Dr Angie Nguyen, Education Design and Quality Manager at UNSW Sydney, shares how partnering with students as ethical “white hat hackers” can help academics redesign assessments for the generative AI era while strengthening learning, academic integrity and authentic assessment. 

“Can you show me how you would use generative AI to complete this assessment?” 

For many academics, that sounds like a question we should never ask. For our “White hat hacking” and rethinking assessment with Students-as-Partners project at UNSW Law & Justice, it became the starting point for rethinking assessment in the age of generative AI. 

Like many universities, we have spent the last few years grappling with the rapid emergence of generative AI. Much of the conversation has focused on preserving academic integrity, preventing misuse, and protecting the validity of assessment. At the same time, academic staff are navigating increasing workloads, changing student expectations, and ongoing sector-wide disruption. Asking colleagues to simply “do more” is neither practical nor sustainable. Thus, one question kept returning: how should we redesign assessment for an AI-enabled world? 

Rather than seeing students as part of the problem, we saw an opportunity to make them part of the solution. Our students were already using generative AI and were often more familiar with its capabilities than we were. Instead of designing new assessment approaches for students, why not design them with students? Students’ lived experiences with AI make them uniquely positioned to identify weaknesses in assessment design and suggest ways to strengthen authentic learning. This aligns with the growing Students-as-Partners literature, which highlights the value of staff and students working together to navigate emerging educational challenges through shared inquiry and co-design. 

Inspired by the concept of white hat hacking in cybersecurity – where ethical hackers identify vulnerabilities before they can be exploited – we invited students to do something unexpected: stress-test our assessments using generative AI. 

It turned out to be one of the most valuable conversations we have had about assessment. 

Our approach 

We developed a five-stage “White hat hacking” and rethinking assessment with Students-as-Partners process that positions students as collaborators in strengthening assessment rather than simply completing it. 

The project begins by identifying courses for review and recruiting a diverse group of student partners. Students are introduced to the project’s purpose and ethical expectations before attempting assessment tasks using generative AI. Some adopt an AI-first approach, allowing AI to generate an initial response, while others use AI as a partner, working iteratively with AI to support their thinking. Throughout the process, students document their prompts, AI interactions, outputs and reflections, creating rich evidence of how AI interacts with assessment design. 

These findings are then brought into collaborative discussion sessions involving students, academics, educational developers and academic integrity specialists. Together, we examine where assessments are vulnerable, where learning risks emerge and where opportunities exist to better assess authentic learning. 

The next stage moves beyond identifying problems to co-designing solutions. Students and staff work together to redesign assessments that make students’ thinking more visible, encourage appropriate AI use, strengthen higher-order learning and enhance academic integrity. Rather than simply making assessments “AI-proof”, the goal is to design assessments that remain meaningful in a world where AI is readily available. 

The project also focuses on sharing what we learn. Assessment redesign guides, case studies and examples of effective practice are developed to support other teaching teams, while workshops and presentations build institutional capability. Continuous project evaluation ensures that feedback from both staff and students informs future iterations, creating an ongoing cycle of improvement. 

What we learned 

The process was implemented in 11 courses across four programs offered by the Faculty of Law & Justice, University of New South Wales in Australia during 2025. We adopted a structured, yet scalable, model that reframed generative AI as a catalyst for improving assessment rather than simply a threat to academic integrity. One of the most significant outcomes was not just better assessments, but better conversations. Students provided insights that academics simply could not access on their own. They demonstrated how they actually used AI, where assessment tasks could be completed with minimal learning and which aspects of assessments genuinely required human judgement, disciplinary reasoning and personal reflection. 

The success of the project encouraged us to extend the partnership model beyond assessment. In 2026, we launched a program-level initiative across UNSW Law & Justice to support students’ AI literacy, confidence and ethical use of generative AI. Once again, students were engaged as partners; not simply reviewers therefore, but co-creators of learning resources. Working alongside staff, students developed AI guidance, exemplars and practical resources designed by students-for-students. Grounded in student lived experiences, these resources help embed responsible AI use consistently across programs while reducing confusion about expectations across different courses. 

Generative AI is challenging many of our assumptions about assessment, but it also offers an opportunity to rethink how we work with students. Our project and its model demonstrate that students can contribute far more than feedback surveys or focus groups. They can help us identify vulnerabilities, test assessment authenticity and co-design learning experiences that better develop disciplinary thinking while supporting responsible AI use. Importantly, this is a low-cost, scalable approach that can be adapted across disciplines and institutions. By repositioning students as partners rather than potential offenders, we shift the conversation from policing AI to improving learning.

Dr Nga Thanh Nguyen (aka Dr Angie Nguyen) is an Education Design and Quality Manager, leading an award-winning team that drives innovation and transformation at University of New South Wales, Australia. She has extensive expertise in curriculum design and development, evaluation in education, leadership and management in education. Angie’s work focuses on enhancing educational quality through collaborative design and evidence-based practice.