Description of the Scientific Process: Observation
Observation and Finding a Problem to Study
The first step in doing an experiment is finding your system[1]. Thinking of something specific to study that is interesting to you is often the most difficult part of the process, so you shouldn’t feel like a failure at this step. (Failure comes later.) You need to ask yourself some questions[2].
First, what are you interested in? Do you like a particular field of science the most? This question won’t get you to your experiment, but it will narrow the list of possible experiments down. If you happen to come up with an experiment that is outside of what you think of as your favorite kind of science, though, that’s fine. One of the best things about being a scientist is that our work constantly changes. Let’s say you like biology. That is the study of life, all life. That might be a bit too broad, so you will need to narrow it down. With something like biology, you can do that several ways. You can break it down by the kinds of life you want to study (by taxon, as a biologist would say.) That could lead you to zoology (animals), botany (plants), microbiology (bacteria and other small things), or mycology (fungi). Alternatively, you can break it down by approach: genetics, biochemistry, physiology, anatomy, etc. Preferably, you should do both. Alternatively, you can choose based on application. Consider, for example, cancer research, toxicology, or robotics. You may be limited to whatever your materials allow you to do, and you should accept that as a positive thing, since it narrows your choices.
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A lot of scientific research is performed on model systems. These are well-studied systems that are well-understood, so scientists can control for pitfalls and more easily reference other work. In biology, they are very common, as there are a number of model organisms. While humans can be considered a model organism, it’s hard to design and fill out the paperwork for ethical experiments with people, so experiments are done with Pan troglodytes (chimpanzee) and Macaca mulatta (rhesus macaque). Others include Drosophila melanogaster (fruit fly), Arabidopsis thaliana (a weed), and Escherichia coli (a kind of bacteria), Dictyostelium discoideum (a slime mold), and Caenorhabditis elegans (a tiny worm). In human research, HeLa lines (human cells derived from one woman’s cancer in 1951—it’s a fascinating and compelling story that you should look into) are frequently used, since they have human genes. |
That still doesn’t necessarily give you a project, so here’s another bit of advice: think locally. If you want to do original research for your science fair project, think about what’s immediately around you. You’ll have ready access to local problems. The odds that someone has studied a local kind of rock, organism, or whatever are smaller than if you think about something everyone already knows is big and important. Local quirks about wildlife and geology are often very interesting but unexplored.
Speaking of local, consider what other people have told you. Maybe a friend of your parents mentioned that something was funny about the soil near his home. That might be something to look at. Likewise, you can ask people you know what they think would be interesting to study. Most folks will look at you blankly, but you might get a few people who give you the start of an idea that you can follow.
Instead of asking non-experts, you can look at what the experts say. While a lot of real scientific research is behind a pay wall (paying $25 to $50 for access to a 10-page paper is ridiculous but common) enough of it is available to you for free that you can skim through it. You will be looking through titles that seem really technical or really vague, but you can read the abstracts. When you do so, you are looking for experiments that were done on systems similar to the ones you’re looking at. A scientist did a study on wheat growth relative to clay in the soil. Why not repeat that with a local weed[3]? Look at the scientist’s methodology and repeat it for your weed.
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John’s anecdote: Reading abstracts is something that scientists do all the time. I once had a boss who described his reading of papers as follows:
You could just start by reading the whole paper, but this is more efficient when you’re just exploring the literature. |
One of the most important things to think about at all stages of the scientific process is variation. At this point, think about how your subject might vary against something else that might vary. In the simplest case, you will have some measure that can vary from subject to subject, i.e., the height of a plant, and you will have another measure that you can control, i.e., the amount of water the plant receives. We call the first measure the dependent variable and the second measure the independent variable. You may have several of each of these, and we’ll talk about how to manage those when we talk about experimental design. Right now, you need to think about what different things might vary.
What if you want to examine something that you aren’t controlling? Consider a lake and the soils surrounding a lake. You might find that the soils vary in consistency or type (soil science is a big and complicated field; you can find a lot of job opportunities in soil science, by the way) and that the distance from the lake has a lot to do with that. The soil type would be your dependent variable, and the distance from the lake would be your independent variable. In another experiment on wild plants and animals, both distance from the lake and soil type would be considered independent variables. We call an experiment like this a natural experiment, and it’s something you see frequently in medicine, geology, ecology, and even in social sciences like economics. Natural experiments are often more difficult to perform and noisier[4], but they can shed light on problems that cannot be examined with traditional experiments.
So, you’ve found something you want to test. What next? Can you just jump into your experiment? No! You need to create a hypothesis. The relevant Oxford English Dictionary definition of the hypothesis is, “A supposition or conjecture put forth to account for known facts; esp. in the sciences, a provisional supposition from which to draw conclusions that shall be in accordance with known facts, and which serves as a starting-point for further investigation by which it may be proved or disproved and the true theory arrived at.” But that’s stuffy English professor speech. Here’s what you need to know. Your hypothesis is a reasonable guess of what might be going on with your system that can be tested with an experiment. “I hypothesize that the plant species Taraxacum officinale (common dandelion) will have less biomass when it has less available water,” is a reasonable, if boring, hypothesis. Other examples:
- I hypothesize that plant or microbial communities differ in sites with different amounts of sedimentary rock.
- I hypothesize that the seed of Acer negundo (boxelder) will fall more quickly than the seed of Acer rubrum (red maple.)
- I hypothesize that farmers will be more accepting of controlled burns than city residents will be.
- I hypothesize that beef fat content will decrease in cattle raised in drought conditions relative to normal climatic conditions.
- I hypothesize that the traffic capacity of a local avenue will decrease after a new traffic light is added.
- I hypothesize that different quantities of water and sodium citrate will be needed to emulsify different kinds of cheeses.
- I hypothesize that molded ABS plastic will have higher flexural strength than 3D printed ABS plastic.
- I hypothesize that mutant cyanobacterial cells with defects in their light-capturing antennae will require more light to achieve the same growth rate as normal cells.
So, you’ve got your hypothesis. What now?
[1] The word system will be used throughout this paper. It’s kind of vague, but basically it is the thing that you are studying. It could be the lake in the park, the drought response of Capsella bursa-pastoris (shepherd’s purse), or how four-year-olds respond to the prisoner’s dilemma. It’s a very general term for the thing you are studying.
[2] Note from Andrew: I would say that it is important to think of many possibilities, some of which are certain not to work when you really start to look at them closely!
[3] Don’t do experiments on illegal things here. This is a science fair project, so your research will be publically known.
[4] Noise is a term that scientists use to refer to variations in the data that are not meaningful. It’s like static on an analog radio set. Scientists often refer to separating the signal from the noise. The signal is the meaningful information that you can find in variation. It’s like the music on a radio station. We will talk more about how you can use statistics to separate the signal from the noise in a separate part of this document.