Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach. (25th June 2021)

• Record Type: Journal Article
• Authors: Ferns, Sonia; Phatak, Aloke; Benson, Susan; Kumagai, Nina
• Is Part Of: Teaching statistics. Volume 43(2021)Supplement 1
• Page Start: S216
• Page End: S225
• Publication Date: 2021-06-25
• Subjects: employability -- industry partners -- interdisciplinary -- learning -- project‐based -- teaching -- work‐integrated learning; Statistics -- Study and teaching (Elementary) -- Periodicals; Statistics -- Study and teaching (Secondary) -- Periodicals; 373
• DOI: 10.1111/test.12272
• Languages: English
• ISSNs: 0141-982X

Abstract

Abstract: In the contemporary workplace, data scientists who are capable of interdisciplinary collaboration are in high demand. Universities need to provide data science students with a plethora of learning opportunities that involve collaboration in interdisciplinary contexts and engagement with industry partners. Curtin University and Lab Tests Online Australasia (LTO AU ) collaborated to provide an interdisciplinary, industry‐focused learning experience for data science students. Upon completing the project, students reported improved understanding of the range of applications for data science skills. The experience delivered opportunities for greater self‐awareness and highlighted the importance of teamwork, decision‐making and leadership skills. This chapter presents Interdisciplinary Project‐based Work‐Integrated Learning (IPjWIL), an educational approach that equips data science students with the necessary skills to navigate the future world of work. The results of the pilot project described demonstrate how interdisciplinary, industry‐focused learning experiences enhance the capabilities of data science students, thereby augmenting employability.