Build a working model of human learning grounded in the cognitive-science evidence base, not pedagogical folk wisdom: encoding, retrieval, spacing, interleaving, prior knowledge, cognitive load, transfer, and the illusion of fluency. Well enough to make teaching decisions from principle rather than instinct. Cognitive science is to teaching what database internals are to backend work. You can write working software without knowing how a B-tree splits — but the moment performance matters, the people who know the storage engine leave the others behind. Same here: you can teach without knowing what working memory is, but the moment a real learner is struggling, the engineer who can name what's failing (overloaded working memory? missing prior knowledge? fluency illusion?) will fix it, and the one who can't will repeat the explanation louder. This module is the systems-internals reading for the teaching career. And the forgetting curve is a cache TTL: writes that are never re-read expire. Design for the TTL or lose the data.
This course unlocks once you've finished its prerequisite. Open prerequisite →
The honest opening: you probably already know 40-60% of what is in this module. Make It Stick has been a popular book for a decade; "spaced repetition" and "retrieval practice" ge…
Most engineering teaching fails for one of three reasons: it ignores prior knowledge, it overloads working memory, or it confuses recognition with mastery. All three are addressed…
Approach: Essential
Approach: Essential
Approach: Important
Approach: Important
Approach: Important
1. Retrieval-test yourself on Make It Stick — for each chapter, book closed, write what you remember; then check. (You are experiencing the method you'll be designing with.) 2. Ru…
8 lessons. Read in order; spiral back when you need to. By the end you'll have used the core ideas twice — once on the abstract, once on something you'll meet at work next week.