AI-Based Education: Transforming Learning for Physical Education Students at Universitas Muhammadiyah Luwuk in the Digital Era
DOI:
https://doi.org/10.63185/mejps.v1i1.108Keywords:
Artificial Intelligence, Physical Education, Digital Learning, Higher Education, Sports TechnologyAbstract
Objectives: The primary objective of this study is to analyze the role of AI in enhancing learning engagement, personalized feedback, and skill acquisition among Physical Education students. Additionally, the study seeks to identify the key challenges faced in the implementation of AI-based learning, including technological literacy and infrastructure limitations.
Materials and Methods: This research employs a mixed-method approach, combining quantitative and qualitative methodologies. The study involves surveys and structured interviews with 100 students and 10 faculty members at Universitas Muhammadiyah Luwuk. AI-powered learning tools such as motion analysis software, interactive training modules, and virtual simulations were utilized. Data analysis includes descriptive statistics for quantitative findings and thematic analysis for qualitative responses.
Results: Findings indicate that AI significantly enhances student engagement and learning efficiency. Statistical analysis demonstrates a 30% increase in knowledge retention among students using AI-integrated modules compared to traditional teaching methods. Additionally, AI-driven feedback mechanisms improve students' understanding of biomechanics and sports strategies. However, barriers such as insufficient technological infrastructure, lack of AI training for instructors, and limited student access to AI tools hinder full adoption.
Conclusions: This study underscores the transformative potential of AI in sports education. AI-based learning tools provide personalized and data-driven learning experiences, fostering better comprehension and skill development. However, successful implementation requires strategic investments in infrastructure, faculty training, and digital literacy programs. Further research is recommended to explore long-term impacts and best practices for integrating AI into Physical Education curricula.
References
Adegbija, M. V., & Fakomogbon, M. A. (2013). Instructional Media In Teaching And Learning: A Nigerian Perspective. Global Media Journal African Edition, 6(2). https://doi.org/10.5789/6-2-114
Adewale, M. D., Azeta, A., Abayomi-Alli, A., & Sambo-Magaji, A. (2024). Impact of artificial intelligence adoption on students’ academic performance in open and distance learning: A systematic literature review. Heliyon, 10(22), e40025. https://doi.org/10.1016/j.heliyon.2024.e40025
Afzal, I., & Torralba, A. (2024). Cognitive Skills Development through AI Tools: Critical Thinking and Pedagogics Design in Modern Education. Unpublished. https://doi.org/10.13140/RG.2.2.34811.53281
Al Meslamani, A. Z. (2023). Technical and regulatory challenges of digital health implementation in developing countries. Journal of Medical Economics, 26(1), 1057–1060. https://doi.org/10.1080/13696998.2023.2249757
Alamäki, A., Khan, U. A., Kauttonen, J., & Schlögl, S. (2024). An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust. Education Sciences, 14(12), 1386. https://doi.org/10.3390/educsci14121386
Arellano, L., Alcubilla, P., & Leguízamo, L. (2023). Ethical considerations in informed consent. In Ethics—Scientific Research, Ethical Issues, Artificial Intelligence and Education [Working Title]. IntechOpen. https://doi.org/10.5772/intechopen.1001319
Brown, C. (2008). Sport, modernity and nation building: The Indonesian National Games of 1951 and 1953. Bijdragen Tot de Taal-, Land- En Volkenkunde / Journal of the Humanities and Social Sciences of Southeast Asia, 164(4), 431–449. https://doi.org/10.1163/22134379-90003650
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., Everett, J. A. C., Gigerenzer, G., Greenhow, C., Hashimoto, D. A., Holt-Lunstad, J., Jetten, J., Johnson, S., Kunz, W. H., Longoni, C., … Viale, R. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6), pgae191. https://doi.org/10.1093/pnasnexus/pgae191
Cobo, R., García-Mesa, Y., García-Piqueras, J., Feito, J., Martín-Cruces, J., García-Suárez, O., & A. Vega, J. (2020). The Glial Cell of Human Cutaneous Sensory Corpuscles: Origin, Characterization, and Putative Roles. In T. Suzuki (Ed.), Somatosensory and Motor Research. IntechOpen. https://doi.org/10.5772/intechopen.91815
Hakimi, M., Ezatullah Ahmady, Abdul Wajd Fazil, & Abdulkhaliq Qarizada. (2024). The Transformative Power of Information and Communication Technology in Empowering Women in Afghanistan. International Journal of Integrated Science and Technology, 1(6), 883–898. https://doi.org/10.59890/ijist.v1i6.1103
James, W., Oates, G., & Schonfeldt, N. (2024). Improving retention while enhancing student engagement and learning outcomes using gamified mobile technology. Accounting Education, 1–21. https://doi.org/10.1080/09639284.2024.2326009
Kabudi, T., Pappas, I., & Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial Intelligence, 2, 100017. https://doi.org/10.1016/j.caeai.2021.100017
Koçak, H., Kuday, A. D., Kınık, K., Çalışkan, C., Çelebi, İ., & Açıksarı, K. (2025). Evaluating the Turkish Red Crescent’s (Türk Kızılay) disaster response: Insights from the 2023 Kahramanmaraş earthquakes. BMC Public Health, 25(1), 783. https://doi.org/10.1186/s12889-025-21950-x
Kyei-Akuoko, C., Mensah, R. O., Kuusongno, D. D., Ebow Yalley, C., & Darko Amponsah, K. (2025). Evaluation of blended learning: Challenges, academic performance shifts, and the pros and cons in a selected Technical University. Cogent Arts & Humanities, 12(1), 2435713. https://doi.org/10.1080/23311983.2024.2435713
Leuciuc, F. (2018). Perception on Physical Education among Students. Revista Romaneasca Pentru Educatie Multidimensionala, 10(2), 134. https://doi.org/10.18662/rrem/51
Munk, M., & Agergaard, S. (2024). What is the meaning of PE? Exploring the influence of an educational curriculum approach on students’ participation and non-participation in physical education. European Physical Education Review, 1356336X241285977. https://doi.org/10.1177/1356336X241285977
Naeem, M., Ozuem, W., Howell, K., & Ranfagni, S. (2023). A Step-by-Step Process of Thematic Analysis to Develop a Conceptual Model in Qualitative Research. International Journal of Qualitative Methods, 22, 16094069231205789. https://doi.org/10.1177/16094069231205789
Olivas-Padilla, B. E., Manitsaris, S., & Glushkova, A. (2024). Explainable AI in human motion: A comprehensive approach to analysis, modeling, and generation. Pattern Recognition, 151, 110418. https://doi.org/10.1016/j.patcog.2024.110418
Rizvi, M. (2023). Investigating AI-Powered Tutoring Systems that Adapt to Individual Student Needs, Providing Personalized Guidance and Assessments. The Eurasia Proceedings of Educational and Social Sciences, 31, 67–73. https://doi.org/10.55549/epess.1381518
Sasikala, P., & Ravichandran, R. (2024). Study on the Impact of Artificial Intelligence on Student Learning Outcomes. Journal of Digital Learning and Education, 4(2), 145–155. https://doi.org/10.52562/jdle.v4i2.1234
Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355
Tannoubi, A., Guelmami, N., Bonsaksen, T., Chalghaf, N., Azaiez, F., & Bragazzi, N. L. (2022). Development and Preliminary Validation of the Physical Education-Study Process Questionnaire: Insights for Physical Education University Students. Frontiers in Public Health, 10, 856167. https://doi.org/10.3389/fpubh.2022.856167
Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., Monés, A. M., & Ioannou, A. (2023). Impacts of digital technologies on education and factors influencing schools’ digital capacity and transformation: A literature review. Education and Information Technologies, 28(6), 6695–6726. https://doi.org/10.1007/s10639-022-11431-8
Ward, B., Bhati, D., Neha, F., & Guercio, A. (2024). Analyzing the Impact of AI Tools on Student Study Habits and Academic Performance (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.02166
Xu, Z. (2024). AI in education: Enhancing learning experiences and student outcomes. Applied and Computational Engineering, 51(1), 104–111. https://doi.org/10.54254/2755-2721/51/20241187
Yaseen, H., Mohammad, A. S., Ashal, N., Abusaimeh, H., Ali, A., & Sharabati, A.-A. A. (2025). The Impact of Adaptive Learning Technologies, Personalized Feedback, and Interactive AI Tools on Student Engagement: The Moderating Role of Digital Literacy. Sustainability, 17(3), 1133. https://doi.org/10.3390/su17031133
