Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics

In recent years, the educational issues have attracted more and more researchers’ and teachers’ attention. On the other hand, the development of data mining technology, provides a new method to extract the useful information from the complex educational data. In order to increase the chance of stude...

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Main Authors: Xiaoling Huang, Yangbing Xu, Shuai Zhang, Wenyu Zhang
Format: Article
Language:English
Published: Kassel University Press 2018-03-01
Series:International Journal of Emerging Technologies in Learning (iJET)
Subjects:
Online Access:http://online-journals.org/index.php/i-jet/article/view/8382
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spelling doaj-ed3ecd7aa3b5414a8b3f00a46115baa42020-11-25T00:45:20ZengKassel University PressInternational Journal of Emerging Technologies in Learning (iJET)1863-03832018-03-01130310011310.3991/ijet.v13i03.83823632Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and EconomicsXiaoling Huang0Yangbing Xu1Shuai Zhang2Wenyu Zhang3School of International Education, Zhejiang University of Finance and EconomicsSchool of Information, Zhejiang University of Finance and EconomicsSchool of Information, Zhejiang University of Finance and EconomicsSchool of Information, Zhejiang University of Finance and EconomicsIn recent years, the educational issues have attracted more and more researchers’ and teachers’ attention. On the other hand, the development of data mining technology, provides a new method to extract the useful information from the complex educational data. In order to increase the chance of students to be awarded in discipline competition, it is better to select the proper students to take part in the proper discipline competition. Therefore, in this study, we collect the information of 164 undergraduate students as a case study. All students majored in Software Engineering in Zhejiang University of Finance and Economics. The Apriori algorithm with group strategy is used to find the relationship between the students’ courses scores and competition awards. According to the results of association rule mining, we find that the students with higher scores of C# Development, Object-Oriented, Internet Web Design, Data Structure(C#), and Basic Programming will have a higher probability to be awarded in the competition.http://online-journals.org/index.php/i-jet/article/view/8382association rule miningApriori algorithmR programmingdiscipline competition
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoling Huang
Yangbing Xu
Shuai Zhang
Wenyu Zhang
spellingShingle Xiaoling Huang
Yangbing Xu
Shuai Zhang
Wenyu Zhang
Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
International Journal of Emerging Technologies in Learning (iJET)
association rule mining
Apriori algorithm
R programming
discipline competition
author_facet Xiaoling Huang
Yangbing Xu
Shuai Zhang
Wenyu Zhang
author_sort Xiaoling Huang
title Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
title_short Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
title_full Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
title_fullStr Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
title_full_unstemmed Association Rule Mining for Selecting Proper Students to Take Part in Proper Discipline Competition: A Case Study of Zhejiang University of Finance and Economics
title_sort association rule mining for selecting proper students to take part in proper discipline competition: a case study of zhejiang university of finance and economics
publisher Kassel University Press
series International Journal of Emerging Technologies in Learning (iJET)
issn 1863-0383
publishDate 2018-03-01
description In recent years, the educational issues have attracted more and more researchers’ and teachers’ attention. On the other hand, the development of data mining technology, provides a new method to extract the useful information from the complex educational data. In order to increase the chance of students to be awarded in discipline competition, it is better to select the proper students to take part in the proper discipline competition. Therefore, in this study, we collect the information of 164 undergraduate students as a case study. All students majored in Software Engineering in Zhejiang University of Finance and Economics. The Apriori algorithm with group strategy is used to find the relationship between the students’ courses scores and competition awards. According to the results of association rule mining, we find that the students with higher scores of C# Development, Object-Oriented, Internet Web Design, Data Structure(C#), and Basic Programming will have a higher probability to be awarded in the competition.
topic association rule mining
Apriori algorithm
R programming
discipline competition
url http://online-journals.org/index.php/i-jet/article/view/8382
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