Research on a new teaching quality evaluation method based on improved fuzzy neural network for college English

被引：18

作者：

Jiang, Yixuan ^{[1
]}

Zhang, Jingjing ^{[1
]}

Chen, Changai ^{[2
]}

机构：

[1] Henan Univ Chinese Med, Foreign Languages Dept, Zhengzhou, Henan, Peoples R China

[2] Henan Univ Chinese Med, Dept Informat Technol, Zhengzhou, Henan, Peoples R China

来源：

INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING | 2018年 / 28卷 / 3-4期

关键词：

fuzzy logic; neural network; back-propagation learning method; evaluation system; teaching quality;

D O I：

10.1504/IJCEELL.2018.098072

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

For the heavy workload and complicated statistics of college English teaching work, the progress and limitations of neural network, and the existing characteristics of fuzzy information, fuzzy logic and RBF neural network are introduced to integrate the advantages of learning, association, identification, adaptation and fuzzy information processing to propose an improved fuzzy RBF neural network model based on back-propagation learning. Then the teaching quality evaluation method of college English based on improved fuzzy neural network is proposed to obtain the more objective and reasonable evaluation result. To test the effectiveness of the teaching quality evaluation method, the college English teaching in Henan University of Chinese Medicine is selected as study case. The results show that the proposed teaching quality evaluation method can effectively overcome the subjectivity and randomness of the traditional teaching quality evaluation methods, and make the evaluation results more in line with the actual situation.

引用

页码：293 / 309

页数：17