Predicting Academic Success for Business and Computing Students

Predicting Academic Success for Business and Computing Students

Kawtar Tani (Universal College of Learning (UCOL), New Zealand) and Andrew Gilbey (Massey University, New Zealand)
DOI: 10.4018/978-1-5225-2584-4.ch053


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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Study 1: Using Enrolment Data To Predict Academic Success

Student retention and programme completion are important goals of academic institutions. Amongst the most consistent predictors of retention are high school achievements (Astin, Korn, & Green, 1987). Astin et al. studied 8000 students and found that students with an ‘A’ average in high school were seven times more likely to attain tertiary qualifications than students with a ‘C’ average. Similarly, Levitz, Noel and Richter (1999) showed that schools with the highest averages of test scores reported a retention rate of 91 percent of first- and second-year. However, this rate dropped to 56 percent among students with the lowest test score averages.

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