The science of spaced retrieval
NeuroDash is built on a few well-established findings from learning science. None of this is unique to us — what we do is apply it faithfully to clinical reasoning, and keep it low-pressure.
Testing yourself beats re-reading
Pulling an answer out of memory — retrieval practice — strengthens it far more than reading it again. The effort of recall is the learning. This is why every NeuroDash lesson ends in questions you answer before the rationale appears, not a summary you skim.
Roediger & Karpicke, the testing effect.
Spacing beats cramming
The same number of reviews spread over time produces stronger, longer-lasting memory than the same reviews packed together. A little forgetting between sessions is not failure — it is what makes the next recall do real work.
The spacing effect; Bjork's desirable difficulties.
Review just before you would forget
Each fact has a moment where recall is about to slip. Reviewing then — not sooner, not much later — is the most efficient time to reinforce it. NeuroDash estimates that moment per item and schedules the next review around it, so you study less and remember more.
The forgetting curve; modern spaced-repetition scheduling.
The algorithm: FSRS
NeuroDash uses FSRS (the Free Spaced Repetition Scheduler), an open, modern model that predicts when each item is likely to be forgotten from your own answer history and sets the next review accordingly. It is the same family of scheduler behind serious memory tools. We did not invent it; we apply it honestly and keep the schedule visible and forgiving.
FSRS, an open-source spaced-repetition algorithm.