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

<p>The comparison and study of ideological and political education methods in Chinese and American universities can enable us to improve ideological and political education methods further. In this paper, we use the global optimization performance of the genetic algorithm to overcome the disadvantage that the K-means algorithm is sensitive to initial values and tends to converge only to local optimum points and propose an improved K-means algorithm based on the genetic algorithm. Meanwhile, the combination with the simulated annealing algorithm eliminates the problem that the K-means algorithm is sensitive to isolated points, makes the algorithm less susceptible to extreme data, and improves the analysis ability of the algorithm. In analyzing the content of ideological and political education in China and the United States, the main contents of ideological and political education in American colleges and universities include civic education, patriotic education and religious education. The first content of ideological and political education in Chinese schools is “mental health education”, accounting for 94.44%, and the second is “moral quality education”, accounting for 75.97%. The second is “ideal and belief education” and “education on life and values”, accounting for 73.23% and 72.70%, respectively. Therefore, American colleges and universities cultivate responsible citizens with the American spirit, while Chinese Civic Education cultivates socialist builders who serve the people.</p>
</abstract>

The comparison and study of ideological and political education methods in Chinese and American universities can enable us to improve ideological and political education methods further. In this paper, we use the global optimization performance of the genetic algorithm to overcome the disadvantage that the K-means algorithm is sensitive to initial values and tends to converge only to local optimum points and propose an improved K-means algorithm based on the genetic algorithm. Meanwhile, the combination with the simulated annealing algorithm eliminates the problem that the K-means algorithm is sensitive to isolated points, makes the algorithm less susceptible to extreme data, and improves the analysis ability of the algorithm. In analyzing the content of ideological and political education in China and the United States, the main contents of ideological and political education in American colleges and universities include civic education, patriotic education and religious education. The first content of ideological and political education in Chinese schools is “mental health education”, accounting for 94.44%, and the second is “moral quality education”, accounting for 75.97%. The second is “ideal and belief education” and “education on life and values”, accounting for 73.23% and 72.70%, respectively. Therefore, American colleges and universities cultivate responsible citizens with the American spirit, while Chinese Civic Education cultivates socialist builders who serve the people.

Comparative strategies of domestic and foreign ideological and political education in universities in the context of big data

Applied Mathematics and Nonlinear Sciences

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

The comparison and study of ideological and political education methods in Chinese and American universities can enable us to improve ideological and political...

Comparative strategies of domestic and foreign ideological and political education in universities in the context of big data

Online veröffentlicht: 06. Sept. 2023

Seitenbereich: -

Eingereicht: 20. Nov. 2022

Akzeptiert: 17. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00291

Schlüsselwörter
Ideological and political education, Genetic algorithm, K-means algorithm, Chinese and American universities, Simulated annealing algorithm

© 2023 Rongyun Zhang, published by Sciendo

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

Comparative strategies of domestic and foreign ideological and political education in universities in the context of big data

Online veröffentlicht: 06. Sept. 2023

Seitenbereich: -

Eingereicht: 20. Nov. 2022

Akzeptiert: 17. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00291

SchlüsselwörterIdeological and political education, Genetic algorithm, K-means algorithm, Chinese and American universities, Simulated annealing algorithm

© 2023 Rongyun Zhang, published by Sciendo

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

Schlüsselwörter
Ideological and political education, Genetic algorithm, K-means algorithm, Chinese and American universities, Simulated annealing algorithm