Artificial intelligence (AI) has been sold to schools as a marking assistant for years. This year AI marking finally has evidence behind it. Three new studies and a case study from an English classroom show AI can judge pupils’ writing almost as consistently as teachers and return feedback in seconds. What it cannot replace is a pupil’s sense that someone who knows them has read their work.
The short version: AI feedback on writing now performs close to teacher feedback in trials, and AI judging can cut marking time sharply. The gains come when teachers spend the saved time reading and checking the work. For anything that counts towards a qualification, the exams regulator says AI cannot be the sole marker.
What the research on AI marking found
Feedback on writing: close to the teacher, and faster
The most useful study for secondary teachers comes from researchers at the Leibniz Institute for Science and Mathematics Education in Kiel. They ran an experiment with 391 secondary pupils learning English as a foreign language. Pupils received written feedback from their teacher or from a large language model (LLM), either straight away or after a delay.
The results, presented at the Learning at Scale conference in June 2026, showed small differences in favour of teacher feedback, but they were neither statistically nor practically significant. Pupils rated the immediate AI feedback as more useful and more motivating. In the authors’ view the value of AI feedback lies in “redistributing instructional effort”, and they argue for hybrid systems rather than replacement. The full paper is open access.
Judging writing: high agreement with human judges
A second study, posted as a preprint on 19 October 2026, looked at younger writers. Researchers at the University of Houston and the University of British Columbia collected writing from 237 pupils in Grades 3 to 5 across five American elementary schools, 57% of them emerging bilingual. They used comparative judgement, where a judge sees two scripts side by side and picks the better one, and compared human judges with ChatGPT.
ChatGPT agreed with human judges on 76% to 81% of identical pairs, and its overall scores correlated with the human scores at 0.91 to 0.92. Accuracy held up for emerging bilingual pupils. Switching the model’s reasoning mode on or off made no practical difference. It is a preprint, so treat it as promising rather than settled.
Where AI feedback is weakest
A third study is a useful corrective. A team at Vrije Universiteit Brussel evaluated feedback from a recent OpenAI model on handwritten university mathematics in a paper released on 20 October 2026. Reviewers rated 157 feedback messages. The suggested practice exercises were strong 95.5% of the time. Diagnostic specificity, meaning whether the feedback pinned down what had actually gone wrong, was strong only 41.1% of the time, and clarity and tone only 33.4%. Mathematical accuracy was strong in 62.1% of messages and deficient in 8.3%.
Two details matter. The feedback given on the lowest-scoring answers was the least actionable, so the students who most needed precise help got the vaguest. And across the two cohorts studied there were no statistically significant differences in later exam performance after adjustment. This was undergraduate maths, but the pattern is worth knowing.
What happened when one English department tried it
Daisy Christodoulou of No More Marking has published a case study from King Edward VI School in Stratford-upon-Avon. English teacher Amaryllis Barton set 26 Year 9 pupils a magazine article task and judged the scripts using comparative judgement with AI doing most of the judging. Each script received ten judgements. The teacher made 10% of them, 26 judgements in all, so she still saw every script twice.
Her decisions took an average of 41.5 seconds each, including recording a short spoken comment, and the whole job took under 20 minutes. Christodoulou estimates the same task would have taken at least four hours to mark traditionally. The judging reliability was 0.88, and the teacher agreed with the AI on 62% of the pairs she checked. AI turned her spoken comments into written feedback.
The pupils’ reaction is the part I keep coming back to. They said that knowing a human had read their work mattered more than they had expected. They accepted AI comments only when their teacher agreed with them, and they disliked a vague AI note about capital letters. What they valued was feedback that helped them improve the piece, rather than feedback that simply graded it.
The time AI marking saves is only worth having if a teacher spends some of it reading the work.
What the exams regulator says
In England the Office of Qualifications and Examinations Regulation (Ofqual) has been clear. Its approach to regulating AI, updated in July 2026, says AI may not be the sole marker of any assessment that forms part of a regulated qualification. It sees potential for lower stakes classroom marking, and Ofqual has supplied a bank of expertly marked scripts to a Department for Education (DfE) pilot aimed at improving AI marking and feedback tools.
The more interesting document is Ofqual’s 104-page working paper, Principles of AI use in marking, published in January. It warns that “agreement with human marks alone is insufficient for assuring validity”. It also notes that people may be worse at checking than at the original task, especially when most of what they check is correct. If a teacher waves through AI decisions, the AI is still the one deciding. Ofqual’s accompanying blog put it plainly: AI is promising for quality assurance and marker training, but “for the moment it’s nowhere near ready to take over high stakes marking.”
The same applies in classrooms. A teacher skimming a hundred AI comments at 10pm is unlikely to catch the one that is subtly wrong.
How to use AI marking well in your classroom
The evidence suggests AI is good at speed and consistency, while teachers are needed for judgement and for the pupils who are struggling most. Some practical steps follow.
- Read every piece yourself at least once. The Stratford pupils noticed when a human had read their work.
- Check the AI’s feedback on your lowest attaining pupils first. That is where the Brussels study found it least precise.
- Use the speed for redrafting. Immediate feedback was rated more motivating in the Kiel study, so build in a lesson where pupils act on it the same day.
- Look closely at disagreements. Where you and the AI differ, you learn something about the work or the tool.
- Keep AI out of anything that counts towards a qualification unless your exam board allows it, and follow the latest Joint Council for Qualifications guidance on coursework.
- Tell pupils and parents what you are doing. No More Marking, for example, asks schools to sign a General Data Protection Regulation (GDPR) agreement and recommends notifying parents, and offers a draft letter.
Imagine a Year 8 class writing an opening for a dystopian story. On Monday the AI judges the scripts and drafts comments. That evening you read each piece once, record a 30-second spoken comment for each, and set aside the five where your judgement differs from the AI’s. On Tuesday pupils redraft with your comment in front of them, and you spend the lesson with the five.
Be honest about the limits too. None of these studies shows that AI feedback makes pupils learn more than teacher feedback. What they show is that pupils can get feedback of similar quality faster, which frees teacher time. If you have been following our coverage of AI and teacher workload, you will know saved minutes have a habit of disappearing.
As with AI retrieval practice, the pupil has to do the thinking. AI can tell a pupil what to fix. The pupil still has to fix it, and the teacher still has to notice whether they did.
Frequently asked questions
Can artificial intelligence (AI) mark pupils’ work accurately?
Increasingly, for writing. In a 2026 preprint, AI judging of primary pupils’ writing agreed with human judges on 76% to 81% of pairs, and a Kiel trial found AI feedback on secondary pupils’ writing close to teacher feedback. It is weaker at diagnosing exactly what went wrong, especially in low-scoring work, so teachers should check it.
Can AI mark General Certificate of Secondary Education (GCSE) or A level work?
Not as the sole marker. The Office of Qualifications and Examinations Regulation (Ofqual) says AI may not be the sole marker of any assessment that forms part of a regulated qualification, which includes GCSEs. It sees more promise in quality assurance, marker training and lower stakes classroom marking.
Does AI feedback help pupils learn more than teacher feedback?
No study so far shows that. The Kiel trial found no significant difference between teacher and AI feedback, and a Brussels study of university maths found no significant difference in later exam results. The main benefit is faster feedback and teacher time saved.
Should schools tell parents they use AI marking?
Yes. Pupils’ writing is being processed by an outside provider. No More Marking, for example, asks schools to sign a General Data Protection Regulation (GDPR) agreement and recommends notifying parents, with a draft letter provided.
Have you tried AI marking or AI feedback with a class yet, and did your pupils notice the difference? Tell us in the comments.
