In Science, the “How?” is Just as Important as the “What?”
This one science experiment in elementary school is burned into my brain. Our teacher asks us to determine whether or not a bean sprout needs light to grow. In response, we each write down our version of the “If… then…” hypothesis statement. “If we take away the plant’s light, then it won’t grow.” And then we set up our experiment, placing one plant by the windowsill, in the sunlight, and another in the closet, the door shut, where light can’t reach it.
Before I got to college, I always thought of science in that same way I was taught in elementary school. Scientists have a question about some piece of the universe, and then they set out, their hypothesis, that “If… then…” statement in tow, in search of better understanding. They set up their experiment, they wait for their results, and then they have their answer.
I never gave a second thought to the tools they needed to answer their question, let alone where those tools came from. If we think back to that elementary school experiment, the tools needed to answer the teacher’s question and our hypotheses are easy to find: a couple plants, sunlight, a closet. But what happens when the tools we need aren’t available yet?
Some scientists spend their careers building those tools. This type of science, method development, is essential to scientific progress. Don’t just take my word for it though; take it from the Nobel Prize committee: about 1 in every 6 Noble Prizes in the sciences has been awarded for the development of a method.
And yet, our scientific education almost never taps into method development. Instead, we are constantly taught the what’s of science. What do we know about gravity, about our bodies, about the periodic table of elements? We don’t usually discuss how we arrived at the answer, or what tools we needed to answer them. If we do, it’s not what students are taught to care about. After all, the how, unlike the what, almost certainly doesn’t appear on a test.
Gabriella Reggiano works in a computational structural biology lab, a fancy way of saying she spends her time at a computer, writing a bunch of code and looking at a lot of protein models. Unlike most scientists, her goal isn’t to answer a fundamental question about the universe, but to develop a method that will make it easier for scientists to understand how proteins move, so they can answer whatever questions spark their curiosity (as long as they’re about proteins).