Entrepreneur Hub · Year 10 · Term 1 · Generative AI

AI in the Community.

Build a working AI-powered solution to a real local problem, pilot it with the community, and prove its impact.

10 weeks30 lessons15–16 ages4 checkpointsFree sample
AI in the Community
At a glance

What students make, learn and show.

01

What they make

A working AI-powered solution to a genuine local problem: a tool, service or assistant a community organisation can actually use, piloted with real people.

02

What they learn

  • Build a working AI-powered solution to a real local problem.
  • Apply responsible and ethical AI in practice.
  • Pilot with the community and prove impact with evidence.
03

How it ends

A Community Showcase: teams present the solution, the pilot results and the impact data to the partner organisation and an invited audience.

The ten-week plan

Week by week.

Three 50-minute lessons a week. Checkpoints at weeks 2, 4, 6 and 8 keep every team on track; the teacher guide gives each lesson a starter, a main activity and a plenary.

Weeks 1–2
Discover
Spot and frame the opportunity. Teams research the audience, problem or market behind AI in the Community, agree what they are solving and for whom, and set team roles.
Checkpoint 1 · opportunity statement
Weeks 3–4
Design
Turn the opportunity into a concept and a plan: generate and compare options, choose one, and plan how it will be built and tested.
Checkpoint 2 · concept and plan
Weeks 5–6
Make
Create the real deliverable: a working ai-powered solution to a genuine local problem. Test it against the brief and fix what fails.
Checkpoint 3 · working deliverable
Weeks 7–8
Test & refine
Trial it with real people, gather the evidence (user validation, results, trading figures, reach or impact data) and improve the work from what the evidence says.
Checkpoint 4 · real-world evidence
Week 9
Pitch
Craft and rehearse a persuasive pitch with Q&A: the problem, the solution, the evidence and what happens next.
Pitch rehearsal with feedback
Week 10
Showcase
A Community Showcase: teams present the solution, the pilot results and the impact data to the partner organisation and an invited audience. Individual project journal reflection completes the assessment evidence.
Showcase · assessment submitted

Lesson-by-lesson sequence illustrative, from the programme arc, until the teacher guide is supplied.

Lesson preview

See one lesson in full.

Every lesson in the teacher guide follows the same shape: what students should be able to do by the end, a starter, a main activity, a plenary, and the resources to run it. This one is open to everyone.

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Week 2 · Lesson 4Can AI help here? Judging a tool before you trust it
By the end, students canExplain what an AI tool can and cannot do for the partner’s problem, and name two risks (accuracy, bias, privacy) with a way to reduce each.
Starter · 10 minThree real outputs from an AI assistant, one wrong. Teams spot which and explain how they knew.
Main · 30 minTeams test an approved AI tool against their problem statement using a structured prompt sheet, log accuracy and failure cases, and score it on a four-point ethics check.
Plenary · 10 minEach team states go / no-go for AI in their solution and the one safeguard they will build in. Recorded in the project journal.
ResourcesSlides · prompt sheet · ethics check · journal prompt · teacher notes on tool approval and data rules
Assessment

Four parts. Same model every project.

Each part has its own criteria and rubric in the teacher guide. Judge students at each checkpoint and at the showcase on the tracker, so the evidence is complete when the project ends.

35%
Real deliverable
The product, venture, solution or campaign itself: does it do what it set out to do, for the people it was made for?
25%
Pitch + Q&A
The showcase pitch or demo to an audience or panel, including handling questions with composure.
20%
Real-world evidence
Proof it works with real people: user validation, pilot results, trading figures, reach and impact data.
20%
Project journal
Reflection and process across the project: how students thought, adapted and grew.
Rubric, criteria, checkpoint tasks and the class tracker are in the teacher pack, mapped to the frameworks you report against.How assessment works on Campus →
In the teacher pack
  • Teacher guide: 30 lesson plans with starter, main and plenary
  • Lesson slides, ready to present
  • Student materials and checkpoint tasks
  • Assessment rubric, criteria and checkpoint tracker
  • Partner and audience brief templates, consent forms
  • Showcase running order and audience guide
Standards & streams
Secondary SubjectMapped to EntreComp (EU), CEE (US) and ACARA v9 (Australia). Criterion references to follow
CambridgeAdapted to Cambridge Global Perspectives
IBAdapted to IB MYP Design

Full curriculum alignment →

Responsible AI & data

Students use educator-approved AI tools only. No identifiable personal data about participants is entered into AI tools; consent is obtained for research and publication; AI assistance is recorded alongside students’ own decisions. The teacher guide sets out the tool-approval and data rules for this project.

Free sample project

Teach AI in the Community, free, in full.

The complete project: the teacher guide, slides, student materials and the assessment rubric. No card required. Use it with a real class and assess how the learning framework works for you.

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