Differentiation and Scaffolding with AI
Make one lesson reachable for every pupil without lowering the goal for anyone
A taste of a lesson
I asked for an easier version of my history source and it removed the bit about propaganda, which is the whole point. What went wrong?
The AI optimised for 'easier' and didn't know what mattered, so it cut the hardest idea, which happened to be your objective. Tell it explicitly what must survive: 'Shorten the sentences and explain hard words in brackets, but keep the point that the poster was designed to make people fear the enemy.' Then read both versions side by side and ask: could a pupil answer the lesson question from the adapted one? Can you write the one sentence that must survive your adaptation?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Adapt a text or task with AI while keeping the core concept and subject vocabulary
- Design scaffolds that fade over a sequence of lessons
- Write stretch tasks that deepen thinking instead of adding volume
- Check adapted resources for accuracy and hidden drops in expectation
Lesson plan
- 1 Same goal, different routes Define differentiation as adapting support while keeping the learning goal shared by the whole class. Start
- 2 Adapting texts without losing the idea Ask AI for adapted reading levels and check that the key concept and vocabulary survive. Start
- 3 Scaffolds and worked examples Build sentence starters, organisers and faded worked examples that support pupils toward independence. Start
- 4 Stretch that deepens Use AI to draft challenge tasks that require reasoning, transfer or evaluation rather than more of the same. Start
- 5 Supporting pupils learning English Adapt language load while keeping content age appropriate and respectful. Start
- 6 A sustainable differentiation workflow Create a weekly routine that adapts resources quickly without breaking privacy rules. Start
Try asking
About this tutor
For teachers who already use AI a little and want help adapting tasks and texts for mixed attainment classes. The aim is the same learning goal for everyone, reached by different routes: scaffolds, worked examples, sentence starters, adapted reading levels and stretch tasks. We practise asking AI for adapted versions of a real resource, then checking that simplification has not removed the key idea or introduced errors. You learn to spot when 'differentiation' quietly becomes lower expectations, how to fade scaffolds over time, and how to support pupils learning English. Every example uses anonymised class descriptions and your school's approved tools.
Reviews
4.5
2 ratingsSample
- Olumide B.Sample
The 'route not destination' idea reframed everything for me. My adapted texts now keep the subject vocabulary with a glossary instead of losing it.
- Saskia V.Sample
Good on faded worked examples, which I now use in maths every week. The section on EAL support felt a bit short, I wanted more examples.
About the teacher
Former classroom teacher helping schools use AI with care for pupils, workload and good teaching
9 tutors 425 lessons taught Sample
I taught secondary science for a long stretch, then coordinated teaching and learning across a school, which meant planning, observing lessons and helping colleagues through every new initiative. When AI tools arrived in staffrooms I saw both the relief they offered tired teachers and the shortcuts they tempted pupils into. I now teach teachers and school leaders how to use...
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