SquareCat
Miles Corran · 
Streaks, badges, leaderboards and games are on most wish lists for a learning app, and for good reason. They give people a reason to come back tomorrow. But every one of them is a reward, and a reward teaches people what to do. If the quickest way to earn it is to cram, guess or replay the easy bits, that’s what people will learn to do.
The question to ask of any game mechanic isn’t “is it fun?” but “what does it reward?” Here’s how we’ve answered that in our own products.
A game where knowing the cards wins
Brain Defense is a tower defense game for Braineos. Enemies walk a road, you build towers beside it, and the gold for towers comes from answering questions from the deck you’re studying. We’ve written about how we balanced it. The short version is that we set a contract before anyone playtested:
- someone who knows the cards should win;
- someone who ignores the questions should lose;
- the middle should feel like a fight.
A scripted bot then played whole games at different accuracies. In simulation, a bot that answered nothing right lost on wave 6 every time, and a bot answering 70% or more right won every run. That table is a test in the build, so a change to the game’s numbers that breaks the contract fails the build.
The learning shows up in smaller choices too. A missed question comes back a few questions later, so a run spends more time on what you don’t know. Cards with long, sentence-length answers are left out of the game, and the game says how many, because they make bad buttons. And relaxed mode slows the game down rather than pausing it, which gives people time to read.
Don’t let the game game the app
Braineos has a streak and a weekly leaderboard. A game inside it shouldn’t become the fastest way up either. So a finished run records one score: the number of different cards answered right at least once. That can never be more than the deck has, which is the same ceiling as a study session. Playing the same easy deck over and over doesn’t pile up points.
Play also doesn’t touch the spaced-repetition schedule. Fast, partly guessed multiple-choice answers would make it noisier, so reviews still come from studying. The game is a way to practise, not a way to skip the practice.
Badges for things that already happened
Braineos has eight badges, each with up to four tiers from Bronze to Platinum. We wrote about how they work, and one choice matters most for anyone commissioning a learning app: nothing stores badge progress. Every badge is worked out from what the learner has actually done, such as their streak, their review count, the decks they’ve mastered and their challenge results.
That has two benefits beyond tidiness. The numbers can’t drift out of step with reality, because there’s no second copy to drift. And it makes “how close am I?” free: the same rule that awards a tier drives the Next up bars on the Progress page, so learners can see what their next bit of practice is worth.
When we launched badges, existing learners had their past study counted, and those badges were awarded silently. People who had studied for months didn’t start with an empty trophy case, and nobody got a pile of pop-ups on launch day.
Different products reward different things. Each site on our platform chooses its own list of badges. Braineos rewards things like deck creation and having your decks studied by others. CertBrain, where learners take courses rather than make decks, has its own list planned around courses and practice readiness, not switched on yet.
When cramming looks like mastery
The trickiest version of this problem isn’t in a game at all. It’s in the scoring underneath.
Building CertBrain’s Readiness page, which scores each exam domain from spaced-repetition data, we noticed the data could lie. Studying a deck again with “Study anyway” moved every correct card up a review box, even when it wasn’t due. An afternoon of cramming could push a card to a 30-day interval without a single real gap. For a readiness score, that meant cramming would read as mastery.
The fix: a right answer on a card that isn’t due yet now leaves its schedule alone. A wrong answer still resets it, because forgetting is real information whenever it happens. We’ve written up the whole readiness score, and it’s a good example of a rule we keep coming back to. Anything that rewards progress is only as honest as the data it reads.
Questions to ask of any mechanic
If you’re planning game features for a learning product, these are worth asking about each one:
- What earns the reward? Is it learning something, or just doing something a lot?
- Is there a ceiling? Can someone farm it by repeating what they already know?
- Does it touch the learning data? Fast or guessed answers shouldn’t change what the app believes someone knows.
- Can it be worked out from what already happened? Then it can’t fall out of step.
- What does a learner who ignores the content get? Ideally, not much.
Getting these right is mostly a matter of deciding early, before the mechanics are built. If you’re planning streaks, badges or a game for your own learning product, our education apps page explains how we work, or you can tell us what you have in mind.
