The Sustainable Development of Psychological Education in Students’ Learning Concept in Physical Education Based on Machine Learning and the Internet of Things

Xingxing Zong, Mariusz Lipowski, Taofeng Liu, Meng Qiao and Qi Bo ()
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Xingxing Zong: Faculty of Physical Culture, Gdansk University of Physical Education and Sport, 80-336 Gdansk, Poland
Mariusz Lipowski: Faculty of Physical Culture, Gdansk University of Physical Education and Sport, 80-336 Gdansk, Poland
Taofeng Liu: Physical Education Institute (Main Campus), Zhengzhou University, Zhengzhou 450001, China
Meng Qiao: Faculty of Physical Culture, Gdansk University of Physical Education and Sport, 80-336 Gdansk, Poland
Qi Bo: Sports Department, Central South University, Changsha 410083, China

Sustainability, 2022, vol. 14, issue 23, 1-16

Abstract: Aim: This paper aims to enhance the emphasis of college physical education (P.E.) in the psychological education of P.E. students and provide a reference for the innovation of P.E. teaching methods. Methodology and procedures: On the basis of the Internet of Things (IoT) and a deep-learning algorithm, combined with psychological education, the teaching effect and the influence on learning philosophy are comprehensively evaluated through the construction of teaching evaluation index system for college P.E. students. Results: The theoretical courses of P.E. students in colleges and universities lack the integration of psychological-education concepts. It is found that the new teaching mode not only has a significant effect on improvement of training courses, but also promotes learning enthusiasm and theoretical courses. In the aspect of psychological quality evaluation, emotional-control ability significantly improved, the average score increased from below 60 to above 79, and self-challenge ability and adaptability to adversity also effectively improved. In the evaluation of deep-learning ability, students’ critical thinking ability improved most obviously, and their complex problem-solving ability also improved to some extent. Conclusions: Based on the IoT and machine learning, college P.E. teaching mode can effectively improve students’ psychological quality and ability, effectively improve students’ training and theoretical achievements, and significantly improve their academic achievements. It can also improve students’ self-learning ability. Practical applications: This paper reforms the traditional P.E. teaching mode, effectively demonstrates the hypothesis through practical teaching, designs the teaching evaluation index system of college P.E. students, and improves their learning ability and comprehensive achievements.

Keywords: Internet of Things; deep learning; physical-education teaching; psychological education; learning evaluation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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