Construction and Application of Tennis Teaching Digital Resources Based on Deep Learning

Abstract

Tennis teaching is an important part of traditional physical education in China. It aims to cultivate students' lifelong exercise habits, improve learning efficiency, and promote social development. Therefore, based on the concepts of deep learning and digital resource construction, this paper proposes the course structure design. This paper first describes the current situation of tennis teaching, then studies the relevant content of deep learning, and discusses the most commonly used neural network algorithm in the field of deep learning. Then, using the research method of the questionnaire survey, combined with the digital teaching mode, the teaching of Chinese college students tennis group research, and compared with the traditional teaching mode. The results showed that the experimental group (EP) learned more balanced technical movements than the control group (CP). The teaching effect of digital resource tennis course is better than conventional teaching, which shows that digital resource tennis course can master students' skills better than conventional teaching. Therefore, the construction of digital resources based on deep learning can improve students' tennis technology and stimulate students' interest in tennis.