Abstract
Today’s business colleges are attempting to meet the industry demand by developing marketable ERP (Enterprise Resource Planning) skills and delivering exposure to the realities of modern business into the curricula. Role adaptions in real-world settings such as ERP systems use can enhance students’ ability to learn conceptual knowledge for practical application. The situated learning theory capitalizes on a specified context where the context extensively impacts learning. Education data text mining is emerging to produce new possibilities for gathering, analyzing, and presenting student learning outcomes. This chapter aims to reveal ERP learning patterns and themes as evidence of knowledge transfer in ERP role adaptions. The results demonstrate amplified learning through role play in a simulated ERP learning environment.
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Biography
Mary M. Dunaway, Ph.D. is the Director of Data Science Programs and Assistant Professor at the University of Virginia in the College of Continuing and Professional Studies. As a rising scholar, she has successfully published several journal articles, book chapters, and conference proceedings. Also, Dr. Dunaway is leading the effort to develop and launch an Applied Data Analytics graduate certificate program. She is a dynamic STEM academic who is a sought-out speaker and panelist for numerous conferences/workshops sharing her expertise in Information Systems and Data Science.
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Dunaway, M.M. (2018). An Examination of ERP Learning Outcomes: A Text Mining Approach. In: Deokar, A., Gupta, A., Iyer, L., Jones, M. (eds) Analytics and Data Science. Annals of Information Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-58097-5_19
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