IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i23p15947-d988445.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Xingxing Zong & Mariusz Lipowski & Taofeng Liu & Meng Qiao & Qi Bo, 2022. "The Sustainable Development of Psychological Education in Students’ Learning Concept in Physical Education Based on Machine Learning and the Internet of Things," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15947-:d:988445
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/23/15947/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/23/15947/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Donglin Hu & Shi Zhou & Zachary J. Crowley-McHattan & Zhiyun Liu, 2021. "Factors That Influence Participation in Physical Activity in School-Aged Children and Adolescents: A Systematic Review from the Social Ecological Model Perspective," IJERPH, MDPI, vol. 18(6), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianliu Zhu, 2023. "Matching Prediction of Teacher Demand and Training Based on SARIMA Model Based on Neural Network," International Journal of Information Technology and Web Engineering (IJITWE), IGI Global, vol. 18(1), pages 1-15, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anwar Al-Nuaim & Ayazullah Safi, 2023. "Factors Influencing Saudi Youth Physical Activity Participation: A Qualitative Study Based on the Social Ecological Model," IJERPH, MDPI, vol. 20(10), pages 1-15, May.
    2. Lin Zhou & Wei Liang & Yuxiu He & Yanping Duan & Ryan E. Rhodes & Hao Liu & Hongmei Liang & Xiaowei Shi & Jun Zhang & Yingzhe Cheng, 2022. "Relationship of 24-Hour Movement Behaviors with Weight Status and Body Composition in Chinese Primary School Children: A Cross-Sectional Study," IJERPH, MDPI, vol. 19(14), pages 1-14, July.
    3. Changqing Xiang & Jie Zhao & Tengku Fadilah Tengku Kamalden & Wenting Dong & Hua Luo & Normala Ismail, 2023. "The effectiveness of child and adolescent sports engagement in China: an analysis of China’s results for the 2016–2022 Global Matrix report cards on physical activity," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    4. Romain Marconnot & Jorge Pérez-Corrales & Juan Nicolás Cuenca-Zaldívar & Javier Güeita-Rodríguez & Pilar Carrasco-Garrido & Cristina García-Bravo & Eva Solera-Hernández & Sonia Gutiérrez Gómez-Calcerr, 2021. "The Perspective of Physical Education Teachers in Spain Regarding Barriers to the Practice of Physical Activity among Immigrant Children and Adolescents: A Qualitative Study," IJERPH, MDPI, vol. 18(11), pages 1-15, May.
    5. Rodrigo Soto-Lagos & Carolina Cortes-Varas & Solange Freire-Arancibia & María-Alejandra Energici & Brent McDonald, 2022. "How Can Physical Inactivity in Girls Be Explained? A Socioecological Study in Public, Subsidized, and Private Schools," IJERPH, MDPI, vol. 19(15), pages 1-18, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15947-:d:988445. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.