Student Behavior Analysis and Research Model Based on Clustering Technology

Now, entering the 21st century, with the continuous improvement of my country’s higher education level, the enrollment rate of all colleges and universities across the country is increasing year by year. Faced with the information management of a large number of students, the workload and work press...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Guozhang Li, Rayner Alfred, Xue Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/d8dd02e937df4e74b4b7138bbe8cdad6
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:d8dd02e937df4e74b4b7138bbe8cdad6
record_format	dspace
spelling	oai:doaj.org-article:d8dd02e937df4e74b4b7138bbe8cdad62021-11-15T01:19:29ZStudent Behavior Analysis and Research Model Based on Clustering Technology1875-905X10.1155/2021/9163517https://doaj.org/article/d8dd02e937df4e74b4b7138bbe8cdad62021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9163517https://doaj.org/toc/1875-905XNow, entering the 21st century, with the continuous improvement of my country’s higher education level, the enrollment rate of all colleges and universities across the country is increasing year by year. Faced with the information management of a large number of students, the workload and work pressure of consultants at various universities have doubled. The rapid and effective development of modern computer software and hardware has also initiated and effectively developed the informatization process of universities. The student management system is the core and foundation of the entire school education management system. This study mainly introduces the application of student behavior analysis and research models based on clustering technology. This paper uses the application research of student behavior analysis and research model based on clustering technology, uses clustering technology to analyze student behavior, and reasonably analyzes the feasibility of KMEANS algorithm and campus data mining. The cluster analysis algorithm is used to divide students into different groups according to the characteristics of the students, and then, data analysis and data association rules’ mining are performed on each group of students. At the same time, the decision tree algorithm is used to predict the future of students based on the historical data of the students and the current data of the students. The development status of the school helps the school to understand the situation of the students in real time, make predictions and warnings for possible situations, provide personalized applications for teachers and students, and provide decision-making support for the management. It can be seen from the experimental analysis that the application of student behavior analysis and research models based on clustering technology has increased the efficiency of student education by 17%. The limitations of student behavior analysis and research on clustering technology provide good applications for the KMEANS algorithm. Analysis, discussion, and summary of the methods and approaches are obtained to enrich the academic research results.Guozhang LiRayner AlfredXue WangHindawi LimitedarticleTelecommunicationTK5101-6720ENMobile Information Systems, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Telecommunication TK5101-6720
spellingShingle	Telecommunication TK5101-6720 Guozhang Li Rayner Alfred Xue Wang Student Behavior Analysis and Research Model Based on Clustering Technology
description	Now, entering the 21st century, with the continuous improvement of my country’s higher education level, the enrollment rate of all colleges and universities across the country is increasing year by year. Faced with the information management of a large number of students, the workload and work pressure of consultants at various universities have doubled. The rapid and effective development of modern computer software and hardware has also initiated and effectively developed the informatization process of universities. The student management system is the core and foundation of the entire school education management system. This study mainly introduces the application of student behavior analysis and research models based on clustering technology. This paper uses the application research of student behavior analysis and research model based on clustering technology, uses clustering technology to analyze student behavior, and reasonably analyzes the feasibility of KMEANS algorithm and campus data mining. The cluster analysis algorithm is used to divide students into different groups according to the characteristics of the students, and then, data analysis and data association rules’ mining are performed on each group of students. At the same time, the decision tree algorithm is used to predict the future of students based on the historical data of the students and the current data of the students. The development status of the school helps the school to understand the situation of the students in real time, make predictions and warnings for possible situations, provide personalized applications for teachers and students, and provide decision-making support for the management. It can be seen from the experimental analysis that the application of student behavior analysis and research models based on clustering technology has increased the efficiency of student education by 17%. The limitations of student behavior analysis and research on clustering technology provide good applications for the KMEANS algorithm. Analysis, discussion, and summary of the methods and approaches are obtained to enrich the academic research results.
format	article
author	Guozhang Li Rayner Alfred Xue Wang
author_facet	Guozhang Li Rayner Alfred Xue Wang
author_sort	Guozhang Li
title	Student Behavior Analysis and Research Model Based on Clustering Technology
title_short	Student Behavior Analysis and Research Model Based on Clustering Technology
title_full	Student Behavior Analysis and Research Model Based on Clustering Technology
title_fullStr	Student Behavior Analysis and Research Model Based on Clustering Technology
title_full_unstemmed	Student Behavior Analysis and Research Model Based on Clustering Technology
title_sort	student behavior analysis and research model based on clustering technology
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/d8dd02e937df4e74b4b7138bbe8cdad6
work_keys_str_mv	AT guozhangli studentbehavioranalysisandresearchmodelbasedonclusteringtechnology AT rayneralfred studentbehavioranalysisandresearchmodelbasedonclusteringtechnology AT xuewang studentbehavioranalysisandresearchmodelbasedonclusteringtechnology
_version_	1718428952532353024

Student Behavior Analysis and Research Model Based on Clustering Technology

Ejemplares similares