Quantitative analysis of business English civic education: construction of an evaluation model based on fuzzy theory

Authors

  • Menglin Deng Foreign Language School, Hunan University of Humanities, Science and Technology, Loudi, Hunan, 417000, China
  • Ken Chen Jiayuan Branch of Beijing No. 80 Middle School, Beijing, 100015, China

DOI:

https://doi.org/10.70917/ijcisim-2026-0214

Keywords:

civic education; fuzzy evaluation; weight matrix; hierarchical analysis; Business English

Abstract

In order to accurately measure the effect of Business English Civic and Political Education, this paper constructs a corresponding evaluation index system. The Fermatean fuzzy set of indicator data is established to calculate the uncertainty of evaluation indicator data. At the same time, through the sorting function and Zhenyuan integral operator, the relationship between the index attributes is judged to improve the accuracy of the evaluation indexes. In the fuzzy evaluation stage, the factor set and factor subset are established, the classification weights are calculated according to the indicator level, and the weight matrix is composed to judge the evaluation results. Hierarchical analysis and weight consistency test are introduced to complete the reasonable adjustment of weights and reduce the quantitative analysis error rate. In the evaluation index system of the effect of business English civic education, the highest weight is political quality, which reaches 0.4781. The weight consistency test is less than 0.1000. The subordination degree of the first and second level of the comprehensive rating of the civic teachers is more than 0.05, which is at a good level. Through fuzzy evaluation, the level of Business English Civics education can be judged intuitively.

Downloads

Download data is not yet available.

Downloads

Published

2026-02-07

How to Cite

Menglin Deng, & Ken Chen. (2026). Quantitative analysis of business English civic education: construction of an evaluation model based on fuzzy theory. International Journal of Computer Information Systems and Industrial Management Applications, 18, 14. https://doi.org/10.70917/ijcisim-2026-0214

Issue

Section

Original Articles