Every student has made flashcards at some point — a stack of index cards, or a notes app screen split into question and answer. The habit is sound. The part that usually breaks down is deciding which cards to look at today, and for how long. Most students either flip through the whole deck every time, which wastes minutes on things they already know cold, or they only open the deck the night before a test, by which point half of it needs relearning from scratch. We built Review to take that decision away from the student and hand it to a scheduling algorithm that has been doing this job, in one form or another, for decades.
Turning a topic into a deck
The starting point is ordinary. A student picks a subject — say, Biology, or Nepali grammar, or a set of English vocabulary from a chapter — and creates a deck of cards, each with a term or question on one side and the answer or explanation on the other. Decks stay organized by subject, the same way a student's homework and notes already are inside the platform, so a deck for photosynthesis sits next to the notes and homework for that same unit rather than living in a separate flashcard app the student has to remember to open.
None of that is new. Students and teachers have made flashcards by hand for as long as there have been exams. What Review changes is what happens after the deck exists — specifically, what the student sees the next time they sit down to study, and why.
How the system decides what comes back, and when
Each card in a deck carries a small piece of memory: how many times it has been reviewed, how well the student has been rating their recall, and when it is next due. When a student answers a card, they are asked to rate how well they knew it — something close to "I had no idea," "I got it but it took effort," or "I knew it instantly." That rating feeds a scheduling algorithm from the SM-2 family, the same lineage of spacing algorithms used by long-established tools like Anki. A card rated as easy gets pushed further out — a few days, then a couple of weeks, then a month, growing each time it is answered well. A card rated as shaky or wrong comes back much sooner, often the next day, until it has been answered correctly enough times in a row to earn a longer gap.
The result is that no two students are studying the same deck on the same schedule, even if they made it from the same class notes. One student's card on mitochondria might not resurface for three weeks because they have nailed it four times running. Another student's card on the same term might come back tomorrow, and the day after, until it sticks. The deck is shared; the schedule is personal, because it is built from each student's own history of getting that specific card right or wrong.
Why timing the review matters as much as the content
This is not a new idea in learning science, and we did not invent it. The observation that spacing reviews out — rather than massing them together in one sitting — produces sturdier long-term memory has been studied by cognitive scientists for a long time, and it sits inside a broader, well-established body of work on retrieval practice: the finding that actively trying to recall something (as a flashcard forces you to do) tends to build more durable memory than passively re-reading the same material. Researchers sometimes describe this as a form of "desirable difficulty" — the small effort of pulling an answer out of memory, especially right before you would naturally have forgotten it, does more for retention than either cramming everything at once or reviewing on a fixed schedule regardless of how well you already know it.
That idea has shaped a wave of study tools worldwide, from long-running flashcard platforms like Anki and Quizlet to a newer generation of AI-assisted study apps, all trying to automate some version of the same question: given what this specific learner does and does not yet know, what should they look at today? Review sits in that same tradition. We are not claiming a new technique — we are trying to bring a well-tested one inside a school platform a Nepali student is already using for homework and notes, rather than asking them to adopt yet another separate app just to get the benefit of it.
"Due today," not "study everything"
The most visible part of Review, day to day, is a simple view: the cards due today, across all of a student's decks and subjects, in one place. The student does not need to decide which deck needs attention or guess how long it has been since they last looked at a topic. The algorithm has already worked that out from the ratings given on previous reviews, and it surfaces exactly the cards that are due right now — no more, no less.
- A student opens Review for five or ten minutes between classes and clears whatever is due, rather than setting aside an evening.
- A deck built weeks ago for a unit that has since been covered in class does not get forgotten — cards from it still resurface on their own schedule.
- Before a test, the due list naturally includes a mix of old and recent cards, which is closer to how the exam itself will ask questions than reviewing only the newest chapter.
The effect we were aiming for is not a study system that demands more time from students — it is one that asks for a little time, consistently, instead of a lot of time occasionally. A ten-minute daily habit, kept up over a term, tends to beat a four-hour session the night before a unit test, and it is far less stressful to sustain.
The rating is the honest part
The one place this system depends on the student telling the truth is the rating after each card. If a student always taps "I knew it" regardless of how the recall actually felt, the algorithm will push that card out too far, and it will resurface after the student has genuinely forgotten it. We kept the rating options simple and low-pressure for exactly this reason — there is no penalty for saying a card was hard, and the whole point of rating honestly is that the next interval gets shorter and the card comes back sooner, which is exactly what a student who is still shaky on that topic wants.
The deck is shared; the schedule is personal, because it is built from each student's own history of getting that specific card right or wrong.
What Review is not trying to replace
Flashcards are good at one particular kind of learning — recalling terms, definitions, dates, formulas, vocabulary, the building-block facts a subject rests on. They are not a substitute for working through a maths problem, writing an essay, or having a teacher explain why an answer is wrong and not just that it is wrong. We built Review as one tool among several inside the platform, sitting alongside homework help and notes, not as a replacement for either classroom teaching or the kind of practice that requires actually doing the work, not just recalling a fact about it.
The scheduling underneath Review is quiet by design. Students do not need to understand SM-2 or the spacing effect to benefit from it, any more than they need to understand how a car engine works to drive one. What they see is simpler: open the app, a short list of cards is waiting, and clearing it takes a few minutes. The algorithm is doing the harder, less visible work of deciding what belongs on that list — so that studying, over time, looks less like an emergency and more like a habit.