Educational integrity in GenAI-augmented assessment: making judgement visible

The adoption of generative artificial intelligence (GenAI) has unsettled established approaches to educational integrity, particularly those that rely on detection and verification of independent authorship. This conceptual and practice-informed paper extends postplagiarism by operationalizing its ethical commitments through assessment design. It argues that detection and verification-based approaches are increasingly misaligned with GenAI-augmented assessment, where human judgement and technological generation are deeply entangled. Drawing on the concept of postplagiarism, it translates ethical commitments into structural assessment principles that foreground evaluative judgement. It reframes educational integrity as a pedagogical practice enacted through evaluative judgement rather than as compliance secured through surveillance. Through practice-informed examples, the paper illustrates how assessment structures can make decision-making, responsibility, and transparency visible within hybrid human-GenAI systems. In doing so, this paper advances educational integrity scholarship by shifting integrity governance from detection-based compliance models to structurally embedded assessment design.