Journal Article

Predicting Academic Success for Business and Computing Students

Gilbey, Andrew, Tani, Kawtar

2016

Overview

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.

• Publisher: IGI Global
• Subject: Academic Achievement / Age / Business / Business Administration Education / Business students / Communications technology / Computation / Computer Science Education / Education / Education parks / Educational attainment / Enrollment / Enrollments / Ethnicity / First year / Foreign Countries / Grade Point Average / Grades (Scholastic) / Higher Education / Information Technology / Mathematical models / Postsecondary Education / Predictions / Predictor Variables / School enrollment / School facilities / Statistical Analysis / Students / Success / Telecommunications / Variables