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CodeKit. Wolsingham School · an AI programming tutor for a one-teacher computing department

A student stuck on a Python exercise gets coached through it rather than handed the answer. The tutor works from the lessons the school’s own teachers write, so the help matches what the class was taught. The school used it in class with Year 10 and below.

Pro bono Coaches through the problem Basis of a won DfE bid

The CodeKit AI tutor coaching a student through a Python exercise, working from the school's own lesson library

An AI tutor for a school with one computing teacher.

CodeKit began as pro bono work for Wolsingham School in County Durham, where OpenKit has held enterprise adviser roles for years. The school has one IT teacher and limited access to computing equipment, which makes offering computer science at GCSE something they were trying to build toward rather than something they could simply run. The gap is resourcing.

So we built an AI tutor for learning to code: Python exercises with a tutor sitting alongside them that reviews what a student has written and tells them how to improve it. The design rule was that it coaches rather than answers, because a tool that writes the solution teaches a student to ask it for solutions. It was aimed at Year 10 and below, and it was deployed and used in the school.

  • 01

    An AI tutor that reviews a student’s Python and comes back with feedback and a next step to try.

  • 02

    Python running in the browser, so a lesson does not begin with thirty environment problems.

  • 03

    A relationship that goes past the software: lessons in the school, career days, and years on the enterprise adviser side.

Where the teaching time actually went.

What stops a computing lesson working is usually practical: a machine that will not run the interpreter, or a typo the student cannot see. A full department absorbs those problems between its staff, and with one teacher they become the whole lesson.

CodeKit was built against that constraint. It runs in the browser, so nothing needs installing on a school machine, and it gives every student something patient to ask when they get stuck. The curriculum stays the school’s, and the teacher gets a view of where the class is struggling so their attention lands where it counts.

Inside CodeKit.

Python that runs in a school browser

The student opens a tab and writes code, with the output next to the editor. There is nothing to install and no version to match, so a lesson can begin on the first exercise rather than with a class waiting for thirty machines to reach the same state.

In-browser Python interface with a code editor on one side and live output on the other

Exercises the school authors

Lessons and exercises are written by the teaching side and organised by topic and difficulty, and the tutor works from that same library. Help that contradicts the lesson is worse than no help, so the tutor never gets to invent its own curriculum.

Lesson library with units and exercises organised by topic and difficulty

Where the class is stuck

Per-student progress and topic-level gaps across the group, so a teacher covering everything on their own can see where to spend the attention they have rather than guessing at it between questions.

Mission log showing per-student progress and topic mastery across the class

Working with the school beyond the software.

  • 01

    Lessons delivered in person at the school, taught by the people who built the tutor.

  • 02

    Career days, so students hear what the work looks like from people doing it.

  • 03

    Enterprise Adviser roles held at the school through the regional partnership, over several years.

What CodeKit led to.

When the Department for Education opened a competition for AI tools in education, the bid did not start from a standing position. We already had a subject-specialised assistant that reviewed student work and explained itself in language a fourteen-year-old could use, a school that knew us, and a working answer to the question every education buyer asks first, which is whether the thing does the child’s homework for them. That experience and that codebase became the basis of the application, and we won the first phase.

The build

  • AI tutor agent grounded on the curriculum
  • In-browser Python sandbox
  • Lesson and exercise authoring tool
  • Mission-log progress tracking

OpenKit certifications

  • ISO 27001
  • ISO 9001, UKAS-accredited
  • Cyber Essentials

Controls on this project

  • Operates to UK GDPR
  • UK data residency

More of the work.

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