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

Authors

  • Xiaoling Huang School of International Education, Zhejiang University of Finance and Economics
  • Yangbing Xu School of Information, Zhejiang University of Finance and Economics
  • Shuai Zhang School of Information, Zhejiang University of Finance and Economics
  • Wenyu Zhang School of Information, Zhejiang University of Finance and Economics

DOI:

https://doi.org/10.3991/ijet.v13i03.8382

Keywords:

association rule mining, Apriori algorithm, R programming, discipline competition

Abstract


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.

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Published

2018-03-05

How to Cite

Huang, X., Xu, Y., Zhang, S., & Zhang, W. (2018). 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), 13(03), pp. 100–113. https://doi.org/10.3991/ijet.v13i03.8382

Issue

Vol. 13 No. 03 (2018)

Section

Papers

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