Optimization of English Teaching Mode in Colleges and Universities Based on Deep Learning in the Improvement of Intercultural Communication Skills

The application of technologies such as big data, mobile Internet, artificial intelligence and so on has triggered a major change in the field of education and promoted the classroom reform in colleges and universities.Taking deep learning theory as the research perspective, this paper constructs a college English teaching model based on deep learning, and applies the model to actual teaching practice, with a view to promoting students' English learning level and enhancing their intercultural communication ability.Among them, the K-means algorithm improved by the whale optimization algorithm is also used to cluster and stratify the English proficiency of students in a class to illustrate the specific application of deep learning in English teaching.The results classified the sample students into four categories, A, B, C and D. The English level of students in category A is the highest and the largest, accounting for 35.56%, and teachers can design differentiated teaching based on the results of student stratification.After carrying out the experiment of the teaching model, the practicing students' English scores improved by 4.01%, and at the same time, they gained 18.87%~28.45%and 18.82%~39.01%of competence in the personal domain and the communicative domain, respectively, which confirms the effect of the constructed English teaching model on the enhancement of the students' English learning level and cross-cultural communicative competence.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-03-30
DOI
https://doi.org/10.61091/jcmcc127a-487
Primary Topic
Educational Technology and Pedagogy
Type
article
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article

Optimization of English Teaching Mode in Colleges and Universities Based on Deep Learning in the Improvement of Intercultural Communication Skills

Journal of Combinatorial Mathematics and Combinatorial Computing
Educational Technology and Pedagogy
article

Optimization of English Teaching Mode in Colleges and Universities Based on Deep Learning in the Improvement of Intercultural Communication Skills

article en

Abstract

The application of technologies such as big data, mobile Internet, artificial intelligence and so on has triggered a major change in the field of education and promoted the classroom reform in colleges and universities.Taking deep learning theory as the research perspective, this paper constructs a college English teaching model based on deep learning, and applies the model to actual teaching practice, with a view to promoting students' English learning level and enhancing their intercultural communication ability.Among them, the K-means algorithm improved by the whale optimization algorithm is also used to cluster and stratify the English proficiency of students in a class to illustrate the specific application of deep learning in English teaching.The results classified the sample students into four categories, A, B, C and D. The English level of students in category A is the highest and the largest, accounting for 35.56%, and teachers can design differentiated teaching based on the results of student stratification.After carrying out the experiment of the teaching model, the practicing students' English scores improved by 4.01%, and at the same time, they gained 18.87%~28.45%and 18.82%~39.01%of competence in the personal domain and the communicative domain, respectively, which confirms the effect of the constructed English teaching model on the enhancement of the students' English learning level and cross-cultural communicative competence.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Quality Education
Openalex Percentile: Top 96%
Educational Technology and Pedagogy
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Optimization of English Teaching Mode in Colleges and Universities Based on Deep Learning in the Improvement of Intercultural Communication Skills · Journal of Combinatorial Mathematics and Combinatorial Computing (2025) | TGRS Research Map | TGRS