The Science of Learning
This course is about the evidence behind how people actually learn — and how good learning technology is built on it. Most of what feels like effective studying (rereading, highlighting, cramming) is among the weakest things you can do; the methods that work best often feel harder. Here you’ll meet the research — the forgetting curve, the testing effect, the spacing effect, mastery learning, knowledge tracing — and, just as importantly, how to tell a real efficacy claim from marketing.
Every module is hands-on and runs entirely in your browser: you’ll watch a memory decay and a review reset it, race rereading against retrieval practice, schedule a spaced-repetition deck, run a mastery-learning classroom, and watch an adaptive engine update its estimate of what a learner knows. Each ends with a short mastery check; pass it to mark the module complete. It pairs naturally with the Item Response Theory course — this one is the why, that one is the measurement.
How learning works
Module 1How Learning Works — Memory & Forgetting
Encoding, storage, retrieval, and the forgetting curve. Why memory fades and what brings it back. Activity: watch a memory decay over days, then drop in a review and see the curve reset and flatten.
What actually works
Module 2The Testing Effect — Retrieval Practice
Pulling information out of memory beats putting it back in by rereading. Why the better method feels worse. Activity: race two study strategies and compare what each remembers a week later.
Module 3Spaced Repetition
The spacing effect, expanding intervals, and the Leitner / SM-2 schedulers behind apps like Anki. Activity: run a flashcard deck and watch review intervals stretch with each success and snap back on a lapse.
Module 4Mastery Learning & the Zone
Hold the standard fixed and let time vary; Bloom’s 2-sigma problem; Vygotsky’s zone of proximal development and scaffolding. Activity: run a mastery-based class vs. a fixed-pace one and compare who reaches the bar.
Module 5Feedback & Motivation
What makes feedback work (specific, timely, actionable), formative vs. summative, and intrinsic vs. extrinsic motivation — including when gamification backfires. Activity: tune feedback timing and detail and watch learning respond.
Technology & evidence
Module 6Adaptive Learning & Knowledge Tracing
How a system decides what to show next: Bayesian Knowledge Tracing and a running estimate of mastery. The bridge to Item Response Theory. Activity: answer items and watch the mastery probability climb and dip.
Module 7Learning Analytics
What dashboards should measure, leading vs. lagging indicators, vanity metrics, and the ethics and privacy of learner data. Activity: sort real metrics into useful vs. vanity, and leading vs. lagging.
Evaluating the claims · Capstone
Module 8 · CapstoneDoes It Actually Work? Evaluating Ed-Tech
The skill that separates real learning science from hype: evidence tiers (ESSA), randomized trials vs. anecdote, effect sizes, and the replication problem. Activity: judge real-sounding efficacy claims and rank the evidence. Ties every earlier module together.