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Understanding industry dynamics through work-integrated learning data

Wednesday 3 July: Conference day one, 2:00pm – 2:30pm parallel session



Room 3 – 303-G15 Sem



Associate Professor Christy Collis
Queensland University of Technology, Australia




Work-integrated learning (WIL) is most often seen as an important immersive learning experience for students. WIL, however, also generates valuable industry data and insights for academic researchers. This paper thus asks, what do WIL data tell us about the dynamics of the creative industries sector? The paper takes the QUT Creative Industries Faculty WIL program as its analytical focus. This program scaffolds approximately 1000 students in 500 industry internships per year, offering a significant dataset for analysis. This paper has as its foundation the premise that organisations that are prepared to take on university interns have a growth orientation, which includes an active interest in potential new employees and new ideas. The dynamics of the creative industries sector are notably difficult to determine, given the non-traditional nature of much creative industries employment, the prevalence of SMEs, and the “embedding” of many creative industries roles in other industry sectors (Higgs & Cunningham 2016). This paper supplements existing industry data with evidence from the QUT CIF WIL program. An analysis of five years of WIL internship data provides a substantial evidence base about the creative industries organisations which are signalling a growth orientation through taking on interns; the same data also points up areas of sectoral stagnation. Industry insights generated by this data provide an evidence base for better alignment of university curricula and employability education with sectoral trends. The paper complements Lima and Bakhshi’s analysis of job advertisement data to reveal sectoral dynamics of the creative industries, providing  “an example of how policymakers can mine web-based labour market data… to develop timely and detailed insights related to employment” (2018, p.7) and to employability.



Higgs, Peter L. & Cunningham, Stuart D. (2016) Creative industries mapping: Where have we come from and where are we going? In Potts, Jason D. (Ed.) The Economics of Creative Industries. Edward Elgar Publishing, Cheltenham, United Kingdom, pp. 843-866.
Lima, A., & Bakhshi, H. (2018) Classifying occupations using web-based job advertisements: an application to STEM and creative occupations. ESCoE Discussion Paper 2018-08. Retrieved 5 Feb 2019 from


Presentation topic

Tertiary – New Developments

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