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
DOI:
https://doi.org/10.47197/retos.v66.113540Palabras clave:
educación física, motivación estudiantil, prevención de lesiones, aprendizaje inmersivo, RA, IAResumen
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
Número
Sección
Licencia
Derechos de autor 2025 Shirinkyz Shekerbekova, Guldina Kamalova, Makpal Iskakova, Aigul Aldabergenova, Elmira Abdykerimova, Karlygash Shetiyeva

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Los autores que publican en esta revista están de acuerdo con los siguientes términos:
- Los autores conservan los derechos de autor y garantizan a la revista el derecho de ser la primera publicación de su obra, el cuál estará simultáneamente sujeto a la licencia de reconocimiento de Creative Commons que permite a terceros compartir la obra siempre que se indique su autor y su primera publicación esta revista.
- Los autores pueden establecer por separado acuerdos adicionales para la distribución no exclusiva de la versión de la obra publicada en la revista (por ejemplo, situarlo en un repositorio institucional o publicarlo en un libro), con un reconocimiento de su publicación inicial en esta revista.
- Se permite y se anima a los autores a difundir sus trabajos electrónicamente (por ejemplo, en repositorios institucionales o en su propio sitio web) antes y durante el proceso de envío, ya que puede dar lugar a intercambios productivos, así como a una citación más temprana y mayor de los trabajos publicados (Véase The Effect of Open Access) (en inglés).
Esta revista sigue la "open access policy" de BOAI (1), apoyando los derechos de los usuarios a "leer, descargar, copiar, distribuir, imprimir, buscar o enlazar los textos completos de los artículos".
(1) http://legacy.earlham.edu/~peters/fos/boaifaq.htm#openaccess