Artificial intelligence as a virtual coach: comparative effectiveness of automated feedback versus traditional methods in Physical Education
DOI:
https://doi.org/10.47197/retos.v72.117154Keywords:
artificial intelligence, autonomous, motivation, interactive learning, personalized feedback, Physical EducationAbstract
Introduction: Physical education is essential for an holistic child development, fostering physical, cognitive, and emotional growth. As technology reshapes education, the potential of AI to enhance this vital subject is increasingly recognized. The advent of language models like GPT-3 has opened opportunities for innovative and interactive learning experiences in physical education. While these models demonstrate remarkable capabilities in generating human-like text, their potential as virtual coaches remains largely unexplored.
Objective: To assess whether AI can provide athletes with personalized feedback comparable to human coaching.
Methodology: The study employed Walter+, an AI tool designed for educational settings, in a pilot trial with three groups: professor-led (TG1), notes-based (NG2), and chatbot-assisted (WG3). Motivational, autonomy-related, and academic performance variables were analyzed.
Results: Interactive learning (TG1 and WG3) outperformed passive note-taking (NG2) in motivation and engagement. WG3 excelled in autonomy support (32.00) and autonomous motivation (21.00), while TG1 led in intrinsic motivation (24.00) and competence (27.67). NG2 showed marginal academic gains (40% exam score) but scored lowest in psychological and behavioral metrics.
Discussion: Chatbots proved highly effective in fostering autonomy and intrinsic motivation, nearly matching professor-led interaction. Passive learning underperformed in engagement despite slight test advantages, highlighting the limitations of rote methods. The findings position AI as a promising tool for interactive learning.
Conclusions: The results indicate that interactive learning, whether with a professor or a chatbot, is more effective than passive learning using only notes. Each method has its own advantages and may be more suitable depending on the specific educational goal.
References
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901. https://doi.org/10.48550/arXiv.2005.14165
Cohen, L., Manion, L., & Morrison, K. (2002). Research methods in education. Routledge.
Dillenbourg, P. (2013). Design for classroom orchestration. Computers & education, 69, 485-492. https://doi.org/10.1016/j.compedu.2013.04.013
Fox, E. (2002). Processing emotional facial expressions: The role of anxiety and awareness. Cognitive, Affective, & Behavioral Neuroscience, 2(1), 52-63. https://doi.org/10.3758/cabn.2.1.52
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of educational research, 77(1), 81-112. https://doi.org/10.3102/003465430298487
Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: exercise effects on brain and cognition. Nature reviews neuroscience, 9(1), 58-65. https://doi.org/10.1038/nrn2298
Kandlbinder, P. (2014). Constructive alignment in university teaching. HERDSA News, 36(3), 5-6.
Lonsdale, C., Sabiston, C. M., Taylor, I. M., & Ntoumanis, N. (2011). Measuring student motivation for physical education: Examining the psychometric properties of the Perceived Locus of Causality Questionnaire and the Situational Motivation Scale. Psychology of Sport and Exercise, 12(3), 284-292. https://doi.org/10.1016/j.psychsport.2010.11.003
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. London: Pearson.
Moore, R. L., & Miller, C. N. (2022). Fostering Cognitive Presence in Online Courses: A Systematic Review (2008-2020). Online Learning, 26(1), 130-149. https://doi.org/10.24059/olj.v26i1.3071
Noodle Factory. (n.d.). Walter: AI teaching assistant for educators. Noodle Factory. https://www.noodlefactory.ai/
Olmos Gómez, M. del C., Portillo Sánchez, R., & Parra González, M. E. (2025). Educación Física e Inteligencia Artificial. Validación de un instrumento sobre uso y percepción de la IA en jóvenes. Retos, 67, 46–56. https://doi.org/10.47197/retos.v67.112460
Pedró, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. United Nations Educational, Scientific and Cultural Organization.
Prieto-Andreu, J. M., & Labisa-Palmeira, A. (2024). Quick Review of Pedagogical Experiences Using GPT-3 in Education. Journal of Technology and Science Education, 14(2), 633-647. https://doi.org/10.3926/jotse.2111
Reeve, J. (2013). How students create motivationally supportive learning environments for themselves: The concept of agentic engagement. Journal of educational psychology, 105(3), 579-595. https://doi.org/10.1037/a0032690
Roediger III, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological science, 17(3), 249-255. https://doi.org/10.1111/j.1467-9280.2006.01693.x
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Publications. https://doi.org/10.1521/978.14625/28806
Sanabria Navarro, J. R., Niebles Núñez, W. A., & Silveira Pérez, Y. (2024). Análisis bibliométrico de la inteligencia artificial en el deporte (Bibliometric analysis of artificial intelligence in sport). Retos, 54, 312–319. https://doi.org/10.47197/retos.v54.103531
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
Smit, E. S., Dima, A. L., Immerzeel, S. A. M., van den Putte, B., & Williams, G. C. (2017). The virtual care climate questionnaire: development and validation of a questionnaire measuring perceived support for autonomy in a virtual care setting. Journal of medical internet research, 19(5), e155. https://doi.org/10.2196/jmir.6714
Standage, M., Duda, J. L., & Ntoumanis, N. (2005). A test of self‐determination theory in school physical education. British journal of educational psychology, 75(3), 411-433. https://doi.org/10.1348/000709904x22359
Van der Kleij, F. M., Feskens, R. C., & Eggen, T. J. (2015). Effects of feedback in a computer-based learning environment on students’ learning outcomes: A meta-analysis. Review of educational research, 85(4), 475-511. https://doi.org/10.3102/0034654314564881
Warburton, D. E., Nicol, C. W., & Bredin, S. S. (2006). Health benefits of physical activity: the evidence. Canadian Medical Association Journal, 174(6), 801-809. https://doi.org/10.1503/cmaj.051351
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Joel Manuel Prieto Andreu, António Lopes
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and ensure the magazine the right to be the first publication of the work as licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of authorship of the work and the initial publication in this magazine.
- Authors can establish separate additional agreements for non-exclusive distribution of the version of the work published in the journal (eg, to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Is allowed and authors are encouraged to disseminate their work electronically (eg, in institutional repositories or on their own website) prior to and during the submission process, as it can lead to productive exchanges, as well as to a subpoena more Early and more of published work (See The Effect of Open Access) (in English).
This journal provides immediate open access to its content (BOAI, http://legacy.earlham.edu/~peters/fos/boaifaq.htm#openaccess) on the principle that making research freely available to the public supports a greater global exchange of knowledge. The authors may download the papers from the journal website, or will be provided with the PDF version of the article via e-mail.
