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

Authors: Yixuan Jiang; Jingjing Zhang; Changai Chen

Addresses: Foreign Languages Department, Henan University of Chinese Medicine, Zhengzhou, China ' Foreign Languages Department, Henan University of Chinese Medicine, Zhengzhou, China ' Information Technology Department, Henan University of Chinese Medicine, Zhengzhou, China

Abstract: 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.

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

DOI: 10.1504/IJCEELL.2018.098072

International Journal of Continuing Engineering Education and Life-Long Learning, 2018 Vol.28 No.3/4, pp.293 - 309

Received: 22 Aug 2017
Accepted: 22 Jun 2018
Published online: 01 Mar 2019 *

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