UTILIZING BP NEURAL NETWORKS TO ENHANCE INNOVATION AND ENTREPRENEURSHIP IN COLLEGE SPORTS EDUCATION PROGRAMS

Abstract

Background: As the importance of innovation and entrepreneurship within sports education gains recognition, universities are increasingly emphasizing these skills in their physical education programs. Despite the growing interest, there remains a lack of a comprehensive evaluation system that can accurately measure the effectiveness of such initiatives, particularly in China, where this educational approach has emerged more recently compared to other regions. Objective: This study aims to develop and validate an evaluation model for innovation and entrepreneurship education in college sports programs, employing a BP neural network to analyze and enhance educational outcomes. Methods: Focusing on the sports department at S University as a case study, this research establishes a set of evaluation indicators specific to innovation and entrepreneurship in sports education. Using these indicators, a BP neural network model was designed and implemented to assess the current state of these educational programs and their impact on student development. Results: Preliminary findings suggest that the BP neural network provides a robust framework for evaluating and improving innovation and entrepreneurship training in sports education. The model not only assesses existing programs but also identifies key areas for enhancement, offering significant insights that can guide future curriculum development. Conclusion: This study contributes a novel approach to the evaluation of sports education programs, integrating advanced neural network technology to facilitate more effective training in innovation and entrepreneurship. The findings underscore the potential of such technologies to revolutionize educational assessment and support the development of more entrepreneurial and innovative sports professionals. Future research should expand this model to other institutions and continuously refine the evaluation metrics to further its applicability and accuracy.