<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Hebei University of Environmental Engineering

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study explores the application of intelligent teaching in higher education, especially for the digital transformation of English learning. Relying on...

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

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 08 gen 2024

Accettato: 18 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0403

Parole chiave
Smart teaching, Teaching platform, Deep learning, Clustering algorithm, Rasch model

© 2024 Dan Yan, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Pubblicato online: 26 feb 2024

Pagine: -

Ricevuto: 08 gen 2024

Accettato: 18 gen 2024

DOI: https://doi.org/10.2478/amns-2024-0403

Parole chiaveSmart teaching, Teaching platform, Deep learning, Clustering algorithm, Rasch model

© 2024 Dan Yan, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Smart teaching, Teaching platform, Deep learning, Clustering algorithm, Rasch model