Abstract

The rapid development of artificial intelligence brings new development opportunities and challenges to English teaching university. This paper explores the concept of “smart education” and the path of building an ecological information-based teaching model of English college by interpreting the concepts of artificial intelligence, deep learning, ecological linguistics, and language education. Artificial intelligence, especially deep learning, will be promising in many aspects, such as the analysis of individual differences of language learners, customized learning content, diversified and three-dimensional teaching media, the role of teachers as smart classroom designers, and multidimensional and dynamic formative assessments. By relying on the data mining technology of deep learning to analyze learners’ characteristics, the smart classroom design, the promotion of language learners’ independent learning, and the establishment of dynamic and complete learner profiles, the language learning process is no longer a linear process but an evolving open loop, ultimately forming a harmonious development of various ecological niches in the language learning process. In this paper, we study and design a deep learning-based English informatics teaching system to develop a deep learning-based scoring prediction model. The model incorporates deep learning models based on word embedding and text convolutional networks, which can uncover the hidden interest features of academics for English. The experimental research results prove that the online e-learning service platform cannot only effectively meet the diverse and personalized English learning needs of university students, but also improve the learning efficiency of teachers and students.

Highlights

  • Academic Editor: Naeem Jan e rapid development of artificial intelligence brings new development opportunities and challenges to English teaching university. is paper explores the concept of “smart education” and the path of building an ecological information-based teaching model of English college by interpreting the concepts of artificial intelligence, deep learning, ecological linguistics, and language education

  • We study and design a deep learning-based English informatics teaching system to develop a deep learning-based scoring prediction model. e model incorporates deep learning models based on word embedding and text convolutional networks, which can uncover the hidden interest features of academics for English. e experimental research results prove that the online e-learning service platform cannot only effectively meet the diverse and personalized English learning needs of university students, and improve the learning efficiency of teachers and students

  • For the role explored in the form of translation, we mention deep learning for teaching English professional translators, which made significant achievements and breakthroughs in the field of English translation and has achieved certain pedagogical results in teaching English translation

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Summary

A Study of English Informative Teaching Strategies Based on Deep Learning

Artificial intelligence, especially deep learning, will be promising in many aspects, such as the analysis of individual differences of language learners, customized learning content, diversified and three-dimensional teaching media, the role of teachers as smart classroom designers, and multidimensional and dynamic formative assessments. E deep learning language platform can provide students with a large amount of listening materials with a wide variety of difficulty and topics to meet the different needs of different students for English listening In such an environment, can students choose the corresponding English learning materials according to their interests for in-depth learning, and deep learning can automatically match students with suitable listening materials and learning contents through the analysis of their basic information. Deep learning has a great advantage in teaching English as a foreign language, as the English communication environment becomes more colorful because of educational robots, and real-time conversations help students to use English.

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