Objectives: This study empirically examined the effects of a digital game-based physical activity program (AI-FIT) on elementary school children’s health-related physical fitness while exploring the role of educational technology (EdTech) as a practical solution to post-pandemic physical inactivity. Methods: This study was conducted over a 12-week period, from September to December 2024, with 40 students (grades 4 to 6) from an elementary school located in a mid-sized city in South Korea. The participants had a mean age of 10.8 years (SD = 0.69). The experimental group (n = 20) participated in the AI-FIT program, while the control group (n = 20) received regular physical education classes. To ensure baseline equivalence between the groups, propensity score matching was employed. Health-related physical fitness was assessed through pre- and post-tests, including flexibility, muscular endurance, cardiorespiratory endurance, explosive power, and Physical Activity Promotion System (PAPS) grade. Analyses were conducted using both dependent (paired) and independent t-tests, along with effect size calculations (Cohen’s d), to examine within-group and between-group differences. In addition, gender-based subgroup analyses were performed to examine potential differences in responsiveness to the intervention. Intervention: Results indicated that the AI-FIT program had a large effect on flexibility (d = 0.90) and muscular endurance (d = 0.80) and a moderate-to-large effect on PAPS grade (d = 0.69). In contrast, no statistically significant improvements were observed in cardiorespiratory endurance or explosive power. Conclusions: These findings suggest that a digital program integrating AI-based personalized exercise prescriptions and gamification elements can effectively enhance the health-related fitness of elementary students. Moreover, this study supports the educational efficacy of EdTech-based interventions in physical education settings.

This study aimed to empirically examine the effects of a digital game-based physical activity program (AI-FIT) on improving health-related physical fitness among elementary school students. Specifically, the study sought to explore the potential of educational technology (EdTech) in physical education and to propose a practical intervention to address the decline in physical activity levels following the COVID-19 pandemic. The study was conducted over a 12-week period, from September to December 2024, with 40 students in grades 4 to 6 from an elementary school located in a mid-sized city in South Korea. The experimental group (n = 20) participated in the AI-FIT program, while the control group (n = 20) received regular physical education classes. To ensure baseline equivalence between the groups, propensity score matching was employed. Health-related physical fitness was assessed through pre- and post-tests, including body mass index (BMI), flexibility, muscular endurance, cardiorespiratory endurance, power, and Physical Activity Promotion System (PAPS) grade. Analyses were conducted using both statistical comparisons and effect size calculations (Cohen’s d). Results indicated that the AI-FIT program had a large effect on flexibility (d = 0.90) and muscular endurance (d = 0.80), and a moderate-to-large effect on BMI (d = 0.72) and PAPS grade (d = 0.69). In contrast, no statistically significant improvements were observed in cardiorespiratory endurance or power. These findings suggest that a digital program integrating AI-based personalized exercise prescriptions and gamification elements can effectively enhance the health-related fitness of elementary students. Moreover, the study supports the educational efficacy of EdTech-based interventions in physical education settings.