Analytics Modules for Business Students

Paula Carroll ()
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Paula Carroll: University College Dublin

SN Operations Research Forum, 2023, vol. 4, issue 2, 1-20

Abstract: Abstract Data science is a relatively new requirement for business students. Historically, many business students shied away from business statistics and quantitative or operational research (OR) modules believing them to be boring and irrelevant. The high-profile use of analytics and modelling during the COVID pandemic has drawn awareness to the relevance of analytics. Greater availability of data and modelling tools afford business students an opportunity to re-engage with operational research and analytics and to enjoy the satisfaction of modelling and solving real-world problems, but the challenge of the mathematical modelling skills gap of business students remains. In this paper, we describe a learning pathway of modules in business analytics that can enhance business students’ confidence and capabilities in performing statistical and analytical business tasks. We recommend modelling tools and incremental innovative mathematical modelling teaching approaches that are pedagogically sound and suitable for business students with varying quantitative backgrounds.

Keywords: Business analytics; Teaching & learning; Analytics pedagogy; Analytics curriculum (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-023-00216-5

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