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.
Acknowledgements
The authors acknowledge the significant contribution to this paper from their late colleague and co-author, Professor Neil Doherty. The authors would also like to acknowledge the support of the Operational Research Society who part-funded and supported this research, as part of the charitable project titled Is Operational Research in UK Universities ‘Fit-for-Purpose’ for the Growing Field of Analytics? For any readers interested in applying the methods used in this paper, a technical addendum has been produced, including a list of all steps and source code where available that we are happy to share with any interested parties. Please contact the authors using the correspondence email address given at the start of the article.
Disclosure statement
No potential conflict of interest was reported by the authors.