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

<p>In this paper, after the extraction of teaching resource features by mutual information method, the classification of Civics teaching resources is realized by constructing a decision tree classifier. According to the current situation of Civics education in university sports courses, the set segmentation correlation function is determined, the contribution of each factor is combined using the correlation matrix, the correlation coefficient weights are calculated, and the design of the Civics multimodal corpus is accomplished based on big data technology. Nine universities in Guangzhou City were selected as the objects of this study, and the research data were obtained through questionnaire surveys of physical education teachers in these nine schools. SPSS26.0 and Origin 2019 software were used to study the Civics and Politics of Physical Education Courses in Colleges and Universities. The results show that the convergence speed of the objective function of the algorithm in this paper and the classification accuracy has been improved substantially, compared with other algorithms, by about 0.3 to 0.7, i.e., it shows that the algorithm in this paper has a good performance of classification of the course Sijian. The scores of national sentiment and sports core literacy are 0.76 and 0.76, respectively, with a rank of medium (less than 0.79), and the score of physical and mental health is 0.82, with a rank of high (greater than or equal to 0.8). That is, the public physical education (volleyball) class has a relatively satisfactory effect on the cultivation of students’ physical and mental health, while there is still room for progress in the cultivation effect of family and national sentiment and sports core literacy. This study supplements, to a certain extent, the lack of an evaluation index system for the effect of sports courses’ ideology and nurturing and promotes the better development of public sports courses’ ideology.</p>
</abstract>

In this paper, after the extraction of teaching resource features by mutual information method, the classification of Civics teaching resources is realized by constructing a decision tree classifier. According to the current situation of Civics education in university sports courses, the set segmentation correlation function is determined, the contribution of each factor is combined using the correlation matrix, the correlation coefficient weights are calculated, and the design of the Civics multimodal corpus is accomplished based on big data technology. Nine universities in Guangzhou City were selected as the objects of this study, and the research data were obtained through questionnaire surveys of physical education teachers in these nine schools. SPSS26.0 and Origin 2019 software were used to study the Civics and Politics of Physical Education Courses in Colleges and Universities. The results show that the convergence speed of the objective function of the algorithm in this paper and the classification accuracy has been improved substantially, compared with other algorithms, by about 0.3 to 0.7, i.e., it shows that the algorithm in this paper has a good performance of classification of the course Sijian. The scores of national sentiment and sports core literacy are 0.76 and 0.76, respectively, with a rank of medium (less than 0.79), and the score of physical and mental health is 0.82, with a rank of high (greater than or equal to 0.8). That is, the public physical education (volleyball) class has a relatively satisfactory effect on the cultivation of students’ physical and mental health, while there is still room for progress in the cultivation effect of family and national sentiment and sports core literacy. This study supplements, to a certain extent, the lack of an evaluation index system for the effect of sports courses’ ideology and nurturing and promotes the better development of public sports courses’ ideology.

Digitization of Civics in College Physical Education Courses Based on the Correlation Matrix

Applied Mathematics and Nonlinear Sciences

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

In this paper, after the extraction of teaching resource features by mutual information method, the classification of Civics teaching resources is realized by...

Digitization of Civics in College Physical Education Courses Based on the Correlation Matrix

Data publikacji: 20 gru 2023

Zakres stron: -

Otrzymano: 15 lut 2023

Przyjęty: 30 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01576

Słowa kluczowe
Decision tree classifier, Relevance function, Correlation matrix, Multimodal corpus, Sports course ideology and politics

© 2023 Jing Liu et al., published by Sciendo

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

Digitization of Civics in College Physical Education Courses Based on the Correlation Matrix

Data publikacji: 20 gru 2023

Zakres stron: -

Otrzymano: 15 lut 2023

Przyjęty: 30 cze 2023

DOI: https://doi.org/10.2478/amns.2023.2.01576

Słowa kluczoweDecision tree classifier, Relevance function, Correlation matrix, Multimodal corpus, Sports course ideology and politics

© 2023 Jing Liu et al., published by Sciendo

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

Słowa kluczowe
Decision tree classifier, Relevance function, Correlation matrix, Multimodal corpus, Sports course ideology and politics