Quality evaluation model of innovation and entrepreneurship teaching effect based on fuzzy clustering algorithm

Abstract

Under the background of modern education, the importance of innovation and entrepreneurship teaching has become increasingly prominent, and how to effectively evaluate the teaching effect a quality evaluation model of innovation and entrepreneurship teaching effect based on fuzzy clustering algorithm, so as to improve the evaluation efficiency and accuracy of teaching effect. The design of the model framework considers the integration of multi-dimensional data, combining information from different sources, ensuring a comprehensive analysis of teaching effectiveness. In the aspect of model parameter selection and ambiguity control strategy, the key parameters are optimized by cross-validation and heuristic search to improve the reliability of clustering effect. By dynamically adjusting the ambiguity coefficient, the fuzziness in the model is effectively controlled, and the representativeness of clustering results is improved. Dynamic ambiguity control for adaptive fuzzy clustering, improving noise resistance by 18%. According to the further analysis of innovation and entrepreneurship education, it is found that teachers’ recognition of teaching content is 64%. During the evaluation process, 38.62% of the students said that the classroom atmosphere was active, which could stimulate their interest in learning. Although 94% of teachers think that the curriculum design is reasonable, 66% of students still feel that the curriculum content is out of touch with the practical application, and only 54.39% of students think that the curriculum meets their expectations.