Using Apriori Algorithm on Students’ Performance Data for Association Rules Mining

DOI

10.2991/iserss-19.2019.105How to use a DOI?

Keywords

data mining, apriori algorithm, association rules, students’ achievement analysis

Abstract

With the development of information technology, many colleges and universities have established student information management system. The long-term operation of the student information management system will generate big data for colleges and universities. Moreover, there exists valuable information in the huge amount of data. Hence, it is necessary to use the data mining method to mine the massive data and get some valuable reference information so as to improve the teaching and management of students. In this paper, the Apriori algorithm is used to mine association rules of 34 courses of 100 students majoring in computer science and technology, so as to find out the correlation between courses and the factors that lead to the high or low grades of courses. R is used to conduct the experiment to discover the association rules, and the association rules are analyzed and discussed. The results of data mining on students’ achievements in this work are expected to provide a reference for improving the teaching quality of computer science and technology courses.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaodong Wu
AU  - Yuzhu Zeng
PY  - 2019/06
DA  - 2019/06
TI  - Using Apriori Algorithm on Students’ Performance Data for Association Rules Mining
BT  - Proceedings of the 2nd International Seminar on Education Research and Social Science (ISERSS 2019)
PB  - Atlantis Press
SP  - 205
EP  - 208
SN  - 2352-5398
UR  - https://doi.org/10.2991/iserss-19.2019.105
DO  - 10.2991/iserss-19.2019.105
ID  - Wu2019/06
ER  -