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# Do we really forget 80% of what we learn within a week? LLM Brief

Human page: https://drillster.com/en/blog/did-you-know-80-of-new-knowledge-fades-within-1-week

## Description
Learn what the forgetting curve actually says about memory loss after training and which practices help people retain knowledge and competences. If you want to apply it in your organization, talk to Drillster.

## Content
# Do we really forget 80% of what we learn within a week?

The claim that we forget 80% of what we learn within a week gets repeated because it captures a familiar experience: someone completes training today, then a few days later struggles to explain or apply the key points. The exact percentage is not universal, but the direction of the problem is. When learning is not reactivated, memory fades quickly.

## Where does the idea come from?

The historical reference point is Hermann Ebbinghaus. More than a century later, Murre and Dros replicated his famous forgetting curve and again showed a steep drop in recall shortly after learning ([PLOS ONE](https://journals.plos.org/plosone/doi?id=10.1371%2Fjournal.pone.0120644)).

The important point is not to turn that finding into a rigid slogan. The 80% figure works as a popular simplification, but the real outcome depends on the type of material, the depth of understanding, the context, and whether the learner has opportunities to retrieve what was learned. That conclusion is a reasonable inference from the forgetting curve and later research on memory and learning ([Nature Reviews Psychology](https://www.nature.com/articles/s44159-022-00089-1)).

### The issue is not the exact number, but the speed of decay

In practice, the better question is whether your learning system allows knowledge to decay without detecting the loss until the next course, exam, or audit.

That alone is reason to rethink how training is designed. If critical knowledge cools down until the next review cycle, the organization is not measuring durable recall or sustained readiness. It is mostly observing how close the learner is to the last refresh.

## Why do we forget so quickly after training?

Forgetting does not always mean the training was poor. Quite often it means the brain did what it usually does: it keeps what gets used again and lets go of what is not reactivated.

### Seeing content is not the same as retrieving it

Reading a policy, watching a video, or listening to an explanation can create an immediate sense of progress. That feeling is misleading. The review in [Nature Reviews Psychology](https://www.nature.com/articles/s44159-022-00089-1) and the systematic review by Agarwal, Nunes, and Blunt in _Educational Psychology Review_ show that retrieval practice improves retention more reliably than passive exposure to content ([Educational Psychology Review](https://link.springer.com/article/10.1007/s10648-021-09595-9)).

That is why it helps to combine exposure with effort. When someone has to remember, decide, or explain without looking at the answer, learning moves beyond surface recognition and starts to consolidate. This connects directly to what we explain in [why assessment-based learning strengthens long-term memory](/en/blog/assessment-based-learning-strengthens-long-term-memory).

The same principle sits underneath the Drillster approach. Drillster combines adaptive learning, microlearning, and spaced repetition to reactivate knowledge before it degrades in day-to-day work. If you want a broader view of the model, you can see [how Drillster works](/en/what-is-drillster).

### The brain holds on better to what it needs again

Memory is selective. It holds on better to what reappears, gets used in context, or is tied to a real decision. If a topic is touched only once, the brain receives a fairly clear signal that it is not a priority.

That helps explain why so many organizations confuse completion with readiness. A learner finishes the course, the dashboard turns green, and the report says "completed." That only confirms that something happened at one point in time. It does not confirm that competence is still available when the work demands it.

> Completing a course can close an administrative task, but it does not confirm that knowledge and competences are still available when real work demands them.

## What works better if you want people to remember?

The forgetting curve is reduced more effectively when training reactivates recall several times over time instead of concentrating everything into a single exposure.

### Ask people to retrieve before you show the answer again

When someone has to retrieve an answer before seeing it, the route back to that knowledge becomes stronger. This can happen through short questions, cases, scenarios, or frequent micro-assessments. There is no need to wait for a final exam.

The principle is simple: effort first, feedback after. If you want to go deeper into that method, we explain [what assessment-based learning is](/en/blog/what-is-assessment-based-learning) and why it often produces more usable long-term recall than purely expository content.

### Spread practice over time

The evidence on spacing and retrieval practice points in the same direction: remembering something multiple times over a distributed period generally works better than cramming everything into one session ([Nature Reviews Psychology](https://www.nature.com/articles/s44159-022-00089-1)). This matters even more for critical knowledge, where the real question is not "did they know it yesterday?" but "can they use it correctly two weeks or two months from now?"

Operationally, that usually means three concrete choices:

- **Fewer heavy blocks:** reduce dependence on one-off, overloaded sessions.
- **More short reactivations:** turn review into a brief, repeatable habit.
- **Immediate updates:** when a rule or process changes, reactivate the content instead of waiting for the next annual cycle.

### Design for application, not just approval

If the work requires people to detect risk, interpret nuance, or make decisions under pressure, training should resemble that work. A memory-based test can check recognition. It does not go far enough to demonstrate judgment.

This also changes what it makes sense to measure. Instead of asking only who completed or passed today, ask also:

- **Recall:** can the person retrieve the answer after a time gap?
- **Application:** can they act correctly in a realistic case?
- **Persistence:** does that level hold over time?

This shift avoids another common problem: turning learning into a snapshot. If you want to see why that snapshot is often too weak, this article explains [why certificates are a poor indicator of competence](/en/blog/why-certificates-are-a-poor-indicator-of-competence).

## How do you turn fragile memory into continuous competence?

Many L&D teams already have enough content. The real challenge is having a system that keeps critical knowledge alive and connected to performance. That is where the conversation changes from delivering training to sustaining capability.

### Measure permanence, not just completion

When organizations look only at attendance, completion, or immediate pass rates, they reward the event more than the staying power. That pushes them toward courses that are easy to complete and just as easy to forget.

A stronger system looks at whether knowledge resurfaces at the right moment, whether a person can respond without pre-study, and whether behavior improves on the job. That matters in compliance, safety, operations, sales, and any context where an error may appear later but cost a lot when it does.

In regulated or high-risk environments, the difference becomes visible quickly. A forgotten procedure does not always create an incident the same day, but it does raise the chance of improvisation, rework, or noncompliance when a critical situation appears.

### Where Drillster fits

At Drillster, we help organizations retain **knowledge and competences** continuously. In practice, that means reactivating memory with feedback, spacing, and context so each learner gets reinforcement when it is most needed.

That is why Drillster combines adaptive learning, microlearning, and spaced repetition to support useful recall over time. The goal is that people can remember, decide, and act when the moment arrives.

If you want to review how to reduce forgetting in your training program and keep knowledge and competences available in real work, you can [schedule a free consultation call](/en/request-demo).

## References

- Murre, J. M. J. and Dros, J. (2015). [Replication and Analysis of Ebbinghaus' Forgetting Curve](https://journals.plos.org/plosone/doi?id=10.1371%2Fjournal.pone.0120644).
- Carpenter, S. K., Pan, S. C. and Butler, A. C. (2022). [The science of effective learning with spacing and retrieval practice](https://www.nature.com/articles/s44159-022-00089-1).
- Agarwal, P. K., Nunes, L. D. and Blunt, J. R. (2021). [Retrieval Practice Consistently Benefits Student Learning: a Systematic Review of Applied Research in Schools and Classrooms](https://link.springer.com/article/10.1007/s10648-021-09595-9).
