Predicting Academic Success for Business and Computing Students

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Author(s): Kawtar Tani (Universal College of Learning (UCOL), New Zealand)and Andrew Gilbey (Massey University, New Zealand)
Copyright: 2018
Pages: 12
Source title: Student Engagement and Participation: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-2584-4.ch053

Keywords: Curriculum Development and Instructional Design / Education / Information Science Reference / Instructional Design

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Abstract

Various means to predict the success rate of students have been introduced by a number of educational institutions worldwide. The aim of this research was to identify predictors of success for tertiary education students. Participants were 353 students enrolled on Business and Computing programmes between 2009 and 2014, at a tertiary education provider in New Zealand. Enrolment data were used to determine the relationships between completion of the programme and prior academic achievement, age, ethnicity, gender, type of enrolment, and programme of study. These variables, as well as the overall GPA of the programme, were used to examine their relationship with the first year GPA. Results showed that pre- and post-enrolment data can be used for prediction of academic performance in ICT programmes. Based on the significance of some variables, tertiary education institutions can identify students who are likely to fail, these students can therefore be considered for additional support in the early stages of their study, in order to increase their chances of succeeding academically.

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Predicting Academic Success for Business and Computing Students

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