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

<p>In the era of big data, the constantly innovative technology provides a new model for the development of ideological and political education. In this paper, on the basis of the data mining process, regression analysis and clustering algorithms are used to construct a visual analysis model of ideological and political education data in order to better provide teachers with more information about students’ data and explore the factors influencing ideological and political education. On this basis, an innovative mechanism for ideological and political education has been constructed, and the Introduction to International Politics course at X University of G Province is used as an example to analyze its effectiveness. The results show that there is a significant difference between the two groups, except that there is no significant difference in the overall learning motivation level (p=0.241>0.05). Compared with the pre-test, students in Group A showed a small downward trend in national identity, learning motivation, academic level, and its sub-dimensions as a whole (0.028-0.162). In contrast, Group B showed an upward trend, with an enhancement of between 0.134 and 0.352. The adopted innovative mechanism of ideological and political education can significantly improve students’ national identity and academic level in all aspects and effectively stimulate students’ endogenous learning motivation.</p>
</abstract>

In the era of big data, the constantly innovative technology provides a new model for the development of ideological and political education. In this paper, on the basis of the data mining process, regression analysis and clustering algorithms are used to construct a visual analysis model of ideological and political education data in order to better provide teachers with more information about students’ data and explore the factors influencing ideological and political education. On this basis, an innovative mechanism for ideological and political education has been constructed, and the Introduction to International Politics course at X University of G Province is used as an example to analyze its effectiveness. The results show that there is a significant difference between the two groups, except that there is no significant difference in the overall learning motivation level (p=0.241>0.05). Compared with the pre-test, students in Group A showed a small downward trend in national identity, learning motivation, academic level, and its sub-dimensions as a whole (0.028-0.162). In contrast, Group B showed an upward trend, with an enhancement of between 0.134 and 0.352. The adopted innovative mechanism of ideological and political education can significantly improve students’ national identity and academic level in all aspects and effectively stimulate students’ endogenous learning motivation.

Construction of Ideological and Political Education Innovation Mechanism in the Era of Big Data - Based on Data Analysis Methods

Applied Mathematics and Nonlinear Sciences

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

In the era of big data, the constantly innovative technology provides a new model for the development of ideological and political education. In this paper, on...

Construction of Ideological and Political Education Innovation Mechanism in the Era of Big Data - Based on Data Analysis Methods

Online veröffentlicht: 05. Juli 2024

Seitenbereich: -

Eingereicht: 27. Feb. 2024

Akzeptiert: 26. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1729

Schlüsselwörter
Data mining, Regression analysis, Clustering algorithm, Ideological and political education, Innovative mechanism

© 2024 Haitao Sun., published by Sciendo

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

Construction of Ideological and Political Education Innovation Mechanism in the Era of Big Data - Based on Data Analysis Methods

Online veröffentlicht: 05. Juli 2024

Seitenbereich: -

Eingereicht: 27. Feb. 2024

Akzeptiert: 26. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1729

SchlüsselwörterData mining, Regression analysis, Clustering algorithm, Ideological and political education, Innovative mechanism

© 2024 Haitao Sun., published by Sciendo

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

Schlüsselwörter
Data mining, Regression analysis, Clustering algorithm, Ideological and political education, Innovative mechanism