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Download fileCreating a typology of analytics Master's degrees in UK universities: Implications for employers and educators
journal contribution
posted on 2019-04-09, 14:50 authored by Michael J. Mortenson, Neil Doherty, Stewart RobinsonIn recent years there has been a growth in specialised analytics Masters 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 paper analyses UK Masters 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.
History
School
- Business and Economics
Department
- Business
Published in
Journal of the Operational Research SocietyVolume
71Issue
9Pages
1327-1346Citation
MORTENSON, M.J., DOHERTY, N. and ROBINSON, S., 2019. Creating a typology of analytics Master's degrees in UK universities: Implications for employers and educators. Journal of the Operational Research Society, doi:10.1080/01605682.2019.1605468.Publisher
Taylor & Francis © Operational Research SocietyVersion
- AM (Accepted Manuscript)
Publisher statement
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 14 June 2019, available online: http://www.tandfonline.com/10.1080/01605682.2019.1605468.Acceptance date
2019-04-05Publication date
2019-06-14Copyright date
2020ISSN
0160-5682eISSN
1476-9360Publisher version
Language
- en