SCI - Experimentation Lesson
Learning Target:
- Identify the features of experimental methods that enable researchers to determine causal relationships.
Courtesy of the AP psychology course and exam description, effective fall 2024. (n.d.). Links to an external site.
Understanding Experimental Methods in Research
The experimental method is crucial for scientists to establish cause-and-effect relationships. By manipulating variables, researchers can observe outcome changes. An experiment has two key variables: the independent variable (IV) and the dependent variable (DV). The independent variable is what is being manipulated in the experiment, such as a drug in a study of its effects. The dependent variable is the behavior change that results from manipulating the independent variable.
In an experiment, there are typically two groups: the experimental group, which is exposed to the independent variable, and the control group, which is not exposed to it. The control group serves as a baseline for comparison to determine if the independent variable caused a behavior change. Having a control group in an experiment is crucial because it allows researchers to compare the effects of the independent variable to a baseline condition. Any observed changes in the experimental group can be attributed to manipulating the independent variable by keeping all variables constant except for the independent variable. This helps to establish a cause-and-effect relationship and ensures that other factors do not influence the results.
Participants must be randomly assigned to the experimental or control group to ensure unbiased results. Confounding variables, external factors that can influence the dependent variable, must also be carefully controlled. One example of a confounding variable is the placebo effect, in which participants' behavior changes after receiving a fake treatment. Experimenter bias can also impact results, so researchers sometimes use double-blind procedures to minimize bias.
Conducting an Experiment
To illustrate this concept, consider a hypothetical experiment conducted by Mr. Smith. In this experiment, Mr. Smith wanted to investigate the effects of different study techniques on students' performance in mathematics. He divided the students into two groups: Group A and Group B.
- Group A (Experimental Group): Students were provided with practice problems and encouraged to engage in problem-solving actively.
- Group B (Control Group): Students were only given the answers to the practice problems without actively solving them.
After a few weeks, both groups were tested on their math skills. The results showed that students in Group A, who actively engaged in problem-solving, performed significantly better than those in Group B. This difference in performance can be attributed to the independent variable, which in this case was the study method.
Key Elements of Experimental Design
- Independent Variable: The factor that is purposefully changed in an experiment.
- Dependent Variable: The factor that is measured and may change in response to manipulating the independent variable.
- Confounding Variables: Other factors that can potentially influence the study results.
- Random Assignment: Ensures that participants are assigned to groups unbiasedly, minimizing pre-existing differences.
Take a moment to read the scenarios below and determine the IV and DV for each experiment. Remember the IV is usually something that is being added or taken away and the DV is the effect.
Ensuring Validity in Experiments
To maintain an experiment's validity, researchers must control for confounding variables, such as experimenter bias or placebo effects. Random assignment and precise operational definitions of variables are essential for ensuring that the study accurately tests what it is intended to measure.
By understanding the features of experimental methods, researchers can uncover valuable insights and establish reliable cause-and-effect relationships between variables in their studies.
The Placebo Effect
Experimental methods are crucial in enabling researchers to determine causal relationships between variables. Researchers must carefully control for other influencing factors to establish a treatment's effect. In evaluating new drugs and psychological therapies, participants are randomly assigned to different research groups. One group is given a placebo or fake treatment, while the other receives the actual treatment being studied, such as an antidepressant medication. In single-blind procedures, participants are unaware of the treatment they are receiving.
In contrast, in double-blind studies, participants and administering staff are kept unaware of who is receiving the treatment. This methodology helps researchers differentiate the actual effects of a treatment from any psychological influences, such as the well-documented placebo effect. For instance, individuals have reported increased vigor and alertness even after consuming decaf coffee if they believed it contained caffeine, showcasing the power of perception in affecting outcomes.
Quasi-Experiments
One important type of experimental design is a quasi-experiment, which resembles an actual experiment but lacks random assignment to groups. In quasi-experiments, researchers take advantage of naturally occurring differences in groups to study the effects of variables. While they may not provide the same level of control as true experiments, quasi-experiments are valuable in situations where random assignment is not feasible, such as studying the impact of trauma on individuals. By understanding both experimental methods and quasi-experiments, psychologists can gain valuable insights into human behavior and advance our knowledge in psychology.
[CC BY 4.0] UNLESS OTHERWISE NOTED | IMAGES: LICENSED AND USED ACCORDING TO TERMS OF SUBSCRIPTION