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The Construction of English Smart Teaching Platform for Colleges and Universities Based on Deep Learning under the Core Idea of Functional Linguistics

Authors :
Yan Dan
Source :
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Publication Year :
2024
Publisher :
Sciendo, 2024.

Abstract

This study explores the application of intelligent teaching in higher education, especially for the digital transformation of English learning. Relying on online English teaching resources, the article successfully constructs an innovative teaching platform for English teaching in higher education by integrating advanced tools such as deep learning technology, clustering algorithms, and Rasch models. The platform takes students’ self-management awareness as the core. It emphasizes teachers’ evidence-based teaching ability, while considering multidimensional factors such as teaching environment, emotions and characteristics to provide a comprehensive and interactive learning environment. Through in-depth analysis of the application effect of the platform, the study found that students’ agreement in all five key dimensions exceeded 0.24, especially in the teaching emotion dimension with the highest deal of 0.2970, and the results fully proved the significant role of the intelligent teaching platform in enhancing learning effect and stimulating learning interest. This study successfully realizes the efficient interaction between teachers and students. Also, it lays a solid foundation for constructing a natural, harmonious and energetic bright English teaching environment, which is of great theoretical and practical significance for promoting the modernization and transformation of the education and teaching system.

Details

Language :
English
ISSN :
24448656
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Applied Mathematics and Nonlinear Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.9d8119ea309c4569822e381a44debe4d
Document Type :
article
Full Text :
https://doi.org/10.2478/amns-2024-0403