Flipped classroom supported by music combined with deep learning applied in physical education

With the rapid development of information technology, multimedia teaching has basically become popular in education. As one of the teaching modes produced under the application of educational informatization, the flipped classroom has also attracted great attention from experts in the educational field in China since it was proposed in the United States and practiced overseas. The objective is to explore the application effect of flipped classrooms supported by music integrated with deep learning in physical education to improve the autonomous learning ability of students. Aiming at problems such as less teacher-student interaction, unskilled mastery of skills, and hidden safety hazards in physical education (PE) teaching, the new teaching mode of the flipped classroom is applied to PE teaching. In addition, deep learning and music are integrated to build a model for the application of flipped classrooms to physical education with the support of music integrated with deep learning. Finally, the control group, the experimental group M, and the experimental group N are set up through the control experimental design to compare and analyze the effect of the teaching mode proposed. The results show that the physical quality, mastery of motor skills, deep learning ability, and autonomous learning ability of middle school students in experimental group N with the support of music integrated with deep learning in the flipped classroom improved greatly, showing obvious differences compared with the control group and experimental group M (P < 0.05). Among them, the average scores of 50 meters running, sit-ups/pull-ups, 800/1000 meters, sitting forward bending, and cross-direction running reach 80.41, 82.35, 81.01, 79.79, and 79.83, respectively. It is found that the constructed system can effectively improve the physical quality, mastery of motor skills, deep learning ability, and autonomous learning ability in physical education teaching of students and can achieve the effect of deep learning. The results can provide an experimental reference for research on later adolescent education.(c) 2023 Published by Elsevier B.V.