Analysis of high quality collaborative development path of university civic education based on Rete’s pattern matching algorithm

The prerequisites for the separation of fuzzy sets for the assessment of ideological and political education in colleges are first looked at in this essay. Then the implementation of the quality evaluation algorithm is discussed, the factors associated with the system and the corresponding data are selected, then the theoretical domain of the data is defined, the set contained in the theoretical domain is calculated, and the final value of the non-fuzzy values is calculated by the nonfuzzification method. To get the evaluation findings, the evaluation method is then used to build a thorough evaluation factor set and evaluation set, choose the weight coefficients, and create the fuzzy connection matrix. The assessment method is then used to examine the existing state of political and ideological education, identify its challenges, and provide solutions for high-quality growth. In terms of regional development, the eastern area is ranked 0-6, the middle region −2 to 3, and the western region −2 to 2 in terms of ideological and political development. 80% of instructors agree that learning should incorporate the primary job of building moral education when it comes to growth approaches. 39% think that the curricular strategy needs to be improved. 54% of respondents think that teaching practices should be standardized in schools. 44% think that teaching strategies need to be improved. Based on the Rete pattern matching algorithm and fuzzy evaluation algorithm, it is important for the development and construction of college ideology and politics.