2026 Assessment Redesign Framework

Resources & Tips

Practical tips for redesigning assessment, the postplagiarism concept, and a comprehensive reading list.

Tips for Redesigning Your Assessment

The following practical tips provide a starting point for educators looking to redesign their assessments in response to GenAI.

1

Start with the learning outcomes.

Clearly define what you are assessing — application of knowledge, critical thinking, problem solving, analytical or evaluative skills — and determine whether the use of GenAI would support or undermine those outcomes.

2

Be explicit about AI permissions.

Clearly communicate whether learners are permitted to use GenAI and, if so, to what extent and for which purposes. Where expectations cannot realistically be monitored or evidenced, consider redesigning the task so that learning is made visible rather than relying on unenforceable restrictions.

3

Balance higher-order thinking with foundational knowledge.

Design assessments that prioritise analysis, evaluation, and creation, while also ensuring that students demonstrate the essential disciplinary knowledge needed to underpin those higher-order skills — sometimes independently of AI support.

4

Use multi-faceted and individualised assessment formats.

Combine artefact-based tasks with lower-risk approaches such as oral presentations, peer evaluation, drafts or sketches, reflective journals, or short viva-style discussions to verify understanding and personalise learning.

5

Assess the learning process, not only the final product.

Build in touchpoints or staged components where each part of the assessment develops from the previous one. This might include proposals, annotated drafts, progress reflections, or interactive oral elements. These approaches make student thinking visible and strengthen assessment validity.

6

Incorporate structured collaboration.

Include opportunities for collaborative problem-solving, peer feedback, or group projects, with mechanisms to recognise individual contributions. Collaboration reflects authentic professional practice and makes learning less easily outsourced.

7

Engage students in dialogue about AI and assessment.

Facilitate open conversations about GenAI use, academic integrity, and responsible practice. Where appropriate, involve learners in aspects of assessment design — such as discussing criteria or co-creating elements of marking rubrics — in line with inclusive and UDL-informed approaches.

Postplagiarism

Historical definitions of plagiarism will not be rewritten because of artificial intelligence; they will be transcended

— Sarah Eaton

As AI technology continues to develop at a rapid pace, it is important to consider what the future may look like for educators. While plagiarism traditionally refers to the copying or paraphrasing someone else's work without proper attribution, 'postplagiarism' in the context of GenAI is a term that encapsulates the new challenges to academic integrity in higher education.

Key Aspects of Postplagiarism

AI-Generated Content

Students and researchers might use AI to generate essays, reports, or other academic materials. The question arises as to whether this content should be considered original or if it constitutes a form of plagiarism, especially if the use of AI is not disclosed.

Authorship and Ownership

Traditional academic work is credited to individuals based on their intellectual contribution. However, when AI plays a significant role in content creation, the lines of authorship and ownership become blurred.

Attribution

There is ongoing debate about how to attribute AI-generated content. Should students cite the AI as a source, similar to a book or article? Or is the use of AI tools similar to using a calculator or spellchecker?

Academic Integrity Policies

Updating these policies has become necessary to reflect the challenges presented by AI, to achieve a balance in encouraging the responsible use of technology with maintaining the integrity of academic work.

Ethical Considerations

The ease of generating content with AI is tempting for students and researchers to submit work they didn't meaningfully engage with or understand.

While there are significant challenges, there are also opportunities to develop innovative approaches and embrace new mindsets.

6 Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence by Sarah Elaine Eaton (2023). The six tenets are: Hybrid Human-AI Writing Will Become Normal, Human Creativity is Enhanced, Language Barriers Disappear, Humans can Relinquish Control but not Responsibility, Attribution Remains Important, and Historical Definitions of Plagiarism No Longer Apply.
6 Tenets of Postplagiarism — Sarah Elaine Eaton (February 2023)

Conclusion

GenAI does not diminish the value of assessment; it sharpens our understanding of why assessment matters. In an AI-enhanced world, assessment is no longer simply a mechanism for measuring knowledge, but a means of making learning visible and revealing how students think, apply, question, create, and grow.

Redesigning assessment in response to GenAI requires informed, reflective, and collaborative engagement from educators. It also requires institutional support, space for professional development, and recognition of the emotional and cognitive load that rapid technological change can bring. Equity, access, and ethical considerations must remain central.

This framework affirms that sustainable academic integrity is achieved not through surveillance or detection alone, but through thoughtful, structurally sound assessment design, the development of AI literacy, and a culture that values learning processes as much as outcomes.

Initially developed as part of the N-TUTORR national project GenAI:N3, this framework is a living resource that continues to evolve. The approaches outlined here can be adapted, combined, and expanded in response to disciplinary needs, emerging research, and evolving technologies.

Many thanks to reviewers Dr Jim O'Mahony, MTU and Damien Raftery, SETU.

Reading List

Downloads

2026_Assessment_Redesign_Framework.pdf PDF — 1.2 MB — February 2026