Enhancing College Physical Education through Bioinformatics: A Digital Transformation Approach

Abstract

This study explores the application of bioinformatics technology in enhancing physical education teaching at the collegiate level. By integrating digital development techniques with bioinformatics, we harness the power of DNA molecular structures and RNA transcription processes to analyze and interpret student movement data. This innovative approach utilizes biological enzyme catalysis to convert biological signals into precise movement, health, and performance data for students. Using support vector machines, we have developed a robust framework for analyzing biomechanical information, which in turn has facilitated the creation of a personalized teaching platform. This platform tailor’s physical education strategies to individual student needs, optimizing both engagement and educational outcomes. The effectiveness of our method is demonstrated through significant improvements in teaching performance, achieving a performance score of 98.61. Moreover, our approach received high approval ratings, with an 87.5% satisfaction rate among students regarding their improved understanding of theoretical physical education concepts and satisfaction with the new teaching modalities. The findings confirm the substantial benefits of leveraging bioinformatics and digital technologies in physical education, offering a model that significantly enhances the quality of teaching. This method not only improves the delivery of physical education but also provides a scalable model that could be adapted to other educational fields where individualized data analysis could enhance learning outcomes.