Reimagining the Artificial Intelligence Assessment Scale: A refined framework for educational assessment

Abstract

Higher education institutions, educators, and students continue to grapple with the wide-ranging implications of Artificial Intelligence (AI) and Generative Artificial Intelligence (GenAI). The ability of advanced GenAI models to complete educational assessments continues to be one of the most pressing issues for academia. In early 2024, we published the AI Assessment Scale (AIAS), which describes a practical framework for addressing GenAI use in educational assessment. The AIAS was well received and has been implemented in hundreds of institutions worldwide and translated into 30 languages. Building on our experience using the AIAS and drawing on feedback and critiques received worldwide, in this paper, we provide an updated version of the AIAS. The updated AIAS encompasses several important developments, including clarifying the theoretical basis of the scale through social constructivist principles, developing the AIAS to function as an assessment redesign framework to enhance validity, and adjusting the visual assets of the AIAS to function inclusively and non-hierarchically. Furthermore, in anticipation of future developments in the field of AI and the increasing focus on preparing students to function in an AI-augmented world, we introduce an additional level, ‘AI exploration’. Through this paper we also seek to clarify both the intended and unintended applications of the AIAS. We provide implementation guidance through practical examples and explain how the AIAS functions as both a communication tool and a framework for task redesign that strengthens validity.