Hermann Ebbinghaus: the first researcher to measure forgetting
Hermann Ebbinghaus (1850–1909) was the first psychologist to study memory experimentally and quantitatively. By using lists of meaningless syllables as learning material—to remove familiarity effects—he measured retention rates at different intervals after learning.
His results, published in 1885 in Über das Gedächtnis (On Memory), revealed two foundational findings still valid today: the forgetting curve and the spaced learning curve.
What the curve actually shows
The forgetting curve is a decreasing exponential curve. It describes how fast information fades from memory when no review occurs:
- After 20 minutes: about 42% is already lost
- After 1 hour: about 56% is lost
- After 24 hours: about 67% to 70% is lost
- After 1 week: about 75% is lost
- After 1 month: about 79% is lost
These numbers concern information learned once, with no review at all. They are striking—but they do not mean the situation is hopeless.
Ebbinghaus obtained exact percentages with artificial material (nonsense syllables). With meaningful content—courses, vocabulary, concepts—the curve is less steep because meaning supports encoding and associations. The overall shape stays valid, but percentages are usually less severe in real learning contexts.
The curve logic: why forgetting accelerates early
The drop is especially fast in the first hours after learning. This is linked to short-term memory dynamics: recently encoded information is temporarily stored in the hippocampus. Without consolidation—mainly happening during sleep—it starts degrading quickly.
As time passes, the curve “flattens”: memories that survive the first hours are relatively more stable. But that stability remains fragile without periodic reactivation.
The concept of “memory strength”
Later research introduced the concept of memory strength: strongly consolidated information resists forgetting better and requires much longer review intervals. Poorly consolidated information decays rapidly.
This concept underlies modern spaced-repetition algorithms: they estimate each memory's strength and schedule the next review accordingly.
How review “resets” the curve
Ebbinghaus's most useful finding is not the forgetting curve itself, but what he observed about review effects. Each time you review, several things happen:
- Retention rises again—sometimes near 100% if review happens early enough
- The curve slope softens—the information will fade more slowly after this review than after first exposure
- The optimal interval before the next review increases—so you can review less often while maintaining the same retention level
This is the core mechanism of spaced repetition: exploit forgetting-curve dynamics to maximize retention with minimal reviews.
Reviewing too early (while retention is still very high) is inefficient: the memory is already strong, so the added gain is small. Reviewing too late (after memory collapse) forces near-relearning from scratch. The optimal interval is when retention starts dropping meaningfully—typically around 70% to 90% retention depending on the study.
Ebbinghaus and modern algorithms
Ebbinghaus's work directly inspired spaced-repetition algorithms developed from the 1970s onward. Piotr Wozniak, creator of SuperMemo, formalized optimal intervals in the SM-2 algorithm, still the base for many flashcard apps today, including Anki.
More recently, FSRS (Free Spaced Repetition Scheduler) refined this model by integrating newer cognitive findings—especially memory stability and perceived card difficulty. Results show significantly better interval precision than older algorithms.
Applying the forgetting curve in daily practice
Understanding the forgetting curve changes three behaviors in practice:
1. Review quickly after first learning
The first review should happen quickly—ideally within 24 hours, and certainly before the end of the week. This is where the curve drops fastest, so review has the greatest relative impact. A quick evening pass over notes can cut information loss dramatically.
2. Avoid massed review right before an exam
Cramming creates short-term fluency but very weak retention after 48 hours. Content reviewed all at once the night before follows the forgetting curve from the next day—with a rapid, predictable drop.
3. Accept partial forgetting as normal—and useful
A partially forgotten memory reactivated just before disappearing consolidates more strongly than one reviewed while still very fresh. Partial forgetting is a condition for durable memorization, not an obstacle.
A Cepeda et al. (2009) study analyzed optimal intervals across thousands of question-answer pairs and confirmed that spacing should grow exponentially with successful repetitions. Their model predicts that after one learning event, the ideal delay before first review is one to two days—not a few hours, not a week.
Cepeda et al. (2009), Optimizing Distributed Practice, Experimental PsychologyFrequently asked questions
It applies to declarative learning—facts, vocabulary, concepts, dates. The slope varies with meaning, attention during encoding, and associations. For procedural learning (motor skills, automatisms), forgetting is usually less steep—skills resist time better.
Yes. That is exactly what spaced repetition does over time. With enough well-spaced reviews, intervals can stretch to months or even years. Some highly consolidated memories seem to resist forgetting indefinitely, though the notion of truly permanent memory remains debated.
It depends on complexity and spacing quality. In many cases, 4 to 6 well-spaced reviews are enough to stabilize memory for months. With an SRS algorithm, this happens naturally without manually calculating intervals.