Retracted Gold Open Access 2022

Retraction:Application of the PBL Model Based on Deep Learning in Physical Education Classroom Integrating Production and Education

LH
Li, Honghai
 DH
Deng, Hongtao
 ZY
Zhang, Yi
Computational Intelligence and Neuroscience
Journal · Vol. 2022 · Art. 4806763
Abstract

This study aims to arouse students' interest in physical education (PE) in response to President Xi Jinping's call to strengthen students' physical quality because cultural courses occupy PE classes. Problem-based learning (PBL) is introduced, and a new teaching method of PE is proposed based on the convolutional neural network (CNN) in deep learning (DL). This method is employed to teach the experimental subjects in solid ball throwing. The students' interest, learning ability, and physical quality in the solid ball are investigated by a questionnaire survey. The questionnaire survey shows that the students' academic performance in solid ball throwing is improved, and their problem-solving ability, group cooperation ability, and theory learning ability are improved. Their time on a 1000-meter long run is shortened, and their body flexibility is improved. Therefore, it is believed that this new teaching method based on DL plays a significant role in improving students' physical quality. © 2022 Honghai Li et al.

Keywords

Author Keywords

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Index Keywords

Learning systems Teaching Teaching methods human questionnaire Humans Surveys and Questionnaires Education computing Students medical student Students, Medical Learning models Problem based learning Deep learning Problem-Based Learning New teaching physical education Physical Education and Training Learning abilities Students' interests Questionnaire surveys Surveys Group theory Physical quality Solid ball
Author Affiliations
Northwest Normal University China, Lanzhou, Gansu, China
Department of Physical Education, Xi'an University of Finance and Economics, Xi'an, China
School of Management, Xi'an University of Finance and Economics, Xi'an, China
Funding & Acknowledgements
No funding information
References 10 References
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