Research on AI Interaction to Promote Junior School Students’ Interest in ‎Physical Learning and Health Behaviors: A Big Data Analysis

This research investigates the potential impact of AI-driven tools on student engagement in physical education, focusing on physical activity ‎participation, health behaviors, and overall well-being. A quantitative approach with big data analysis was employed to analyze how AI ‎interactions influenced junior school students' interest in physical education and their health outcomes. Data were collected from AI-powered educational platforms tracking students' physical activities, health behaviors, and engagement with physical education programs. A ‎total of 1,000 students from Shandong Province participated in the study, and the data were processed using regression analysis and ma-‎machine learning models. The results showed a significant positive correlation between AI interaction frequency and both physical activity ‎participation and health behaviors. The findings indicate that as the frequency of AI interactions increased, students' physical activity levels ‎and health behaviors improved, suggesting that AI-driven tools are effective in promoting healthier lifestyles. The research also highlights ‎that personalized AI interventions, such as virtual coaches and gamified fitness apps, played a critical role in increasing student engagement ‎in physical education. However, the limitation of this study is that the sample is confined to junior high school students in Shandong Prov-‎ince, and the results may not fully reflect the situation in other regions or age groups. Future research could expand the sample size and ‎examine the long-term effects of AI tools in various educational settings to provide further insights into their potential for improving student ‎health outcomes and education quality.