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<!doctype html>
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content="Framework Overview - Understanding the foundations of assessment redesign in the age of GenAI. Part of the 2026 Assessment Redesign Framework."
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<meta name="author" content="Dr Hazel Farrell" />
<title>Framework Overview | 2026 Assessment Redesign Framework</title>
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<h1>Framework Overview</h1>
<p>
Understanding the foundations of assessment redesign in the age of
GenAI.
</p>
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<div class="page-content">
<!-- Introduction -->
<section id="introduction">
<h2 class="mt-0">Introduction</h2>
<p>
Since the launch of ChatGPT in November 2022 and subsequent surge in
Generative Artificial Intelligence (GenAI) technology, the education
sector has been impacted significantly, with efforts to develop
policies, strategies, and guidelines to support staff and students
in navigating the changing landscape. While these technologies offer
great potential for enhancing learning experiences, they also pose
significant challenges to academic integrity.
</p>
<p>
Assessment methods such as essays, unsupervised open-book or remote
exams, and online quizzes, are increasingly vulnerable, as students
can access AI tools to produce content that appears to be original
but is not their own work.
</p>
<p>
Although AI detection tools have emerged, their reliability remains
limited, and they cannot serve as definitive evidence of academic
misconduct. The focus therefore shifts from detection to prevention,
with emphasis on authentic learning experiences. This presents an
urgent need for higher education institutions to reconsider their
assessment strategies to uphold academic standards and ensure that
assessments accurately reflect students' knowledge and skills.
</p>
</section>
<!-- The Evolving Policy Context -->
<section id="policy-context">
<h2>The Evolving Policy Context</h2>
<p>
Assessment redesign is not solely a pedagogical issue but also a
governance, quality, and ethical responsibility. National and
international bodies now emphasise that assessment practices must
remain robust when AI is increasingly accessible.
</p>
<div class="callout callout-info">
<h4>Key Developments</h4>
<ul>
<li>
<a
href="https://hea.ie/assets/uploads/2025/12/hea-genai-policy-framework.pdf"
target="_blank"
rel="noopener"
>National guidance</a
>
encouraging AI literacy, transparency, and equitable access
</li>
<li>
<a
href="https://www.unesco.org/en/artificial-intelligence/recommendation-ethics"
target="_blank"
rel="noopener"
>UNESCO's Recommendation on the Ethics of AI</a
>, which emphasises human oversight, inclusion, and
accountability
</li>
<li>
The evolving
<a
href="https://artificialintelligenceact.eu/"
target="_blank"
rel="noopener"
>EU AI Act</a
>, which highlights education as a high-impact context requiring
transparency and risk mitigation
</li>
</ul>
</div>
<p>
These developments reinforce the central argument of this framework:
assessment must be redesigned structurally, rather than focusing on
detection.
</p>
</section>
<!-- Objectives -->
<section id="objectives">
<h2>Objectives</h2>
<p>
The goal of assessment redesign is to develop robust, fair, valid,
and educationally meaningful approaches that ensure students can
demonstrate genuine learning, understanding, and capability.
</p>
<ul>
<li>
Rather than focusing solely on preventing misuse of AI tools,
assessment should be designed to make learning visible
</li>
<li>
Incorporating a diverse range of assessment types, balancing
formative and summative approaches
</li>
<li>
Greater emphasis on process, reasoning, and development over time
</li>
<li>
Redesigning assessment presents challenges, including time
constraints, large class sizes, and evolving institutional
expectations
</li>
<li>
Some assessments may appropriately integrate AI while others may
require independent demonstration
</li>
<li>
The central guiding principle remains the alignment of assessment
with programme and module learning outcomes
</li>
</ul>
</section>
<!-- Scope -->
<section id="scope">
<h2>Scope</h2>
<p>
This framework supports educators and programme teams in rethinking
assessment design in the context of GenAI.
</p>
<p>The framework supports educators to:</p>
<ul>
<li>
Consider the purpose of each assessment and determine whether
GenAI use supports or undermines the intended learning outcomes
</li>
<li>
Identify assessment types that may be particularly vulnerable to
inappropriate AI use and prioritise these for structural redesign
</li>
<li>
Explore assessment approaches in collaboration with
discipline-area colleagues
</li>
<li>
Consider where and how GenAI can be meaningfully integrated into
assessment
</li>
<li>
Ensure coherence across modules and stages, contributing to a
balanced programme-level assessment strategy
</li>
</ul>
<div class="callout callout-warning">
<p>
This framework does not prescribe a single solution, but offers
principles and strategies that can be adapted to disciplinary
contexts, institutional policies, and evolving technological and
regulatory environments.
</p>
</div>
</section>
<!-- Reconsidering the Purpose of Assessment -->
<section id="purpose">
<h2>Reconsidering the Purpose of Assessment</h2>
<p>
In an educational landscape where AI has become so embedded,
reconsidering the purpose of assessment becomes imperative to foster
a more meaningful and authentic learning experience.
</p>
<ul>
<li>
Focus should shift towards assessing higher-order thinking skills,
such as critical analysis, creativity, and problem-solving
</li>
<li>
Assessments can better reflect real-world applications and prepare
students for the modern workforce
</li>
<li>
Students are evaluated not just on what they know, but on how they
think and adapt
</li>
<li>
The redefined purpose should aim to cultivate lifelong learners
equipped with skills to navigate and innovate in an AI-driven
world
</li>
</ul>
<blockquote>
<p>
<a
href="https://drphilippahardman.substack.com/p/a-post-ai-learning-taxonomy"
target="_blank"
rel="noopener"
>Phillippa Hardman</a
>
has suggested alternatives to Bloom's Taxonomy that focus on
skills AI "enhances rather than replaces," encouraging educators
to prioritise competencies where human judgement, creativity, and
contextual reasoning remain essential.
</p>
<cite>Phillippa Hardman</cite>
</blockquote>
<figure style="margin: var(--space-xl) 0; text-align: center">
<img
src="images/hardman-taxonomy.png"
alt="A Post-AI Learning Taxonomy by Dr Philippa Hardman, showing 6 levels: 1. Analyse, 2. Understand, 3. Apply, 4. Create, 5. Collaborate, 6. Disrupt — focusing on skills AI enhances rather than replaces."
class="lightbox-img"
style="
max-width: 100%;
border-radius: var(--radius-md);
border: 1px solid var(--color-border);
"
/>
<figcaption
style="
margin-top: var(--space-sm);
font-size: 0.85rem;
color: var(--color-text-muted);
"
>
A Post-AI Learning Taxonomy — Dr Philippa Hardman (DOMS)
</figcaption>
</figure>
</section>
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2026 Assessment Redesign Framework | Dr Hazel Farrell |
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