Abstract

With the continuous development of society and the rapid development of science and technology, virtual reality technology is also developing rapidly. It has been widely used in all walks of life and is playing an irreplaceable role. Modern education has also begun to integrate with science. Sports are also constantly deepening the application of information technology. In order to make students have a new understanding of college physical education and sports training and improve the technical level and training quality of college sports athletes, this paper studies the application of virtual reality technology in physical education and sports training. In this paper, the semisupervised framework is used to implement motion input and interactive virtual scene algorithms. First, based on Q statistics, virtual simulation and differential selection algorithms are used to select athletic students with strong autonomous learning ability and then use the classifier’s neighbor confidence. The formula selects the student with the highest learning level and marks it. Experimental results show that this method can effectively assist physical education activities and improve students’ learning efficiency. Students’ efficiency in sports has increased by 30%. At the same time, 2/3 of people believe that their interest in sports training has increased 80% and another 90% of college coaches believe that the use of virtual reality technology in physical education is very necessary, which can improve the technical level and training quality of college sports athletes and contribute to the reserve of Chinese competitive sports talents.

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