If it is about a causal relationship and involves an independent variable that can be manipulated, the experimental approach is typically preferred. Otherwise, the nonexperimental approach is preferred. But the two approaches can also be used to address the same research question in complementary ways. Similarly, after his original study, Milgram conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study Milgram, [2].
Nonexperimental research falls into three broad categories: single-variable research, correlational and quasi-experimental research, and qualitative research. First, research can be nonexperimental because it focuses on a single variable rather than a statistical relationship between two variables.
Although there is no widely shared term for this kind of research, we will call it single-variable research. He was primarily interested in one variable—the extent to which participants obeyed the researcher when he told them to shock the confederate—and he observed all participants performing the same task under the same conditions.
The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of single-variable research.
As these examples make clear, single-variable research can answer interesting and important questions. What it cannot do, however, is answer questions about statistical relationships between variables. This detail is a point that beginning researchers sometimes miss. The first thing that is likely to occur to these researchers is to obtain a sample of middle-school students who have been bullied and then to measure their self-esteem.
But this design would be a single-variable study with self-esteem as the only variable. Although it would tell the researchers something about the self-esteem of children who have been bullied, it would not tell them what they really want to know, which is how the self-esteem of children who have been bullied compares with the self-esteem of children who have not.
Is it lower? Is it the same? Could it even be higher? To answer this question, their sample would also have to include middle-school students who have not been bullied thereby introducing another variable. If the goal is to describe or to predict, a non-experimental approach is appropriate.
But the two approaches can also be used to address the same research question in complementary ways. However, Milgram subsequently conducted experiments to explore the factors that affect obedience. He manipulated several independent variables, such as the distance between the experimenter and the participant, the participant and the confederate, and the location of the study Milgram, [1]. Non-experimental research falls into two broad categories: correlational research and observational research.
The most common type of non-experimental research conducted in psychology is correlational research. Correlational research is considered non-experimental because it focuses on the statistical relationship between two variables but does not include the manipulation of an independent variable. More specifically, in correlational research , the researcher measures two variables with little or no attempt to control extraneous variables and then assesses the relationship between them.
Observational research is non-experimental because it focuses on making observations of behavior in a natural or laboratory setting without manipulating anything. He was primarily interested in the extent to which participants obeyed the researcher when he told them to shock the confederate and he observed all participants performing the same task under the same conditions.
The study by Loftus and Pickrell described at the beginning of this chapter is also a good example of observational research. When psychologists wish to study change over time for example, when developmental psychologists wish to study aging they usually take one of three non-experimental approaches: cross-sectional, longitudinal, or cross-sequential.
Cross-sectional studies involve comparing two or more pre-existing groups of people e. What makes this approach non-experimental is that there is no manipulation of an independent variable and no random assignment of participants to groups. Using this design, developmental psychologists compare groups of people of different ages e. Of course, the primary limitation of using this design to study the effects of aging is that differences between the groups other than age may account for differences in the dependent variable.
For instance, differences between the groups may reflect the generation that people come from a cohort effect rather than a direct effect of age. But there are other reasons too. While this sounds like the kind of solid, evil experimental design that a mad scientist would love, it might not be a very sound way of investigating the effect in the real world. For instance, suppose that smoking only causes lung cancer when people have poor diets, and suppose also that people who normally smoke do tend to have poor diets.
One distinction worth making between two types of non-experimental research is the difference be- tween quasi-experimental research and case studies. Some other disadvantages of experimental research include the following; extraneous variables cannot always be controlled, human responses can be difficult to measure, and participants may also cause bias. In experimental research, researchers can control and manipulate control variables, while in non-experimental research, researchers cannot manipulate these variables.
This cannot be done due to ethical reasons. For example, when promoting employees due to how well they did in their annual performance review, it will be unethical to manipulate the results of the performance review independent variable. That way, we can get impartial results of those who deserve a promotion and those who don't. Experimental researchers may also decide to eliminate extraneous variables so as to have enough control over the research process. Once again, this is something that cannot be done in non-experimental research because it relates more to real-life situations.
Experimental research is carried out in an unnatural setting because most of the factors that influence the setting are controlled while the non-experimental research setting remains natural and uncontrolled.
One of the things usually tampered with during research is extraneous variables. In a bid to get a perfect and well-structured research process and results, researchers sometimes eliminate extraneous variables. Although sometimes seen as insignificant, the elimination of these variables may affect the research results.
Consider the optimization problem whose aim is to minimize the cost of production of a car, with the constraints being the number of workers and the number of hours they spend working per day. In this problem, extraneous variables like machine failure rates or accidents are eliminated. In the long run, these things may occur and may invalidate the result. The relationship between cause and effect is established in experimental research while it cannot be established in non-experimental research.
Rather than establish a cause-effect relationship, non-experimental research focuses on providing descriptive results. Although it acknowledges the causal variable and its effect on the dependent variables, it does not measure how or the extent to which these dependent variables change.
It, however, observes these changes, compares the changes in 2 variables, and describes them. Experimental research does not compare variables while non-experimental research does. It compares 2 variables and describes the relationship between them. The relationship between these variables can be positively correlated, negatively correlated or not correlated at all.
For example, consider a case whereby the subject of research is a drum, and the control or independent variable is the drumstick. Experimental research will measure the effect of hitting the drumstick on the drum, where the result of this research will be sound.
That is, when you hit a drumstick on a drum, it makes a sound. Non-experimental research, on the other hand, will investigate the correlation between how hard the drum is hit and the loudness of the sound that comes out.
That is, if the sound will be higher with a harder bang, lower with a harder bang, or will remain the same no matter how hard we hit the drum. Experimental research is a quantitative research method while non-experimental research can be both quantitative and qualitative depending on the time and the situation where it is been used.
An example of a non-experimental quantitative research method is correlational research. Researchers use it to correlate two or more variables using mathematical analysis methods. The original patterns, relationships, and trends between variables are observed, then the impact of one of these variables on the other is recorded along with how it changes the relationship between the two variables.
Observational research is an example of non-experimental research, which is classified as a qualitative research method.
Experimental research is usually single-sectional while non-experimental research is cross-sectional. That is, when evaluating the research subjects in experimental research, each group is evaluated as an entity. For example, let us consider a medical research process investigating the prevalence of breast cancer in a certain community.
In this community, we will find people of different ages, ethnicities, and social backgrounds. If a significant amount of women from a particular age are found to be more prone to have the disease, the researcher can conduct further studies to understand the reason behind it.
A further study into this will be experimental and the subject won't be a cross-sectional group. A lot of researchers consider the distinction between experimental and non-experimental research to be an extremely important one.
This is partly due to the fact that experimental research can accommodate the manipulation of independent variables, which is something non-experimental research can not. Therefore, as a researcher who is interested in using any one of experimental and non-experimental research, it is important to understand the distinction between these two. This helps in deciding which method is better for carrying out particular research.
Collect and analyze data for your research projects with Formplus. The primary objective of any study is to determine whether there is a cause-and-effect relationship between the variables.
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