<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Physical education needs to focus on improving students’ physical fitness and quality and psychological training for students. Therefore, this paper proposes a strategy to combine sports psychology with realistic teaching to optimize innovative teaching paths in line with students’ development to develop students’ comprehensive quality level in college sports psychology teaching. The indicators in the teaching evaluation are classified and summarized to complete a multi-indicator evaluation to improve the quality of teaching. The theory of sports psychology is adjusted and improved, and the teaching guideline is changed to apply PCA (principal component analysis algorithm) of multivariate statistical analysis to teaching evaluation. The raw data of students’ evaluation were processed by calculation and analysis to determine the main factors affecting teaching quality and analyzed with experiments. The results show that 78.1% of college students think that physical exercise can enhance self-confidence and 77.4% think physical exercise can promote healthy growth. It can be seen that combining the content of sports psychology with practical training effectively improves students’ sports psychological quality.</p>
</abstract>

Physical education needs to focus on improving students’ physical fitness and quality and psychological training for students. Therefore, this paper proposes a strategy to combine sports psychology with realistic teaching to optimize innovative teaching paths in line with students’ development to develop students’ comprehensive quality level in college sports psychology teaching. The indicators in the teaching evaluation are classified and summarized to complete a multi-indicator evaluation to improve the quality of teaching. The theory of sports psychology is adjusted and improved, and the teaching guideline is changed to apply PCA (principal component analysis algorithm) of multivariate statistical analysis to teaching evaluation. The raw data of students’ evaluation were processed by calculation and analysis to determine the main factors affecting teaching quality and analyzed with experiments. The results show that 78.1% of college students think that physical exercise can enhance self-confidence and 77.4% think physical exercise can promote healthy growth. It can be seen that combining the content of sports psychology with practical training effectively improves students’ sports psychological quality.

Optimization of innovative information-based teaching paths in college sports psychology based on principal component analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Physical education needs to focus on improving students’ physical fitness and quality and psychological training for students. Therefore, this paper proposes a...

Optimization of innovative information-based teaching paths in college sports psychology based on principal component analysis

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 04. Juli 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00383

Schlüsselwörter
Principal component analysis algorithm, Innovative teaching, Path optimization, Multiple indicator evaluation, Multivariate statistical analysis

© 2023 Guohua Shao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Optimization of innovative information-based teaching paths in college sports psychology based on principal component analysis

Online veröffentlicht: 09. Juni 2023

Seitenbereich: -

Eingereicht: 04. Juli 2022

Akzeptiert: 15. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00383

SchlüsselwörterPrincipal component analysis algorithm, Innovative teaching, Path optimization, Multiple indicator evaluation, Multivariate statistical analysis

© 2023 Guohua Shao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Principal component analysis algorithm, Innovative teaching, Path optimization, Multiple indicator evaluation, Multivariate statistical analysis