Analytics Modules for Business Students

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 CO...

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Bibliographic Details
Main Author: Carroll, P. (Author)
Format: Article
Language:English
Published: Springer International Publishing 2023
Subjects:
Online Access:View Fulltext in Publisher
View in Scopus
LEADER 01864nam a2200193Ia 4500
001 10.1007-s43069-023-00216-5
008 230529s2023 CNT 000 0 und d
020 |a 26622556 (ISSN) 
245 1 0 |a Analytics Modules for Business Students 
260 0 |b Springer International Publishing  |c 2023 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1007/s43069-023-00216-5 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159034339&doi=10.1007%2fs43069-023-00216-5&partnerID=40&md5=dcbf5df65683b3f1a91e0b60959c22d3 
520 3 |a 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. © 2023, The Author(s). 
650 0 4 |a Analytics curriculum 
650 0 4 |a Analytics pedagogy 
650 0 4 |a Business analytics 
650 0 4 |a Teaching & learning 
700 1 0 |a Carroll, P.  |e author 
773 |t Operations Research Forum