Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

The Influence of Computer Network Technology Using Digital Technology on the Quality of Physical Education in Colleges under Complex Scenes

Published: 01 January 2022 Publication History

Abstract

Recently, college physical education has received a lot of attention. Traditional physical education and teaching are unable to meet the demand of students in today’s society and cannot attract students’ interest in sports. In this study, the challenges of college physical education classrooms are examined and the teaching objectives, contents, and teaching evaluation of the course are established to improve students’ deep learning (DL) and the effect and quality of college PE. The flipped classroom model based on DL is applied to PE teaching in colleges, and the influence of classroom teaching is explored. Moreover, a teaching experiment is conducted and the teaching effect before and after the experiment is compared. The results show that the P values of the three groups of students in the five items of 50 m running, sit-up/pull-up, 800 m/1000 m, sit and reach, and crossing direction change running are 0.003, 0.012, 0.024, 0.024, and 0.048, respectively. This indicates significant improvements in the physical quality of the three groups of students after the experiment. In addition, the three groups of students have significant differences in basketball technical and tactical application ability, DL ability, and autonomous learning ability after the experiment. This exploration integrates the concept of DL with the flipped classroom, providing a theoretical supplement for the design of flipped classrooms in college PE.

References

[1]
Q. Wang and P. Lu, “Research on application of artificial intelligence in computer network technology,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 33, no. 5, pp. 1959015.1–1959015. 12, 2019.
[2]
V. Ginneken and H. Bram, “Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning,” Radiological Physics and Technology, vol. 10, no. 1, pp. 1–10, 2017.
[3]
A. Rajkumar, “Scalable and accurate deep learning for electronic health records,” npj Digital Medicine, vol. 1, no. 1, p. 18, 2018.
[4]
Y. Chen, Z. Lin, Z. Xing, W. Gang, and Y. Gu, “Deep learning-based classification of hyperspectral data,” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, vol. 7, no. 6, pp. 2094–2107, 2014.
[5]
C. W. Tsai, P. D. Shen, and C. H. Lin, “How to solve students' problems in a flipped classroom: a quasi-experimental approach,” Universal Access in the Information Society, vol. 16, no. 1, pp. 225–233, 2017.
[6]
L. Jing, W. Xu, and J. Shi, “Network education platform in flipped classroom based on improved cloud computing and support vector machine,” Journal of Intelligent and Fuzzy Systems, vol. 39, no. 99, pp. 1–11, 2020.
[7]
F. J. Ruzic, “A framework for teaching security design analysis using case studies and the hybrid flipped classroom,” Computing Reviews, vol. 60, no. 12, pp. 479–480, 2019.
[8]
J. Meng, “Artificial Intelligence and Edge Computing in Mobile Information Systems,” Mobile Information Systems, vol. 2021, 11 pages, 2021.
[9]
J. Zhang and Z. Zhang, “Research on the reform strategy of college physical education under the background of internet+,” Journal of Hebei University of Engineering (Social Science Edition), vol. 36, no. 1, pp. 98–100, 2019.
[10]
Y. U. Wei-Ping and L. Jin-Song, “Rethinking the reform of college physical education courses in the new era,” Journal of Heb Sport University, vol. 1, no. 1, pp. 35–37, 2019.
[11]
S. Silvrman, “Technology and Physical Education: Present, Possibilities, and Potential Problems,” Quest, vol. 49, no. 3, pp. 306–314, 2012.
[12]
P. Tearle and G. Gordle, “The use of ICT in the teaching and learning of physical education in compulsory education: how do we prepare the workforce of the future?” European Journal of Teacher Education, vol. 31, no. 1, pp. 55–72, 2008.
[13]
M. Papastergioua, V. Gerodimosa, and P. Antoniou, “Multimedia blogging in physical education: effects on student knowledge and ICT self-efficacy,” Computers & Education, vol. 57, no. 3, pp. 1998–2010, 2011.
[14]
S. Hoshang, T. A. Hilal, and H. A. Hilal, “Investigating the acceptance of flipped classroom and suggested recommendations,” Procedia Computer Science, vol. 184, no. 3, pp. 411–418, 2021.
[15]
X. Zhang, J. Wang, and J. Hu, “A heterogeneous linguistic MAGDM framework to classroom teaching quality evaluation,” Eurasia Journal of Mathematics Science & Technology Education, vol. 13, no. 8, pp. 4929–4956, 2017.
[16]
B. Wang, W. Jing, and G. Hu, “College English classroom teaching evaluation based on particle swarm optimization–extreme learning machine model,” International Journal of Emerging Technologies in Learning, vol. 12, no. 5, p. 82, 2017.
[17]
M. H. Sun, Y. G. Li, and B. He, “Study on a quality evaluation method for college English classroom teaching,” Future Internet, vol. 9, no. 3, p. 41, 2017.
[18]
J. Hiebert, E. Miller, and D. Berk, “Relationships between mathematics teacher preparation and graduates' analyses of classroom teaching,” Elementary School Journal, vol. 117, no. 4, pp. 687–707, 2017.
[19]
L. Bollen, P. V. Kampen, and M. Cock, “Development, implementation, and assessment of a guided-inquiry teaching-learning sequence on vector calculus in electrodynamics,” Physical Review Physics Education Research, vol. 14, no. 2, pp. 20115–20115, 2018.
[20]
J. White, K. Costilow, and D. Shockley, “Guided-inquiry experiment for teaching the calibration method of standard addition in the analysis of lead with graphite furnace atomic absorption spectroscopy,” Journal of Chemical Education, vol. 98, no. 2, pp. 620–625, 2021.
[21]
A. Dagnew and D. Mekonnen, “Effect of using guided inquiry teaching method in improving grade eight students' concept of photosynthesis, primary school: Ethiopia,” International Journal of Innovative Research in Education, vol. 7, no. 1, pp. 01–15, 2020.
[22]
A. Ferrari, P. Spoletini, and D. Zowghi, “SaPeer and reverse SaPeer: teaching requirements elicitation interviews with role-playing and role reversal,” Requirements Engineering, vol. 25, no. 4, pp. 417–438, 2020.
[23]
R. Natoli, Z. Wei, and E. Chapple, “Teaching IFRS: evidence from course experience and approaches to learning in China,” Accounting Research Journal, vol. 33, no. 1, pp. 234–251, 2020.
[24]
H. Yadav, S. Ramakrishnappa, and B. Karikalan, “Reverse teaching- a strategy for undergraduate medical education in pathology,” Indian Journal of Pathology and Oncology, vol. 6, no. 2, pp. 233–236, 2019.
[25]
H. L. Francisco, A. D. Inmaculada, and C. María, “Incidence of the flipped classroom in the physical education students' academic performance in university contexts,” Sustainability, vol. 10, no. 5, p. 1334, 2018.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image Mobile Information Systems
Mobile Information Systems  Volume 2022, Issue
2022
19033 pages
ISSN:1574-017X
EISSN:1875-905X
Issue’s Table of Contents
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Publisher

IOS Press

Netherlands

Publication History

Published: 01 January 2022

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 0
    Total Downloads
  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Dec 2024

Other Metrics

Citations

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media