Design and Development of Quality Evaluation of Physical Education in Colleges and Universities based on BP Neural Network

The traditional Physical Education (PE) teaching model is on the verge of elimination. With the constant change of learning needs, it is urgent to innovate and reform the teaching model. Physical education (PE) teaching has taken on greater significance in the modern classroom environment. There are currently several issues with the PE teaching style in most colleges and universities, such as a non-interactive teaching environment, inconsistent teaching data, and a lack of technical support for the system. In this research paper, IoT (Internet of Things) based Neural Networks is proposed for promoting the effective evaluation of the PE in educational institutions. This paper first constructs a physical education teaching system based on the Kaggle Datasets, then employs the Backpropagation-based Neural Networks (BP-NN) for reforming the physical education classroom teaching and gives a specific teaching application model. Finally, Optimized BP-Neural Network is used to evaluate the application model of college physical education. Through experiments and investigations, the new teaching mode improves the teaching efficiency by 15.8%, improves the teaching quality, and provides a reference for the next development of AI in teaching.