Understanding the Scientific Method Improves Science Fair Projects
The title of this blog, Understanding the Scientific Method Improves Science Fair Projects, is also a hypothesis. We will discuss how to test it below.
While tremendous emphasis is placed on the concept of scientific hypotheses in precollege science education, there is an amazingly wide variety of interpretations of what exactly they are and how to use them. Even the scientific method itself can be found to differ slightly from reference to reference on an Internet search. This is probably reasonable, since each practicing scientist has her/his own view of these matters and conducts their original scientific investigations with a unique style. There are undoubtedly many different legitimate ways of considering the scientific method. However, for students in the K-12 system, it is best to settle upon a given approach and stick to it, rather than introducing variations from grade level to grade level.

At the heart of the scientific method is the ability to state a hypothesis, make testable predictions based on the hypothesis, and identify the important variables. As you will see below, we have chosen a method of approaching the issue of hypothesis, prediction, and variables with a two step, rather automatized, system that many teachers and students we have worked with have found useful. First, the hypothesis is presented as a simple statement. Second, a prediction is constructed in which the hypothesis and the independent and dependent variables are embedded in an “If > then” formulation. It is quite easy to learn.
Observations
One of the key features of modern experimental science is that an idea must always be tested. Testing an idea means that someone has an hypothesis and then goes about testing his or her prediction about the hypothesis by exploring which variables need to be considered. To do this, we also need to consider why someone would be making a hypothesis or prediction in the first place. Usually, this occurs because someone makes an observation and wants to explain or understand it further.
What is an observation and what might someone observe? Think about observations as things you notice about the system you are studying. For example, what are its parts, why is it of interest, what are potential variables? Most people make observations about phenomena they experience or about data they view from an event. It’s then almost inevitable that someone asks how the thing he or she observes (one variable) is related to something else he/she observes (other variables). That person may also question what might happen if he/she begins to make changes in the variables.
Let’s take an example and assume someone was observing a phenomenon such as the construction of a circuit. They may observe that a circuit includes batteries, wires, and resistors and that an electrical current travels through the circuit. The resistors and other components provide resistance to the flow of electrical current. The batteries provide a source of voltage for the circuit. (Note: It is not necessary to understand the concept of a circuit, resistance, or voltage at this time, we are only using circuits as an example.)
Questions that result from these observations about circuits might be:
- What would happen if the voltage of the circuit changed?
- Does a change in the voltage produce a change in the current of the circuit?
- Do changes in resistors change the current in a circuit?
Variables
The questions above can help us to determine the variables of an experiment. One way to think about variables is to consider how different properties, pieces of data, or observations are related to each other. If we take the last two questions above, we can highlight the variables:
- Does a change in the voltage produce a change in the current of the circuit?
The variables are voltage and current.
- Do changes in resistors change the current in a circuit?
The variables are resistors and current.
Hypotheses and Predictions
Hypotheses and predictions are often ways to propose and test a relationship between variables. A hypothesis is a statement, NOT a question about observations or the relationship between variables. For example, from our observations and questions above, one hypothesis might be: Current is related to resistance. Notice that this is a simple statement.
A prediction is a statement that presents the relationship between variables in a hypothesis in a way that can be tested. One easy way to think about predictions is to consider them as “If-then” statements that include the hypothesis.
Let’s take our hypothesis from above as an example. Using that hypothesis, one prediction might be: If current is related to resistance, then changing the current would change the resistance.
Putting It All Together
Now that we’ve looked at variables, hypotheses, and predictions individually, let’s try to see if we can identify each of these when they are put together. The paragraph below describes a situation in which a girl made some observations and then created an experiment to test her observations.
Julia had a pet lizard. She observed that it did not feel the same temperature all of the time. She thought that the lizard’s body temperature is directly related to the air temperature. Julia proposed that if the lizard’s body temperature is directly related to the air temperature, then increasing the air temperature will increase the lizard’s body temperature.
Let’s see if you can identify the variables, hypothesis, and prediction in this example. Take a moment to reread the paragraph above. Then look below to find the answers. In the paragraph below, the hypothesis is italicized; the variables are in bold, and the prediction is underlined.
Julia had a pet lizard. She observed that it did not feel the same temperature all of the time. She thought that the lizard’s body temperature is directly related to the air temperature. Julia proposed that if the lizard’s body temperature is directly related to the air temperature, then increasing the air temperature will increase the lizard’s body temperature.
Julia asked her Mom for help. They placed the lizard in cages of different temperatures for a day and then measured its body temperature. The table below shows the data.
|
Air Temperature (oC) |
Body Temperature of Lizard (oC) |
|
15 |
14 |
|
20 |
21 |
|
25 |
24 |
|
30 |
30 |
Look at the data. You should see that as the air temperature increased, the body temperature of the lizard increased. This suggests that Julia’s prediction was true. She predicted that increasing the air temperature would increase the lizard’s body temperature. The data from the table is consistent with this prediction.
In addition, Julia’s hypothesis was proven by her results. The body temperature of the lizard is directly related to the air temperature.
Back to the Beginning (Hypothetical Experiment Only: Don’t Perform with Your Class!)
Now we can get back to the title of this blog and apply what we have learned about hypotheses, predictions, and variables to the issue of the scientific method and science fair projects.
Hypothesis: Understanding the Scientific Method Improves Science Fair Projects
Prediction: If understanding the scientific method improves science fair projects, then teaching students the scientific method will improve the quality of their science fair projects.
Variables: 1) learning the scientific method and 2) science fair performance
Experiment: Fifteen students (experimental group) were thoroughly taught the scientific method with emphasis on what a hypothesis, prediction, and variables are and how to use them. Another fifteen students (control group) were not taught the scientific method. Students were randomly assigned to the two groups. Both groups prepared science fair projects. At the science fair, judges rated all 30 of the projects on a scale of 1 (poor quality) to 10 (high quality). After the fair, an average score was calculated for both the experimental and control groups of contestants. The following are samples of potential results that could be obtained from this experiment:
Results – Scenario One:
| Average Science Fair Score | |
| Experimental Group | 9.6 |
| Control Group | 6.1 |
Results – Scenario Two:
| Average Science Fair Score | |
| Experimental Group | 6.0 |
| Control Group | 9.1 |
Results – Scenario Three:
| Average Science Fair Score | |
| Experimental Group | 7.7 |
| Control Group | 7.8 |
Consider the three different types of results presented in the three scenarios above and the likely conclusions that may be drawn from them:
In Scenario One, the group that was taught the scientific method (experimental group) scored better on their science fair projects, on average, than the group that was not taught the scientific method (control group). This scenario agrees with the prediction and tends to support the original hypothesis. The hypothesis would be correct.
In Scenario Two, the experimental group scored lower on their science fair projects, on average, than the control group. This scenario disagrees with the prediction and therefore does not support the original hypothesis. The hypothesis would be wrong.
In Scenario Three, the experimental group and the control group scored about the same. This scenario does not agree with the prediction and does not support the original hypothesis. The hypothesis would therefore be wrong again.
Based on the three potential outcomes of the experiment we see that two of the three outcomes (Scenarios Two and Three) suggest that the original hypothesis is likely incorrect. Only one of the potential results (Scenario One) agrees with the prediction and supports the original hypothesis!
This is a good experiment because regardless of the results we will learn something about the involvement of understanding the scientific method on science fair performance.
Summary
Hypotheses, predictions, and variables are important because they present a way to think about, test, and potentially solve a problem or answer a question. Whether you are conducting experiments to determine causes of an oil spill, factors involved in increasing the efficiency of an internal combustion engine, or the effect of certain velocities of impact on human brain concussions, understanding the relationship between hypotheses, predictions, and variables can help you comprehend and apply your data.







