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Higher Education Curriculum Evaluation Method Based on Deep Learning Model
Higher education plays an important role in the improvement of people's quality and the development of our country. Therefore, it is necessary to evaluate the higher education curriculum. This paper analyzes and constructs the deep network learning system and self-encoder and evaluates the Chon...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635907/ https://www.ncbi.nlm.nih.gov/pubmed/34868300 http://dx.doi.org/10.1155/2021/9036550 |
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author | Zuo, Mei Wang, Jixiang |
author_facet | Zuo, Mei Wang, Jixiang |
author_sort | Zuo, Mei |
collection | PubMed |
description | Higher education plays an important role in the improvement of people's quality and the development of our country. Therefore, it is necessary to evaluate the higher education curriculum. This paper analyzes and constructs the deep network learning system and self-encoder and evaluates the Chongqing higher education curriculum based on the deep learning network selected by 50 universities in Chongqing. It is found that the numbers of test objects, indicators, and hidden layers have an impact on the evaluation results. At the same time, a classroom teaching model is designed to improve the quality of higher education and solve the problem of insufficient curriculum quality of higher education. |
format | Online Article Text |
id | pubmed-8635907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-86359072021-12-02 Higher Education Curriculum Evaluation Method Based on Deep Learning Model Zuo, Mei Wang, Jixiang Comput Intell Neurosci Research Article Higher education plays an important role in the improvement of people's quality and the development of our country. Therefore, it is necessary to evaluate the higher education curriculum. This paper analyzes and constructs the deep network learning system and self-encoder and evaluates the Chongqing higher education curriculum based on the deep learning network selected by 50 universities in Chongqing. It is found that the numbers of test objects, indicators, and hidden layers have an impact on the evaluation results. At the same time, a classroom teaching model is designed to improve the quality of higher education and solve the problem of insufficient curriculum quality of higher education. Hindawi 2021-11-24 /pmc/articles/PMC8635907/ /pubmed/34868300 http://dx.doi.org/10.1155/2021/9036550 Text en Copyright © 2021 Mei Zuo and Jixiang 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 Zuo, Mei Wang, Jixiang Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title | Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title_full | Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title_fullStr | Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title_full_unstemmed | Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title_short | Higher Education Curriculum Evaluation Method Based on Deep Learning Model |
title_sort | higher education curriculum evaluation method based on deep learning model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635907/ https://www.ncbi.nlm.nih.gov/pubmed/34868300 http://dx.doi.org/10.1155/2021/9036550 |
work_keys_str_mv | AT zuomei highereducationcurriculumevaluationmethodbasedondeeplearningmodel AT wangjixiang highereducationcurriculumevaluationmethodbasedondeeplearningmodel |