Application of Artificial Intelligence Technology in Martial Arts Education Governance

Author:

Ye Weiwu1,Li Shihong1,Liu Shuaibing2,Zhou Yuan3ORCID

Affiliation:

1. College of National Traditional Sports, Harbin Sport University, Harbin 150008, China

2. College of Martial Arts and Arts, Nanjing Sport Institute, Nanjing 210014, China

3. Public Course Department, Hubei Institute of Fine Arts, Wuhan 430205, China

Abstract

Martial arts education has a relatively comprehensive educational function. Compared with other educational methods, it has some unique features. When martial arts education carries out moral education, it not only attaches importance to the teaching of moral norms but also requires martial arts practitioners to practice moral norms, so martial arts education is more practical in improving moral literacy. In fact, the role of martial arts education is far from just playing its role in strengthening the body. This kind of prejudice of mindset conceals the diversity characteristics of martial arts education. This paper proposes to apply artificial intelligence technology in martial arts education governance, which uses the target tracking algorithm based on deep learning to track and analyze the movement of martial arts practitioners. At the same time, this paper uses the pose estimation algorithm of coordinate regression to predict the key points of the human body from the global perspective of the human body and then locates the key points of the human body from the features. It greatly simplifies the prediction of key points and solves the problem of nonstandard movements of students in martial arts education. The experimental analysis part includes the results and analysis of the impact of AI-based flipped classroom teaching on students’ martial arts learning and the comparison and analysis of students’ martial arts learning in the two classes after the experiment. The analysis results show that the P values of the four aspects of learning interest, active participation attitude, independent exploration ability, and analysis and problem-solving ability of the two classes are all less than 0.01, indicating that there is a significant difference.

Funder

Ministry of Education of the People's Republic of China

Publisher

Hindawi Limited

Subject

Modeling and Simulation

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