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

<p>This paper firstly researches the optimization of the teaching process and teaching language according to the English teaching objectives and teaching contents and summarizes the optimization strategy of university English teachers’ language so as to improve the efficiency of English teaching. Secondly, on the basis of applying the optimization theory, the formal description of English utterances and word splitting is carried out, followed by obtaining the features of English utterances through the selection function and further constructing the English utterance alignment model by using the particle swarm optimization algorithm. Then, we study the application of English utterance alignment in English teaching, which is mainly embodied in the construction of the English teaching corpus, word frequency list, and core word lexicon, followed by the analysis of the practical application in English teaching. The results show that in terms of algorithm performance, the correct rate of utterance alignment based on the particle swarm optimization algorithm is 0.82, and the correct rate of utterance alignment is also improved to a great extent. On speaking teaching, self-efficacy showed a significant correlation with cognitive strategies, metacognitive strategies, affective strategies, communicative strategies, compensatory strategies, and memory strategies, and their corresponding coefficient values were 0.652, 0.716, 0.741, 0.732, 0.718, and 0.748, which indicated that the better self-efficacy was, the higher the scores of speaking memory strategies were.</p>
</abstract>

This paper firstly researches the optimization of the teaching process and teaching language according to the English teaching objectives and teaching contents and summarizes the optimization strategy of university English teachers’ language so as to improve the efficiency of English teaching. Secondly, on the basis of applying the optimization theory, the formal description of English utterances and word splitting is carried out, followed by obtaining the features of English utterances through the selection function and further constructing the English utterance alignment model by using the particle swarm optimization algorithm. Then, we study the application of English utterance alignment in English teaching, which is mainly embodied in the construction of the English teaching corpus, word frequency list, and core word lexicon, followed by the analysis of the practical application in English teaching. The results show that in terms of algorithm performance, the correct rate of utterance alignment based on the particle swarm optimization algorithm is 0.82, and the correct rate of utterance alignment is also improved to a great extent. On speaking teaching, self-efficacy showed a significant correlation with cognitive strategies, metacognitive strategies, affective strategies, communicative strategies, compensatory strategies, and memory strategies, and their corresponding coefficient values were 0.652, 0.716, 0.741, 0.732, 0.718, and 0.748, which indicated that the better self-efficacy was, the higher the scores of speaking memory strategies were.

Applying Optimisation Theory in English Language Teaching in Practice

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Applying Optimisation Theory in English Language Teaching in Practice"}

This paper firstly researches the optimization of the teaching process and teaching language according to the English teaching objectives and teaching contents...

Applying Optimisation Theory in English Language Teaching in Practice

Pubblicato online: 15 nov 2023

Pagine: -

Ricevuto: 21 feb 2023

Accettato: 26 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.01158

Parole chiave
Optimization theory, Particle swarm optimization algorithm, Formal description, English utterance alignment, Formal description, Corpus

© 2023 Feifei Dang, published by Sciendo

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

Applying Optimisation Theory in English Language Teaching in Practice

Pubblicato online: 15 nov 2023

Pagine: -

Ricevuto: 21 feb 2023

Accettato: 26 mag 2023

DOI: https://doi.org/10.2478/amns.2023.2.01158

Parole chiaveOptimization theory, Particle swarm optimization algorithm, Formal description, English utterance alignment, Formal description, Corpus

© 2023 Feifei Dang, published by Sciendo

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

Parole chiave
Optimization theory, Particle swarm optimization algorithm, Formal description, English utterance alignment, Formal description, Corpus