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.
Highlights
In recent years, the issue of how to extract the useful information from educational data to promote the students’ overall development has attracted a lot of researchers’ and teachers’ attention
Because the R Programming, as a free platform, is a powerful tool for data mining, we adopt R 3.4.0 to do association rule mining from the data of 164 undergraduate students who majored in Software Engineering in Zhejiang University of Finance and Economics
In order to select the proper students to take part in the proper discipline competition, we use the Apriori algorithm with group strategy to extract the useful information from 164 undergraduate students who majored in Software Engineering in Zhejiang University of Finance and Economics
Summary
The issue of how to extract the useful information from educational data to promote the students’ overall development has attracted a lot of researchers’ and teachers’ attention. The development of computer science and data mining technology provides a new method to find the relationship between students’ courses scores and other features. In order to select proper students to take part in the proper discipline competition so that the probability for them to be awarded in the discipline competition becomes higher, in this article, we aim to find the relationship between the students’ courses scores and discipline competition awards. The conclusion and further work are introduced in the last section
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