The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment- A Preprint
Leon Furze, Mike Perkins, Jasper Roe, Jason MacVaugh

TL;DR
This study introduces the AIAS framework to integrate GenAI into higher education assessments, reducing misconduct and improving student outcomes by encouraging innovative, ethically aligned use of AI tools.
Contribution
The paper presents the AIAS, a novel five-level framework for incorporating GenAI into assessments, demonstrating its effectiveness in a pilot at British University Vietnam.
Findings
Significant reduction in GenAI-related misconduct
5.9% increase in student attainment
33.3% increase in module passing rates
Abstract
The rapid adoption of Generative Artificial Intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices, and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. This paper presents the findings of a pilot study conducted at British University Vietnam (BUV) exploring the implementation of the Artificial Intelligence Assessment Scale (AIAS), a flexible framework for incorporating GenAI into educational assessments. The AIAS consists of five levels, ranging from 'No AI' to 'Full AI', enabling educators to design assessments that focus on areas requiring human input and critical thinking. Following the implementation of the AIAS, the pilot study results indicate a significant reduction in academic misconduct cases related to GenAI,…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education
MethodsFocus
