IN-PERSON MADRID FOCUS ON PEDAGOGY. SECTION B

Abstract

Generative AI is not simply reshaping creative production; it is destabilising the foundations of assessment in studio-based education. Traditional grading models in art and design have long privileged the originality, craft, and resolution of final artefacts. However, when AI systems can generate technically sophisticated outputs within seconds, output-based evaluation risks collapsing as a meaningful measure of student learning. Drawing on a mixed-methods survey of 32 art and design educators across UK and international higher education institutions, this paper examines how assessment practices are being renegotiated in response to AI integration. Educators report heightened concern around originality, authorship, and intellectual integrity, alongside institutional uncertainty about acceptable AI use. The findings suggest that artefact-focused marking criteria are increasingly inadequate in distinguishing between superficial production and deep creative reasoning. The paper argues that documentation, process logs, iterative development records, reflective commentary, and explicit disclosure of human–AI interaction, must become central to assessment. Such transparency shifts the evaluative focus from product to judgement, intention, and critical positioning. This transition also exposes the politics of originality, challenging inherited assumptions about authorship in collaborative human–machine workflows. Rather than banning AI or reverting to analogue assessment models, the paper proposes a principled re-writing of rubrics. AI-responsive assessment should foreground conceptual development, ethical awareness, and decision-making rationale over aesthetic polish alone. By reframing assessment as the evaluation of thinking rather than output, design education can preserve academic integrity while adapting to technological transformation.