Abstract

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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call