Presenter: Prof Francois Cilliers

Reimagining Assessment in a Generative AI World

In response to generative AI (genAI), universities have rushed to ‘safeguard’ assessment - locking down formats, ramping up invigilation, and seeking new strategies to uphold academic integrity. While understandable, such responses are often reactive, defensive, and driven more by institutional anxiety than educational purpose. They position genAI primarily as a threat to be contained, rather than as a catalyst for reimagining assessment itself. The resultant efforts to protect assessment may be solving the wrong problem.

Instead of asking, “How do I safeguard my assessment from genAI?”, we argue that educators should be asking, “Are my intended learning outcomes still relevant in a world shaped by genAI?”

This interactive workshop introduces two practical tools developed through a collaborative institutional project on the implications of genAI for assessment in higher education:

  • A five-category typology for reviewing intended learning outcomes to determine their relevance and vulnerability in an AI-pervasive context.
  • The Framework for Purposeful Assessment Redesign, a structured process for adapting learning outcomes, reviewing alignment with educational intent and aligning assessment tasks with those outcomes, while foregrounding principles of equity and justice.
     

Participants will apply the typology to critically review learning outcomes, then use the framework to explore redesign possibilities. Through small-group work and plenary discussion, participants will consider how assessment can both leverage and ethically navigate genAI, moving beyond anxiety-driven safeguards toward creative, critical, and principled responses.

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