At first, students learned foundational fire science — heat transfer, fuel loads, and topography. We built small-scale models to visualize how a fire reacts to changes in slope and wind.
Students also tested different vegetation models to see how fuel type changed burn rate. We gathered local samples of grass, leaves, and branches, dried them, and recorded how quickly they ignited. From there, we began comparing real data to digital simulations.
Not everything worked. One group’s digital simulation crashed repeatedly during our first demo. Another group discovered that their data set included inaccurate wind readings, throwing off an entire week’s worth of modeling.
Instead of giving up, we learned new habits: verifying data before running a model, saving backup versions, and sharing problems early instead of trying to fix them alone. These setbacks became part of the story — they showed that real science is full of uncertainty, iteration, and teamwork.
The most powerful feedback came from outside the classroom. Captain Ortega from the local fire department told us, “You’re looking at things we don’t always have time to dig into. That helps us see our work from a new perspective.”
Community members who attended our final presentation shared personal stories about living through evacuations and losing property. Their openness helped us see the emotional dimension of this work — the human side of data and models.
Our mentors reminded us that listening is a kind of science too. It shapes what questions we ask next.
By the end of the year, students didn’t just understand how fires behave. They saw how learning itself can be a form of service.
We grew more confident asking questions without easy answers, taking responsibility for accuracy, and communicating findings publicly.
Many of us now see science as something alive — something that connects curiosity to care.
One reflection summed it up best: “We started studying fire. We ended up learning what it means to protect what matters.”