Provide examples of experimental and nonexperimental research design. Contrast the levels of control applied to each.
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Experimental research design:
1. Randomized controlled trial (RCT): Participants are randomly assigned to either an experimental group or control group. The experimental group receives the intervention or treatment, while the control group does not. For example, researchers may investigate the efficacy of a new drug by randomly assigning participants to either receive the drug or a placebo. The level of control in an RCT is high, as researchers can control the manipulation of variables, random assignment, and ensure that the only difference between groups is the intervention.
2. Quasi-experimental design: This type of design lacks the random assignment of participants. For example, researchers may study the effects of smoking during pregnancy by comparing a group of pregnant women who smoke to a group of pregnant women who do not smoke. In this case, the level of control is lower compared to an RCT, as researchers cannot randomly assign participants to groups. However, they still have control over the independent variable (smoking) and can collect data on the dependent variable (effects on pregnancy).
Nonexperimental research design:
1. Descriptive research: This type of research aims to describe and interpret observations or behaviors without intervention or manipulation of variables. For example, researchers may conduct a survey to understand the opinions or attitudes of a specific population. In descriptive research, the level of control is lower as researchers cannot manipulate variables or control for extraneous factors. However, they can control data collection methods and ensure accurate representation of the population being studied.
2. Correlational research: This type of research investigates the relationship between two or more variables without manipulation. For example, researchers may examine the correlation between hours of study and exam scores among college students. Correlational research offers less control compared to experimental designs as variables are not manipulated or controlled. However, researchers can still measure and analyze the strength and direction of the relationship between variables.
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