Application and innovation of computer-assisted instruction in physical education

Abstract

A multimodal computer-aided instructional system combining virtual reality and advanced sensor fusion was developed to address persistent challenges in physical education, particularly for skill-based sports training. The main goal of this study is to observe and analyze the performance of athletes in basketball shooting training thru real-time inertial and vision-based data integration. The primary goal was to evaluate the impact of immersive adaptive feedback on motor skill acquisition and compare it to standard training. Participants were assigned to either a traditional control group or a virtual reality-assisted guidance group according to a stratified randomized study design. The sensor array processes biomechanical data with feedback latency of less than 50 milliseconds. According to the results of quantitative assessment, the VR intervention group reduced the movement variability and improved the shooting accuracy by 30%. Further analysis addressed technical issues such as sensor drift and system latency. Active calibration procedures and adaptive filtering models ensure data fidelity and feedback consistency. These results suggest that data-driven physical education can be applied more widely in education. This type of physical education can be achieved through real-time analysis, artificial intelligence and interactive virtual environments. This engineering approach helps to accurately assess the school or institutional environment.