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ERIC Number: EJ1299886
Record Type: Journal
Publication Date: 2021
Pages: 10
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0141-982X
EISSN: N/A
Available Date: N/A
Building Employability Capabilities in Data Science Students: An Interdisciplinary, Industry-Focused Approach
Ferns, Sonia; Phatak, Aloke; Benson, Susan; Kumagai, Nina
Teaching Statistics: An International Journal for Teachers, v43 spec iss 1 pS216-S225 Sum 2021
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.
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.bibliotheek.ehb.be/en-us
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Australia
Grant or Contract Numbers: N/A
Author Affiliations: N/A