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Block 3 Unit 3 Quasi Experimental Design

1) Define and describe the quasi-experimental design.

A quasi-experimental design is a research method that resembles a true experiment but lacks at least one of its defining characteristics, typically random assignment of participants to different conditions. In a quasi-experiment, researchers select subjects from pre-existing groups, rather than assigning them randomly, and may also lack full control over the manipulation of the independent variable. They are used to study cause-and-effect relationships in settings where the controlled conditions of true experiments are not possible or ethical.

2) Differentiate between a true experimental design and a quasi-experimental design.

The key difference between true experimental and quasi-experimental designs lies in the degree of control that researchers have over the variables:

• True Experimental Design:
  • Researchers have full control over the manipulation of the independent variable.
  • Participants are randomly assigned to different groups or conditions, ensuring that the groups are comparable at the beginning of the experiment.
  • It aims to isolate the effect of the independent variable on the dependent variable, reducing the influence of confounding variables.
  • It aims to have high internal validity.
• Quasi-Experimental Design:
  • Researchers may not have full control over the manipulation of the independent variable or may not manipulate it at all.
  • Participants are not randomly assigned to groups; instead, they are selected from pre-existing groups which may be naturally occuring.
  • The lack of random assignment makes it more challenging to control for confounding variables.
  • It may have better external validity compared to true experimental designs but the internal validity may be lower than a true experiment.

3) Discuss with examples the non-equivalent control group design.

The non-equivalent control group design is a type of quasi-experimental design in which a researcher includes both a treatment (or experimental) group and a control group, but participants are not randomly assigned to these groups. The groups are "non-equivalent" because they are pre-existing groups, which means there may be pre-existing differences between them that could influence the results.

• Example: Imagine a researcher wants to study the impact of a new teaching method on student performance. Instead of randomly assigning students to different classes, the researcher might use two existing classes. One class (the experimental group) receives the new teaching method, while the other (the control group) continues with the traditional method. The researcher would then measure the performance of both groups after the intervention and compare their scores. Since students were already in those classes prior to the study, this is a pre-existing group and not a random sample, therefore, a non-equivalent control group design is being used.
• Challenges: A significant concern with non-equivalent control group designs is that the two groups may differ on variables other than the independent variable which was manipulated by the researcher, which may affect the dependent variable under study. The differences may be due to selection bias or other pre-existing differences that may not be immediately apparent. These differences can make it difficult to determine whether the observed differences in the dependent variable were caused by the independent variable or by these other extraneous factors.

4) What are the various types of quasi-experimental designs?

There are several types of quasi-experimental designs, each with its own specific application and approach. Some of the commonly used quasi-experimental designs mentioned in the sources include:

• Non-Equivalent Group Posttest-Only Design: This design involves comparing two pre-existing groups after one group has received a treatment and the other has not. There is no pre-test.
• Non-Equivalent Control Group Design: As discussed above, this design includes a treatment and control group without random assignment; and usually with both pre and post tests
• The Separate Pretest-Posttest Sample Design: Here, a pre-test is given to one group of people and a post-test is given to a different group of people.
• The Double Pretest Design: In this design, all participants take two pretests prior to the treatment.
• The Switching Replications Design: In this design, the treatment is first given to one group and then to another after the first group has completed their treatment; in essence, the groups switch roles.
• Mixed Factorial Design: This design combines both between-subjects and within-subjects factors.
• Interrupted Time Series Design: This design involves repeatedly measuring a single group of participants over time, before and after a treatment or intervention.
• Multiple Time Series Design: This design is similar to the interrupted time series design but includes a control group, thus reducing any threats to internal validity.
• Repeated Treatment Design: This design uses a single group to receive multiple treatments, each followed by a measurement.
• Counterbalanced Design: This design uses multiple treatments but the order of treatments is varied across the group of participants.

These designs offer researchers a variety of options for studying cause-and-effect relationships in real-world settings where true experimental control is not feasible.

Important Points

• Trait anxiety is a quasi-experimental variable.
• Quasi-experimental designs typically have lower internal validity compared to true experimental designs due to the lack of random assignment and control over extraneous variables.
• Quasi-experiments are often used when random assignment and manipulation of variables are not feasible.
• In quasi-experiments, there is a lack of random assignment of subjects in groups. This is a key characteristic distinguishing quasi-experiments from true experiments.
• Quasi-experimental designs are highly valuable in various fields of psychological research, especially when studying real-world settings and naturally occurring phenomena.
• It is possible to assign subjects to conditions in a true experiment; in a quasi-experiment, it is necessary to select subjects from pre-existing groups.
• The external validity of a quasi-experiment is higher than a true experiment. Quasi-experiments often have better external validity due to their use of real-world settings.
• The research design that allows the same group to be compared over time is known as time series design.
• In a multiple time series design, we have two groups.
• Manipulation of independent variable is made by selection in quasi experimental design.