CCCU is introducing the Artificial Intelligence Assessment Scale (AIAS) to help module leads assess the appropriate level of students’ engagement with Generative Artificial Intelligence (GenAI) in their module assessments.
This webpage is designed to support Module Leads, and those who work with them to manage courses, deliver teaching or mark assessed work, to consider the impact of GenAI on student learning and assessment and make a reasoned judgement as to what level of engagement with GenAI is appropriate for each module.
It should be read alongside the GenAI guidance for Staff and the guidance for Students.
The appropriate level of GenAI engagement for each module can be decided in collaboration with colleagues with teaching and marking responsibility for the module and the Course Director, but it is the module leader’s responsibility to make the decision.
The AIAS scale has been integrated into the Module Handbook Template to give students clear guidance on whether, and to what extent, they may use GenAI in the preparation and production of work for assessment.
However, the AIAS is not an assessment security tool. Levels 2-5 of the AIAS allow varying use of GenAI, but it remains impossible to draw a hard line between levels, students or their work and know without doubt when one level crosses into another. We have not got, and have never had, a clear-cut way to know whether students are following our guidance and policies. Therefore, robust assessment design, transparent conversations with students, clear and directed teaching on the positive use and limitations of GenAI, combined with consistent marking practices, continue to be essential to maintaining academic integrity for our assessments.
When deciding on which level of the AIAS to rate your assessment you need to consider the following:
1. The module learning outcomes
Consider, for example:
a. Will I substantially advantage or disadvantage any particular students’ achievement of the learning outcomes by dis/allowing the use of GenAI in my module?
b. Will allowing GenAI use in the module get in the way of students achieving the learning outcomes?
c. Do the module learning outcomes specify that students must achieve independent written communication skills that prohibit, or substantially inhibit, the use of technology? I.e., to what extent is it important to the module learning outcomes that students’ written expression is entirely their own? This would be extremely important in a linguistics essay, but perhaps less so in a chemistry lab report.
d. If the learning outcomes specify students must demonstrate criticality, can this be achieved through critical engagement with GenAI outputs, or must it be achieved solely through traditional synthesis of academic sources?
2. The type of assessment
Consider, for example:
a. Is your assessment an in-person exam, skill demonstration or performance? Is your assessment a take-home exam, where critical use of sources is expected? How would each scenario be impacted by the use of GenAI?
b. To what extent would it benefit students to incorporate GenAI into their assessment preparation or production? How might it disadvantage them?
c. What are the advantages to student accessibility and inclusion if GenAI is designed into or out of the module assessment?
d. What are the risks to learning and assessment security? How can these be planned for and mitigated?
3. The level of study
Consider, for example:
a. What is your students’ level of critical thinking and information literacy skills to approach the use of GenAI ethically?
b. Have your students developed an understanding of data privacy that will allow them to engage with GenAI safely?
c. Have your students understood the risks GenAI poses due to bias in training data? Do they have the skills to triangulate information with trusted sources to verify its accuracy?
4. Marking criteria
Consider, for example:
a. Do my marking criteria allow me to give credit to the skills that support effective use of GenAI, such as critical analysis, evaluation or reflection? Or do they give credit for skills that are easy to replicate with GenAI, such as repetition of knowledge, correct grammar or structure?
b. Would it be appropriate to reward process as well as product via marking criteria?
5. The type and cost of GenAI platforms available to students to achieve the module’s outcomes.
Consider, for example:
a. Does your assessment require specific GenAI-enabled platforms to achieve the Module Learning Outcomes successfully? If so, how will you ensure equitable access to these for all students?
b. How will you identify and address digital poverty among your students, to ensure an equitable learning and assessment experience?
6. Students’ existing GenAI literacy and how you will scaffold their knowledge & skills
Consider, for example:
a. Do your students already use GenAI platforms in their study and home lives? If so, how?
b. What is their level of knowledge and comfort with using GenAI for University study? How will you support them to improve their knowledge and skills?
c. How well do your students understand what constitutes quality information, and can they critique GenAI outputs?
7. Students’ existing understanding of Academic Integrity and how you will teach them the knowledge and skills necessary to maintain integrity in a complex digital information environment.
Consider, for example:
a. Do your students know what academic integrity means? Do they understand the principles of attribution (citation and referencing)?
b. Do your students have the basic tools to determine if information is trustworthy or not?
c. Can students explain, in a level appropriate way, the nature of knowledge (epistemology) and engage with the process of knowledge production (either by humans or machines) in a critical manner?
8. The necessity of using GenAI to meet disciplinary, sector, employability and learning needs for your module.
Consider, for example:
a. Do your students need to develop technical skills using GenAI for their future employment?
b. Do they need to develop their confidence using GenAI interfaces to be competitive in their chosen sector?
c. Would your students be at a substantial disadvantage if they did not have a critical, functional understanding of the role GenAI plays in all our digital lives?
Once you have decided on the appropriate level of the AIAS for your module, you will need to communicate this clearly and consistently to students studying the module. They may be studying two or more modules concurrently which may have been assessed at different levels on the AIAS.
Under CCCU’s Academic Integrity Policy unpermitted and unacknowledged inclusion of outputs from GenAI tools is considered academic misconduct. See the Academic Integrity and Misconduct webpages, including the Academic Integrity Policy, for more information.
All assessments now require a declaration regarding GenAI. The pro forma statements for this declaration are available in the Module Handbook. Guidance on how to reference GenAI is available in Cite Them Right 13th Edn, or later. Students can use the textbook or visit the Cite Them Right website – both are accessible via LibrarySearch (for the web version, login using your CCCU email).
Alongside the AIAS we should consider the following:
1. How will I communicate my module’s approach to GenAI for learning and assessment to students?
2. How will I communicate the reasoning for the AIAS level I have selected clearly and effectively?
3. How will I teach students the knowledge and skills to use GenAI ethically and effectively for my module, if they chose to?
4. How will I effectively teach students about academic integrity, declaring use of GenAI and appropriate referencing practices?
5. Have I checked and updated my marking criteria to reflect the level of GenAI use I have selected for the module?
6. What further support do I need to successfully integrate the AIAS into my module?
7. What further development might my students need to successfully complete my module?
To support you and your students to use GenAI mindfully and effectively the University has Staff Guidance and Student Guidance. Guidance for research students will be available soon.
If you, or your team, would benefit from further support and development in any area of assessment practice, including the use of the AIAS and GenAI, please contact the Education and Student Success team (formerly Learning and Teaching Enhancement) at lte-admin@canterbury.ac.uk* or contact emma.scanlan@canterbury.ac.uk directly.
If you think your students would benefit from further support and development interpreting, implementing and referencing the AIAS and GenAI in their work, please contact your Learning Developers and Academic Librarians at learner@canterbury.ac.uk.
*email subject to change, in line with departmental name change
Recommended Reading
Furze, L. (2025) How I use the AI Assessment Scale. Available at: https://leonfurze.com/2025/06/11/how-i-use-the-ai-assessment-scale-part-1/. Accessed 17 June 25
Further Resources
CCCU (2022) Assessment Criteria. Accessed 17 June 25
CCCU (2023) Generative Artificial Intelligence (AI): Guidance for Staff. Accessed: 11 June 25
CCCU. (2024) Welcome to your generative AI Guidance. Accessed: 11 June 25
Furze, L., Perkins, M., Roe, J. and MacVaugh, J. (2024) “The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment”, Australasian Journal of Educational Technology. 40(4): 38–55. DOI: 10.14742/ajet.9434. Accessed: 11 June 25
Learning Skills Team. (2025) Learning Skills Hub. CCCU. Accessed: 11 June 25
Perkins, M., Furze, L., Roe, J. and MacVaugh, J. 2025. AI Assessment Scale (AIAS). Available at: https://aiassessmentscale.com/ Accessed: 11 June 25
Perkins, M., Furze, L., Roe, J. and MacVaugh, J. 2025. Custom AIAS GPT. Accessed: 11 June 25
Roe, J., Perkins, M. and Furze, L., (2025) “From Assessment to Practice: Implementing the AIAS Framework in EFL Teaching and Learning”. arXiv preprint arXiv:2501.00964.