Paper Info
Title
Creating a typology of analytics Master's degrees in UK universities: Implications for employers and educators.
Abstract
In recent years there has been a growth in specialised analytics Master's degrees, in the UK and beyond. However, there has been little research into the contents of such degrees. In particular, the role disciplines such as operational research play within them remains an under-explored area. Using a mixed-methods approach, this article analyses UK Master's degrees in analytics to determine a typology of provisions. Firstly, a support vector classifier is used to identify the traditional disciplines analytics degrees most closely align with. Secondly, a hybrid approach to analyse the modules included in analytics curricula is employed, as part of which a new metric (module topic weighting) is presented. The analysis identifies two main categories of degrees, the first aligning with machine learning and computing topics; the second operational research and business themes. The paper concludes by evaluating the implications this has for students, employers, educators and the operational research discipline.
Year
DOI
Venue
2020
10.1080/01605682.2019.1605468
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
Keywords
DocType
Volume
Analytics,support vector machines,curricula development,machine learning
Journal
71.0
Issue
ISSN
Citations 
9.0
0160-5682
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Michael J. Mortenson100.34
Neil F. Doherty200.34
Stewart Robinson358350.51