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<p>The primary objective of Civics education in higher education institutions is to guide students toward acquiring appropriate political identities and values. To achieve this, we advocate for the incorporation of a knowledge-tracking model in Civics curriculum instruction, highlighting that the practical application of in-depth knowledge tracking manifests throughout the educational process. Addressing the challenges inherent in the Civic Politics teaching model that integrates knowledge tracking, we propose solutions focused on the dimensions of student performance behavior and learning capabilities within the Civic Politics course. This involves the use of clustering grouping and attention mechanisms to refine the construction of the knowledge tracking model for Civics teaching. Building on this foundation, we define the research subjects and tools and provide an illustrative case study of the implemented knowledge-tracking model in Civic Politics education. The results are presented in terms of t-value and p-value, political identity (t=-6.351, p=0.009), moral quality (t=-4.528, p=0.002), and learning interest (t=-4.444, p=0.005), the p-value is less than the critical value of 0.05, and all three have significant differences. This study can effectively improve students’ political identity, moral quality, and learning interest, and promote digital innovation and the development of college curriculum in Civics.</p>
</abstract>

The primary objective of Civics education in higher education institutions is to guide students toward acquiring appropriate political identities and values. To achieve this, we advocate for the incorporation of a knowledge-tracking model in Civics curriculum instruction, highlighting that the practical application of in-depth knowledge tracking manifests throughout the educational process. Addressing the challenges inherent in the Civic Politics teaching model that integrates knowledge tracking, we propose solutions focused on the dimensions of student performance behavior and learning capabilities within the Civic Politics course. This involves the use of clustering grouping and attention mechanisms to refine the construction of the knowledge tracking model for Civics teaching. Building on this foundation, we define the research subjects and tools and provide an illustrative case study of the implemented knowledge-tracking model in Civic Politics education. The results are presented in terms of t-value and p-value, political identity (t=-6.351, p=0.009), moral quality (t=-4.528, p=0.002), and learning interest (t=-4.444, p=0.005), the p-value is less than the critical value of 0.05, and all three have significant differences. This study can effectively improve students’ political identity, moral quality, and learning interest, and promote digital innovation and the development of college curriculum in Civics.

Digital Intelligent Innovative Teaching Mode of Curriculum Civics and Politics Integration

Applied Mathematics and Nonlinear Sciences

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

The primary objective of Civics education in higher education institutions is to guide students toward acquiring appropriate political identities and values....

Digital Intelligent Innovative Teaching Mode of Curriculum Civics and Politics Integration

Online veröffentlicht: 10. Juni 2024

Seitenbereich: -

Eingereicht: 19. Feb. 2024

Akzeptiert: 28. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1467

Schlüsselwörter
Deep knowledge tracking, Attention mechanism, Cluster grouping, Curriculum civic politics

© 2024 Jiajia Li, published by Sciendo

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

Digital Intelligent Innovative Teaching Mode of Curriculum Civics and Politics Integration

Online veröffentlicht: 10. Juni 2024

Seitenbereich: -

Eingereicht: 19. Feb. 2024

Akzeptiert: 28. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1467

SchlüsselwörterDeep knowledge tracking, Attention mechanism, Cluster grouping, Curriculum civic politics

© 2024 Jiajia Li, published by Sciendo

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

Schlüsselwörter
Deep knowledge tracking, Attention mechanism, Cluster grouping, Curriculum civic politics