International Journal of Soft Computing
ISSN: OnlineISSN: Print 1816-9503
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 student’s level of involvement in the listed factors in quantitative measure. The questionnaire represented the student’s 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 student’s 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.
How to cite this article:
Amenawon Ehigbochie and Olufunke Oladipupo. A Fuzzy-Mining Predictive Model for Analysing Student’s Academic Performance.
DOI: https://doi.org/10.36478/ijscomp.2017.210.217
URL: https://www.makhillpublications.co/view-article/1816-9503/ijscomp.2017.210.217