What Is the Forgetting Curve? Ebbinghaus's Discovery, Explained

Short answer. The forgetting curve is a graph showing how memory of new material decays over time without review. Hermann Ebbinghaus first plotted it in 1885 by memorizing and re-testing nonsense syllables; the basic shape has been replicated and extended ever since.

What the curve shows

Without any review:

The exact numbers vary by material type, prior knowledge, and individual differences. The shape — fast early loss, slower decay later — is consistent.

Why this matters

If you study a chapter once and don't review:

The fix: spaced review

Each review at the right interval flattens the curve. Modern algorithms (FSRS, SM-2) schedule reviews just before predicted forgetting — extending the "stability" of each memory item.

Without spaced review, the forgetting curve dominates and most study time is wasted. With spaced review, the same total time produces dramatically more retention.

Caveats and modern updates

The original Ebbinghaus curve used nonsense syllables — a worst-case for forgetting. Real-world meaningful material (chapter content, language vocabulary, medical facts) shows somewhat slower decay, especially when connected to prior knowledge.

The curve also isn't fixed: deeper encoding (using active recall and elaboration), better sleep, and emotional salience all flatten it independently of review schedule.

Ebbinghaus's experimental method

Ebbinghaus was both the experimenter and the only subject — he memorised lists of 13-letter nonsense syllables (DAX, BAP, REK, etc., chosen to avoid prior associations), then re-tested himself at varying delays, measuring how many additional repetitions he needed to relearn the list to the original criterion ("savings"). The fewer the relearning repetitions needed, the more memory had been retained. He ran this on himself for over a year. By modern standards the methodology is single-subject and not generalisable on its own, but the basic shape of the curve has been replicated under stricter conditions ever since.

What changes the slope

Memory decay is not a single number — it's a curve whose slope depends on:

How modern tools fight the curve

FSRS, SM-2, the Leitner system, and SimpleQuizMaker's review queue all do roughly the same thing: predict when each fact will reach a critical threshold of forgetting, then prompt a review just before. Each successful review flattens the next decay slope. Stack 4-6 well-spaced reviews and you go from 5% retention at 30 days to 90%+ retention at 6 months — same total time, dramatically different outcome.

Related reading

Ebbinghaus and the original data

Hermann Ebbinghaus published *Über das Gedächtnis* in 1885 — the first systematic experimental study of human memory. He memorized lists of nonsense syllables (CVCs like "WID", "ZOF") and tested his own recall at intervals from minutes to days.

The pattern that emerged: retention drops sharply in the first 24 hours, then decays more slowly. Specific numbers from his data:

These numbers are imperfect — small sample (one researcher), nonsense syllables don't transfer perfectly to meaningful material — but the shape of the curve has held up in hundreds of replications. The exact retention percentages vary by material type and individual, but the steep early drop followed by slower long-term decay is universal.

Why the curve looks the way it does

Two mechanisms compound:

Both processes are non-linear. The biggest losses happen early because that's when reinforcement is most likely missing and interference is most aggressive. Material that survives the first 24-48 hours has, by definition, gotten some kind of consolidation already.

How review reshapes the curve

Each successful retrieval flattens the curve:

The math behind modern spaced-repetition algorithms is essentially: schedule the next review just before the curve drops too far, but as late as possible to maximize efficiency.

Practical implications for study schedules

Why the curve matters for content design

If you're designing training (educator, L&D pro, instructional designer), the curve has implications:

Tools that fight the curve

Try a study workflow built around fighting the forgetting curve.