STEM excellence. GCSEs and A-levels. Real project-based work.
At Catalyst, students achieve some of the highest GCSE and A-level scores in the world — through 1-to-1 teaching with world-leading educators, deep STEM project work, and AI embedded in every lesson. The Catalyst AI Diploma runs alongside formal qualifications, ensuring students leave with strong credentials and a portfolio of real work they can defend in depth.
How the programme is structured.
Foundation
Deep STEM subject teaching across the curriculum, with daily 1-to-1 sessions with world-leading educators. AI literacy is taught explicitly from Year 9 — prompting, evaluation, bias, provenance. Students begin their first project cycles here, building the skills that will carry them through their GCSEs and beyond.
GCSE & Diploma Core
Students sit GCSEs — consistently achieving above 90% pass rates, with many scoring among the highest marks in the world. Alongside this, five extended Diploma projects run across two years, each supervised by a subject specialist and ending in a public defence. Both tracks reinforce each other.
A-Level & Senior STEM Phase
Students complete A-levels with results that regularly place them among the top performers globally. Simultaneously, they specialise in STEM research through extended projects with university and industry mentors — producing published papers, working systems, and patentable designs that open doors at the world's leading universities.
Broad subject teaching with project cycles built in.
In Years 7–9, students study the full curriculum. There are no exams, but there is rigour — daily reading, mathematics every day, hands-on science, languages, history and geography, art, music and physical education. AI tutors run alongside teachers to deliver instant feedback, retrieval practice and one-to-one support.
Each term ends with a short project cycle: a piece of work, a public presentation, and a defence. The skill we are building is the habit of finishing things, defending them, and learning from the questions.
The Catalyst AI Diploma — Phase 2
From age 14, the work gets serious. Students complete five extended projects over two years. Each project takes a full term, is supervised by a subject specialist, ends in a viva, and lives in a portfolio that follows the student to whatever comes next.
Why this exists
Working life is project-shaped, not exam-shaped. People are paid to scope problems, gather what they need, ship things that work, and explain every choice in them. The Diploma teaches that skill directly. By 16, our students have shipped five substantial pieces of work each — and can talk about every line, every decision, every dead end.
The five units
Build & Ship
Design, build and release a working AI-powered tool that solves a real problem for a real user. Assessed on code quality, user research and ethical review.
Investigate & Argue
A long-form research project on a contemporary issue. AI assistance is permitted and logged; the viva tests independent understanding.
Model & Simulate
Build a quantitative model of a system — economic, environmental, biological — and defend its assumptions, limits and failure modes.
Create & Critique
Produce a substantial creative work (writing, film, music, design) that uses AI tools deliberately, with a written critical commentary.
Capstone
A self-directed project of the student's design, supervised by a faculty mentor and an external partner. Public showcase at year-end.
How it's assessed
| Component | Weight | How it works |
|---|---|---|
| Portfolio of work | 50% | The five project artefacts, with provenance logs and reflective commentary. |
| Viva voce | 30% | One-to-one defence with internal and external assessors. Tests independent understanding. |
| Process journal | 10% | Weekly entries showing iteration, dead ends and what was learned. |
| Public showcase | 10% | Capstone presentation to faculty, families and an invited external panel. |
What students leave with at 16
A Catalyst student finishing Phase 2 at 16 holds: their GCSE results (consistently 90%+ pass rates, with world-leading scores), a Catalyst AI Diploma award (Distinction* to Pass), the full project portfolio, and — crucially — internationally recognised industry certifications including AWS Certified Engineer and Red Hat credentials. These are not school certificates. They are the real vendor-issued qualifications that technology employers use to hire working engineers. A Catalyst 16-year-old holds them.
Qualified engineers. At sixteen.
Alongside GCSEs and the Catalyst AI Diploma, every Phase 2 student earns globally recognised industry certifications. These are not school awards — they are the same credentials working engineers hold, issued by the vendors themselves, accepted by employers across every major sector worldwide.
The age our students hold AWS and Red Hat certifications. Most technology professionals never sit these exams. Our students complete them as part of their standard programme by the time they turn sixteen.
AWS Certified Engineer
The global benchmark for cloud infrastructure. Students design, deploy, secure and manage cloud systems to AWS professional standards — the same certification used to hire cloud engineers at banks, technology firms and government agencies worldwide.
Red Hat Certified Technician
Red Hat's industry-leading enterprise Linux and system administration certification. Recognised across defence, finance, healthcare and technology sectors globally. A credential that most IT professionals spend years working toward.
Further industry certifications
Depending on a student's specialism, additional certifications in cybersecurity, networking, data engineering and cloud platforms may also be completed. All are vendor-issued, globally portable, and employer-recognised.
What this means in practice
A Catalyst leaver at 16 walks into sixth form, college, or the job market holding credentials that adults in the technology industry spend years trying to earn. Universities notice. Employers notice. This is the Catalyst difference.
STEM specialism, university-grade output.
From 16, our students go deep. Each Senior Phase student takes a primary specialism, a secondary specialism, and a working language. They spend two years on extended research projects with university and industry mentors. The output is not a set of exam grades — it's a body of work credible enough to take a graduate seat at a research group, an apprenticeship offer at a tech firm, or a place at a university that admits on portfolio and interview.
Mathematics
Pure, applied and computational mathematics. Symbolic AI as a "second pair of eyes" on proofs; original problem-solving as the assessed output.
Physics & Engineering
From electromagnetism to robotics. Workshop access, in-house fabrication, partnerships with university engineering departments.
Chemistry
Molecular visualisation, reaction prediction and synthesis planning alongside traditional practical work.
Biology & Bioinformatics
Working with real genomic and ecological datasets using AI-assisted analysis. Lab work in partnership with university bio departments.
Computer Science & AI
Students build and deploy real production systems — LLM-based applications, ML pipelines, embedded systems. Outputs are working software, not exam answers.
Research methods
A shared spine for every senior student: literature review, experimental design, statistics, technical writing, peer review.
What the timetable looks like.
Subject teaching
Timetabled lessons across the curriculum, with AI-supported feedback loops. Written work returned within 24 hours.
Project workshop
Protected afternoon for project work. Faculty mentors available; AI tools used openly and logged.
Subject teaching
Lessons designed around the previous day's AI-generated retrieval practice and intervention groupings.
Build day & weekly defence
Full day of project work, ending with a stand-up where each student presents progress to peers and faculty.