How Spaced Sets works
Spaced Sets is a learning companion that ensures you remember the topics you study, using science backed techniques (FSRS) by scheduling your revision sessions at the right times to improve your neural connections.
1 · Retrievability & the forgetting curve
The moment you finish reviewing a topic, your ability to recall it is at its peak — call it 100%.
From there it decays along a curve. FSRS models this as retrievability R(t) —
the probability you could recall the topic right now, t days since your last review.
FSRS schedules the next review the moment R(t) is predicted to fall to your
target retention (90%). This is when a card becomes due. It is
early enough that you haven't forgotten, late enough that the recall effort strengthens the memory.
2 · Why spacing works
Each successful review does two things: it resets the recall back towards 100%, and it increases the memory's stability so that the next decay is slower. That's why the intervals between successful revisions get longer and longer. Reviewing a topic when it's due, by actively recalling it before you are forced to look at your notes or the solution, is what makes it stick.
3 · The memory score (your health bar)
The memory score, the big number on your dashboard answers one simple thing: "How much of what I've learned am I currently holding at full strength?" It's built directly on FSRS retrievability, in three simple steps:
recall = R(t) — ~100% just after a review, decaying over time, 0% if never reviewed
# 2. turn it into a "full strength?" score, capped at 100%
health = min( recall / 0.9, 1.0 ) — at/above the 90% target counts as full
# 3. the dashboard score is the average across all your reviewed cards
score = average(health) × 100
Because a card counts as "full strength" until it decays past the target (90%), the score reads 100% when you're fully caught up — i.e., nothing overdue. As cards come due it slips, and reviewing them pushes it back up. That's the game: keep the bar topped up and be able to retrieve what you study.
- 100% — everything is caught up, nothing overdue. The number to chase.
- It drifts down when cards fall due and you don't review - that's honest, not a bug.
- Never-reviewed cards sit at 0% until their first review.
This is also why the dashboard can tell you ↑ how much you'd gain by studying and ↓ how much you'd lose by skipping - it simply re-computes the score for those two futures.
4 · Durability & “durability-days”
Every card also has a stability — the number of days its recall takes to decay down to the target (90%). That's the width of the forgetting curve at the top of this page: a wider curve = a more durable memory that lasts longer before it's due again.
Each successful review widens that curve — with increasing gaps between reviews each time. So when the dashboard says “studying today adds ~N durability-days”, it means: if you review all your due cards, their stabilities will grow by N days in total.
Where the memory score is a health bar that rises and falls, durability-days are the ground you've permanently gained - a number that only ever grows when you study.
5 · How your ratings feed back in
When you review a card you rate your recall, and FSRS updates the schedule accordingly:
- Again - you forgot. The card resets to short intervals (back tomorrow).
- Hard - recalled with effort. Shorter next interval.
- Good - recalled cleanly. The standard, growing interval.
- Easy - effortless. An even longer interval.
There's also a practice-daily toggle per card that ignores FSRS pacing and brings a card back every day - handy for things you want to drill regardless of the schedule.
6 · Further reading & the science
Spaced Sets stands on decades of memory research. Here are some of the most-cited papers and a few accessible deep-dives if you want to go further. (Paper titles link to Google Scholar.)
The spacing & testing effects — why spacing reviews and self-testing work:
- Ebbinghaus, H. (1885). Memory: A Contribution to Experimental Psychology. The original forgetting curve.
- Cepeda, Pashler, Vul, Wixted & Rohrer (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin — the definitive meta-analysis of the spacing effect.
- Roediger & Karpicke (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science — the testing/active-recall effect.
- Karpicke & Roediger (2008). The critical importance of retrieval for learning. Science — retrieval beats repeated study.
- Dunlosky, Rawson, Marsh, Nathan & Willingham (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest — rates practice-testing & distributed practice as the two highest-utility techniques.
From science to a schedule — the algorithms:
- Settles & Meeder (2016). A trainable spaced repetition model for language learning. ACL — Duolingo's half-life regression.
- Ye, Su & Cao (2022). A stochastic shortest path algorithm for optimizing spaced repetition scheduling. ACM SIGKDD — the research behind FSRS, the algorithm this app runs on.
- FSRS — the Free Spaced Repetition Scheduler. The open-source algorithm & its wiki (the DSR model explained).
Accessible deep-dives:
- Augmenting Long-term Memory — Michael Nielsen. A superb long essay on how spaced repetition changes how you learn.
- Spaced Repetition for Efficient Learning — Gwern Branwen. Deep, evidence-heavy survey of the practice.
- How To Remember Anything Forever-ish — Nicky Case. An interactive comic — the gentlest possible intro.
The plots above are generated from the actual scheduler this app runs - not a stylised illustration.