Predicting academic success of undergraduate architecture students : using k nearest neighbour algorithm

Aluko, Ralph; Aigbavboa, Clinton; Oshodi, Olalekan Shamsideen

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Aluko, Ralph, Aigbavboa, Clinton, Oshodi, Olalekan Shamsideen. Predicting academic success of undergraduate architecture students : using k nearest neighbour algorithm. 2016.

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Please use this identifier to cite or link to this item: http://hdl.handle.net/10210/215564

Title: Predicting academic success of undergraduate architecture students : using k nearest neighbour algorithm
Creator: Aluko, Ralph
Creator: Aigbavboa, Clinton
Creator: Oshodi, Olalekan Shamsideen
Subject: Academic success
Subject: Architecture students
Subject: Classification
Date: 2016
Description: Abstract: The number of applicants considered during the admission selection process for universities has increased exponentially. This has led to development and improvement of the admission criteria so as to ensure that new intakes that possess the potential to achieve academic success are selected. The aim of the present study is to examine the relationship between academic success of architecture student and prior academic performance using K-nearest neighbour algorithm (k-NN). Data on prior academic performance, which is considered during admission process, and academic success was collected on four cohorts of architecture students. Then the data is divided into two parts: training set (70%) and test set (30%). Finally, the k-NN was developed using the training sets and the predictive performance was evaluated using the test set. The experimental results shows that the overall accuracy of the k-NN model is 73.33%. It is anticipated that the developed model could provide useful information that can be used to identify new intakes whom possess adequate intellectual capabilities to succeed in undergraduate architecture programs in Nigeria.

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collection(s): Conference proceedings
Identifier: http://hdl.handle.net/10210/215564
Identifier: uj:21432
Identifier: Citation: Aluko, R., Aigbavboa, C & Oshodi, O.S. 2016. Predicting academic success of undergraduate architecture students : using k nearest neighbour algorithm.
Language: English
Rights: ©2016, authors
Type: Conference proceedings
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Conference proceedings Predicting academic success of undergraduate architecture students : using k nearest neighbour algorithm

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