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<p>Under the background of big data, college students’ Civic Education has realized the adjustment of teaching technology and educational paradigm, and the value of big data technology for college students’ Civic Education has become increasingly intuitive. In this paper, firstly, the data points designated for clustering are selected in the dataset as the initial clustering centroids. In response to the Euclidean distance treating variables equally, the coefficient of variation method is proposed for subjective weighting. The support vector machine for solving the two-class classification problem is obtained as a real-valued function to test the parallel efficiency of different clustering mining algorithms in the same experimental setting. Finally, for the training sample input data, it is concluded that the algorithm has a better clustering effect and improves the speed and accuracy of clustering. The feasibility of the proposed influence path is demonstrated by comparing it with the data application of the subjective empirical weighting method. The results show that 8% of students before the experiment thought that integrating Confucianism into Civic Education was valuable and meaningful, and after the experiment, the number of students who thought it was valuable and meaningful increased from 8% to 58%. It indicates that the integration of excellent traditional Confucianism into the ideological and political education of college students is very important to strengthen the ideological and political education of college students.</p>
</abstract>

Under the background of big data, college students’ Civic Education has realized the adjustment of teaching technology and educational paradigm, and the value of big data technology for college students’ Civic Education has become increasingly intuitive. In this paper, firstly, the data points designated for clustering are selected in the dataset as the initial clustering centroids. In response to the Euclidean distance treating variables equally, the coefficient of variation method is proposed for subjective weighting. The support vector machine for solving the two-class classification problem is obtained as a real-valued function to test the parallel efficiency of different clustering mining algorithms in the same experimental setting. Finally, for the training sample input data, it is concluded that the algorithm has a better clustering effect and improves the speed and accuracy of clustering. The feasibility of the proposed influence path is demonstrated by comparing it with the data application of the subjective empirical weighting method. The results show that 8% of students before the experiment thought that integrating Confucianism into Civic Education was valuable and meaningful, and after the experiment, the number of students who thought it was valuable and meaningful increased from 8% to 58%. It indicates that the integration of excellent traditional Confucianism into the ideological and political education of college students is very important to strengthen the ideological and political education of college students.

Analysis of the Influence Path of Confucianism in the Civic Education of Contemporary College Students in the Context of Big Data

Applied Mathematics and Nonlinear Sciences

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

Under the background of big data, college students’ Civic Education has realized the adjustment of teaching technology and educational paradigm, and the value...

Analysis of the Influence Path of Confucianism in the Civic Education of Contemporary College Students in the Context of Big Data

Online veröffentlicht: 07. Okt. 2023

Seitenbereich: -

Eingereicht: 06. Dez. 2022

Akzeptiert: 17. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00515

Schlüsselwörter
Confucianism, K-means clustering algorithm, Euclidean distance, Support vector machine, Training samples

© 2023 Cheng Chen, published by Sciendo

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

Analysis of the Influence Path of Confucianism in the Civic Education of Contemporary College Students in the Context of Big Data

Online veröffentlicht: 07. Okt. 2023

Seitenbereich: -

Eingereicht: 06. Dez. 2022

Akzeptiert: 17. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00515

SchlüsselwörterConfucianism, K-means clustering algorithm, Euclidean distance, Support vector machine, Training samples

© 2023 Cheng Chen, published by Sciendo

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

Schlüsselwörter
Confucianism, K-means clustering algorithm, Euclidean distance, Support vector machine, Training samples