[HYBRID] Assessment in a Postplagiarism era: The AI Assessment Scale as a framework for academic integrity in an AI transformed world
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[HYBRID] Assessment in a Postplagiarism era: The AI Assessment Scale as a framework for academic integrity in an AI transformed world In-Person / Online
Developments in Generative AI are leading us closer to the concept of ‘postplagiarism’, with traditional concepts of academic integrity being fundamentally challenged by these technologies. This lecture explores how the AI Assessment Scale (AIAS) offers a pragmatic response to this upcoming paradigm shift, moving beyond futile attempts at AI detection towards thoughtful assessment redesign. In a world where AI-generated content is becoming indistinguishable from human work, the AIAS (Perkins et al., 2024) provides a five-level framework that acknowledges this new reality whilst maintaining academic authenticity.
Rather than treating AI as a threat to be policed, the AIAS embraces it as a tool to be thoughtfully integrated where appropriate. From ‘No AI’ assessments that preserve foundational skill development, to ‘AI Exploration’ tasks that prepare students for an AI-saturated workplace, this framework offers educators practical strategies for the postplagiarism landscape. This talk will demonstrate how institutions can move from an adversarial ‘catch and punish’ mentality to a collaborative approach that recognises both learning integrity and technological advancement. The session will challenge traditional academic integrity paradigms and offer actionable insights for this new era of university assessment.
Please note that this session will be recorded.
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