Optimization of English Language and Literature Teaching Management System Based on Artificial Intelligence and Computer-Aided Design

Abstract

Computer-assisted teaching systems have been widely promoted in today's society, and teaching quality and efficiency have been improved. With the rapid development of artificial intelligence technology, it has also brought new strategies to the teaching management system, and intelligent technology can be integrated into the English language and literature teaching management system. This solves the shortcomings of traditional computer-assisted teaching systems, such as lack of intelligence, lack of teaching curriculum essence, and lack of human-computer interaction. This research combines the advantages of artificial intelligence technology and the advantages of computer-assisted teaching systems to optimize and predict the English language and literature education management system. For the recognition of image features in English language and literature, this paper adopts a convolutional neural network to predict, and extracts features from long and short memory loop neural networks that have time characteristics such as English vocabulary or sentences. And some statistical parameters related to prediction accuracy are used to explore the accuracy and generalization ability of the model in this paper. The research results show that the artificial intelligence neural network proposed in this paper has high accuracy in the application of English language and literature teaching management system, and its prediction error is only 2.38%.