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A fuzzy-Mining Predictive Model for Analyzing Student's Academic Performance

Oladipupo, O. O. (2017) A fuzzy-Mining Predictive Model for Analyzing Student's Academic Performance. International Journal of Soft Computing, 12 (4). pp. 210-217. ISSN 1816-9503

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Abstract

In recent years, serious concerns have been expressed about the alarming rate of weak academic performance of students. A number of factors have been attributed to this trend. To this effect, this study analyzed the syndicate effect of some socio-economic factors: student’s interest, relationship status, entrepreneurial activities, peer influence, health and family background on academic performance. Fuzzy mining approach was used to capture interesting patterns about the socio-economic factors and the student academic performance. Questionnaire approach was used to harvest students’ level of involvement in the listed factors in quantitative measure. The questionnaire represented the students’ opinions from 2 public and 2 private universities in Nigeria. The involved students are from 200 level and above, so as to accommodate for experience in the university system. Fuzzy Association rule mining Algorithm with triangular membership function was used for the mining process and fuzzy models. The result shows various hidden previously unknown patterns of students’ involvement and the effect on their academic performance. This study interprets the patterns according to their inference as regards student academic performance. This, we hope, will help institutions to monitor the student’s academic performances with regard to these socio-economic factors and also serve as an indicator of measure for the students.

Item Type: Article
Uncontrolled Keywords: Academic performance, Socio-economic factors, Fuzzy association rule mining algorithm, Fuzzy model, Triangular membership function
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Dr ibukun Afolabi
Date Deposited: 11 Sep 2017 08:40
Last Modified: 11 Sep 2017 08:40
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/9254

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