The AI in Marking and Feedback Pilot launched earlier this year (the announcement blog for which is linked here), is now well underway across a range of institutions. Designed to explore how AI tools can reduce workload around marking and feedback processes, the pilot includes three platforms—Graide, Keath, and TeacherMatic— being piloted by 14 colleges and 21 universities, and it is already surfacing valuable lessons around AI’s impacts in this area.
Emerging Insights
From the outset, pilot participants have emphasised the need for educators to retain responsibility for any marking and feedback issued to students. This principle has underpinned discussions across all sessions, reinforcing the importance of human oversight in AI-supported assessment.
Student reactions to AI tools have been mixed, with some raising concerns around trust, ethics, and the role of automation in education and wider society. However, positive responses have also been reported, particularly where students have been reassured that human oversight remains central to the marking process.
Workload remains a key consideration. While AI tools are being explored for their potential to reduce marking burdens, participants have noted the effort involved in setup, training, and familiarisation with new platforms. This insight has been helpful in informing Jisc’s approaches to planning and communicating its AI pilots.
Cohort and platform-specific sessions have provided valuable forums for sharing ideas and resources. Institutions have exchanged ethics approval templates, student communication approaches, and strategies for embedding tools into workflows—highlighting the collaborative spirit of the pilot.
Diverging Approaches
Institutions are taking varied approaches to piloting, shaped by their own contexts and governance structures. Some are embedding AI tools into live assessment workflows, while others are opting for experimental conditions, e.g. using historical student submissions. Key considerations when choosing from these approaches include workload, governance/due diligence, and validity of findings.
As data controllers, institutions are also determining their own legal basis for data processing. Some are proceeding under legitimate interest, while others are using consent-based models. This autonomy reflects the diversity of institutional contexts and the importance of aligning pilot practices with internal policies.
Looking Ahead
As the pilot progresses, institutions will continue to refine their approaches and evaluate the impact of AI tools on marking and feedback. Fortnightly check-ins and collaborative sessions will continue to help surface emerging issues and inform future development. Stay tuned for further updates as we proceed with the pilot.
Participating Institutions
The following institutions are participating in the pilot, and are each piloting one of Graide, Keath, and TeacherMatic.
ACL Essex; Anglia Ruskin University; Aston University; Avant Skills Academy; Ayrshire College; Birkbeck College, University of London; Brockenhurst College; Brunel University; Cardiff and Vale College; Chesterfield College; City St George’s, University of London; Coastland College; Colchester Institute; Coventry University; De Montford University; Edge Hill University; Gloucestershire College; Hull College; London South Bank University; Loughborough University; Manchester Metropolitan University; Myerscough College; Northampton College; NPTC; Oldham Sixth Form College College; Queen Mary University London; Swansea University; The Manchester College; University College Birmingham; University of Chichester; University of Exeter; University of Greenwich; University of Huddersfield; University of London; University of Southampton; University of Westminster; Vision West Nottinghamshire College.
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One reply on “AI in Marking and Feedback Pilot: Early-Stage Reflections ”
This is an area of great interest to the FE sector , this article does not really say very much about impact or learning.