Students’ Performance Prediction Using Classsification Algorithms
Babajide Olakunle Afeni, Iyanuoluwa Ayomide Oloyede, Damilola Okurinboye
Journal of Advances in Mathematics and Computer Science · pp. 1–9 · Published 18 Jan 2019
10.9734/JAMCS/2019/45438Abstract
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.
Cited by 4
Ilias Papadogıannıs, Vassilis Poulopoulos, Manolis Wallace · International Journal of Educational Research Review · 2020
Ijaz Muhammad Khan, Abdul Rahim Ahmad, Nafaa Jabeur · International Journal of Emerging Technologies in Learning (iJET) · 2021
Yousuf Nasser Al Husaini, Nur Syufiza Ahmad Shukor · 2024 Sixth International Conference on Intelligent Computing in Data Sciences (ICDS) · 2024
Unknown author, Langelihle Lucky Mhlongo
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