Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

February 26, 2024


Pages


DOI

Article

The Infiltration and Integration of the Concept of Ideological and Political Education in the Employment of College Students in the Era of Big Data

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Authors

Yu Wang Affiliation:
Nanjing Institute of Tourism and Hospitality, Nanjing, Jiangsu, 210000, China.
and Yu Zhou Affiliation:
Hefei Normal University, Hefei, Anhui, 230000, China.


Abstract

This paper studies integrating and penetrating the concept of Civic and Political Education in the employment guidance of college students to improve the effect of employment education in the context of big data. This paper uses genetic algorithm and projection tracking method to construct a measurement and evaluation model of Civic and Political Education and employment integration level. It is found that the coupling degree between Civic and Political Education and student employment in college A has increased year by year from 2010 to 2023, showing the effective integration of Civic and Political Education and jobs. The coupling degree risen from 0.136 in 2010 to 0.987 in 2023, indicating that the penetration and integration of Civic and Political Education in employment increased significantly. Strengthening the integration of Civic and Political Education and Employment Guidance can help improve the quality of student employment and student employment satisfaction. This study provides empirical support for integrating civic and political education and employment guidance in colleges. It confirms the importance and effectiveness of civic and political education in employment guidance in colleges and universities in the era of big data.


Keywords

Big data, Ideological and political education, College employment, Integration analysis, 00A66


Citation

Wang, Y. & Zhou, Y. (2024). The infiltration and integration of the concept of ideological and political education in the employment of college students in the era of big data. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0629

Published by: Engineering Journals

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