature review: Strategies for active and creative learning in Elementary School Physical Education. ACTIVE: Journal of Physical Education, Sport, Health and Recreation, 13(3), 542-547.

Asare, S., Kyenkyehene, S. A., & Emmanuel, M. K. (2023). Interactive Technology in Physical Education Classroom: A Case of a Ghanaian College of Education. American Journal of Education and In-formation Technology, 7(2), 51-58. https://doi.org/10.11648/j.ajeit.20230702.11

Omarov, N., Omarov, B., Azhibekova, Z., & Omarov, B. (2024). Applying an augmented reality game-based learning environment in physical education classes to enhance sports motivation. Retos, 60, 269–278. https://doi.org/10.47197/retos.v60.109170

Al Balushi, J. S. G., Al Jabri, M. I. A., Palarimath, S., Maran, P., Thenmozhi, K., & Balakumar, C. (2024, Ju-ne). Incorporating artificial intelligence powered immersive realities to improve learning using virtual reality (VR) and augmented reality (AR) technology. In 2024 3rd International Confer-ence on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 760-765). IEEE. https://doi.org/10.1109/ICAAIC60222.2024.10575046

Li, X., Tan, W. H., Li, Z., Dou, D., & Zhou, Q. (2024). Adaptive fitness enhancement model: Improving exercise feedback and outcomes through tailored independent physical education plan. Educa-tion and Information Technologies, 1-33. https://doi.org/10.1007/s10639-024-12616-z

Essa, S. G., Celik, T., & Human-Hendricks, N. E. (2023). Personalized adaptive learning technologies based on machine learning techniques to identify learning styles: A systematic literature re-view. IEEE Access, 11, 48392-48409. https://doi.org/10.1109/ACCESS.2023.3276439

Hsia, L. H., Hwang, G. J., & Hwang, J. P. (2024). AI-facilitated reflective practice in physical education: An auto-assessment and feedback approach. Interactive Learning Environments, 32(9), 5267-5286. https://doi.org/10.1080/10494820.2023.2212712

Omarov, B., Omarov, N., Mamutov, Q., Kissebayev, Z., Anarbayev, A., Tastanov, A., & Yessirkepov, Z. (2024). Examination of the Augmented Reality Exercise Monitoring System as an Adjunct Tool for Prospective Teacher Trainers. Retos, 58, 85–94. https://doi.org/10.47197/retos.v58.105030

Cho, K., Tsuda, E., & Ward, P. (2024). Developing adaptive teaching competence in preservice physical education teachers. European Physical Education Review, 1356336X241240621. https://doi.org/10.1177/1356336X241240621

Omarov, B., Omarov, B., Rakhymzhanov, A., Niyazov, A., Sultan, D., & Baikuvekov, M. (2024). Develop-ment of an artificial intelligence-enabled non-invasive digital stethoscope for monitoring the heart condition of athletes in real-time. Retos, 60, 1169–1180. https://doi.org/10.47197/retos.v60.108633

Liu, T. C. (2022). A case study of the adaptive learning platform in a Taiwanese Elementary School: Precision education from teachers’ perspectives. Education and Information Technologies, 27(5), 6295-6316. https://doi.org/10.1007/s10639-021-10851-2

Abu-Rasheed, H., Weber, C., & Fathi, M. (2023, July). Context based learning: a survey of contextual indi-cators for personalized and adaptive learning recommendations–a pedagogical and technical perspective. In Frontiers in Education (Vol. 8, p. 1210968). https://doi.org/10.3389/feduc.2023.1210968

Arif, Y. M., Nugroho, F., Aini, Q., Fauzan, A. C., & Garcia, M. B. (2025). A Systematic Literature Review of Serious Games for Physical Education: Technologies, Implementations, and Evaluations. Global Innovations in Physical Education and Health, 1-36. https://doi.org/10.4018/979-8-3693-3952-7.ch001

Ranasinghe, I., Yuan, C., Dantu, R., & Albert, M. V. (2021, December). A Collaborative and Adaptive Feed-back System for Physical Exercises. In 2021 IEEE 7th International Conference on Collabora-tion and Internet Computing (CIC) (pp. 11-15). IEEE. https://doi.org/10.1109/CIC52973.2021.00012

Singh, B., Kaunert, C., Lal, S., & Arora, M. K. (2025). Enhancing AI-Augmented Classrooms: Teacher-Centric Integration of Intelligent Tutoring Systems and Adaptive Learning Environments. In Fostering Inclusive Education With AI and Emerging Technologies (pp. 99-130). IGI Global. https://doi.org/10.4018/979-8-3693-7255-5.ch004

Mokmin, N. A. M. (2020). The effectiveness of a personalized virtual fitness trainer in teaching physical education by applying the artificial intelligent algorithm. International Journal of Human Movement and Sports Sciences, 8(5), 258-264. https://doi.org/10.13189/saj.2020.080514

Joshitha, K. L., Madhanraj, P., Roshan, B. R., Prakash, G., & Ram, V. M. (2024, April). AI-FIT COACH-Revolutionizing Personal Fitness With Pose Detection, Correction and Smart Guidance. In 2024 International Conference on Communication, Computing and Internet of Things (IC3IoT) (pp. 1-5). IEEE. https://doi.org/10.1109/IC3IoT60841.2024.10550400

Lu, Y. (2023). Personalized Exercise Program Design with Machine Learning in Sensor Networks. Scal-able Computing: Practice and Experience, 24(4), 1157-1168. https://doi.org/10.12694/scpe.v24i4.2440

Thakur, S. N., Sinha, A., Singh, M. K., Bagaria, M. K., Grover, R., & Shrivastava, K. (2023, December). Opti-mizing Wellness: A Comprehensive Examination of a Conversational AI-Driven Healthcare BOT for Personalized Fitness Guidance. In 2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI) (Vol. 1, pp. 1-8). IEEE. https://doi.org/10.1109/ICAIIHI57871.2023.10489319

Ouyang, F., Xu, W., & Cukurova, M. (2023). An artificial intelligence-driven learning analytics method to examine the collaborative problem-solving process from the complex adaptive systems per-spective. International Journal of Computer-Supported Collaborative Learning, 18(1), 39-66. https://doi.org/10.1007/s11412-023-09387-z

Liu, Y., Sathishkumar, V. E., & Manickam, A. (2022). Augmented reality technology based on school physical education training. Computers and Electrical Engineering, 99, 107807.

Almusawi, H. A., Durugbo, C. M., & Bugawa, A. M. (2021). Innovation in physical education: Teachers’ perspectives on readiness for wearable technology integration. Computers & Education, 167, 104185. https://doi.org/10.1016/j.compedu.2021.104185

Wang, Y., Muthu, B., & Sivaparthipan, C. B. (2021). Internet of things driven physical activity recognition system for physical education. Microprocessors and Microsystems, 81, 103723.

Demchenko, I., Maksymchuk, B., Bilan, V., Maksymchuk, I., & Kalynovska, I. (2021). Training future physical education teachers for professional activities under the conditions of inclusive educa-tion. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 12(3), 191-213. https://doi.org/10.18662/brain/12.3/227

Tanucan, J. C. M., Hernani, M. R., & Diano, F. (2021). Filipino physical education teachers’ technological pedagogical content knowledge on remote digital teaching. International Journal of Infor-mation and Education Technology, 11(9), 416-423. https://doi.org/10.18178/ijiet.2021.11.9.1544

Le Noury, P., Polman, R., Maloney, M., & Gorman, A. (2022). A narrative review of the current state of extended reality technology and how it can be utilised in sport. Sports Medicine, 52(7), 1473-1489. https://doi.org/10.1007/s40279-022-01669-0

Nahavandi, D., Alizadehsani, R., Khosravi, A., & Acharya, U. R. (2022). Application of artificial intelli-gence in wearable devices: Opportunities and challenges. Computer Methods and Programs in Biomedicine, 213, 106541. https://doi.org/10.1016/j.cmpb.2021.106541

Shaik, T., Tao, X., Higgins, N., Li, L., Gururajan, R., Zhou, X., & Acharya, U. R. (2023). Remote patient mon-itoring using artificial intelligence: Current state, applications, and challenges. Wiley Interdisci-plinary Reviews: Data Mining and Knowledge Discovery, 13(2), e1485. https://doi.org/10.1002/widm.1485

Dimitriadou, E., & Lanitis, A. (2023). A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms. Smart Learning Environ-ments, 10(1), 12. https://doi.org/10.1186/s40561-023-00231-3

Altayeva, A., Omarov, B., Jeong, H. C., & Im Cho, Y. (2016). Multi-step face recognition for improving face detection and recognition rate. Far East Journal of Electronics and Communications, 16(3), 471. http://dx.doi.org/10.17654/EC016030471

Olabanji, S. O., Olaniyi, O. O., Adigwe, C. S., Okunleye, O. J., & Oladoyinbo, T. O. (2024). AI for identity and access management (IAM) in the cloud: Exploring the potential of artificial intelligence to im-prove user authentication, authorization, and access control within cloud-based systems. Au-thorization, and Access Control within Cloud-Based Systems (January 25, 2024). http://dx.doi.org/10.2139/ssrn.4706726

Cereda, F. (2024). Gamification in physical education: exploring efficacy, challenges, and ethical con-siderations. Lifelong Lifewide Learning, 21(44), 312-326. https://doi.org/10.19241/lll.v21i44.851

Alam, A., & Mohanty, A. (2023). Educational technology: Exploring the convergence of technology and pedagogy through mobility, interactivity, AI, and learning tools. Cogent Engineering, 10(2), 2283282. https://doi.org/10.1080/23311916.2023.2283282

Liu, Y., Sathishkumar, V. E., & Manickam, A. (2022). Augmented reality technology based on school physical education training. Computers and Electrical Engineering, 99, 107807. https://doi.org/10.1016/j.compeleceng.2022.107807

Cossich, V. R., Carlgren, D., Holash, R. J., & Katz, L. (2023). Technological breakthroughs in sport: Current practice and future potential of artificial intelligence, virtual reality, augmented reality, and modern data visualization in performance analysis. Applied Sciences, 13(23), 12965. https://doi.org/10.3390/app132312965

Hu, Z., Liu, Z., & Su, Y. (2024). AI-Driven Smart Transformation in Physical Education: Current Trends and Future Research Directions. Applied Sciences, 14(22), 10616. https://doi.org/10.3390/app142210616

Song, C., Shin, S. Y., & Shin, K. S. (2023). Optimizing foreign language learning in virtual reality: a com-prehensive theoretical framework based on constructivism and cognitive load theory (VR-CCL). Applied Sciences, 13(23), 12557. https://doi.org/10.3390/app132312557

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Published

08-04-2025

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Original Research Article

How to Cite

Shekerbekova, S., Kamalova, G., Iskakova, M., Aldabergenova, A., Abdykerimova, E., & Shetiyeva, K. (2025). Exploring the use of Artificial Intelligence and Augmented Reality tools to improve interactivity in Physical Education teaching and training methods. Retos, 66, 935-949. https://doi.org/10.47197/retos.v66.113540