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

<p>Using political and ideological education as a starting point, this paper creates a knowledge map of political and ideological education by gathering data, extracting knowledge, fusing knowledge, and using knowledge reasoning. It uses kernel problems as hints to accurately represent the primary competencies of the field of political and ideological education through task completion or problem-solving. Three data analysis perspectives are used to validate the validity of the knowledge map: the knowledge map algorithm, the ideological and political education visualization, and the possibilities and problems associated with ideological and political education. The findings indicate that the average profile value S is 0.8348, which is larger than 0.7, and the Q value of the keyword grouping network knowledge map is 0.5268, which is greater than 0.3, based on the examination of high-frequency keyword clustering in ideological and political education. According to the data, the keyword clustering findings we were able to generate are realistic and can more accurately depict the link and connection between various terms. Furthermore, it demonstrates the effectiveness of the knowledge map for political and ideological education created for this research in assessing the state of political and ideological education today.</p>
</abstract>

Using political and ideological education as a starting point, this paper creates a knowledge map of political and ideological education by gathering data, extracting knowledge, fusing knowledge, and using knowledge reasoning. It uses kernel problems as hints to accurately represent the primary competencies of the field of political and ideological education through task completion or problem-solving. Three data analysis perspectives are used to validate the validity of the knowledge map: the knowledge map algorithm, the ideological and political education visualization, and the possibilities and problems associated with ideological and political education. The findings indicate that the average profile value S is 0.8348, which is larger than 0.7, and the Q value of the keyword grouping network knowledge map is 0.5268, which is greater than 0.3, based on the examination of high-frequency keyword clustering in ideological and political education. According to the data, the keyword clustering findings we were able to generate are realistic and can more accurately depict the link and connection between various terms. Furthermore, it demonstrates the effectiveness of the knowledge map for political and ideological education created for this research in assessing the state of political and ideological education today.

Opportunities and Challenges of Ideological and Political Education for College Students in the Internet Era

Sichuan University of Science & Engineering

Applied Mathematics and Nonlinear Sciences

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

Using political and ideological education as a starting point, this paper creates a knowledge map of political and ideological education by gathering data,...

Opportunities and Challenges of Ideological and Political Education for College Students in the Internet Era

Published Online: Dec 18, 2023

Page range: -

Received: Mar 29, 2023

Accepted: Jun 28, 2023

DOI: https://doi.org/10.2478/amns.2023.2.01530

Keywords
Knowledge extraction, Knowledge mapping, Visualization, Keyword clustering, Ideological and political education

© 2023 Wei Zhang, published by Sciendo

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

Opportunities and Challenges of Ideological and Political Education for College Students in the Internet Era

Published Online: Dec 18, 2023

Page range: -

Received: Mar 29, 2023

Accepted: Jun 28, 2023

DOI: https://doi.org/10.2478/amns.2023.2.01530

KeywordsKnowledge extraction, Knowledge mapping, Visualization, Keyword clustering, Ideological and political education

© 2023 Wei Zhang, published by Sciendo

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

Keywords
Knowledge extraction, Knowledge mapping, Visualization, Keyword clustering, Ideological and political education