Building Employability Capabilities in Data Science Students: An Interdisciplinary, Industry-Focused Approach

Autor/inn/en	Ferns, Sonia; Phatak, Aloke; Benson, Susan; Kumagai, Nina
Titel	Building Employability Capabilities in Data Science Students: An Interdisciplinary, Industry-Focused Approach
Quelle	In: Teaching Statistics: An International Journal for Teachers, 43 (2021), (10 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Ferns, Sonia) ORCID (Phatak, Aloke)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0141-982X
DOI	10.1111/test.12272
Schlagwörter	Employment Potential; Data; Statistics Education; Interdisciplinary Approach; College Students; Foreign Countries; Skill Development; Data Analysis; Teamwork; Decision Making Skills; Leadership; Active Learning; Student Projects; Australia + Suchen Sie Ihr Suchwort? Arbeitsmarktbezogene Qualifikation; Beschäftigungsfähigkeit; Daten; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Collegestudent; Ausland; Kompetenzentwicklung; Qualifikationsentwicklung; Auswertung; Führung; Führungsposition; Aktives Lernen; Schulprojekt; Australien
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[superscript 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. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01