Afeni, Babajide Olakunle and Oloyede, Iyanuoluwa Ayomide and Okurinboye, Damilola (2019) Students’ Performance Prediction Using Classsification Algorithms. Journal of Advances in Mathematics and Computer Science, 30 (2). pp. 1-9. ISSN 24569968
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Abstract
It is imperative to analyze educational data especially as it relates to students’ performance. Educational institutions need to have a fairly accurate knowledge of admitted students’ prior academic ability to predict their future academic performance. This helps to identify the good students and also provides an opportunity to pay attention to and improve those who would possibly not perform too well. As a solution, this paper proposed a system which can predict the performance of students from their previous academic record using concepts of data mining techniques under Classification. The dataset contains information about students, such as gender, age, SSCE grade, UTME score, post UTME score and grade in students first year. ID3 (Iterative Dichotomiser 3) and C4.5 classification algorithms was applied on the data to predict the academic performance of students in future examinations.
Item Type: | Article |
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Subjects: | West Bengal Archive > Mathematical Science |
Depositing User: | Unnamed user with email support@westbengalarchive.com |
Date Deposited: | 04 May 2023 07:00 |
Last Modified: | 28 Aug 2024 13:44 |
URI: | http://article.stmacademicwriting.com/id/eprint/457 |