Journal of Applied Computing and Information Technology
ISSN 2230-4398, Volume 25, Issue 1, 2021/2022
Incorporating the NACCQ publications:
Bulletin of Applied Computing and Information Technology,
ISSN 1176-4120
Journal of Applied Computing and Information Technology, ISSN 1174-0175
Welcome
- Executive Editor: Dr. Emre Erturk (eerturk@eit.ac.nz), or
- Senior Associate Editor: Dr. Donald Joyce (dcjoyce@xtra.co.nz).
Welcome to this issue of Computing and Information Technology Research and Education, New Zealand (CITRENZ) Journal of Applied Computing and Information Technology (JACIT), an amalgamation of two publications from the National Advisory Committee of Computing Qualifications (NACCQ): JACIT and the Bulletin (BACIT).
Are you interested in contributing a paper to JACIT? Please refer to the guidelines and templates available on the Authors tab, and then contact the editors:
Curriculum Article (2022)
An Analysis of Structure and Features of Data Science Postgraduate Courses in Australia and New Zealand
Guozhen G. Huang, Emre Erturk and Farhad Mehdipour
This article analyses the structure and features of the Master of Data Science courses that are offered by 21 universities in Australia and New Zealand. The primary data is a corpus of their course descriptions, outlines and other related information. The data is analysed in R for text mining of the corpus to visualise the important terms and their associations. The visualised terms are then compared with those that are drawn from 82 data scientist job descriptions that were collected in SEEK (the largest job market portal in Australia and New Zealand) over the last six months for triangulation. The primary findings are seven competency areas (subjects or units) and the proportions how the contents of these areas are distributed in the two-year course structure. It is believed that the findings will not only fill a gap in the literature of data science curriculum studies, but also provide a useful source of information for higher education institutions especially those who are interested to develop postgraduate courses in data science. The findings may also assist the professional accrediting authorities in quality assurance and evaluation of data science related courses.