The AI Assessment Scale (AIAS)

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Evidence · 3 claims (1 for, 1 mixed, 1 against) · 2 studies (2 qualitative), q2 · 0 of 2 report an effect size · 3 claims rest on one study

Description

A scale-based framework developed by Perkins et al. for guiding universities, staff, and students in specifying appropriate generative-AI use in assessment while considering integrity, equity, and learning outcomes.

Components

• The AI Assessment Scale (AIAS) as a structured framework for embedding GenAI into assessment design: The AIAS is a scale-based framework providing structured guidance for embedding generative AI into assessment design across the dimensions of integrity, equity, and pedagogy. It assigns levels that specify permitted GenAI use, functioning in practice as "a shared language" through which faculty, students, and institutions negotiate expectations. This study examines its enactment at two universities, showing its value depends on implementation conditions rather than framework choice alone. (Perkins et al. (2026))
• AI Assessment Scale (AIAS) and FACT framework: tiered taxonomies for bounding and disclosing AI use in assessment: The AIAS (AI Assessment Scale) is "a tiered taxonomy that maps different levels of AI involvement onto different assessment contexts", letting faculty design tasks where AI use is explicitly bounded, disclosed, and critically evaluated rather than covert. The FACT (Fundamental, Applied, Conceptual, Thinking) framework similarly supports transparent definitions of ethical tool use. Both treat AI as "a pedagogical variable to be deliberately managed" rather than an adversary, aligning policy with post-graduation professional realities. (Md Zarzees Uddin Shah Chowdhury et al. (2026))

Claims

• Academic staff experienced the AIAS as a shared language that legitimised GenAI use in teaching and assessment [+M]
• Retrofitting an AIAS level to an unchanged assessment task creates a validity risk in which the assessment measures use of the scale rather than intended learning outcomes [~M]
• Existing GenAI assessment frameworks (traffic light, two-lane, AIAS) remain broad, lack discipline-specific applicability, and are unvalidated in authentic settings [-W]

Related Products and Programmes

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Key Sources

• Perkins, M., Postma, D., Roe, J., Sisay, S., & Holdcroft, C. (2026). 'A bit of chaos and madness': The AI Assessment Scale and the work of assessment reform. Preprint. doi:10.48550/arxiv.2606.26729
• Md Zarzees Uddin Shah Chowdhury and Samin Rahman Khan. (2026). Evaluation in the Age of AI: Output as Evidence of Learning. https://arxiv.org/abs/2608.22660

Page metadata

Field	Value
type	product
id	the-ai-assessment-scale-aias
title	The AI Assessment Scale (AIAS)
description	A scale-based framework developed by Perkins et al.
status	review
product_kind	framework
generated	by process:settle-candidates on 2026-10-10
trust	unverified — no one has confirmed this page's content

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