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The LearnClash SRS Retention Curve: 3 Stages [2026]

LearnClash's 3-stage SRS retention curve: wrong cards return at 7 days, known at 90, then mastery exits the pool. Performance-based, not 1/3/7/21.

David Moosmann
Founder & Developer · · 18 min read

David built LearnClash after 12 years of daily quiz duels with his mum to combine the fun of competition with real spaced-repetition learning. He writes about competitive learning, spaced repetition, and the product decisions behind LearnClash.

Updated Fact-checked
LearnClash SRS retention curve hero: 3-stage SRS diagram with 7-day, 90-day, and mastered checkpoints overlaid on the Ebbinghaus forgetting curve

The 1/3/7/21 schedule on every memory blog is a calendar dressed up as spaced repetition.

LearnClash’s 3-stage SRS uses a performance-based memory retention curve instead. Cards move through three states: a wrong card returns after 7 days, a known card after 90 days, and a mastered card exits the active pool at around day 97. That three-checkpoint curve is the artifact this article describes.

Below: how the curve is shaped, why we picked 3 stages instead of an interval ladder, what demote-by-one actually means, and how the design handles cards that sit at the edge of recall. Duel me on memory psychology →

That matters because a retention curve is only useful if it changes product decisions: it should tell us which cards to show, which cards to retire, and which cards look mastered but are actually stuck in a loop. Otherwise it is just a chart.

What Is an SRS Retention Curve?

An SRS retention curve plots the percentage of cards a learner still answers correctly at each spaced interval. In LearnClash, the curve traces three checkpoints: how many cards pass the 7-day check, how many pass the 90-day check, and how many exit the pool as mastered. It’s our overlay on top of the classic forgetting curve Hermann Ebbinghaus measured in 1885.

Ebbinghaus forgetting curve overlaid with LearnClash 3-stage SRS checkpoints at day 7 and day 90, showing retention dropping to 33% at 24 hours without review and the SRS resetting the curve at each spaced checkpoint Figure 1: The Ebbinghaus forgetting curve drops to ~33% at 24 hours without review. LearnClash’s 3-stage SRS resets the curve at the 7-day and 90-day checkpoints, then retires the card.

The unmodified forgetting curve is brutal. Ebbinghaus measured 58% retained after 20 minutes, 44% at one hour, 33% at 24 hours, 21% at one month. Murre and Dros replicated those numbers in 2015 using a different language and got nearly the same shape, 130 years later. The curve is one of the most durable findings in cognitive psychology.

Did you know? Ebbinghaus ran his entire 1885 study on himself, sitting alone memorizing nonsense syllables. The curve has now been replicated across dozens of studies in multiple languages without changing shape.

A retention curve is what you get when you draw the opposite of forgetting. Each spaced review resets the slope. The interval-by-interval pass rate is the curve’s signature, and it’s how learning apps benchmark whether an SRS algorithm is doing its job.

LearnClash’s curve has three points instead of an open-ended ladder. That’s the design choice the rest of this article unpacks.

What Shape Does the LearnClash Retention Curve Take?

The curve traces three checkpoints: a 7-day Known check, a 90-day Mastered check, and a finite endpoint where a mastered card exits the active pool at around day 97. Unlike an open-ended interval ladder, the LearnClash curve has an end. For how the same design connects to the broader system, see the full LearnClash design overview.

LearnClash SRS retention curve shape: a 7-day Known check, a 90-day Mastered check, and a finite endpoint where mastered cards exit the pool at around day 97, contrasted with random review that flatlines without spaced checkpoints Figure 2: The shape of LearnClash’s retention curve. The 7-day and 90-day checkpoints reset the forgetting slope; mastery retires the card. Random review, with no SRS, flatlines within the same window.

Two things shape that curve, and both come from the learning literature rather than from the calendar.

The 7-day check sits well above what a baseline forgetting curve predicts at the same interval (Ebbinghaus measured roughly 25-33% retained for unfamiliar nonsense material, higher for meaningful material). The lift comes from active recall during the original encounter. Testing once at encoding and again at 7 days roughly doubles unaided retention, which matches the Roediger-Karpicke testing-effect literature.

Key takeaway: A pass at the 7-day check reflects memory plus the testing effect from the original encounter, which is why a well-designed SRS sits well above raw forgetting predictions.

The 90-day check is where a counterintuitive effect kicks in: the pass rate at 90 days tends to run higher than at 7 days, not lower. The reason is survivor bias. A card that reaches the 90-day check has already cleared the 7-day check, so the 90-day cohort is pre-selected for cards the player has actually encoded. Survivor bias works in the curve’s favor.

Did you know? A 2024 meta-analysis of 29 spaced-practice studies found 25-50% better long-term retention than cramming. LearnClash’s 7-day and 90-day intervals sit inside that band.

Why 3 Stages Beat the 1/3/7/21 Heuristic Most Memory Blogs Cite

The popular 1/3/7/21 schedule is a calendar dressed up as spaced repetition. LearnClash’s 3-stage SRS advances cards on accuracy, not time. We chose 3 stages because the data says you need a few performance gates to predict memory retention, not a daily review cadence borrowed from a high-school study planner.

Generic 1/3/7/21 day SRS heuristic vs LearnClash 3-stage SRS comparison: heuristic uses fixed calendar intervals, 3-stage advances cards on performance not time, hits Cepeda 10-20% retention scaling band Figure 3: The 1/3/7/21 schedule schedules everyone the same way. The 3-stage SRS branches based on whether the player actually recalled the card.

Here’s the side-by-side:

1/3/7/21 heuristicLearnClash 3-stage SRS
Trigger for next reviewCalendar dayPlayer accuracy
Stages4 (or more)3 (Wrong, Known, Mastered)
Wrong-answer handlingReset to day 1Demote one stage
MasteryOpen-endedExits pool at ~97 days
Backed byStudy-planner blogsPer-card recall + Cepeda spacing research

The 1/3/7/21 idea has a real cognitive-science cousin: Cepeda et al. (2008) tested 1,354 people across review gaps from 0 to 105 days and final tests up to one year out. Their finding was scaling, not a fixed schedule: the optimal review gap is roughly 10 to 20 percent of how long you want to remember the material.

Cepeda 2008 retention scaling curve: optimal review gap is 10-20% of target retention period, plotted across review gap (1-105 days) and final retention performance, with LearnClash 7-day and 90-day intervals marked inside the band Figure 4: Cepeda’s 10-20% rule visualized. LearnClash’s 7-day and 90-day intervals sit inside the band for monthly and permanent retention.

For a one-week test, review after 1-2 days. For one-year retention, review after 1-2 months. No single ladder fits every retention goal.

Retention goalCepeda 10-20% optimal gapLearnClash interval
1 week1-2 daysn/a (covered by encounter + 7-day check)
1 month3-5 days7-day Wrong→Known check
1 year1-2 months90-day Known→Mastered check
Permanent3-6 monthsMastered exits pool

The 7-day and 90-day intervals in LearnClash sit inside that band. Seven days is the 10-20% gap for monthly retention; 90 days is the 10-20% gap for permanent retention. The two checkpoints hit two real retention windows instead of pretending one ladder fits everything.

So why three stages and not five or twenty? Two reasons.

The statistical reason

With only two interval checkpoints, you need exactly three states: pre-check, between-checks, post-check. Adding more stages would mean adding more checkpoints, and the marginal information gain past day 90 is small (Cepeda’s data flattens by ~6 months for most retention goals). More stages means more reviews per card without much retention payoff.

The product reason

Players don’t want a card to keep cycling forever. The pure-SRS school keeps reviewing forever; LearnClash retires cards. Mastered means done, not “we’ll see you in 365 days.”

Key takeaway: The popular 1/3/7/21 schedule is a heuristic, not science. Real SRS branches on performance, not calendar days. LearnClash’s 3-stage SRS keeps the science (Cepeda’s 10-20% rule) and adds a finite endpoint (mastery retires the card). The longer-form case for why LearnClash threw out the 1/3/7/21 schedule walks through the missing source and the Leitner receipts.

How Does Demote-by-One Differ from Anki’s Reset?

A wrong answer in LearnClash demotes the card by exactly one SRS stage. A missed Known card drops to Wrong with a fresh 7-day cooldown, not a full reset to day zero. That’s a deliberate departure from how Anki SM-2 handles wrong answers, and it matters more than people expect.

Spaced repetition algorithm comparison: LearnClash demote-by-one rule keeps Wrong card at 7 days after second miss, Anki SM-2 reduces ease factor causing ease hell, FSRS three-component model rebuilds difficulty stability and retrievability per review Figure 5: Three SRS algorithms side by side. LearnClash’s demote-by-one is the cleanest middle ground between SM-2’s ease penalty and FSRS’s full-model rebuild.

Here’s how the three algorithms handle a wrong answer:

AlgorithmWrong answer effectLong-term consequence
Anki SM-2Reduce the ease factor by 0.20”Ease hell” if a card flips repeatedly
Anki FSRSRebuild difficulty/stability/retrievabilityMarginal ease change per review
LearnClash 3-stage SRSDemote one stage; cooldown restartsNo ease drift; clean state machine

SM-2 has a known failure mode the Anki community calls ease hell: cards that repeatedly drift below default ease pile up and become impossible to clear. The open-spaced-repetition team built FSRS partly to solve that. FSRS reaches the same memory retention as SM-2 with 15-30% fewer reviews by modeling difficulty, stability, and retrievability separately rather than collapsing them into a single ease number. The current default scheduler is FSRS-6 with recency weighting, benchmarked at 99.6% superiority over SM-2 across 9,999 collections and 349.9M reviews; for the full picture of how Anki and Quizlet handle the same forgetting curve, the AnkiHub stewardship handoff in February 2026 marks the inflection point. For the classroom-side version of the same comparison, Kahoot vs Quizlet maps the curve against Kahoot’s Accuracy Mode, which has no SRS, and Quizlet Learn, whose spacing resets between sessions.

But what does that look like in practice?

Did you know? FSRS officially landed in Anki 23.10 and reached mainstream adoption by 2025. The Anki community recommends it as the default for new decks.

LearnClash’s demote-by-one rule sidesteps both failure modes. There’s no ease factor to drift. There’s no per-card retrievability model to mistune. A card is in exactly one of three states, and a wrong answer moves it back exactly one state. So the algorithm is trivial to reason about and trivial to debug. A player can look at any card and know what state it’s in and why.

The trade-off is gentler punishment for a miss. Anki SM-2 can swing a stuck card into a daily review loop until it’s relearned. But LearnClash’s 7-day Wrong cooldown means a missed card waits a full week before you see it again. That’s too long if you’re cramming for a Friday exam, intentional for the lifelong-learning loop the 3-minute duel format is built around.

Key takeaway: Demote-by-one is a state-machine SRS, not a parameter-tuning SRS. It loses fine-grained ease control but gains transparency and avoids ease hell.

What Does the 90-Day Mastery Threshold Actually Mean?

In LearnClash, a card is mastered when it clears both the 7-day Known check and the 90-day Mastered check on first attempt. Mastered cards exit the active review pool at roughly day 97 and never come back. The active SRS pool stays clean instead of accumulating thousands of “we’ll see you in 5 years” cards the way Anki decks do.

LearnClash card lifecycle timeline: Wrong stage 7-day cooldown, Known stage 90-day cooldown, Mastered exits pool at ~97 cumulative days with sentinel date, no further reviews scheduled Figure 6: A card’s path from first encounter to mastery. The 97-day exit point is what makes the LearnClash retention curve finite instead of open-ended.

The 90-day interval is the back half of the Cepeda 10 to 20 percent retention-scaling rule. For knowledge you want to keep for one year, the optimal final review sits between days 60 and 110. Ninety days is the midpoint of that window.

Short-term cortical buffer to long-term cortical storage transition diagram: at 7 days knowledge sits in hippocampal buffer, at 90 days survives transfer to ventromedial prefrontal cortex long-term storage, mastery exit at ~97 days marks consolidation Figure 7: Short-term to long-term storage at 90 days. Surviving the gap is the consolidation signal LearnClash retires the card on.

A card that survives a 90-day gap has crossed from short-term cortical buffer into long-term cortical storage. That’s what the 2025 ventromedial prefrontal cortex study on spaced learning describes at the neural level.

Why retire mastered cards at all? Three reasons.

ReasonWhy it matters in LearnClash
Cognitive loadA cleared card burns 1 of 18 duel-question slots; cost is much higher than Anki’s “few seconds”
Player motivationMastery has to mean done, not “see you in 5 years”
Pool freshnessActive topics use prime counts (37, 43, 47, 53, 89); retirement keeps pools near target

The cognitive-load argument is the easy one. A card a player has cleared at 90 days is no longer informative for the SRS scheduler. Re-asking the same question burns a duel slot that could go to a card the player still needs to learn. Anki keeps reviewing forever because Anki is a personal-knowledge tool; the cost of a 5-year-out review is a few seconds.

Key takeaway: The retirement choice is product-driven, not science-driven. Pure SRS would keep reviewing; LearnClash retires because each duel slot is expensive.

The player-motivation argument is subtler. Mastery has to mean something. If the card comes back five years later, “mastered” is just a label. By retiring the card with a sentinel date, LearnClash ties the word to a real terminal state.

The pool-freshness argument is the one most pure-SRS apps ignore. Active topics in LearnClash use a prime-number question count (37, 43, 47, 53, 89). When mastered cards exit, the active pool stays close to that target size. A topic with 200 review-due cards is just slower than one with 47 active cards plus a bank of mastered ones, not more rigorous.

How Does the Retention Curve Hold Up Across Difficulty Tiers?

The shape of the retention curve holds across difficulty bands, but the height drops with difficulty. Easy LearnClash questions clear the 7-day check far more often than hard ones, by design. The difficulty bands track the LearnClash difficulty design and Trivia Difficulty Index, the wrong-rate ranking across 570 topics, and sit inside the predicted desirable-difficulty zone.

LearnClash retention curve by difficulty: the easy line floats high across checkpoints because recall is automatic, while the hard line sits low and flat because hard questions live at the recall boundary by design Figure 8: Retention by difficulty band. The hard-question line stays low and flat across re-encounters; the easy line floats high throughout.

A first reaction is “fix the hard questions, the pass rate is too low.” But that’s the wrong instinct. A low hard-tier pass rate is intentional, and it’s what the desirable-difficulty zone described in Bjork’s research on training conditions actually predicts.

Bjork desirable difficulty zone diagram: too-easy questions produce shallow encoding, too-hard questions produce zero retrieval, and the recall-boundary zone produces the strongest testing-effect long-term retention lift Figure 9: Bjork’s desirable-difficulty zone. Recall right at the boundary, where retrieval barely succeeds, is where retention lift is largest.

A hard question that you just barely answer correctly triggers the strongest version of the testing effect. Roediger and Karpicke (2006) showed that retrieval just barely succeeding is what drives the largest long-term memory retention lift.

The flatness of the hard-tier line is also expected. Easy cards stay high across all checkpoints because the recall is automatic. Hard cards stay low because each successful recall barely strengthens the trace; the cognitive effort is roughly the same on encounter two as on encounter one. That flatness is the curve’s signature for a difficulty band sitting at the edge of recall.

Did you know? A LearnClash hard question is engineered around a specific wrong-answer trap: an answer that feels right because it’s adjacent to the correct one. “What year did the Berlin Wall fall?” pulls 1990 (reunification year) instead of 1989 (the actual fall). A low pass rate is what happens when distractors are plausible by design, not filler text.

The difficulty design has a practical implication for how to study effectively: players climbing the tiers shouldn’t grind harder questions inside one topic. They should add more topics. What climbs with rank is breadth, not depth at the recall edge.

The companion production list, 12 questions people get wrong, shows that recall edge in the wild: bananas as berries, Venus phases, skunk warning behavior, and other misses that become stronger after the reveal.

Train your brain with a duel →

How the Curve Handles Cards at the Recall Edge

The shape of the 3-stage curve raises three design considerations worth calling out. Response speed carries information the final answer hides, hard cards stay flat rather than climbing, and demote-by-one allows a “stuck card” edge case. Each one shapes how the next iteration of the algorithm could evolve.

Diagram of how the LearnClash curve handles cards at the recall edge: a fast confident recall versus a slow uncertain one, the flat hard-tier line driven by survivor bias, and the Wrong-Known cycle a card can fall into under demote-by-one Figure 10: Three design considerations at the recall edge: response speed as a hidden signal, the flat hard-tier line, and the Wrong-Known cycle.

Consideration 1: response speed carries information the final answer hides

A correct answer is not all the same. A fast, confident recall and a slow, uncertain one both count as “correct,” but they sit in different places on the memory curve. The slow recall is where the fluency illusion lives: the player feels recall is happening, but slow recognition reconstructed from partial cues is what’s actually going on. Bjork has called this the most counterintuitive finding in SRS research. It’s why response speed, not just final-answer accuracy, is a candidate scheduling signal for future versions of the algorithm.

Consideration 2: hard-tier retention stays flat, it doesn’t climb

You might expect the hard-tier line to climb across re-encounters, because each successful recall should strengthen the trace. It tends not to, and the reason is survivor bias. Cards that pass the 7-day check are pre-selected for cards the player partially knew; the ones that fail demote back to Wrong and re-enter the funnel at the same low rate. So the functional retention curve for hard cards is flat, which is consistent with desirable-difficulty research: cards at the recall boundary need many encounters to consolidate.

Consideration 3: demote-by-one allows a stuck-card edge case

Because a miss demotes a card by exactly one stage rather than retiring it, a card can in principle bounce between Wrong and Known indefinitely. The cycle:

  1. Pass the 7-day check (Wrong → Known)
  2. Miss the 90-day check (Known → Wrong, 7-day cooldown)
  3. Pass the 7-day check again (Wrong → Known)
  4. Miss the 90-day check again (Known → Wrong, repeat)

Call these stuck cards. They never reach mastery and never exit the pool, so a topic’s effective active size can creep up over time. The clean fix the design points to is an explicit escape valve: after N round-trips between Wrong and Known, force a Mastered transition or a topic-level reset.

Key takeaway: These are structural properties of the 3-stage state machine, not bugs. The architecture makes each one easy to reason about, which is exactly why a state machine was chosen over a parameter-tuned scheduler.

How LearnClash Uses the Retention Curve in Practice and Duel Modes

LearnClash hides the retention curve inside competitive gameplay. Practice mode is a 9-question session prioritized by retention-curve risk; Duel mode mixes SRS-due cards into the 18-question game alongside fresh ones. The curve runs while you play, which is the differentiator vs solo flashcard apps where SRS feels like homework.

LearnClash Practice and Duel mode SRS flow: 9-question Practice session prioritized by retention-curve risk, 18-question Duel mixes SRS-due with fresh cards invisibly to opponent Figure 11: Practice mode runs the SRS in the open; Duel mode runs it under the surface. The curve drives both.

ModeCards per sessionSRS visibilityPrimary purpose
Practice9ForegroundPure SRS exposure, no opponent
Duel18 (6 rounds × 3)InvisibleCompetitive recall + SRS
QuestVariableTracked across chainTopic-level mastery progression

In Practice mode, the algorithm picks 9 cards weighted by where they sit on the retention curve. Cards approaching the 7-day Known check get priority, cards approaching the 90-day Mastered check get the next priority, and new cards fill the remaining slots. The session is short by design, just a few minutes, and it’s pure SRS exposure with no opponent.

Practice card-selection priority order:

  1. Cards within 24 hours of their 7-day check
  2. Cards within 24 hours of their 90-day check
  3. Cards last seen but not yet at a checkpoint
  4. New cards (never encountered)

In Duel mode, the curve runs invisibly. Of 18 questions across 6 rounds, the matchmaker pulls a mix of SRS-due cards from the player’s pool and fresh cards weighted by topic and difficulty. The player’s opponent has no visibility into which cards are scheduled reviews and which are new. That competitive pressure adds emotional encoding solo apps can’t reproduce: the answer you got wrong in front of an opponent is one you remember.

Did you know? Players in competitive quiz games remember 25% more information in just 5 days compared to non-competitive review, per published competition-and-memory research.

In Quest mode, the curve runs across topic chains. Work through a topic’s question pool, and the SRS tracks mastery across the entire chain. By the time a player finishes a Quest, the topic’s mastered-cards count tells you which questions cleared both checks, which are still cycling between Wrong and Known, and which never made it past the first 7-day cooldown.

Key takeaway: The retention curve is never the foreground. It’s a “review your 47 due cards” prompt in solo apps; in LearnClash it sits underneath the game and shapes which cards appear, mediated entirely through duels and Quests. That’s why the 3-stage SRS spaced repetition foundations still feel like a game.

Practice your study technique →

The Bottom Line

LearnClash’s 3-stage SRS retention curve is a finite, performance-based version of the classic forgetting curve. Wrong cards return at 7 days, Known cards return at 90 days, Mastered cards exit the pool at around day 97. The 7-day and 90-day checkpoints sit inside Cepeda’s 10 to 20 percent retention-scaling band, and the demote-by-one rule avoids the ease-hell failure modes pure SM-2 produces.

LearnClash 3-stage SRS retention curve summary: four design choices reinforcing each other - 7-day Wrong cooldown, 90-day Known check, ~97-day Mastered exit, demote-by-one rule, all sitting inside Cepeda 10-20% retention-scaling band Figure 12: The four design choices that make the curve work. Remove any one of the four and the system stalls.

The trade-off is gentler wrong-answer punishment, which fits the lifelong-learning loop the short duel format is built around. For the sibling design-rationale piece, see why LearnClash uses prime-number question counts (37, 43, 47, 53, 89), the round-number tax the prime-count rule sidesteps on top of the retention curve above.

Key takeaway: The retention curve is the moat. The 7-day and 90-day checkpoints are inside Cepeda’s evidence band; the demote-by-one rule avoids ease hell; the 97-day exit makes mastery mean something. Remove any one of the four and the system stops working.

If you want to readWhere to go
The broader LearnClash design (ELO, difficulty, modes)LearnClash statistics page
How ELO-matched wins compound the 7-day SRS checkELO matchmaking & the balanced win-rate band
The spacing-effect history and Leitner-to-Wozniak lineageSpaced repetition foundations
The full nine-method study routine using the curveHow to study effectively
How Quizlet’s “SRS” actually works (it isn’t real SRS)Does Quizlet have spaced repetition?
Why MAG Interactive’s 2026 update wave (Arena, Solo Mode, Events) added zero new scheduled-review loopsLearnClash vs QuizDuel

Explore more learning science: Spaced Repetition: Never Forget What You Learn | Does Quizlet Have Spaced Repetition? | The Testing Effect: Why Quizzes Beat Rereading | How the ELO Rating System Works | All Learning Science Articles

Frequently Asked Questions

What is the LearnClash SRS retention curve?

The LearnClash SRS retention curve plots the percentage of questions a player still answers correctly at each spaced interval. It traces three checkpoints: a 7-day Known check, a 90-day Mastered check, and the point where a mastered card exits the active review pool at around day 97.

Why does LearnClash use 7 and 90 days instead of 1/3/7/21?

The 1/3/7/21 schedule is a fixed calendar heuristic, not performance-based SRS. LearnClash's 3-stage SRS advances cards on accuracy, not time. The 7-day and 90-day intervals sit inside the Cepeda 10 to 20 percent retention-scaling band for short-term and long-term retention.

What happens when you miss a question in LearnClash's SRS?

A wrong answer demotes the card by exactly one SRS stage. A missed Known card drops to Wrong with a 7-day cooldown, not a full reset to day zero. That is gentler than Anki SM-2's ease-factor reduction but more decisive than FSRS's marginal-ease handling.

How is LearnClash's retention curve different from Anki's?

Anki keeps reviewing cards forever using SM-2 or FSRS algorithms. LearnClash retires cards once they clear both the 7-day and 90-day checks: mastered means a sentinel date with no further reviews. The retention curve has a finite endpoint at roughly 97 cumulative days per card.

Does the retention curve hold across difficulty levels?

The curve shape holds, but the height drops with difficulty. Easy questions clear the 7-day check far more often than hard ones, because hard LearnClash questions sit at the recall boundary by design. That is where the testing effect does its strongest work: retrieval that just barely succeeds is what builds durable memory.

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