A Study of College Teachers' English Teaching Quality Based on Fuzzy Neural Network

Comput Intell Neurosci. 2022 Aug 1:2022:8162048. doi: 10.1155/2022/8162048. eCollection 2022.

Abstract

In many universities and colleges, the government is now paying more attention to the quality of teaching assessment, and research on English teaching quality evaluation is becoming increasingly significant. The goal of this paper is to investigate how to use a fuzzy neural network to assess the quality of English education. The research of the model NN and the evaluation of the quality of English teaching is detailed first. A fuzzy NN is an algorithm that examines the quality of English instruction evaluation using fuzzy criteria. In the case results, the data show that the previous evaluation of quality teaching is between the intermediate and the intermediate level, while the research on the evaluation quality of English teaching based on fuzzy NN shows that the evaluation quality is between the intermediate and the advanced level. Therefore, the combination of Fuzzy Rules (FR) and NN methods can effectively improve the quality of college teachers' English teaching evaluation. In college English teaching, FRs can simplify the analysis steps of evaluation of quality teaching, accurately judge the quality of college English teaching evaluation, and provide support for the improvement of evaluation of quality teaching.

Publication types

  • Retracted Publication

MeSH terms

  • Humans
  • Neural Networks, Computer*
  • Teaching*
  • Universities