Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

June 9, 2023


Pages


DOI

Article

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

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Authors

Guohua Shao Affiliation:
Institute of physical culture, Inner Mongolia Normal University, Hohhot, Inner Mongolia, 010022, China.


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.


Keywords

Principal component analysis algorithm, Innovative teaching, Path optimization, Multiple indicator evaluation, Multivariate statistical analysis, 62P25


Citation

Shao, G. (2023). Optimization of innovative information-based teaching paths in college sports psychology based on principal component analysis. Applied Mathematics and Nonlinear Sciences, 8(1). https://doi.org/10.2478/amns.2023.1.00383

Published by: Engineering Journals

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