Science has been around for centuries, with records of medicine and natural history going back hundreds and even thousands of years. Indigenous cultures worldwide have developed a rich understanding of the natural world through close observation. For example, indigenous Alaskans have observed thinning sea ice and declining salmon populations, and Aboriginal people in Australia have described the behavior of firehawks, which intentionally spread fires by air-dropping flaming sticks into brush to scare out prey. The word “scientist” has only existed in English since the 19th century, but people from all over the world have been exploring the physical world for a long time. Curiosity about everything around us and within us is the fuel for science, and it includes big questions like what the universe is made of, as well as smaller questions like why does cut grass smell like watermelon. Science can’t answer everything, but it can help us explore the relationships and interactions among living things and their environment. As the process of discovery and knowing science has been formalized with the scientific method, maybe you’ve heard of these six simple steps before:
- Make an observation that leads you to ask a question
- Form a hypothesis (a testable explanation or reasonable prediction of what will happen)
- Test the hypothesis with an experiment that can be repeated
- Analyze the results
- Report the conclusions
- Use the conclusions to make new hypotheses
However, the scientific process does not always follow this idealized version. Instead, it often progresses more like a bunch of looping squiggles that can change direction in ways we don’t even see coming. It is a cycle of testing ideas with evidence and repeating observations to understand cause and effect.
In the middle of the 20th century, biologists started to ask increasingly in-depth questions about life on Earth and how it works on a microscopic scale. The Argentinian biochemist Dr. Louis Federico Leloir and his team wondered if the building blocks of life cells worked the same way outside of an organism as they do inside. To do this, they needed to separate cells from an intact organ and study them.
A huge part of what made the team successful was their collaboration and scrappiness. They had equipment that separates fluids by spinning at high speeds called a centrifuge, but they didn’t have the funds for a refrigerated version. To keep things cold, they filled inner tubes from car tires with water, ice, and salt to create a refrigerating effect. It worked!
Being able to study a cell effectively outside of an organism was a big deal. It allowed scientists, including Leloir, to start asking way more complicated questions about the basic building blocks of life. of a cell membrane into a diagram with arrows and labels that help explain what’s going on
He credited not only the collaboration among his team, but also the ongoing collaborative conversation of science itself. He said, “This is just one step in a much larger project we hardly know even a little.” Bravo so you can see how, in a way, all of science is a team effort. Teams of scientists build on other teams’ work and what’s basically one big ongoing discussion, sort of like that big group text that we mentioned in the opening. Each new observation we communicate adds to the pool of collective knowledge, like each text message building out the larger conversation.
Often a hypothesis gets tested over and over and over again from different angles and then it gets linked up with other hypotheses that are getting tested over and over and evidence for all of them keeps accumulating, like a tiny snowball rolled into a massive snow conclusion… snow inclusion, they’re working on that analogy.
Anyway, that’s how you get a scientific theory. It’s not a theory like your neighbor’s speculation that his cat was King Tut in a former life, but when we use the word theory in a sciency way, that means that the bar for evidence is high. Scientific theories are backed by strong consensus from the scientific community, based on a broad range of evidence, and theories are the basis for studying a subject.
Take the Big Bang Theory, the idea that the universe began with a massive expansion event. There’s still so much to study about the theory of the Big Bang, like the study of leftover energy from the expansion of the universe, and more and more research is being done all the time, spurring more testable hypotheses that add depth to the theory.
New theories are always being revised whenever enough new evidence piles up that doesn’t support them in their current state. And then there are laws, very precise universal statements describing something that always happen in the physical world. For example, the first law of thermodynamics says energy cannot be created or destroyed, and it applies to everything including life. Energy takes different forms as it passes through plants and animals and soil, but the total amount of energy stays the same.
For any scientific idea to become a theory or a law, it needs to be backed by a groundswell of evidence. Scientists decide how much evidence is enough and what it all means through a process called peer review. Scientists will submit their research by writing up what they hypothesized, how they tested it, and what happened. But before their work makes it to the wider world, it gets checked by their peers, other scientists who are also experts in their field. Peer review isn’t perfect, but it’s a really important way of catching mistakes or even outright fraud before papers make it out into the wider world.
That means the world’s experts on platypuses are discussing and reading other platypus experts’ work before it even gets published, and you can bet that group chat is fire. It’s critical that the world scientists reviewing and interpreting this research have high data literacy, that’s an ability to create, organize, understand, and communicate data, which are recorded observations.
Data literacy enables scientists to design experiments that collect reliable data and actually answer the questions they want to ask, and when it’s time to analyze the results, it helps them accurately interpret and understand what the data mean, whether that’s their own research or someone else’s.
And to help them interpret the data, scientists use models to try multiple ways of testing and understanding ideas. Not that kind of model, these kinds of models consider the cell membrane, a thin layer holding together the cell’s squishy parts. It is possible to directly observe cell membranes under a microscope, which is amazing, but there’s a lot happening in that tiny world, three different kinds of molecules wiggling in perpetual motion.
Models, which are representations of scientific theories or processes, can help clarify what’s going on. For example, a visual model can turn a microscope pic of a cell membrane into a diagram with arrows and labels that help explain what’s going on.