Spaced repetition is super valuable, but popular spaced repetition systems today fall short for many people unnecessarily.
Here are 6 ways we can improve spaced repetition for the next generation:
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1 Card creation: Zero friction card creation
2 Card creation: Good cards by default
3 Card maintenance: Eject bad cards quickly
4 Schedule flexibility: Allow people to study more
5 Schedule flexibility: Allow people to study less
6 Review friction: Bring the reviews to the users
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Details here:
davidbieber.com/snippets/2021-
but I'll summarize in this short thread to save you some time:
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* (1,2): Creating good cards should be as easy as a Google search.
I made a prototype with Browserflow that I've fallen in love with: davidbieber.com/snippets/2021-, and we can push this even further with ML
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* (3) The UX of SR systems should lead users to drop bad cards early and often; let's make keeping bad cards hard
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* (4,5): SR systems should encourage studying when you're most motivated; they shouldn't rely on you studying even on a vacation, or discourage extra studying when you complete your day's review. This requires changes to both algorithm and UX.
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* (6) An extra app like Anki is extra friction; brings SR to your email inbox, but you still need to click through to review. Great progress, but we can do even better.
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I want to share these ideas with folks thinking about spaced repetition. So, here's some unsolicited @-ing; I hope you don't mind:
@hermannebbinghaus
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Broadly agreed! Though alas, I believe #1 and #2 are deep research projects: my experiments with cloze-driven extracts like the ones you describe have been pretty unsuccessful in the long-term.
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Do you refactor chunky clozes into Q/As over time or prefer to leave them as blocks?
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Usually either the former or I end up deleting them.