Coauthorship Integrity: Reconceptualising Assessment Validity for the Age of Generative Artificial Intelligence

We consider how a future of pervasive human/AI coauthorship challenges current notions of validity and academic integrity. Specifically, we address widespread concerns that in non-proctored contexts, students are using generative artificial intelligence (GenAI) to submit texts they do not understand. Adopting an assessment validity lens, we show how GenAI undermines the integrity of multiple forms of validity evidence, leading us to propose Coauthorship Integrity as a new conceptual source of validity evidence for addressing these threats. Coauthorship Integrity is violated when students submit AI-generated content that they do not understand. To hold students accountable in this regard, a university needs to explore practical methods to gather evidence that could potentially be implemented at scale. We report progress in the development of an “AI Viva”, a conversational agent that engages students in a hybrid experience, combining elements of a viva voce with comprehension questions of controllable type and complexity, engaging the learner with quantitative and dialogic feedback. To provide preliminary expert validation for this prototype, we report qualitative and quantitative evidence from in-depth evaluations with expert educators and assessment experts. By shifting assessment design towards verifying students’ epistemic ownership of their writing, this work suggests a potential new pathway for integrating GenAI into pedagogically meaningful, validity-aligned assessment practices. This paper’s contributions are thus threefold: conceptual (Coauthorship Integrity), technical (LLM-generated questions of controllable difficulty and type, from arbitrary texts) and empirical (preliminary expert evaluation of the concept and initial implementation of the prototype’s potential for eliciting such evidence).