Learning Science for AI Assisted Teaching
Use what research says about memory and understanding to decide when AI helps learning and when it hurts
A taste of a lesson
My students ask AI to summarise every reading. Is that actually bad for them?
It depends on what the summary replaces. Making your own summary is a generation task: choosing what matters and putting it in your words is where much of the learning happens. If the AI does that, students get a neat text and less memory. A better order: students read, write a short summary from memory, then ask AI what important points they missed. Same tool, more thinking in their heads. Which reading could you try this with next week?
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
- Explain retrieval, spacing, interleaving, worked examples and cognitive load simply
- Judge whether an AI learning activity keeps thinking in the learner's head
- Redesign passive AI uses into active learning activities
- Recognise common learning myths and the limits of current AI research
Lesson plan
- 1 Memory: retrieval and spacing Understand why recalling and spacing practice strengthen memory and how AI can support both. Start
- 2 Worked examples and cognitive load Use worked examples and load management to help novices, and know when to fade support. Start
- 3 Interleaving and desirable difficulty Use mixing and productive struggle to build flexible knowledge. Start
- 4 Explaining to learn Use elaboration and self explanation with AI as a questioning partner. Start
- 5 Offloading, fluency and myths Recognise when AI use replaces thinking and separate evidence from myth. Start
- 6 Designing an AI supported activity Design one learning activity that uses AI in line with the principles. Start
Try asking
About this tutor
For anyone who teaches or designs learning: teachers, lecturers, trainers, tutors and parents. AI can produce explanations, summaries and quizzes instantly, but more content is not more learning. This tutor teaches the well established principles from cognitive science (retrieval practice, spacing, interleaving, worked examples, cognitive load, elaboration) and uses them to judge AI uses: which ones strengthen thinking and which ones let learners skip it. You also learn to spot learning myths, think about cognitive offloading, and design AI activities that keep the effort in the learner's head.
Reviews
4.5
4 ratingsSample
- Ben A.Sample
As a parent I finally understand why rereading feels productive and isn't. My daughter now asks AI to quiz her instead.
- Sofia M.Sample
Good grounding in cognitive load and worked examples. Would have liked more references to read further, though it explained the ideas well.
- Yara K.Sample
Clear and honest about what research shows and what it doesn't. The 'summary from memory first, AI second' routine is now standard in my classes.
- Kofi D.Sample
The fluency illusion section hit home for my trainees. Practical, not academic, which suited our team.
About the teacher
Lecturer and learning designer for universities, workplace training and coaching practices
9 tutors 410 lessons taught Sample
My background is university teaching followed by learning design work, building courses with subject experts and turning them into something people can actually learn from. I have also run workshops for staff in organisations that wanted their teams to use AI sensibly. I teach lecturers, instructional designers, trainers and independent tutors how to bring AI into course design, practice and...
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