ARTIFICIAL INTELLIGENCE (AI)-DRIVEN DATA ANALYTICS AND DECISION-MAKING EFFICIENCY IN PHYSICAL EDUCATION PROGRAMS

The integration of Artificial Intelligence (AI) into educational settings has been transformative, particularly in the realm of physical education. AI driven data analytics offers a sophisticated approach to managing and optimizing physical education programs, enhancing decision making efficiency and improving overall program outcomes. This study explores the impact of AI driven data analytics on decision-making within physical education, emphasizing its potential to revolutionize the field by providing precise, data-driven insights. AI driven data analytics involves using algorithms to process large datasets, generating actionable insights that inform various aspects of program management. In physical education, these insights can range from student performance evaluations to resource allocation, ultimately supporting more informed and effective decision-making processes (Kazakov and Miroshnichenko, 2022). The ability to leverage data in this manner enables educators to tailor their programs to better meet the needs of their students, fostering a more inclusive and supportive learning environment. Recent research highlights the effectiveness of AI in improving decision-making efficiency. Xu (2023) noted that AI tools allow educators to analyze real time data, facilitating timely adjustments to teaching strategies and ensuring that programs are responsive to the dynamic needs of students. This level of responsiveness is crucial for maintaining student engagement and optimizing educational outcomes, particularly in physical education where individual needs can vary widely.