E-learning & AI
Learning nuggets on AI, learning science and digital education: short videos with articles, sources and exercises for teaching and training.
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Mix, don't block: three times better on the test
Why mixed practice beats practising in blocks in the long run, even though it feels harder, and how to mix exercises in your own courses.
Model, LLM, chat, agent: four terms, one picture
Model, LLM, chat and agent often get mixed up. A simple picture of layers shows how the four terms fit together and what that means for your teaching.
RAG explained: your AI never read the handbook
How AI assistants work with your own documents, what the language model really sees, and when everything belongs in the context window.
Three time sinks you can hand over to AI
What a randomised trial in England measured about AI in lesson preparation, which three tasks you can hand over as drafts, and where the boundary stays.
Making assignments AI-robust
Banning achieves little, redesigning does: four building blocks that keep assignments demanding real thinking, even when an AI is within reach.
Less on the slide, more room to think
Why a full slide gets in the way while you speak, what Mayer's redundancy and coherence principles say about it, and how to declutter your next presentation.
The data traffic light: what can go into AI?
Green, yellow, red: a simple traffic light helps teachers and course leaders decide which data they can put into AI tools and which they cannot.
Online is not the same as online
Why "classroom or online?" is the wrong question, and how three dimensions help you describe digital learning offers honestly and choose the one that fits.
Learning isn't an event. It's a rhythm.
What Ebbinghaus found out about forgetting in 1885, why every repetition changes the forgetting curve, and how to build moments of recall into your courses.
AI detectors are not proof
Why even a one percent false alarm rate hits many honest students, what research shows about AI detectors, and what works better in the classroom.
AI doesn't lie. It guesses.
Why language models make things up, why they sound so sure while doing it, and three questions that help learners spot invented answers.