Feedback for Thirty: The Personalisation Problem

Every teacher knows that feedback is where a lot of the real learning happens. Not the mark — the mark is just a number — but the specific, personal guidance that tells a student exactly what they did well, where they went wrong, and what to do differently next time. Good feedback is tailored: it meets a particular learner where they are. And that, precisely, is what makes it nearly impossible to deliver at the scale a real class demands.

To give one student truly personalised feedback, a teacher has to study that student’s work, identify their specific strengths and weaknesses, and frame guidance in a way that fits how that individual learns. Done properly, for one child, it is a genuinely valuable act. Done for thirty children, after every significant piece of work, across every class she teaches, it becomes a quantity of careful, individual attention that there are simply not enough hours to give.

So a very human compromise sets in, and most teachers will recognise it. The richest, most personal feedback goes to the students who are visibly struggling, because that is where the need feels most urgent. The average performers and the strong ones receive something briefer and more generic — “good work,” a tick, a short comment that could apply to half the class. It isn’t neglect; it’s triage. But it means the students in the middle and at the top, the ones who could be pushed furthest by precise feedback, often get the least of it. The edge they are looking for never quite arrives.

The instinct that this is wrong is correct: feedback genuinely needs to be personalised, for every student, not just the ones in difficulty. The reason it isn’t, almost everywhere, is not a failure of care. It is that the process of producing individual feedback for a whole class, by hand, has never been sustainable. If personalisation is going to reach everyone, the process itself has to be streamlined.

This is one of the most striking things a teacher-focused platform can now do. On Tutopiya, when a student completes a quiz or assessment, the platform doesn’t just mark it — it generates detailed, examiner-style feedback on each answer, responding to what that particular student actually wrote, against the mark scheme’s expectations. Every student receives specific guidance on their own work, immediately, regardless of whether they sit at the top, the middle or the bottom of the class.

That doesn’t push the teacher out of the feedback loop — it lets her into it on far better terms. Instead of being the sole, overstretched source of every comment, she reviews feedback that has already been drafted to fit each student, and adds her own expertise on top where it counts — a nuance the tool missed, a word of encouragement, a connection to something said in class. Her judgement is now layered onto every student’s feedback, not rationed out to a desperate few. The feedback stops being generic, because it is built around what each learner specifically needs.

There is an understandable instinct to feel that feedback should come from a human or it isn’t worth much. But the honest alternative was never warm, handwritten paragraphs for all thirty; it was a tick for most and a real comment for a few. A system that gives every student precise, individual feedback — and then invites the teacher to refine it — does not diminish the teacher’s role. It finally makes the ideal she always believed in achievable for the whole class.

Every student deserves to be seen in their own work, not averaged into the group. The personalisation problem was never about whether teachers wanted to give that; it was about whether the day was long enough. Now, for the first time, it can be.