Experimental research is one of the primary ways by which science advances. In experimental paradigms, independent variables (stimuli) are manipulated and the effect of the manipulation on the value of the dependent variable (response) is measured and analyzed. In addition, good experimental research is designed to control as much as possible the effects of extraneous and intervening variables, often by the use of control groups. Experimental research can be performed in the laboratory, through simulations, or through the manipulation of variables in field experiments. These approaches to experimental research allow the design of increasingly more realistic experimental paradigms but give the researcher decreasing control over the experimental situation. In addition to being concerned over designing an experiment that will collect uncontaminated data that can be meaningfully analyzed using inferential statistics, researchers using human subjects also need to be concerned about ethical considerations of the effects of their experiment on its subjects.
In order to be considered a true behavioral scientist, it is necessary for sociologists not only to observe and describe human behavior, but to perform research so that they can better understand and predict behavior. In some situations, it is only possible to collect data using surveys--data collection instruments used to acquire information on the opinions, attitudes, or reactions of people. In other situations, however, it is actually possible to control the research situation and manipulate variables in order to obtain better data and a clearer picture of the processes that underlie human behavior. These experiments are situations that are under the control of a researcher in which an experimental condition (independent variable) is manipulated and the effect on the experimental subject (dependent variable) is measured. Most experiments are designed using the principles of the scientific method and are analyzed using inferential statistics to determine whether or not the results are statistically significant.
In the simplest experimental design, a stimulus is presented to the research subjects and a response is observed and recorded. For example, one might present subjects with pictures of various situations and ask them to describe what they think they would do if they were in that situation. However, what one thinks one would do and what one would actually do can be very different and may depend on a number of factors. Behavior in the real world tends to be complicated, and several types of variables need to be considered when designing an experiment. Of most concern in most research paradigms are the independent variable (i.e., the stimulus or experimental condition that is hypothesized to affect behavior) and the dependent variable (i.e., the observed effect on behavior caused by the independent variable). However, there are typically other variables that need to be considered and controlled as much as possible, particularly in real-world research. As shown in Figure 1, extraneous variables that affect the outcome of the experiment but that have nothing to do with the independent variable may also need to be considered. For example, a person who responded to a picture of an automobile accident by saying that he or she would not stop to help might respond that way because he or she was feeling tired or ill that day and wanted nothing more than to get home. On another day, he or she might give a different response. In most real-world situations, there are innumerable variables that are extraneous to the research question being asked but that still affect the outcome of the research. However, a well-designed experiment is created so that it controls for as many of the extraneous variables as possible. It is, of course, impossible in most cases to anticipate and control for every possible extraneous variable. However, the more of these that are accounted for and controlled in the experimental design, the more meaningful the results will be.
Another type of variable not directly related to the experiment but that might affect the results is the intervening variable. These are things that occur between the manipulation of the independent variable and the measurement of the dependent variable. For example, if a person in the experimental situation responded to a picture of an automobile accident responded that he or she would call 911 but would not stop to help later took a course in CPR, he or she might actually stop to help if encountered with the situation in the real world because of the intervening training. Like extraneous variables, intervening variables need to be controlled as much as possible in the experimental situation so that the effect of manipulation of the independent variable on the dependent variable can be determined and statistically analyzed. Extraneous and intervening variables are often controlled in an experiment by the inclusion of a control group comprising subjects that do not receive the experimental condition in order to level the effects of these variables.
Types of Experiments
There are a number of ways to collect data that can be used by behavioral scientists. These range from laboratory experiments that allow the researcher great control over the conditions and variables in the study to secondary analysis methods that allow researchers to examine the results of studies done in the past but give them no control over the research design or data collection whatsoever. Laboratory research allows the most control over variables. However, it often is far-removed from real life. Laboratory methods tend to be more appropriate to basic research questions where the influences of the real world are not as important as in applied studies. However, as the research situation becomes more realistic, the research loses a greater degree of control over the situation. To be able to extrapolate research results to the real world and have them be meaningful, it is important to design an experiment that not only controls extraneous variables, but also is as realistic as possible.
There are several general types of experimental studies that can be used to explore the behavior of people in the real world. As discussed above, laboratory experiments allow researchers the most control over extraneous variables. However, laboratories tend to be far removed from the reality of how most people live their lives. Simulation is an approach to experimental research that allows a more realistic setting for the experiment while still allowing researchers a great degree of control. Using the example above, research subjects could be placed in a situation where they encounter a simulated automobile accident so that the researcher could determine how they actually would respond in such a condition. Or, the researcher could set up a field experiment in which the experimental condition is introduced into the real world and the researchers observe how people react. For example, the researcher could set up a situation where it looks like someone has had an automobile accident and then determine what percentage of people actually stop. Both simulations and field research have the advantages of being increasingly more realistic and, therefore, more likely to elicit real responses from people than is possible in the artificial setting of the laboratory. However, these approaches to experimental design also decrease the researcher's control over extraneous variables.
Designing an Experiment
The specifics of how one designs a study depend on the goals of the research and the practical constraints placed on the design by the statistical tools needed to analyze it. In general, however, experiments are designed to test hypotheses as part of the theory building process. As shown in Figure 2, research design starts with the development of a tentative theory that is based on real-world observation. For example, from personal experience, the researcher may have observed that people with certain personality traits are more prone to help others than are people without those traits. Based on these observations, the researcher might form an empirically testable hypothesis concerning the relationship between personality traits and willingness to help others. To find out if this hypothesis is true, the researcher would then operationally define the various terms in the hypothesis (i.e., personality traits, helping others). These definitions would include ways to measure the personality traits (e.g., through an existing personality test, the development of a new test, or ratings of friends) and specific criteria for what constitutes "helping others." The researcher would then conduct the experiment,...
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