A Design Model of English Auxiliary Teaching System Using Artificial Neural Networks

Abstract

At present, the development of artificial intelligence has entered a new stage. In the next few years, human life will be greatly covered by artificial intelligence. Artificial intelligence (AI) is an intelligent technology that simulates the human brain for thinking operation. English is very difficult for Chinese students to learn. Moreover, at present, there are still many areas that need to be improved or improved in the design of English assistant instruction system (EAIS) in China. This study aims to study an EAIS based on AI. This study presents an algorithm combined with neural network. This study designs a system that can enable students’ autonomous learning system, English teacher assisted teaching, AI expert intelligent diagnosis, and system administrator to manage and analyze data. And this study tests the actual effect of the system. By comparing the academic performance of two classes in the school, the results show that although the average score of students’ monthly test fluctuates after using the AI EAIS, it tends to rise as a whole. Moreover, its initial score of 81.5 was 1.1 lower than that of the class without the teaching system and finally increased to 90.11. It is 6.89 points higher than the class that does not use the teaching system. This shows that the auxiliary system designed in this study has a certain effect on the improvement of students’ English performance.