AI2 Scheme of work: Neural Networks to Smart Apps - Engineering the Future of AI. Year 8 (6 Lessons)

Move beyond AI awareness - and into intelligent system design

A complete 6-lesson KS3 Artificial Intelligence scheme where students learn to design, test, and improve real AI systems - without coding or technical setup.

Each lesson simulates how intelligent systems see, interpret, and adapt - from neural networks and language processors to fairness testing and ethical redesign. Students don’t just study AI - they work with it.

Perfect for:

• Non-specialist teachers delivering structured, high-impact AI lessons

• Curriculum leads seeking a progressive follow-on from AI1 foundations

• High-ability learners - with full support for mixed-ability classrooms

• Departments focused on ethics, adaptive systems, and real-world application

Why this matters

Once students understand how AI works, the real challenge begins:
Can they spot when it’s wrong, unfair, or incomplete - and know how to fix it?

This scheme develops that next level of thinking.
Students move beyond the basics to train, test, and refine intelligent systems - working directly with bias detection, adaptive logic, and ethical redesign. They explore why fairness in AI depends on the data we choose, the structures we build, and the questions we ask.

By the end, learners aren’t just aware of how AI behaves - they know how to challenge it, improve it, and design it with purpose.

🔍 This is intelligent system design for students ready to think critically - and take AI further.

Lesson structure & progression

Each lesson builds from core neural logic to complex decision-making, giving students hands-on experience with the AI concepts shaping real-world tools.

Lesson titles and focus:

1. Neural Networks Simplified – How Machines ‘Think’. Simulate a 3-layer neural network and explore how weights affect predictions.

2. Computer Vision Basics – How AI ‘Sees’ the World
   Train an image classifier using labelled data - then explore what happens when bias creeps in.

3. Natural Language Processing – How AI ‘Understands’
   Discover the limits of machine language through NLP simulation and analysis.

4. Training AI and Bias – The Importance of Data
   Evaluate fairness in AI predictions and improve outcomes by redesigning training sets.

5. GameSense Part 1 – Blueprint for Intelligence
   Build the logic for an AI coach system using real-world player data and coaching strategy.

6. GameSense Part 2 – Engineering Review and Stress Test
   Peer-test, evaluate, and refine each other’s systems through scenario analysis and ethics review.

What you get

Everything is ready to deliver:

• 6 structured, inspection-ready lesson plans
• PowerPoint presentations with fully scripted teacher notes
• Custom offline simulations with training sets and scenario inputs
• Printable student tasks, model answers, and key vocabulary
• Built-in SEND scaffolds with full classroom adaptation guides
• Optional cover lesson format for any session
• Scheme Inspection Report (intent, implementation, and impact)

Built-in for inspection – without extra workload

Every AI2 scheme includes a complete inspection report covering:

• Curriculum Intent – Logical sequencing, purposeful progression, and inclusive ambition

• Implementation – Delivery model, teaching tools, and built-in scaffolds for accessibility

• Impact – Evidence of systems thinking, progression, and ethical reasoning

• Inclusion & Accessibility – Adaptations for diverse learners, cultural links, and equitable access

This gives subject leaders everything needed to evidence high-quality AI education - clearly and confidently.

Why this scheme works

High engagement
Students design intelligent systems, test real-world logic, and analyse fairness through hands-on tasks.

Teacher-ready
Resources are fully structured, scripted, and printable - ideal for any classroom, with or without prior AI experience.

Inspection-proof
Everything is documented - from outcomes and progression to SEND access and assessment opportunities.

Future-ready
Students don’t just use AI - they evaluate it, challenge it, and learn how to shape it responsibly.