Analysis of Civic Education Discourse in Universities Based on Numerical Analysis Kruskal Algorithm

Abstract

This paper first proposes the discourse system of ideological and political education in colleges and universities, which mainly includes discourse goal innovation, discourse structure innovation, discourse paradigm innovation and discourse behavior innovation. Secondly, to facilitate the analysis and comparison of the data set, it is necessary to standardize various data and construct a similar relationship matrix based on the standardized data. Then, the correlation between teachers’ and students’ characteristics is incorporated to cluster the users to derive the user similarity and the final predicted rating of the Civic Education resources. Simulation experiments and statistical analysis validate the Kruskal algorithm-based example study of Civic Education discourse in colleges and universities. The results show that the measures of value perception and discourse power are in a reasonable interval, with a minimum value of 1 and a maximum value of 5, and the mean values are between 3.72 and 4.03, and the standard deviations are all greater than 0.75, reflecting the wide distribution of the samples, indicating that this study can improve the efficiency of the recommendation of Civic Education resources and the accuracy of discourse power analysis.

Keywords

• kruskal algorithm
• similarity relationship matrix
• user similarity
• predictive scoring
• civic education
• discourse
• 97d60