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Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network

At present, there are some problems in the research of curriculum ideological and political quality evaluation, such as insufficient theme attention, insufficient theoretical research, incomplete data collection, and so on. This study aims to use the BP neural network in the ideological and politica...

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Detalles Bibliográficos
Autores principales: Ding, Yunxia, Zeng, Wei, Ning, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313913/
https://www.ncbi.nlm.nih.gov/pubmed/35898778
http://dx.doi.org/10.1155/2022/8336895
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author Ding, Yunxia
Zeng, Wei
Ning, Zhen
author_facet Ding, Yunxia
Zeng, Wei
Ning, Zhen
author_sort Ding, Yunxia
collection PubMed
description At present, there are some problems in the research of curriculum ideological and political quality evaluation, such as insufficient theme attention, insufficient theoretical research, incomplete data collection, and so on. This study aims to use the BP neural network in the ideological and political quality evaluation system so that the system can more comprehensively and accurately reflect the actual situation of students and point out the direction for the development of students' ideological and political education. The construction of this system can provide a very considerable and accurate way for the quality evaluation of ideological and political education of college students and especially solves the problems of human subjective, factor errors, and the setting of evaluation index weights in the evaluation system.
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spelling pubmed-93139132022-07-26 Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network Ding, Yunxia Zeng, Wei Ning, Zhen Comput Intell Neurosci Research Article At present, there are some problems in the research of curriculum ideological and political quality evaluation, such as insufficient theme attention, insufficient theoretical research, incomplete data collection, and so on. This study aims to use the BP neural network in the ideological and political quality evaluation system so that the system can more comprehensively and accurately reflect the actual situation of students and point out the direction for the development of students' ideological and political education. The construction of this system can provide a very considerable and accurate way for the quality evaluation of ideological and political education of college students and especially solves the problems of human subjective, factor errors, and the setting of evaluation index weights in the evaluation system. Hindawi 2022-07-18 /pmc/articles/PMC9313913/ /pubmed/35898778 http://dx.doi.org/10.1155/2022/8336895 Text en Copyright © 2022 Yunxia Ding et al. 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
Ding, Yunxia
Zeng, Wei
Ning, Zhen
Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title_full Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title_fullStr Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title_full_unstemmed Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title_short Quality Evaluation of Ideological and Political Education in Universities Based on BP Neural Network
title_sort quality evaluation of ideological and political education in universities based on bp neural network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313913/
https://www.ncbi.nlm.nih.gov/pubmed/35898778
http://dx.doi.org/10.1155/2022/8336895
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