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Reimagining success and failure: equitable assessment practices in an age of AI

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Abstract

With disruption comes the affordance to not only think about things differently, but to truly do things differently. In the context of Generative AI in higher education this holds unique promise on how students are assessed, particularly from the viewpoint of equity. For decades, assessments practices and designs have been flawed; compartmentalised, standardised, and as well documented, disadvantaging to many students.  In this conceptual paper, we now explore how the emergence of GenAI may help to challenge entrenched and exclusionary notion of student success in two key dimensions: distribution of knowledge and agentic assessment. We argue that GenAI creates an opportunity to move away from assessment practices that sort and rank students toward approaches that recognise diverse ways of knowing. Thus, rather than viewing GenAI as a threat to academic integrity, we propose it as a catalyst for more equitable assessment that values collaboration and student agency over individual performance and predetermined standards.

Keywords

Generative AI, student equity, Assessment, higher education.

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