Flashcards for deep understanding: rethinking spaced repetition beyond rote memorization

The author pushes back on the common STEM assumption that flashcards are just mechanical memorization tools fit only for vocabulary. After taking the “Learning How to Learn” course, they came to see spaced repetition as a general-purpose technique for retaining knowledge, not a crutch for cramming. The personal motivation is blunt: their memory is poor, and cumulative subjects like math—where theorems build on theorems—collapse without fluent recall of the basics. Chunking makes the case that even deep-understanding fields depend on memory, just differently than fact-heavy ones.

The practical method matters more than the tool. Anki is the software of choice despite gripes about its dated UI, clunky HTML editor, and opaque file format, chosen for its unmatched card flexibility. The key discipline: never memorize what you don’t understand, and write your own cards rather than importing decks, most of which are low-quality textbook transcriptions. Beyond definitions, the author preserves intuitions and “a-ha moments” (with images and links back to source notes tied to a digital garden), and even repurposes spaced repetition as a scheduler for recurring tasks like re-attempting previously botched math problems.

The payoff is being able to pause a book or course for a year and resume without starting over, at a cost of roughly 1–30 minutes of daily review. The author keeps the system lightweight, deleting cards freely since each one is ongoing overhead. They’re candid about the evidence: spaced repetition is well supported, but empirical backing for Anki specifically is thin and drawn mostly from medical students—yet, like most decisions made under imperfect information, they judge it worth it.