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Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm

This article draws on previous research on constructive English teaching models and uses multimodal neural network algorithm theory and constructive English teaching as the theoretical basis, experimental research method, questionnaire survey method, and evaluation method. In this article, we propos...

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Detalles Bibliográficos
Autores principales: Zhang, Nan, Wang, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162813/
https://www.ncbi.nlm.nih.gov/pubmed/35665273
http://dx.doi.org/10.1155/2022/9144656
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author Zhang, Nan
Wang, Hao
author_facet Zhang, Nan
Wang, Hao
author_sort Zhang, Nan
collection PubMed
description This article draws on previous research on constructive English teaching models and uses multimodal neural network algorithm theory and constructive English teaching as the theoretical basis, experimental research method, questionnaire survey method, and evaluation method. In this article, we propose a multimodal neural network consisting of a multiscale FCN module and an LSTM module. The network focuses on both the multiscale geometric spatial features and the numerical time-dependent features of the time series curves, and with the comprehensive knowledge of their characteristics, it can better distinguish the classes to which the series belong. A large-scale perceptual field is achieved by null convolution in the model to ensure that the training pressure does not increase significantly. A series of experiments on the UCR dataset verifies the effectiveness and superiority of the model. Simulation experiments were conducted to build the proposed constructive English teaching model based on a multimodal neural network algorithm, and a test environment was built for use case testing. The experimental results showed that the algorithm can be better applied to constructive English teaching and has better adaptability and accuracy in various scenarios. At the end of the experiment, a posttest of grammar level was conducted in two classes to test whether the constructive English teaching model based on the multimodal neural network model could help students improve their English grammar skills. The results of the data analysis showed that the mean score of the experimental class was significantly higher than that of the control class, and the experimental class showed a more significant improvement, indicating that this new constructive English teaching model was beneficial to improving students' English grammar skills. The interaction strategy proposed under the constructive English teaching model can effectively improve the interaction between teachers and students. This positive feedback effect can provide front-line teachers with corresponding teaching references.
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spelling pubmed-91628132022-06-03 Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm Zhang, Nan Wang, Hao Comput Intell Neurosci Research Article This article draws on previous research on constructive English teaching models and uses multimodal neural network algorithm theory and constructive English teaching as the theoretical basis, experimental research method, questionnaire survey method, and evaluation method. In this article, we propose a multimodal neural network consisting of a multiscale FCN module and an LSTM module. The network focuses on both the multiscale geometric spatial features and the numerical time-dependent features of the time series curves, and with the comprehensive knowledge of their characteristics, it can better distinguish the classes to which the series belong. A large-scale perceptual field is achieved by null convolution in the model to ensure that the training pressure does not increase significantly. A series of experiments on the UCR dataset verifies the effectiveness and superiority of the model. Simulation experiments were conducted to build the proposed constructive English teaching model based on a multimodal neural network algorithm, and a test environment was built for use case testing. The experimental results showed that the algorithm can be better applied to constructive English teaching and has better adaptability and accuracy in various scenarios. At the end of the experiment, a posttest of grammar level was conducted in two classes to test whether the constructive English teaching model based on the multimodal neural network model could help students improve their English grammar skills. The results of the data analysis showed that the mean score of the experimental class was significantly higher than that of the control class, and the experimental class showed a more significant improvement, indicating that this new constructive English teaching model was beneficial to improving students' English grammar skills. The interaction strategy proposed under the constructive English teaching model can effectively improve the interaction between teachers and students. This positive feedback effect can provide front-line teachers with corresponding teaching references. Hindawi 2022-05-26 /pmc/articles/PMC9162813/ /pubmed/35665273 http://dx.doi.org/10.1155/2022/9144656 Text en Copyright © 2022 Nan Zhang and Hao Wang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Nan
Wang, Hao
Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title_full Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title_fullStr Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title_full_unstemmed Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title_short Construction and Research of Constructive English Teaching Model Applying Multimodal Neural Network Algorithm
title_sort construction and research of constructive english teaching model applying multimodal neural network algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9162813/
https://www.ncbi.nlm.nih.gov/pubmed/35665273
http://dx.doi.org/10.1155/2022/9144656
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