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

被引:0
作者
Shao G. [1 ]
机构
[1] Institute of Physical Culture, Inner Mongolia Normal University, Inner Mongolia, Hohhot
关键词
Innovative teaching; Multiple indicator evaluation; Multivariate statistical analysis; Path optimization; Principal component analysis algorithm;
D O I
10.2478/amns.2023.1.00383
中图分类号
学科分类号
摘要
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. © 2023 Guohua Shao, published by Sciendo.
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