We need to address generative artificial intelligence use for students in work-integrated learning. Now!
Bonnie Amelia Dean, University of Wollongong; Joanna Tai, Deakin University; Kelli Nicola-Richmond, Deakin University; Jack Walton, Deakin University; Dave Cormier, Thompson Rivers University, Canada
Higher education is waking up to the risks and opportunities of generative artificial intelligence (GenAI). There has been a spotlight on how to treat GenAI use in assessment, the need for integration into policy, and the development of various metaphors and other mnemonic devices to show staff why GenAI needs special attention compared to other technologies.
However, one area that has avoided attention to date is work-integrated learning (WIL). WIL is where students experience authentic work practices with industry partners such as internships, placements or industry projects. WIL could, at first glance, be seen as relatively unproblematic when it comes to GenAI due to the applied nature of the learning practice and the authenticity in which students apply knowledge and skills. In the University of Sydney’s “Sydney Assessment Framework”, which adopts a two-lane approach to GenAI use, WIL is classified as ‘secured’ alongside invigilated exams and in-class activities. The hands-on, supervised nature of WIL helps mitigate GenAI risks by ensuring clarity on who is doing the work, how learning is being monitored, and what discipline-specific knowledge is being applied in practice.
However, university students undertaking WIL face unique and complex challenges when it comes to GenAI. Entering new workspaces, they must navigate a maze of competing perspectives, diverse policy environments and often obtuse sociotechnical and political landscapes. Added to this are the student’s own preferences and practices for using GenAI, which are often deeply embedded into their daily lives and study. For example, imagine a student who is encouraged to experiment with GenAI tools at university and relies on them for informal correspondence, planning, and ideas. This student feels confident using GenAI. Now, picture this student entering a small to medium enterprise where GenAI use isn't explicitly addressed in formal documents, but it's known that the Director doesn't trust or permit it. How does a new, junior, and temporary employee navigate the workplace culture, rules, tools, and priorities without explicit support beforehand?
The risks are too significant for university staff facilitating WIL to ignore the GenAI conversation with students and industry partners. Beyond immediate ethical and legal concerns, avoiding this discussion can hinder students' confidence, professional identity, and agility when transitioning into workspaces.
To assist university staff, raise awareness among industry professionals and empower students to discuss GenAI, a team from The Centre for Research in Assessment and Digital Learning (CRADLE), with invited colleagues, have developed a set of reflective resources. These resources are designed to initiate conversations and include prompts for educators, industry partners and students, covering all stages of WIL – before, during and after. They aim to raise awareness of key considerations rather than offering one-size-fits-all advice (which would never work!).
For example, before WIL, students could reflect on the following:
Previous use: How have they used GenAI before (e.g., for brainstorming, writing, summarising, or editing)?
Regulatory environment: Do they know any regulations or guidelines in their field about using GenAI? How can they find out more before the WIL experience starts? How can they make sure they follow these rules during the WIL experience?
Current tools: What GenAI tools have they been using in their learning that they might want to keep using during the WIL experience?
Career vision: How do they envision the long-term impact of GenAI on their career?
By reflecting on these questions, either individually or with others, we can better prepare students to understand their own assumptions about GenAI, its implications for their chosen field, and how to manage its use during their WIL experience.
Omitting discussion of GenAI in WIL may prohibit exploration of the infinite possibilities for integrating it creatively, productively or effectively into learning and work practices. To explore some ideas for how WIL educators can collaborate with GenAI for students’ learning and work activities, also view our resource on examples of GenAI in WIL here.
Now is the time to raise the bar for GenAI in WIL. By discussing it openly, supporting our students and industry partners, and exploring imaginative, helpful, and ethical uses, we can ensure that GenAI is an asset in education and the workplace.
The authors launched the resources on 28 April with a webinar hosted by WIL Australia. Here is the link to the recording of the event:
Associate Professor Bonnie Amelia Dean, Head of Academic Development and Recognition, Learning, Teaching & Curriculum, University of Wollongong
Associate Professor Joanna Tai, Senior Research Fellow, Centre for Research in Assessment and Digital Learning (CRADLE), Deakin University
Associate Professor Kelli Nicola-Richmond, Associate Head of School Teaching and Learning in
the School of Health and Social Development, Deakin University
Dr Jack Walton, Research Fellow, Centre for Research in Assessment and Digital Learning (CRADLE), Deakin University
Dave Cormier, Director, Curriculum Development and Delivery (Interim), Thompson Rivers University, Canada