The experiment can either make or break your science project. This is the backbone of the project, and you must put sufficient thought and preparation into it. You should plan to spend most of your time on a feasible experiment after researching. Your research should involve a practical application that includes measurements, analyses, or tests to answer a specific question. Judges look for these individual qualities and will be distracted if your project contains irrelevant facts and data.
Above all, make sure that the work you do follows the scientific method. Judges often see projects that are researched thoroughly and presented in a neat, attractive manner, only to find that they merely present a wellknown idea, model, collection, or display that the public has seen too many times. Such exhibits are not experiments but mere demonstrations that do not merit high marks as science fair projects at the state and regional level. Note however, that when working on an engineering project, you may in fact be constructing, designing, building, troubleshooting, or demonstrating a working model of a new product, a device to improve on an existing model or product, or an inventive model or device that addresses or solves an existing problem. This is the nature of an engineering project and the judges expect it. However, even at the core of an engineering project there is a question or problem that is asked and addressed by the model, design, or device built.
In general, while preparing your project, try to present a question or problem and then prepare a series of tests to solve the problem or support a proposed hypothesis. If you follow the scientific method, your project should be easier to complete and will provide more meaningful results than if you do not use this method.
Because you want your results to be absolutely accurate, you should record all your data in your journal, regardless of whether or not they support your hypothesis. Your project will not be scored low or disqualified simply because your results did not support your hypothesis. You may develop your project by interpreting your end results and explaining why they were different from what you expected.
Keep in mind that judges do not expect you to come up with a revolutionary idea. They are more interested in seeing how much ingenuity and originality you applied to an existing problem you are studying and the approach you took toward your problem. Most projects have been done before in one form or another. They usually differ to the extent that they are different approaches or applied techniques of an original idea or a confirmation of a conclusion under varying circumstances. Some contestants even submit the same project the following year at the same science fair because they have made significant progress in their topic since their first entry. Judges are mainly interested to see whether you chose the best method possible in your investigation, whether you have made the most effective use of materials, equipment, and techniques pertaining to your topic, and whether you have recorded and analyzed your data accurately and effectively.
Step One: Define Your Objective
Before you begin, streamline your proposed question. Decide what you want to prove, and try to attack the most important aspect of your topic. For example, if you chose oil spills as your topic, you would probably research its hazardous byproducts, cleanup solutions, and long-term effects on the environment. Such a broad topic would yield a variety of details without a specific focus or purpose. You must confine your topic to a single purpose or question. You can do this by listing all the different approaches that may be taken in your project through experimentation. Some of these might include:
- Determining the effects that oil spills have on the growth of organisms.
- Comparing health and disease statistics between different oil spill sites.
- Determining the efficiency of a proposed solution such as bioremediation to neutralize and clean up oil from a spill.
After you have listed various approaches to your project, choose one that you think will produce a reasonable and practical experiment.
Given these choices, the first and second alternatives would probably be too broad to work with. Such experiments would require several years for you to compare the growth, health, and disease characteristics of several sites. The work would involve periodic studies of people, animals, and plants, in order to measure their overall health, function, endurance, immunity, and quality of vital functions. Although these are very challenging objectives that would make great long-term studies, they might be too much to satisfy your immediate objective within the time frame you have. However, the third alternative would be a great experiment because it focuses on a central idea, namely, it would study the efficiency of bioremediation (a natural means of using various microorganisms to consume fuel-derived toxins and turn them into carbon dioxide). You could measure the efficiency of various microorganisms in order to find out which one best eliminates oil in seawater. A procedural plan could easily be developed to parallel your purpose.
Step Two: Obtain Scientific Review Committee (SRC) Approval
Since many local, state, and regional science fairs are affiliated with the Intel ISEF, the format and instructions in this book are designed to help you create and present a science fair project that complies with Intel ISEF rules and guidelines. As such, it is important to provide a summary of Intel ISEF science project research and experimental guidelines that may affect your project. As soon as you have narrowed in on a project topic and defined your objective, you should consult with your science teacher or mentor about receiving Scientific Review Committee (SRC) approval before starting your project. Many local, state, and regional science fairs establish SRC approval deadlines long before the deadline for even entering your project in a science fair. Often this deadline is in November or December prior to the date of the science fair. The purpose of the SRC is to ensure the safety of the student performing the research and experiment as well as the subject being tested. The SRC also functions to disapprove research that may be inappropriate or illegal. Projects involving humans, vertebrate animals, pathogenic agents, or recombinant DNA must have SRC approval prior to the start of research. Your science teacher or mentor is likely to be familiar with the rules and guidelines concerning SRC approval and probably has all the forms and paperwork you need in order to be in compliance. If not, contact your local, state, or regional science fair administrator to obtain SRC deadlines and the appropriate forms. For a complete listing of all current Intel ISEF–affiliated science fairs, please see Appendix D at the back of this book.
Step Three: Organize Your Experiment
Once you have reduced your topic to a single purpose or question, you must organize your experiment. In the example regarding bioremediation of oil spills, you must organize an experiment that will allow you to measure the efficiency of various microorganisms in neutralizing the presence of oil in seawater. It would be difficult (not to mention illegal) to add home heating oil to a body of water for the purpose of testing bioremediation over a short time period, so a more practical thing to do would be to collect several large buckets of natural seawater that you can add home heating oil to along with your microorganism variables and test in an environmentally safe area. Your objective would then be to study the effects of various microorganisms in the bioremediation of home heating oil. After you have organized your experiment, you must develop a procedural plan.
Step Four: Create an Experimental Procedural Plan
An experimental procedural plan is a uniform, systematic approach to testing your hypothesis. When you begin this phase you should make a step-by-step list of what you will do to test your hypothesis. To start, first correlate (i.e., bring one thing into a reciprocal relationship with another) what you want to prove. You begin by selecting one thing to change in each experiment. Things that are changed are called variables. You want to be able to correlate two or more variables— the dependent variable and the independent variable. The dependent variable is the one that is being measured; the independent variable is the one that is controlled or manipulated by the experiment. For example, you may want to see whether the health and growth of a tomato plant (the dependent variable) is influenced by the amount of light the plant is exposed to (the independent variable). The correlation here is between the health of a plant and light exposure. Several other independent variables may be used instead, such as water, oxygen, carbon dioxide, nitrogen levels, and so on. However, for the sake of clarity we will use only light as a variable for this example. You should then state how you will change your independent variable and how you will measure the amount of change in the dependent variable.
Establish a Control Group
Next, an experimental group and a control group must be established. The control group provides you with a basis for comparing the experimental group. For example, you may have an experimental group of tomato plants, which is placed in a sunny window for two weeks and watered periodically. At the end of the period, the plants have grown three inches and are very green. At this point, you may conclude that sunlight does indeed increase plant growth. But before you draw this conclusion, you should determine whether the tomato plants would have grown and become green without any sunlight at all. This is where a control group of plants is needed. A control group is used for purposes of comparison with the experimental group so that you can see what occurred by changing your variables.
The control group of plants in our example would be those plants that are given the same treatment as the experimental ones, with the exception that they would not be exposed to sunlight. If the outcome of the experiment were a significant difference between the two groups, then you probably would be justified in concluding that tomato plant growth is influenced by the amount of sunlight the plant receives.
The procedural plan in this example is very simple, but it gives you an idea of the process of an experiment. In essence, the procedural plan advances from one stage to another in an organized fashion. Remember, however, that most experiments are not as simple as the one described here. Often obstacles arise and other interesting characteristics of the subject are revealed in the process. You may even discover existing differences in several trials with only one variable. In fact, this is a frequent occurrence, and it is an important reason why you must keep accurate data records.
Step Five: Conduct Your Experiment
Once you have established your procedural plan for your experiment and have received approval, it is time to collect the materials you will need. You may also need to obtain approval or permission to work in a laboratory or other professional environment. The important thing to keep in mind as you put your procedural plan into action is to collect accurate data results from repeated trials with the same variables and record all of your data for later analysis (see Chapter 5 for this important next step). The benefit to taking this approach is that it increases the accuracy of your results and conclusions. How many times do you need to repeat your experimental procedural plan? This really depends on many different factors, not the least of which is your subject matter.
If you have a mentor who is a professional scientist or engineer, you may already have the supplies and equipment you need through the mentor’s affiliation with a university or company research laboratory.
Avoiding a Failed Experiment
There are several reasons why an experiment may fail to validate a hypothesis, prove a point, or simply do what it was intended to do, for example, mistakes in the way the experiment was carried out (procedural errors), a poor or incomplete final analysis, and an erroneous hypothesis.
Procedural Errors
To avoid procedural problems, you must be consistent and meticulous with your subject variables and controls over repeated trials. For example, in the experiment involving sunlight and tomato plants, if you gave the experimental group of tomato plants more water than the control group or planted them in a soil that contained more nitrogen, you would get artificial results. This means that you are failing to control or hold your variable constant. How can you determine whether it was the sunlight alone or in combination with other factors that made the experimental tomatoes flourish? The same problem with inconsistent maintenance of controls might apply if you were studying the behavior of your friends at a party for a psychological experiment. What would happen if you made your study obvious by taking notes or pictures? Your friends probably would be influenced by your behavior and would not act in their usual manner. In this case, as the old saying goes, “you cannot measure an experiment without affecting the result.” These examples involve manipulated experiments that would yield useless data. Of course, other procedural problems may arise during an experiment, especially if poorly calibrated measuring instruments are used.
Poor Final Analysis
Even after a carefully controlled experiment is completed, errors can still occur, possibly resulting from an incorrect analysis of results. For example, if you concluded that a certain salve cures acne, on the basis of tests that were conducted on female adolescents but not male ones, your final analysis would be inconclusive. While the salve may have worked on the females you tested, it may not work on females in different age groups or on males of all age groups. Other problems with the final analysis may arise from mathematical errors or from data that are irrelevant to the topic.
Erroneous Hypothesis
When an experiment is completed, the results are sometimes quite different from those that were predicted. If this occurs, do not manipulate the results to fit the initial hypothesis. The hypothesis may have been incorrect or vague to begin with, and the experimental results were accurate. If such problems occur in your project, you can salvage your work by finding out why the results were different than expected or by explaining a new or unexpected observation or solution. This will show the judges that you understand the primary aspects that concern your project topic, including the control and handling of variables in experimentation, repeated trials, and approach to reaching conclusions. This actually happens to be a judging criterion that many students overlook. So, if your experimental results are different from what you expected after several trials, take advantage of this situation by thoroughly analyzing and knowing why you received the results you did.
Keep in mind that many scientific investigations do not support their specific goals. However, this does not weaken the validity or value of these investigations. In fact, many experiments require repeated testing and exploration to understand a particular phenomenon. Sometimes, unexpected experimental results lead to surprising discoveries and more interesting science projects!
Summary
- The experiment is an essential part of your science project. It should test, survey, compare, and ultimately aim to solve or answer the problem or question presented.
- You must focus your topic on an experimental approach that will clearly test your hypothesis and will uphold the scientific method.
- After you decide on an experimental approach, you must develop a way of testing your subject. This involves defining your objective, obtaining Scientific Review Committee approval, organizing your experiment, and creating an experimental procedural plan.
- An experimental group containing variables and a control group must be established as part of the experimental procedural plan. Several trials should be made with the same variables to ensure consistent data results from which conclusions can be made.
- Three common ways in which an experiment can fail are procedural errors, poor final analysis, and an erroneous hypothesis.
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