Teachers' Attitudes Toward Modern Physical Education Utilizing the Transformative Potentials of Artificial Intelligence

Background and Purpose
Artificial intelligence (AI) has emerged as a transformative and powerful tool within the field of education, particularly in physical education (PE), where it has the potential to significantly enhance the educational experience by streamlining administrative and instructional processes while simultaneously boosting student motivation. Recent research highlights that AI can effectively bridge the gap between school and home environments, thereby extending learning opportunities beyond the traditional classroom setting. Through sophisticated data analysis and AI-driven algorithms, personalized educational programs can be designed and implemented, which serve to strengthen students’ physical capabilities and engagement in PE.
Despite the promising potential of AI integration in physical education, several challenges hinder its widespread adoption. These challenges include a general lack of teacher readiness and familiarity with AI technologies, ethical concerns related to data privacy and security, and infrastructural limitations such as inadequate access to necessary hardware and software. This study aims to assess the readiness of physical education teachers to integrate AI into their teaching practices and to explore strategies that can enhance the quality of education through AI. The primary research question guiding this study is: What are the perspectives of teachers regarding modern physical education that harnesses the transformative potential of artificial intelligence?
 Methods
This qualitative study employs a thematic analysis methodology combined with an inductive-exploratory approach to thoroughly examine the strengths, weaknesses, and strategic opportunities associated with the integration of AI in physical education and school sports programs. Data were collected through semi-structured interviews conducted with physical education teachers and coaches who were purposively selected based on their work experience, relevant educational background, and familiarity with modern technological tools.
The number of interviewees was determined based on the principle of theoretical saturation, ensuring that data collection continued until no new themes or insights emerged. Interviews were conducted both in-person and remotely to accommodate participant availability and preferences. The interview protocol addressed several key areas, including the perceived benefits of AI, the challenges encountered in its application, strategies for effective utilization, and the need for specialized training in AI-related competencies.
To enhance the validity of the findings, feedback from interviewees was incorporated during the analysis phase. The data were analyzed collaboratively by the principal researcher, an assistant, and an expert in qualitative research methods. The reliability of the coding process was confirmed with an inter-coder agreement rate of 82%, indicating a high level of consistency in theme identification.
The thematic analysis was conducted in three distinct stages. The first stage involved initial coding, where key concepts were identified from the interview transcripts. The second stage consisted of categorization, in which related codes were grouped into coherent sub-themes. The final stage involved theme refinement, organizing the sub-themes into broader main themes that encapsulate the core findings of the study. This structured approach allowed for the extraction of both primary and secondary themes, providing a detailed and comprehensive understanding of the subject matter.
 Findings
The findings of the study reveal a nuanced picture of the strengths, weaknesses, and strategic approaches related to the integration of AI in physical education and sports. The strengths identified include several significant opportunities that AI technologies offer for enhancing PE programs. Notably, AI-driven analytics and simulations enable the optimization of training routines and provide real-time feedback to students, thereby improving sports performance. Personalized education is another key strength, as AI allows for the tailoring of programs to meet the individual needs of students, which enhances learning outcomes and engagement.
Furthermore, AI tools contribute to injury reduction by monitoring physical activity and predicting potential injury risks, enabling timely preventive interventions. The use of gamification and interactive AI-based tools has been shown to increase student motivation and participation in physical activities. Additionally, AI facilitates resource management by streamlining administrative tasks, saving time and reducing the burden on educators and institutions.
Despite these promising strengths, the study also highlights several critical weaknesses and challenges that impede the effective integration of AI in physical education. One major concern is the potential over-reliance on technology, which may reduce human interaction and limit creativity in teaching and learning processes. Financial and infrastructural limitations pose significant barriers, as the high costs associated with acquiring and maintaining advanced AI technologies restrict access, particularly in under-resourced schools.
Another challenge is the lack of teacher expertise and technical knowledge required to effectively utilize AI tools in educational settings. Ethical and privacy concerns related to data security are also prominent, as the collection and analysis of student data raise questions about confidentiality and responsible use. Moreover, educational inequalities are exacerbated by unequal access to AI technologies, which risks widening the gap between privileged and disadvantaged students.
To address these challenges, the study identifies several strategic recommendations. Educational strategies emphasize the development of specialized training programs aimed at enhancing teachers’ technical competencies and incorporating AI literacy into teacher education curricula. Infrastructure and technology strategies call for investments in digital infrastructure and the provision of smart equipment, especially in underprivileged areas, alongside the development of cost-effective AI tools and software.
Managerial and supervisory strategies include the establishment of ethical frameworks and regulatory laws to safeguard data privacy and security, as well as fostering collaboration among schools, governmental bodies, and the private sector to support AI integration. Data-driven educational strategies advocate for the creation of online educational platforms to expand learning opportunities and the use of AI to analyze student performance data to tailor educational interventions effectively.
 Conclusion
This study demonstrates that artificial intelligence technologies hold substantial potential to revolutionize physical education by improving sports performance, enhancing personalized learning experiences, and reducing injury risks. However, realizing the full benefits of AI integration requires addressing significant challenges, including the risk of over-dependence on technology, financial constraints, and ethical considerations.
The findings underscore the necessity of adopting a comprehensive and coordinated approach to AI integration in physical education. Key recommendations include equipping teachers with the necessary skills and knowledge through targeted training programs, investing in the technological infrastructure required for AI implementation, developing robust ethical frameworks to protect student data, and fostering collaborative partnerships among educational institutions, governments, and private sector stakeholders.
By systematically addressing these challenges and implementing the proposed strategies, artificial intelligence can be effectively integrated into physical education programs, thereby enhancing educational quality and fostering the holistic development of students.
Article Message
The central message of this article emphasizes the transformative role of artificial intelligence in improving the quality of physical education through the perspectives of teachers and coaches regarding the application of this emerging technology. The study reveals that although artificial intelligence offers significant opportunities to enhance sports performance, provide personalized education, reduce injuries, increase student engagement, optimize resource management, and expand learning opportunities, various substantial barriers hinder the full exploitation of these benefits. These barriers include insufficient technical knowledge among teachers, infrastructural weaknesses, ethical concerns, and educational inequalities.
The thematic analysis of qualitative data indicates that effective utilization of artificial intelligence in physical education necessitates the development and implementation of comprehensive strategies across multiple domains, including educational, technological-infrastructural, managerial, and data-driven approaches. These strategies should be designed to empower teachers through technical skill development, ensure adequate financial and infrastructural resources, and establish smart, ethical frameworks.
Consequently, the key takeaway from this study is that integrating artificial intelligence into physical education is not only feasible but essential. Achieving this integration demands a holistic approach grounded in education, investment, and supportive policymaking, which together ensure quality, equity, and innovation in physical education, ultimately fostering improved educational outcomes and student development.