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

<p>With the rapid development of the times, civic education and talent cultivation have become an important goal of the reform of civic education, and the reform of civic education under the background of deep learning and the improvement of the quality of talent cultivation has also become the research direction of today’s education reform. Based on the deep learning background, this paper constructs a deep learning model of civic and political education that combines the elements of the education model and evaluation elements. Based on the objectives and specifications of talent cultivation, the curriculum system of civic and political education is designed in reverse, through the framework of deep learning Civic and political education reform talent cultivation combined with factor analysis and multiple linear regression analysis to construct a deep learning-oriented evaluation system for talent cultivation in Civic and political education. The evaluation data are analyzed through practical verification, and in the results of the statistical analysis of the Civic and Political Education Reform, the standard deviation of the overall average score is 0.51 and less than 0.65, and its internal consistency is high. In the results of the talent cultivation survey and analysis, it can be seen that the frequency of scores from 131 to 140 is the highest, the frequency of scores from 151 to 160 is the lowest, and the overall number of high scores is higher, comparing the quality of the effect of talent cultivation, the level of achievement, student enthusiasm, the level of cultivation of comprehensive competence and student satisfaction have been improved compared with the traditional Civic Education. This study can effectively improve the quality and effect of talent cultivation, promote the reform process of Civics education in the context of deep learning, and provide practical significance for the reform of Civics education.</p>
</abstract>

With the rapid development of the times, civic education and talent cultivation have become an important goal of the reform of civic education, and the reform of civic education under the background of deep learning and the improvement of the quality of talent cultivation has also become the research direction of today’s education reform. Based on the deep learning background, this paper constructs a deep learning model of civic and political education that combines the elements of the education model and evaluation elements. Based on the objectives and specifications of talent cultivation, the curriculum system of civic and political education is designed in reverse, through the framework of deep learning Civic and political education reform talent cultivation combined with factor analysis and multiple linear regression analysis to construct a deep learning-oriented evaluation system for talent cultivation in Civic and political education. The evaluation data are analyzed through practical verification, and in the results of the statistical analysis of the Civic and Political Education Reform, the standard deviation of the overall average score is 0.51 and less than 0.65, and its internal consistency is high. In the results of the talent cultivation survey and analysis, it can be seen that the frequency of scores from 131 to 140 is the highest, the frequency of scores from 151 to 160 is the lowest, and the overall number of high scores is higher, comparing the quality of the effect of talent cultivation, the level of achievement, student enthusiasm, the level of cultivation of comprehensive competence and student satisfaction have been improved compared with the traditional Civic Education. This study can effectively improve the quality and effect of talent cultivation, promote the reform process of Civics education in the context of deep learning, and provide practical significance for the reform of Civics education.

Promoting the Reform of Civic and Political Education to Improve the Quality of Talent Cultivation Based on the Background of Deep Learning

Applied Mathematics and Nonlinear Sciences

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

With the rapid development of the times, civic education and talent cultivation have become an important goal of the reform of civic education, and the reform...

Promoting the Reform of Civic and Political Education to Improve the Quality of Talent Cultivation Based on the Background of Deep Learning

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 27 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0197

Mots clés
Factor analysis, Regression analysis, Statistical analysis, Evaluation model, Educational framework, Talent cultivation

© 2024 Yujun Chen, published by Sciendo

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

Promoting the Reform of Civic and Political Education to Improve the Quality of Talent Cultivation Based on the Background of Deep Learning

Publié en ligne: 31 janv. 2024

Pages: -

Reçu: 20 déc. 2023

Accepté: 27 déc. 2023

DOI: https://doi.org/10.2478/amns-2024-0197

Mots clésFactor analysis, Regression analysis, Statistical analysis, Evaluation model, Educational framework, Talent cultivation

© 2024 Yujun Chen, published by Sciendo

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

Mots clés
Factor analysis, Regression analysis, Statistical analysis, Evaluation model, Educational framework, Talent cultivation