Auxiliary Teaching of Badminton Basic Movements Based on Wireless Network Communication and Kinect

Abstract

Badminton is a sport with relatively delicate and complicated technical movements, which is widely welcomed in China. In order to study the specific impact of the sports game teaching method and traditional teaching method on the three aspects of the badminton learning technology mastery level, interest level, and subjective experience, with the reference of the wireless network to the students and Kinect on the students, in a three-month group teaching of students without foundation in a medical school in this city, the badminton action is broken down and the doubling of the badminton action is detected by WiFi and Kinect, to compare the traditional pedagogy and the method with this paper before and the lesson and to draw out conclusions. The results of the study found that badminton-assisted teaching based on wireless network communication and Kinect can achieve good results. The learning efficiency of students is significantly higher than that of traditional teaching methods, and badminton teaching based on wireless network communication and Kinect can effectively improve students’ interest in learning, 24% higher than the traditional method. This shows that wireless network communication and Kinect technology can play an important role in badminton teaching.

Automated Teaching Weighted Recurrent Neural Network (Atwrnn) Model: Analysis of Badminton Teaching Mode Based on Online Teaching Platform

“…In a badminton online teaching platform enhanced with neural network technology, the integration of artificial intelligence (AI) significantly amplifies the depth and effectiveness of the learning experience [15]. Neural networks, a subset of AI inspired by the structure of the human brain, excel at recognizing patterns and making complex decisions based on vast amounts of data.…”