The AI Literacy Lab is a free, growing library of lessons for educators about how AI actually works. Every word, every voice and every image on this site is itself generated by AI — the pedagogies are human-authored and open to inspect, and the content is generated by AI using these. Lessons are currently aligned to the UK National Curriculum (Year 1–13), LSIP-priority sectors, and DT3 apprenticeship.
LessonsEach lesson is written to work with any year group. Curriculum alignment is shown up front. Every activity has a copy-and-paste prompt for Copilot or ChatGPT.
How to use these lessons
Following the framework in Watkins (2025) Papers 1–3, each activity is generated by AI from a human-authored Pedagogy: a set of labelled Elements and their Parameters, plus a Narration parameter for the spoken audio. In Teacher view, click Show pedagogy in any section to see, in Paper 2's canonical table format, the exact rules used to produce the content and the audio.
Every section has a big 🔗 Share button in Teacher view that reveals a QR code — point a phone camera at it and pupils land on that section (or its homework) instantly, no login required. Every lesson also has an aggregate 📮 Homework page with a copy-paste AI prompt per task, plus a pen-and-paper fallback for pupils without home internet or an AI account.
Every lesson exists in five views: the primary variant (English, warm British voice), WCAG AAA (black-on-yellow, high contrast), dyslexia-friendly (OpenDyslexic font, cream + cool blue), Polski and हिन्दी (native translations). Toggle at the top of any lesson with Change how this looks. The pedagogy and the learning outcomes stay the same across all — only the delivery changes.
A small ▶ Listen button in each section's header plays a 25–40 second narration of the section's main idea, voiced by Alice, a warm British female voice from ElevenLabs. Only one section plays at a time; press pause any time. Every variant has its own voice — Bella for the dyslexia view, Charlotte for Polski, Aria for हिन्दी — with scripts translated to match.
The spoken narration is not a separate script — it is generated from the same pedagogy that made the on-screen text, following a Narration parameter that says "warm, 25–40 second spoken intro, drawn from the section's elements". Click Show pedagogy and you can read the exact rule that produced the audio you just heard.
Multiple views of every lesson
What AI does: generates every element from the pedagogy Rule, voiced by Alice (soft British female, ElevenLabs), illustrated by gpt-image-1 in the Grassroots Earth palette.
What stays: this is the reference. Every other view is a documented, human-reviewed transformation on top of this one.
What AI does: nothing. Text and narration are byte-identical to the primary variant. Only CSS changes — pure black background, bright-yellow text, thick outlines.
What stays: every word, every audio file, every image (rendered through a high-contrast CSS filter). Zero AI cost.
What AI does: font swap to OpenDyslexic, wider letter-spacing, taller line-height, warm cream + cool blue palette applied via CSS filter to the primary-variant illustrations.
What stays: text and narration are the primary variant's. Images are the primary variant's, recoloured client-side.
What AI does: translates the whole page to natural teacher-facing Polish, re-voices with Charlotte (native Polish), re-illustrates in a grey-white + Polish-red + forest-green palette.
What stays: the pedagogy, the section order, the composition of every scene, the UK curriculum year references.
What AI does: translates the whole page to Hindi in Devanagari script, re-voices with Aria, re-illustrates in a warm cream + saffron + India-green palette, font swap to Noto Sans Devanagari.
What stays: the pedagogy, the section order, the composition of every scene, the UK curriculum year references.
Tonal, visual and cultural adjustments per view are a principled starting point, not a guarantee of cultural fit. A native educator's eye should sit above them before classroom use — tell us if anything reads awkwardly and we will re-run.
How these lessons are madeEvery word on this page was written by AI. Every voice you hear is AI. The recipe is open at every layer — the architecture is Watkins (2025) Papers 1–3 and every section has a Show pedagogy button that reveals the exact rules that produced it.
A Pedagogy is a bundle of labelled Elements with plain-English Parameters — Rule (what to say), Max words, Structure (how to format), Narration (spoken intro). Written by teachers, published in Papers 1–3 and stored in the pedagogy library. This is the only step where a human writes creative content.
The pedagogy is topic-agnostic. Plug in a Topic variable (non-determinism, bias, tokens…) and an Audience (KS1 → Y13, LSIP workforce, DT3 apprentice) and the FORMATTING variable adapts automatically — KSB emphasis for apprentices, statute anchors for workforce, age-appropriate register for school years.
Claude generates every element following the pedagogy's Rule + Structure, respecting the max-word budget and audience register. Test-yourself sections always render last. Every element is bound to a labelled slot from the pedagogy — no free-form invention.
A Narration parameter drives the spoken audio — voiced by Alice (soft British female, ElevenLabs) on the primary variant. Each section's Image Pedagogy produces a scene concept sent to gpt-image-1 with the Grassroots Earth palette prefix. One image, one voice per section.
A Variant Profile re-renders the primary variant for a different audience without touching the pedagogy. WCAG AAA and dyslexia-friendly are CSS-only passthroughs (zero AI cost). Polski and हिन्दी are translated by Claude and re-voiced with native ElevenLabs voices. Every deploy is human-reviewed; treat images as illustrative not authoritative and tell us if anything reads culturally narrow.
Have a pedagogy of your own — a set of labelled Elements with Parameters — and a Topic you want to see generated on this site? Send it to us with any variables (year group, subject, audience) and we will run it through this exact pipeline: text → images → narration → variants. Your name (and the pedagogy's name) get full credit on the resulting lesson.
Fun warning: we will need to generate an avatar for you to go on the credit line. We will show it to you before it goes anywhere near the internet.
Email joe@grassroots-intelligence.com with your pedagogy, topic and any variables. We aim to reply within a week.
Useful resourcesFree companion resources from Grassroots Intelligence. Editable Word documents for teacher and student use.
Curated prompts for GCSE and A-level, organised by subject.
Download .docx ⬇
A student-facing guide to using AI as a study partner rather than a shortcut.
Download .docx ⬇
Applying Rosenshine's Principles of Instruction to AI-assisted teaching.
Download .docx ⬇
PapersThe academic foundations of Grassroots Intelligence — free to download and share. If you use anything in a classroom, credit is welcome but not required.
A lightweight framework for encoding pedagogical expertise as discrete elements with natural language parameters. The same rules that describe a pedagogy also serve as structured constraints on what an LLM generates. Subject-independent, illustrated with worked examples any teacher can drop into any LLM.
Open PDF ⬇Extends Paper 1 with the primary variant and variant profile: a structured set of learner-facing natural-language rules that tailor the same pedagogy for different individuals or groups (year group, EAL learners, neurodiversity) without changing the pedagogy itself. This is the methodology behind the "Change how this looks" switcher on every lesson.
Open PDF ⬇Shows that the same variant-profile architecture accommodates accessibility (WCAG, dyslexia-friendly), general visual design, cultural adaptation and translation as deterministic rendering parameters — one profile applies to every lesson in a library with no further LLM use and identical results every run.
Open PDF ⬇
This Week in AI x EducationA weekly AI-assisted podcast for teachers. Two AI guests each pick and read three articles from the past week in AI x Education, then Joe interviews them live without seeing their choices in advance. The whole conversation is unrehearsed. New episodes appear here Friday afternoon.
Change logEvery meaningful change to this site — new lessons, re-generated images, re-recorded narration, pedagogy tweaks, front-page features — is logged here. Newest first.
