NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1167746
Record Type: Journal
Publication Date: 2016
Pages: 10
Abstractor: As Provided
ISSN: ISSN-1550-1876
Predicting Academic Success for Business and Computing Students
Tani, Kawtar; Gilbey, Andrew
International Journal of Information and Communication Technology Education, v12 n4 Article 2 p15-24 2016
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.
IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: New Zealand
Grant or Contract Numbers: N/A