Summary
This Guidance for AI- Assisted Marking and Feedback, approved by QuiLT on the 15th July 2026, sets out principles for AI-Assisted Marking and Feedback across Coventry University Group. In addition to the principles listed below the guidance sets out the context for its development and sets out boundaries for implementation. Illustrative scenarios are provided for how AI might be used for assisting marking and feedback within the scope of the principles.
Core Principles for AI‑Assisted Marking and Feedback at Coventry University Group
To support trust, fairness, and academic integrity, the following principles apply:
- Human‑Led Marking and Feedback
Reading, interpreting, and assessing student work must be conducted by academic staff, except where explicitly permitted under approved assessment designs (i.e. automatically marked assessments). - Transparency
Academic staff should explain their approach to AI‑assisted marking and feedback to students, including its purpose and limits. - Mandatory Human Oversight
AI feedback must always be checked for accuracy, relevance, bias, and tone. - Academic Judgement
Where AI has been used appropriately, academic judgement remains that of the marker and is subject to normal moderation and appeals processes. - Approved Technologies
Only Institutionally supported AI tools must be used in preference to public or unsupported systems. - Assessment Design Support
AI may inform the development of marking criteria and rubrics, but final approval rests with academic staff. - Detection Tools
AI tools should not be used to detect student use of AI, as such systems are unreliable and inconsistent with Coventry University Group guidance.
Guidance Detail
- Purpose
- How AI-Assisted feedback can support academic practice
- Staff and student trust in AI-Assisted Marking and feedback
- Operational Guidelines for Academic Staff
- Alignment with Coventry University Group Assessment Principles
- References
- Example Scenarios
