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<!doctype html>
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<meta name="author" content="Dr Hazel Farrell" />
<title>Core Principles | 2026 Assessment Redesign Framework</title>
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<h1>Core Principles of Assessment Redesign</h1>
<p>
Five guiding principles that safeguard academic standards while
supporting meaningful learning.
</p>
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</section>
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<main class="page-wrapper">
<div class="page-content">
<!-- Core Principles -->
<section id="core-principles">
<h2 class="mt-0">Core Principles</h2>
<p class="section-intro">
Assessment redesign should be guided by a clear set of educational
principles that safeguard academic standards while supporting
meaningful learning. Assessment should prioritise:
</p>
<!-- Principle 1: Validity -->
<div class="principle-card" id="validity">
<h3><span class="principle-number">1</span> Validity</h3>
<p>
Ensuring that assessment tasks genuinely measure the knowledge,
skills, and competencies they are intended to assess, even in
contexts where AI tools are widely available.
</p>
</div>
<!-- Principle 2: Fairness and Equity -->
<div class="principle-card" id="fairness">
<h3><span class="principle-number">2</span> Fairness and Equity</h3>
<p>
Recognising differences in access to technology, levels of AI
literacy, language background, and learning needs, and designing
assessment that does not disadvantage particular groups of
students.
</p>
</div>
<!-- Principle 3: Transparency -->
<div class="principle-card" id="transparency">
<h3><span class="principle-number">3</span> Transparency</h3>
<p>
Clearly communicating expectations around the purpose of
assessment, criteria for success, and the extent to which AI use
is permitted or restricted.
</p>
</div>
<!-- Principle 4: Accessibility and Inclusion -->
<div class="principle-card" id="accessibility">
<h3>
<span class="principle-number">4</span> Accessibility and
Inclusion
</h3>
<p>
Aligning assessment design with Universal Design for Learning
(UDL) principles and offering diverse ways for students to
demonstrate their learning.
</p>
</div>
<!-- Principle 5: Alignment with Learning Outcomes -->
<div class="principle-card" id="alignment">
<h3>
<span class="principle-number">5</span> Alignment with Learning
Outcomes
</h3>
<p>
Ensuring that decisions about assessment format, level of
supervision, and AI use are driven by what students are expected
to know, understand, and be able to do.
</p>
</div>
</section>
<!-- In Practice -->
<section id="in-practice">
<h2>In Practice</h2>
<p>In practice, this means placing greater emphasis on:</p>
<ul>
<li>
Higher-order thinking skills, including analysis, evaluation,
synthesis, and creation
</li>
<li>
Authentic application of knowledge in realistic or
discipline-relevant contexts
</li>
<li>
Demonstration of reasoning processes, not just final products
</li>
</ul>
<p>
Educators should critically consider whether the use of GenAI in a
given assessment supports or undermines the intended learning
outcomes. Where AI use is appropriate, expectations should be
explicit and supported through the development of student AI
literacy. Where independent performance is required, this should be
clearly justified and communicated.
</p>
<div class="callout callout-success">
<p>
Together, these principles ensure that assessment redesign remains
pedagogically grounded, ethically informed, and responsive to the
realities of learning in a world where AI continues to become
increasingly prevalent.
</p>
</div>
</section>
<!-- AI Literacy -->
<section id="ai-literacy">
<h2>AI Literacy</h2>
<p>
Assessment redesign and AI literacy are intrinsically linked. As
GenAI becomes embedded in learning, work, and everyday life,
students need more than technical familiarity with tools — they need
the capacity to engage with AI critically, ethically, and
effectively.
</p>
<p>AI literacy includes the ability to:</p>
<ul>
<li>
Critically evaluate AI outputs, recognising inaccuracies, bias,
hallucinations, and limitations
</li>
<li>
Understand how and when AI can be appropriately used, and when
independent thinking or professional judgement is required
</li>
<li>
Use AI ethically and transparently, including disclosure of use
and respect for academic integrity and data privacy
</li>
<li>
Integrate AI as a support for thinking, problem-solving, and
creativity — not as a substitute for learning
</li>
<li>Recognise the role of the human in the learning process</li>
<li>
Understand how AI may influence thinking, behaviour, and
decision-making
</li>
</ul>
<p>At programme level, teams should determine:</p>
<ul>
<li>Where AI literacy is an explicit learning outcome</li>
<li>
Where AI literacy contributes to broader graduate attributes
</li>
<li>
Where foundational disciplinary knowledge must be demonstrated
independently of AI support
</li>
</ul>
<p>Assessment design should therefore include a deliberate mix of:</p>
<div class="track-comparison">
<div class="track-box track1">
<h3>AI-Restricted Tasks</h3>
<p>
Where independent demonstration of knowledge, understanding, or
professional capability is required
</p>
</div>
<div class="track-box track2">
<h3>AI-Supported Tasks</h3>
<p>
Where students are expected to engage with AI tools critically
and responsibly as part of the learning process
</p>
</div>
</div>
<div class="callout callout-important">
<p>
Assessment redesign is therefore not only about preventing misuse,
but about educating students to become informed, critical, and
responsible participants in this rapidly changing technological
world.
</p>
</div>
</section>
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