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

<p>The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet information technology, this paper constructs a digital platform for Civic Education work, in which Shannon’s theory and balanced power allocation are used to optimize channel transmission and enhance the loading speed of Civic Education resources. The XGBoost algorithm is used to effectively cluster students’ learning behaviors as a way to help Civic Education workers understand students’ learning behaviors in Civic Education. The results show that the average response time is 0.327s, and the maximum throughput is 11849.478 bytes/sec. The prediction accuracy of the XGBoost algorithm for student learning behavior is 4.65%, 9.79%, and 21.79% higher than that of LR, RF, GBM, and Stacking classification models, respectively. 9.79%, 21.41%, and 13.5%, respectively. This shows that the university’s thinking and political education work can be developed through the direction of the digital Internet platform, which in turn provides a new research path for the reform and innovation of thinking and political education work.</p>
</abstract>

The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet information technology, this paper constructs a digital platform for Civic Education work, in which Shannon’s theory and balanced power allocation are used to optimize channel transmission and enhance the loading speed of Civic Education resources. The XGBoost algorithm is used to effectively cluster students’ learning behaviors as a way to help Civic Education workers understand students’ learning behaviors in Civic Education. The results show that the average response time is 0.327s, and the maximum throughput is 11849.478 bytes/sec. The prediction accuracy of the XGBoost algorithm for student learning behavior is 4.65%, 9.79%, and 21.79% higher than that of LR, RF, GBM, and Stacking classification models, respectively. 9.79%, 21.41%, and 13.5%, respectively. This shows that the university’s thinking and political education work can be developed through the direction of the digital Internet platform, which in turn provides a new research path for the reform and innovation of thinking and political education work.

Exploration of the development path of university thinking and political education in the background of Internet

Chengdu University of Traditional Chinese Medicine

Applied Mathematics and Nonlinear Sciences

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

The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet...

Exploration of the development path of university thinking and political education in the background of Internet

Published Online: Oct 11, 2023

Page range: -

Received: Nov 17, 2022

Accepted: Apr 21, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00592

Keywords
Shannon’s theory, XGBoost algorithm, Balanced power distribution, Digital platform

© 2023 Siqi Li et al., published by Sciendo

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

Exploration of the development path of university thinking and political education in the background of Internet

Published Online: Oct 11, 2023

Page range: -

Received: Nov 17, 2022

Accepted: Apr 21, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00592

KeywordsShannon’s theory, XGBoost algorithm, Balanced power distribution, Digital platform

© 2023 Siqi Li et al., published by Sciendo

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

Keywords
Shannon’s theory, XGBoost algorithm, Balanced power distribution, Digital platform