Applying predictive analytics in identifying students at risk: a case study

In this article, a case study is presented of an institutional modelling project whereby the most appropriate learning algorithm for the prediction of students dropping out before or in the second year of study was identified and deployed. This second-year dropout model was applied at programme leve...

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Bibliographic Details
Published in:South African journal of higher education 2016-01, Vol.30 (2), p.129-142
Main Authors: Lourens, A, Bleazard, D, 13274694 - Lourens, Amanda
Format: Article
Language:English
Subjects:
Decision trees
Logistic regression
Naive Bayes
Predictive learner analytics
Retention of students
Student dropout
Students at risk
Online Access:Get full text
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