AI in Education [MSc] postgraduate personal statement example

Personal statement example

Last term a Year 10 pupil handed me a page of simultaneous equations that was entirely correct, and when I asked him to talk me through the second one he couldn't. He had typed each question into a chatbot and copied the working. He wasn't being sly about it; he told me cheerfully that it was quicker. What stayed with me was that the tool had done exactly what he asked, and nothing he needed. I want to study AI in education because I think the interesting questions sit in that gap between what a system produces and what a learner takes away from it.

I studied Mathematics at university, and for my final-year project I built a small web-based quiz app for first-year calculus revision. It used a version of the Leitner system, where questions answered correctly move to boxes that are reviewed less often and missed questions return sooner. Twenty-three students used it over five weeks before their exams. I logged which questions were attempted, when, and how often each was answered correctly, then interviewed six of the students. The numbers were too small to say anything firm about learning gains, and my write-up said so. The interviews were more revealing. Several students liked the app but admitted they skipped any question involving integration by parts because it felt slow, which meant the scheduling algorithm was quietly organising their revision around avoidance. I added an option to flag a question as 'too hard right now' so I could at least see this happening, and I recommended in my conclusion that any adaptive tool should make such choices visible to the learner rather than hiding them. Writing the app taught me practical Python and basic database work, but the project's real value for me was learning to treat usage data as evidence that needs interpreting, not as a verdict.

Since graduating I have worked as a cover supervisor in a comprehensive school. I am not a qualified teacher and I don't plan lessons, but I deliver set work across subjects to classes of up to thirty, often with little notice. This has given me a close view of how pupils actually use technology when no specialist is in the room. Some use translation tools sensibly to check vocabulary; others paste whole paragraphs and submit the result. Teachers I work with hold very different views, from enthusiastic to deeply wary, and most are simply short of time to work out a position. I have started keeping notes on the tasks where AI tools seem to help pupils think and those where they replace the thinking, and I would like the methods to study this properly rather than anecdotally.

Outside school I volunteer two evenings a month at a community bike repair co-op. People bring in bikes and we help them fix the problem themselves rather than doing it for them. It is slower, and some visitors would plainly prefer we just sorted it, but most leave able to replace a brake cable. I have found it a useful reminder that good help often means holding back.

On a postgraduate course I want to develop a firmer grounding in learning theory to sit alongside my technical background, and to understand the ethical issues around pupil data, which my project only touched. I am particularly interested in how tutoring systems might prompt explanation rather than supply answers, and in how teachers can judge such tools without needing to be programmers. I bring reliable coding skills, a habit of checking claims against what users actually do, and daily experience of classrooms as they are. I would like to leave the course able to contribute to designing and evaluating tools that the pupil with the perfect equations would have learned something from.