Struggle first. Then it sticks — and it travels.
Our simulations are built on a learning method called productive failure: students wrestle with a real problem before they're taught the solution. In a peer-reviewed PhD study, students taught this way didn't just learn the topic — they could take the way of thinking and apply it to brand-new problems they were never taught.
How the two groups scored on a brand-new problem they were never taught — productive-failure students vs. traditionally-taught students, on a 0–3 scale.
The students who struggled first were clearly better at reasoning through problems they'd never seen before. Researchers call this far transfer — the hardest, most meaningful test of whether learning actually sticks — and the gap was big enough to matter, not a statistical fluke.
Both groups learned the topic itself equally well. The difference showed up where it counts most: taking the thinking somewhere new.
What is productive failure?
Two ways to teach the same lesson. The order is the whole difference.
Direct instruction
Teach the concept first. Then students practice.
Students often recognize the answer — but reach for it only in the situation they were shown.
Productive failure
Students explore the problem first, hit the limits of what they know, then get the instruction that clarifies it.
The early struggle is the point: it primes students to understand why the solution works — not just that it does.
Decades of research across science and social-science classrooms point the same way: when students grapple before they're told, they transfer what they learn further. Our simulations are the "grapple first" engine.
This isn't a hunch. It's a dissertation.
The method behind Learn in Labs was tested in a doctoral study at the University of Sydney (2025). Undergraduate medical students learned about epidemics and complex systems using interactive agent-based simulations — the same kind of hands-on, manipulate-the-variables models our platform is built on.
One group learned by productive failure: explore the simulation first, instruction after. The other learned the traditional way: instruction first, then the simulation. Everything else — the content, the models, the tests — was identical.
It's an early, focused study, not a cast-of-thousands trial. What makes it compelling is the size of the effect and that it lines up with decades of prior research in other fields.
They learned the topic. Then they took the thinking with them.
Here's the part that should matter to any school.
On the topic itself — recalling and explaining the material — both teaching methods worked about equally well. Productive failure didn't lose anything.
But on transfer — applying the underlying way of thinking to a completely different, untaught problem — the productive-failure group pulled clearly ahead. They'd built something more durable than facts about epidemics: they'd built systems thinking — the ability to see how parts interact, how feedback loops and tipping points work — and they could carry it into new territory on their own.
That's the whole promise of a great education in one sentence: don't just learn the lesson — learn a way of thinking you can use everywhere else. The evidence says productive failure does exactly that.
Why simulations, specifically?
Productive failure needs something for students to struggle with — a problem rich enough to explore, safe enough to fail at, fast enough to show consequences. A worksheet can't do that. A lecture definitely can't.
Interactive simulations can. Students change a variable and watch the whole system respond — push the infection rate, drop the ICU capacity, watch the curve bend. They form a hunch, test it, get it wrong, and adjust. That loop — try, fail, see why, try again — is productive failure, made visible.
Safe to fail
Students experiment freely. A wrong guess in a simulation costs nothing — and teaches everything.
Consequences in real time
Change a variable, watch the system respond. Cause and effect become something you can see, not just memorize.
Thinking that transfers
Wrestling with how a system behaves builds the kind of reasoning students can carry into any subject.
See what struggling-first looks like.
Run a real simulation yourself — no account, no credit card. It's the same experience your students get.
Source
Al Hinai, R. Z. (2025). Productive Failure and Learning about Epidemics and Complex Systems in Medical Education (Doctoral dissertation). Faculty of Arts and Social Sciences, School of Education and Social Work, University of Sydney.
Read the full dissertation →Key results: on far (across-domain) transfer, the productive-failure group significantly outperformed the direct-instruction group, t(33) = 4.17, p < .001, d = 0.65 (Bayesian BF₁₀ = 116, "decisive"). On near (within-domain) transfer, the productive-failure group made significant pre-to-post gains (p < .001, d = 0.67) while the direct-instruction group did not. Both groups gained comparably on declarative and explanatory knowledge of the topic itself.