Evaluation of English Teaching Quality Based on Hierarchical Analysis and Fuzzy Decision Tree Algorithm

How to improve classroom teaching evaluation so that it can really play the role of guidance, motivation, and promotion of evaluation in the new classroom model is a problem that needs to be solved urgently. This paper first introduces the concepts of fuzzy hierarchical analysis and fuzzy comprehensive evaluation, defines the fuzzy judgment matrix, designs a multi-level fuzzy comprehensive judgment algorithm, and constructs a fuzzy hierarchical analysis-fuzzy comprehensive evaluation model. Then, the generalized fuzzy decision tree model is constructed to achieve a clearer and more effective hierarchical categorization of teaching quality evaluation indexes, and the teaching evaluation index system is established accordingly. Teaching quality evaluation is carried out in the English classrooms of three different teachers in a university, and it is found that the classification effect of this paper's algorithm is better than that of other comparative algorithms in each evaluation index on the datasets FLAGS and BIRDS. In the university's teaching quality evaluation validation for three English teachers, X, W, and Y, the comprehensive evaluation scores given by this paper's method are 94.98, 85.92, and 73.32, respectively, which are in line with the actual teaching situation of the three teachers. This study provides new ideas and methods for reforming classroom teaching evaluation. © 2024 Haifen Li, published by Sciendo.