AI

Our findings demonstrate that the GenAI-assessment challenge exhibits all ten characteristics of wicked problems. For instance, it resists definitive formulation, offers only better or worse rather than correct solutions, cannot be tested without consequence, and places significant responsibility on decision-makers. In the light of this redefinition of the AI and Assessment problem, we argue that educators require certain institutional permissions – including permission to compromise, diverge, and iterate – to appropriately navigate the assessment challenges they face.

Compromise: It allows educators to state plainly that this assessment prioritizes X at the expense of Y, and here is why. It transforms institutional culture from one that punishes imperfection to one that learns from it. When we stop seeking perfect solutions, we can start having honest conversations about which trade-offs serve our students best, which failures taught us most, and how to be thoughtfully imperfect rather than accidentally inadequate.

Permission to Diverge: At its core, ‘permission to diverge’ means accepting that successful practices in one educational context need not – and often should not – be replicated elsewhere. It is the recognition that divergent approaches to common challenges can reflect contextual wisdom rather than inconsistency or failure. By granting ourselves permission to diverge, we acknowledge that different contexts might require quite different responses. This recognises that quality manifests differently across years, disciplines, cohort sizes, and professional destinations. The business educator who integrates AI because employers demand it and the nursing educator who restricts it to ensure clinical competence are both appropriate. Divergence can reflect wisdom that we can easily mistake for confusion. This permission transforms institutional expectations from uniformity to fitness for purpose. Divergence becomes a sign of thoughtful response rather than institutional failure.

Permission to iterate: When AI capabilities transform monthly, when student behaviours shift each semester, and when professional requirements evolve constantly, the result can be that educators design assessments for yesterday’s technology, implemented with today’s students, preparing for tomorrow’s unknowns. Permission to iterate recognizes that wicked problems evolve continuously, making fixed solutions obsolete.

The permission to iterate recognizes wicked problems evolve continuously, making fixed solutions obsolete. This permission transforms assessment from a product to be delivered to a practice to be refined.

The path forward requires abandoning the search for silver bullets in favour of developing adaptive capacity. This means creating institutional structures that support educator decision-making rather than mandating uniform responses, recognizing divergent approaches as evidence of contextual wisdom rather than institutional inconsistency, and treating assessment iteration as professional development rather than design failure.

Of Australian teachers who used AI, the most common purposes were brainstorming lesson plans and learning about and summarizing content. This was happening for 71% of Australian teachers who used AI.

Australian teachers were unlikely to use AI to review data on student performance (9% of those who use AI, compared to 28% across the OECD) and to assess student work (15%, compared to 30% across the OECD).