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Evaluation and Application of College English Mixed Flipping Classroom Teaching Quality Based on the Fuzzy Judgment Model

With the development of big data technology, there are more and more evaluation models for college English teaching quality, which can better promote the improvement of college English teaching quality. Based on the fuzzy decision model, this paper describes the algorithm establishment process of th...

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Published in:Security and communication networks 2022-08, Vol.2022, p.1-9
Main Author: Gao, Xiaoyan
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description With the development of big data technology, there are more and more evaluation models for college English teaching quality, which can better promote the improvement of college English teaching quality. Based on the fuzzy decision model, this paper describes the algorithm establishment process of the model in detail. Then, the fuzzy evaluation model between teachers and students according to different grades is established. Finally, aiming at the problems in college English teaching, this paper obtained the corresponding countermeasures for the college English teaching platform based on fuzzy judgment model. The results indicate the model improves the quality of college English teaching in different grades and promotes the development of college English. In addition, the model platform can also well predict the measures to improve the quality. In short, this paper provides some theoretical and experimental support for the quality of college English hybrid flipping classroom.
doi_str_mv 10.1155/2022/9611611
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source Wiley Online Library Open Access; Publicly Available Content Database
subjects Algorithms
Classrooms
College students
Cooperation
Distance learning
Education reform
Educational materials
Educational technology
English teachers
Evaluation
Flipped classroom
Human error
Information technology
Internet
Knowledge
Mathematics
Multimedia
Neural networks
Online instruction
Teaching methods
title Evaluation and Application of College English Mixed Flipping Classroom Teaching Quality Based on the Fuzzy Judgment Model
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