Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation

With the increasing demand for applied and professional talents, the talent market has been in short supply. Although there are many talents in the talent market, the quality of talents cannot keep up with the development of quantity. Therefore, it is of great practical significance to establish a v...

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Autores principales:	Lijun Li, Wentao Wang, Fei Bian
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/61b38517486b4f36a4e3634f412c20f0
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id	oai:doaj.org-article:61b38517486b4f36a4e3634f412c20f0
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spelling	oai:doaj.org-article:61b38517486b4f36a4e3634f412c20f02021-11-15T01:20:01ZApplication of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation1099-052610.1155/2021/8321030https://doaj.org/article/61b38517486b4f36a4e3634f412c20f02021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8321030https://doaj.org/toc/1099-0526With the increasing demand for applied and professional talents, the talent market has been in short supply. Although there are many talents in the talent market, the quality of talents cannot keep up with the development of quantity. Therefore, it is of great practical significance to establish a visual evaluation system of personnel training quality in the field of higher education. In view of the unreasonable evaluation and unclear weight relationship in the evaluation of educational indicators, this paper puts forward a big data analysis model to comprehensively evaluate teaching evaluation indicators, which has more scientific significance. In this paper, different systems in the index system are used as the analysis objects and the first-level weight relationship is normalized, which can distribute the weights more reasonably. Through the big data analysis method, the teaching quality evaluation system is more reasonable and scientific. In this paper, the quality index system for higher education background is designed and constructed and the weight relationship of different educational indicators is analyzed through big data, and four main indicators are obtained; then, the weight relationship of secondary indicators is analyzed, and finally, the weight relationship of all indicators is formed. The results show that the weight relationship of four indexes is 0.3285, 0.1973, 0.2967, and 0.1755, and the evaluation model of education quality is given.Lijun LiWentao WangFei BianHindawi-WileyarticleElectronic computers. Computer scienceQA75.5-76.95ENComplexity, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electronic computers. Computer science QA75.5-76.95
spellingShingle	Electronic computers. Computer science QA75.5-76.95 Lijun Li Wentao Wang Fei Bian Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
description	With the increasing demand for applied and professional talents, the talent market has been in short supply. Although there are many talents in the talent market, the quality of talents cannot keep up with the development of quantity. Therefore, it is of great practical significance to establish a visual evaluation system of personnel training quality in the field of higher education. In view of the unreasonable evaluation and unclear weight relationship in the evaluation of educational indicators, this paper puts forward a big data analysis model to comprehensively evaluate teaching evaluation indicators, which has more scientific significance. In this paper, different systems in the index system are used as the analysis objects and the first-level weight relationship is normalized, which can distribute the weights more reasonably. Through the big data analysis method, the teaching quality evaluation system is more reasonable and scientific. In this paper, the quality index system for higher education background is designed and constructed and the weight relationship of different educational indicators is analyzed through big data, and four main indicators are obtained; then, the weight relationship of secondary indicators is analyzed, and finally, the weight relationship of all indicators is formed. The results show that the weight relationship of four indexes is 0.3285, 0.1973, 0.2967, and 0.1755, and the evaluation model of education quality is given.
format	article
author	Lijun Li Wentao Wang Fei Bian
author_facet	Lijun Li Wentao Wang Fei Bian
author_sort	Lijun Li
title	Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
title_short	Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
title_full	Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
title_fullStr	Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
title_full_unstemmed	Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation
title_sort	application of the big data analysis model in higher education talent training quality evaluation
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/61b38517486b4f36a4e3634f412c20f0
work_keys_str_mv	AT lijunli applicationofthebigdataanalysismodelinhighereducationtalenttrainingqualityevaluation AT wentaowang applicationofthebigdataanalysismodelinhighereducationtalenttrainingqualityevaluation AT feibian applicationofthebigdataanalysismodelinhighereducationtalenttrainingqualityevaluation
_version_	1718428925397303296

Application of the Big Data Analysis Model in Higher Education Talent Training Quality Evaluation

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