When Clarity Creates Interpretive Load: A Policy Document Analysis of Student GenAI Governance in Assessment Across the UK's G5 Universities

Abstract

While institutional policies on regulating student generative AI (GenAI) use in assessment have multiplied in higher education, their soaring number may not guarantee effective governance. Previous studies have highlighted persistent barriers including violation of academic integrity, student overreliance, and assessment invalidity, whereas more internal factors around how policy per se can undermine prospective clarity and exacerbate governance dilemma are still underexamined. Therefore, this study interrogates existing issues around institutional GenAI-regulatory materials themselves. Employing the concept of 'interpretive load', this study examines the governance dilemma through a specific lens of how students bear the burden to navigate and understand the institutional policy architecture and language before starting assessments. Through a policy document analysis of a purposive sample of materials published by the UK's G5 universities, this paper identifies three issues – policy proliferation, policy fragmentation, and policy ambiguity. These three findings represent crucial mechanisms that progressively enable institutions to transfer responsibility for clarification to students, consequently placing interpretive load on students. Crucially, this paper concentrates on a relatively new notion of interpretive load, which implies ample scope for theoretical investigation and offers directions for future institutional policy making and research orientations within the field.