Explorando el uso de herramientas de Inteligencia Artificial y Realidad Aumentada para mejorar la interactividad en los métodos de enseñanza y entrenamiento de Educación Física

Autores/as

  • 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

Palabras clave:

educación física, motivación estudiantil, prevención de lesiones, aprendizaje inmersivo, RA, IA

Resumen

Introducción: La llegada de la inteligencia artificial y la realidad aumentada revoluciona la educación física al ofrecer métodos atractivos e interactivos, así como experiencias inmersivas que aumentan la motivación y los resultados de aprendizaje de los estudiantes.

Objetivo: El estudio evaluó rigurosamente el impacto de las tecnologías de IA y RA en la motivación de los estudiantes, la prevención de lesiones y la precisión en la estimación de poses en la educación física. Su objetivo era fundamentar los beneficios educativos y las implicaciones prácticas de integrar estas tecnologías de vanguardia en los entornos educativos.

Metodología: Se implementó un diseño experimental controlado con dos grupos: uno usando entornos mejorados por IA y RA, y otro con métodos tradicionales. Se analizaron datos sobre motivación, lesiones y precisión en la estimación de poses usando pruebas t, chi-cuadrado y ANOVA.

Resultados: Los resultados mostraron que estudiantes usando tecnologías de IA y RA tenían mayor motivación y menos lesiones comparados con métodos tradicionales. Además, estos métodos tecnológicos demostraron mayor precisión en la estimación de poses frente a las técnicas de observación convencionales.

Discusión: Estos resultados coinciden con estudios previos que destacan el impacto positivo de la tecnología en educación, mejorando participación y experiencias de aprendizaje. La reducción de lesiones y mayor precisión en estimación de poses evidencian cómo la IA y RA pueden hacer la educación física más segura y efectiva.

Conclusiones: Los hallazgos confirman que la IA y RA mejoran la educación física aumentando la motivación estudiantil, reduciendo riesgos de lesiones y mejorando la precisión de evaluaciones. Este estudio promueve su integración en currículos educativos, enfatizando la necesidad de superar desafíos en accesibilidad y formación docente.

Referencias

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

Descargas

Publicado

08-04-2025

Número

Sección

Artículos de carácter científico: investigaciones básicas y/o aplicadas

Cómo citar

Shekerbekova, S., Kamalova, G., Iskakova, M., Aldabergenova, A., Abdykerimova, E., & Shetiyeva, K. (2025). Explorando el uso de herramientas de Inteligencia Artificial y Realidad Aumentada para mejorar la interactividad en los métodos de enseñanza y entrenamiento de Educación Física. Retos, 66, 935-949. https://doi.org/10.47197/retos.v66.113540