What is it about?

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. Students developed greater self-awareness, teamwork, decision-making and leadership skills.

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Why is it important?

Digital transformation and data-driven decision-making are disrupting workplaces worldwide, and data scientists are at the forefront of this revolution. Employees with expertise in data science are in great demand as predictive analytics and data-driven evidence-based practice are increasingly central to workplace operations and business efficiencies. Preparing data science students for the dynamics of the future workplace is imperative. Interdisciplinary project-based work-integrated learning in partnership with industry equips students with sophisticated problem-solving skills that enables them to solve complex real-world problems in collaboration with peers from diverse discipline areas.


This article describes the planning, execution and outcomes of an impactful learning strategy that empowers students and builds personal agency and a professional identity. As an academic working with the students on this pilot, the opportunity to work intensely with fellow academics, industry personnel, and amazing students was inspirational. The collaborative learning environment afforded life-changing perspectives for all stakeholders.

Sonia Ferns
Curtin University

Read the Original

This page is a summary of: Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach, Teaching Statistics, June 2021, Wiley,
DOI: 10.1111/test.12272.
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