The AI3Model: Future Directions for Artificial Intelligence, Assessment Innovation, and Academic Integrity

Abstract

The evolution of machine learning and large language models (commonly referred to as “artificial intelligence” [AI]) presents both opportunities and challenges for teaching and learning across K–12 and higher education contexts globally. Among the most pressing concerns is that these tools can undermine the integrity of student assessment and evaluation systems. This article investigates this timely issue by examining the intersections between AI, academic integrity, and assessment innovations through a cross-national research synthesis, resulting in a novel model for educators, policymakers, and researchers. The proposed model promotes assessment policies and practices that support high integrity, authentic learning, and innovative student assessment in an era of generative AI.