Deep Learning Algorithm for Online College Physical Education Teaching with Flipping Classroom

Abstract

In view of the inability to accurately analyze the application of deep learning in college physical education teaching design from the perspective of flipping classroom, this paper puts forward an improved deep learning method based on the integration of flipping classroom vision and deep learning, which can reduce the design ability of physical education teaching design in college physical education teaching design and improve the level of college physical education teaching design. Firstly, the initial data set is established by using the theory of flipping classroom horizon, so that the data meet the requirements of normal distribution and reduce the differences between teaching data; Then, the physical education teaching design is divided into different subdesigns by using the theory of flipping classroom horizon. Find the best design result in this domain in each subinstructional design; Finally, under the guidance of the theory of flipping classroom horizon, each subdesign realizes the optimal allocation of teaching resources. MATLAB simulation shows that under the conditions of initial design scheme and teaching resources setting, the improved deep learning method can improve the accuracy of physical education teaching design and shorten the convergence time of design, which is superior to the original deep learning method. Therefore, the deep learning method is used to analyze the instructional design of college physical education, which has a good design effect and is suitable for the instructional design of college physical education.