It’s time for the annual homeschool science fair. You groan inwardly, as you envision a room filled with baking soda volcanoes, potato clocks, and bar graphs representing the efficacy of various brands of laundry detergent. Yes, these projects are clichéd. But at least the kids are learning, right? Right? RIGHT???
Well, sort of. They are learning how to create colorful posters and shop for the perfect professional, clear plastic binder to impress the judges. Unfortunately, they may not be learning much about good experimental design and careful science.
So here are six simple tips from a theoretical chemist and homeschooling father of four for designing a project that will help your kids learn and appreciate fundamental scientific principles.
Ask a real question; form a real hypothesis
My wife and I homeschool through Classical Conversations and they do a good job hammering home this first point: the scientific method starts with a question and leads to a hypothesis. Unfortunately, this framework does not ensure that students ask good questions or form good hypotheses. Johnny’s mother might admonish him that he needs to ask a question and form a hypothesis about his baking soda volcano. But Johnny will merely ask the question; “What happens when I mix baking soda and vinegar?” And his hypothesis will be: “I hypothesize that it will produce a boring, 7th-grade science fair project.”
Good science depends on asking good questions, real questions, questions which are genuinely interesting and for which the answers are not clear. A good question should elicit a quizzical “hmmm”, not an eye-rolling “duh.” Similarly, a good hypothesis will not be obviously true or obviously false. So Johnny could ask “How does temperature affect the rate of the ‘vinegar plus baking soda’ reaction?” Or “How much vinegar is required to neutralize 10 grams of baking soda?”
Isolate your variable
Most people recognize the importance of using a single independent variable in their experiments. In other words, the experimenter should vary one and only one factor (the independent variable) and then measure the result (the dependent variable). For example, a student who wanted to know which flour produced the best muffins should use precisely the same muffin recipe except for the type of flour (independent variable) and then should try to determine which batch of muffins is the best (dependent variable).
Yet here, students often don’t appreciate just how hard it is to isolate a single independent variable. Take the preceding example. Is it really possible to vary only the type of flour used? What other variables are inadvertently altered from batch to batch? Is each batch mixed for the same amount of time? Does every egg have exactly the same volume and does it contain exactly the same proportion of yolk and white? How stable is the temperature of the oven? Was the muffins’ flavor affected by your toddler dropping his pacifier in the batter and then fishing it out with his feet? What originally looked like one independent variable actually turns out to include dozens of factors which vary, often uncontrollably.
List potential sources of error
The difficulty of isolating a single, independent variable makes it important to include potential sources of error in the summary of your experiment. This disclosure is a crucial part of real scientific papers. A scientist doesn’t merely explain why they think their conclusions are correct, but also lists the ways in which errors may have crept in.
When you’re writing up your project, ask yourself: what are some of the variables that we couldn’t control? What are potential limitations of our set-up? Are there other ways to interpret our results? If you had better equipment (Ahem, NSF/NIH/NASA, hint hint), what could have been improved? Providing thoughtful answers to these questions is key.
Build in repeatability
Repeated measurement is a crucial component of good science and, as a CC judge, I was told to award students points for taking multiple measurements. Unfortunately, they received full credit for performing only five measurements. This criterion is as lax as requiring students to do five jumping jacks to pass a Physical Education course. Ideally, real measurements can be performed hundreds or thousands of times, depending on the difficulty of the experiment. Since a student can’t bake thousands of muffins, it’s therefore crucial to choose experiments that can be repeated quickly and easily.
For example, questions like “How many coin flips will it take, on average, before I get three tails in a row?” or “How accurate are the reported weights of Oreos?” or “How long does it take an object to fall 10 feet?” all require experiments that can be quickly replicated. Students don’t need to perform a sophisticated, mathematical error analysis, but they can still grasp how taking the average over a large number of measurements is more accurate that taking one or only a few measurements.
Do objective, quantitative measurements
Math is the language of science which means that, whenever possible, observations should be quantitative rather than qualitative. Don’t ask: “Does a plant fertilized with Pepsi grow ‘fast‘ or ‘slow‘?” Instead ask: “If we fertilize a plant with Pepsi, how many centimeters per day does it grow?” So far, so good.
Unfortunately, after seeing a number of students quantify muffin “tastiness” on a scale of 1 to 10, I realized that they didn’t understand the importance of measuring objective properties. In other words, your measurement should not depend on the particular tastes or subjective standards of the person doing the measuring. As a rule of thumb, measurements that involve units (e.g. inches, meters, grams, seconds, degrees Fahrenheit, etc…) are objective. Thus, statements about height, weight, volume, and time are objective, while statements about “tastiness,” “quality,” and “convenience” are not.
Finally, too many students don’t take advantage of the incredible technology now available to them in the form of smart phones and other ubiquitous electronic devices. Imagine you wanted to determine the angle at which you should launch a Nerf dart to maximize its flight time. You’ll obviously need to launch the dart multiple times at multiple angles and record its flight time. But too many students will simply use a stopwatch to time the flight, so that the accuracy of the measurement will be limited by their dexterity in turning on and off the timer. Instead, why not simply use a smart phone to record the entire experiment? The students can then carefully parse the video frame-by-frame to determine the exact start time and end time for each flight.
Available technology can be used in many other ways. Do you want to measure which detergent makes your socks the whitest? Take a photo of the socks and use your computer to determine the brightness of the pixels. Are you trying to determine how well pillows and ear plugs muffle the noise of your sister’s clarinet practice? Download an app that allows your phone to measure decibels. The accuracy of your measurements can often be improved by an order of magnitude with nothing more than a phone and a little creativity.
Three closing thoughts.
First, most of the advice I’ve given pertains to experimental design, not experimental technique or analysis. That’s intentional. A famous dictum among chemists is “An hour spent in the library is worth a month in the laboratory.” All the enthusiasm and hard-work in the world can’t offset a poorly planned or fundamentally flawed experiment. So take your time thinking about your project, brainstorming sources of error, and trying to improve your design before hammering, duct-taping, or mixing.
Second, keep it simple. It’s great if your kids ask a question like “How can we design a more efficient battery?” They may even dig up a complicated experimental design on the Internet. But if they try to do too much, they’re likely to fail. More importantly, they may learn less than they would have if they started small because they’ll spend all their time at Radio Shack (do those even exist anymore?) trying to decode the output of their $200 multimeter. In contrast, simple experiments lend themselves beautifully to teaching basic concepts.
Finally, don’t emphasize winning; emphasize learning. Truth be told, science fair judges may indeed be more impressed by a flashy poster and a slick presentation than by solid science (wait until your kids find out about how grant committees and funding agencies work). What matters most is giving your students exposure to science and training them in how to think scientifically.
Good luck and have fun!