A Study on the Changing Role of Primary School Teachers for Enhancing Elementary Physical Education Classes Utilizing Edutech

Objectives This study analyzes the educational value and effects of elementary physical education classes utilizing big data and wearable AI sensors, and explores the changing roles and necessary competency enhancements for elementary school teachers in this context. It aims to propose directions for future elementary physical education by addressing the limitations of traditional, uniform instruction and emphasizing personalized education. Methods The study employs a literature review and theoretical analysis, drawing from academic databases, journals, books, and policy reports. Data analysis includes content analysis to derive educational value and effects, thematic analysis to identify key themes related to teacher roles and competencies, comparative analysis to find commonalities and differences across studies, and critical review to evaluate claims and identify limitations. Data collection involved Google Forms, in-depth semi-structured and unstructured group interviews, and KakaoTalk online interviews during a 15-week period in the second semester of 2024. Triangulation was used to enhance research validity, and participant verification was employed for discourse analysis. Conclusions The integration of wearable AI sensors and big data in elementary physical education enables personalized education, enhances self-directed learning, and boosts motivation. Elementary teachers' roles are shifting from simple instructors to data-driven learning designers, personalized feedback providers, and motivators. This necessitates enhanced teacher competencies in data literacy, technology utilization, and individualized learning design, requiring curriculum reform, systematic training, and collaborative research. This study provides insights for improving the quality of future elementary physical education and realizing student-centered learning.