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Educational data mining (EDM) is a field that concentrates on prediction and is known for its role
in uncovering hidden information from large volume of data. EDM has seen an emergence of
research leading to strategies that aim to address issues of higher education with primary focus on
students’ attrition. An unceasingstudent’s attrition from the undergraduate programmeof Ahmadu
Bello University, Zaria (A.B.U, Zaria) has significant ramification for individuals affected by this
problem and the society in general. This work examines the problem of predicting student’s
dropout in selected programmes of A.B.U Zaria. This work also focuses on addressing students’
attrition by creating a first year at risk model to be used in early detection of students at the risk of
attrition. Various factors that might influence students’ attrition were collected from two (2)
primarysources (student portal and exam processingsoftware) of A.B.U Zariainformation system.
This work applies variants of existing classification algorithms in building predictive models; also
an instance based learning algorithm (k nearest neighbor) was chosen and modified. An initial data
preprocessing, feature selection and a 10-fold cross validation experiment was carried out in the
model development phase of this work using WEKA (an open source tool for data mining tool).
The classification algorithms employed in this work include: Multi-Layer Perceptron, Naïve
Bayes, J48 Decision Tree, Sequential minimal optimization, K-Nearest Neighbor and a modified
K-Nearest Neighbor. Results obtained showed J48 decision tree algorithm have performed nicely
among all, based on our dataset with an average accuracy of 97.9%. Also the modified nearest
neighbor algorithm performed next with an average accuracy of 97.3%. The result obtained were
validated and analyzed using WEKA’s experimenter. To choose the best model, we conducted a
comparative analysis of the classifiers used in this dissertation work.
CHAPTER ONE: GENERAL INTRODUCTION
This chapter discusses the introductory part of the dissertation which includes background of
the study, statement of the problem, research motivation, aim and objectives, scope of the
research, the methodology used to carry out the research and finally the dissertation
contribution to knowledge.
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