Writing with machines? Reconceptualizing student work in the age of AI

Abstract

The rise of generative artificial intelligence (GenAI) such as ChatGPT fundamentally challenges traditional assumptions about student authorship and assessment in higher education. Drawing on Michel Foucault's notion of the “author function” and Roland Barthes' critique of textual authority, this paper argues that AI chatbots expose critical tensions in how we understand and evaluate student work. After examining why conventional approaches to ensuring assessment integrity have become obsolete, I propose a 'tapas model' of assessment that combines different evaluation types: pure human work, bounded AI use, and full AI integration. This model moves beyond binary notions of AI detection and cheating, instead embracing AI as a co-participant in knowledge production while ensuring students develop both traditional and AI-enhanced competencies. The paper argues for shifting from punitive AI detection to transparent AI declaration, treating AI as a methodological consideration rather than a threat to academic integrity. This approach acknowledges that knowledge creation has always involved complex networks and suggests that education must evolve beyond simplistic notions of individual authorship to embrace more nuanced forms of assessment suited to an AI-augmented world.

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