Ask better
The Arena
Students write the prompt themselves. An AI judge scores it on clarity, context, role, output design and iteration — then reveals how an expert would have asked.
AI native learning programme
Every child will use AI.
Few will learn to think with it.
Spark OS turns AI from an answer machine into a thinking partner. Every interaction is moderated, permanently logged, and visible to teachers.
Students, teachers and school leaders sign in. Everyone else — we'd love to hear your problem.
The gap is already open
- 88%
- of students already use AI
- 67%
- say it is harming their own critical thinking
- 70%
- of educators have had no training to guide them
edtechinnovationhub, UK
AI isn't a subject. It's a layer on top of every subject.
When calculators entered classrooms, mathematics didn't disappear — it became more powerful. Students stopped burning twenty minutes on long division and started solving real problems. AI is that moment, for every subject, happening right now.
The subject doesn't change. The student's ceiling does.
Two versions of AI in a classroom
The default
- Homework done for them
- Infinite feeds that farm attention
- A black box no adult can see into
- Interests that narrow to a bubble
Spark OS
- Prompts they craft and defend themselves
- Five facts a day, then a clean stop
- Every word logged, nothing deletable
- A mix engineered to widen curiosity
Four rooms, one habit of mind
Each one teaches a different half of working with AI — asking well, thinking alongside, staying curious, and building something real.
Think alongside
AI Mentor
Socratic by design, and never a homework machine. A Grade 5 question gets a Grade 5 answer, grounded in your own curriculum and always ending in a nudge back to the student.
Stay curious
Discover
A bounded daily ritual, not a feed. Facts are written and moderated in advance, approved by staff, then served five a day. We measure whether interests widen — not how long anyone scrolls.
Build it
Code Studio
Web pages, Python, even a circuit board blinking on their own desk. Student code runs in the browser or on their own hardware — never on our servers.
The Arena
This is what a lesson looks like
The Arena scores a real prompt across five dimensions, explains each one, and hands back a tip. The student rewrites and tries again.
Next time, tell the AI what the learner already understands.
Challenge
Get an AI to explain photosynthesis to a 7-year-old
Student's prompt
You are a friendly science teacher. Explain photosynthesis to a 7-year-old using a picnic as a comparison. Use 4 short sentences and one question at the end.
Score
80/100
- Clarity18
- Context14
- Role20
- Output design17
- Iteration11
Strong role and output design. Add what the child already knows, and you'd score higher on context.
For a school, safety isn't a feature. It's the precondition.
These are structural guarantees, not settings an administrator has to remember to switch on.
Moderated on both sides
Every message is checked before it reaches the model and again before it reaches the child. The classifier fails closed — if it cannot decide, nothing goes through.
A log nobody can rewrite
Mentor conversations are append-only at the database level. No teacher, no administrator, and no engineer can edit or delete what was said.
Safeguarding is automatic
Anything suggesting self-harm is met with care, a clear push toward a trusted adult, and an immediate email to the school's safeguarding lead.
The profile is the student's
Personalisation is a short document the student can read and correct — limited by design to subjects and interests. Never a hidden dossier.
No open-internet chatbots. Students cannot see or override the system's instructions. Built to UK and EU GDPR standards.
A year, not a licence
One session a week across four quarters. Students move from understanding AI, to creating with it, to solving real problems, to presenting their work in public.
- Q1
Understand AI
What AI actually is · prompting as a skill · hallucinations and verification · AI ethics
- Q2
Create with AI
Writing and design support · presentations · voice and video · building a personal AI tool
- Q3
Solve with AI
Students pick real problems and design AI-supported solutions — research, prototype, test, iterate
- Q4
Lead with AI
Refining work · mentoring younger students · presenting at the Annual AI Faire
What they walk out with
Every student finishes the year with something real they can demonstrate and defend.
Grades 5–7
Gesture-controlled games · smart plant diagnosis tools · voice-activated devices · AI logic and classification
Grades 8–10
Subject-based AI assistants · air-quality monitoring · robotics and sensor builds · data storytelling
Grades 11–12
Smart hydroponic systems · health-related prototypes · solutions to real-world challenges
Evidence, not anecdotes
School leaders get an aggregate view every month: how many students are active, how prompt-engineering skill has moved, what safety caught, and exactly what the AI cost. Individual conversations never appear here — those stay in the teacher's review queue.
- Active students & attendance
- Skill growth, start of term to now
- Flags raised and acted on
- AI spend against budget
PDF · 8 pages
The whole programme, on paper
Curriculum by quarter, what students build in each grade band, the safety and governance model, monthly reporting, and exactly what we ask of your school. Everything a board needs to make a decision.
- The full annual pathway, quarter by quarter
- What Spark delivers vs. what your school provides
- Safety, governance and GDPR in detail
Questions? kadri@quantumdatalabs.co.uk
Your problem could be their capstone
Local businesses, charities and families send us real problems worth solving. Approved ones become Arena challenges, and students work on something that actually matters to the place they live.
No account needed. Takes two minutes.
You bring the students. We bring the transformation.