مدل کارکردهای هوش مصنوعی در توانمندسازی مربیان به‌منظور بهینه‌سازی سطح عملکرد ورزشکاران نخبه دوومیدانی

مهسا دانایی‌فرد; حسین  پیمانی‌زاد; مهدی آذرنوش; محمد  کشتی‌دار

Authors

Mahsa Danaeifard Department of Physical Education, Ma.C., Islamic Azad University, Mashhad, Iran. Author https://orcid.org/0009-0001-2609-5541
Hossein Peymanizad Department of Physical Education, Ma.C., Islamic Azad University, Mashhad, Iran. https://orcid.org/0000-0002-6317-8522
Mahdi Azarnoosh Department of Biomedical Engineering, Ma.C., Islamic Azad University, Mashhad, Iran. Author https://orcid.org/0000-0003-0932-0011
Mohammad Keshtidar Department of Physical Education, Faculty of Sports Sciences, Ferdowsi University of Mashhad, Mashhad, Iran. Author https://orcid.org/0000-0002-1705-4940

Keywords:

artificial intelligence functions, coach empowerment, performance optimization, elite athletes, track and field

Abstract

The purpose of this study was to develop a model of artificial intelligence functions for empowering coaches to optimize the performance of elite track and field athletes. This study was applied in terms of purpose and exploratory in nature, using a qualitative grounded theory approach based on Glaser’s emergent methodology. The statistical population consisted of university experts in sports management, specialists in artificial intelligence, and professionals with experience in elite sports. Purposeful sampling was employed, and semi-structured interviews were conducted with 20 experts until theoretical saturation was achieved. Data analysis was carried out simultaneously with data collection through open, axial, and selective coding procedures. MaxQDA software was used to organize and analyze qualitative data. Finally, a conceptual network of antecedents and consequences related to the use of artificial intelligence in coach empowerment and athlete performance optimization was extracted, and the final research model was developed. The findings demonstrated that the antecedents of using artificial intelligence could be categorized into 96 open codes, 8 axial codes, and one selective code. The most important dimensions included technological and infrastructural readiness, coaches’ technological literacy, organizational support, athletes’ psychological acceptance, competitive demands, specialized AI functions, cognitive empowerment of coaches, and multidimensional performance optimization of athletes. Furthermore, the consequences of AI utilization were identified through 69 open codes and 8 axial codes, including professional empowerment of coaches, improvement in training design and control, enhancement of technical and physiological performance, injury reduction, improved coach–athlete interaction, increased motivation and psychological readiness, better sports management, and development of sustainable international competitive advantage. Structural model analysis also confirmed a significant relationship between AI functions and outcomes (T=16.763). The results indicated that artificial intelligence can function as a transformative tool in elite sports coaching by enhancing data-driven analysis, personalizing training programs, predicting injuries, and improving scientific decision-making. The systematic implementation of intelligent technologies can significantly empower coaches, optimize elite athletes’ performance, and contribute to the international advancement and sustainable competitive advantage of track and field sports.

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