The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI supported assessment- A Preprint
This addresses academic integrity and assessment practices in higher education, offering a flexible framework for educators, though it is incremental as it builds on existing educational frameworks.
The paper tackled the challenge of integrating Generative AI in higher education by piloting the AI Assessment Scale (AIAS), resulting in a significant reduction in academic misconduct, a 5.9% increase in student attainment, and a 33.3% increase in module passing rates.
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, a 5.9% increase in student attainment across the university, and a 33.3% increase in module passing rates. The AIAS facilitated a shift in pedagogical practices, with faculty members incorporating GenAI tools into their modules and students producing innovative multimodal submissions. The findings suggest that the AIAS can support the effective integration of GenAI in HE, promoting academic integrity while leveraging the technology's potential to enhance learning experiences. Refer to published version for final text.