In research, variables are key elements that researchers observe, manipulate, and measure. Understanding the different types of variables is crucial for designing and interpreting studies.

Independent Variables:

The independent variable (IV) is the variable that the researcher manipulates or changes. It is considered the presumed cause in a cause-and-effect relationship. Researchers often introduce different levels or conditions of the independent variable to see its effect on the dependent variable.

• Example: In a study investigating the effect of study time on test scores, the amount of time spent studying would be the independent variable. Researchers might have different groups of students study for varying durations (e.g., 1 hour, 3 hours, 5 hours).

Dependent Variables:

The dependent variable (DV) is the variable that the researcher measures. It is the presumed effect or outcome that is influenced by the independent variable. The researcher observes how changes in the independent variable affect the dependent variable.

• Example: Continuing the previous example, the students’ scores on the test would be the dependent variable. Researchers would measure these scores to see if they differ based on the amount of time the students studied (the independent variable).

Extraneous Variables:

Extraneous variables (EVs) are any variables other than the independent variable that could potentially influence the dependent variable. These are unwanted variables that can confound the results of a study, making it difficult to determine the true effect of the independent variable. Extraneous variables can introduce error and provide alternative explanations for the observed outcomes.

• Examples: In the study time and test scores example, extraneous variables could include:
  • Prior knowledge of the subject matter: Students with more background knowledge might perform better regardless of study time.
  • Test anxiety: Different levels of anxiety could affect test performance.
  • Study environment: Noise levels or distractions during study could impact learning.
  • Time of day of the test: Students might perform differently depending on their alertness levels at different times.

Two Ways Researchers Attempt to Control Extraneous Variables:

Researchers employ various techniques to minimize the impact of extraneous variables and increase the internal validity of their studies (the degree to which the observed effects are genuinely due to the independent variable). Two common methods are:

1. Random Assignment: This technique is primarily used in experimental designs where participants are randomly assigned to different conditions or groups (including the control group and the experimental group). Random assignment aims to distribute extraneous participant variables (e.g., prior knowledge, motivation, personality traits) equally across all groups. By ensuring that these individual differences are spread out randomly, researchers reduce the likelihood that these variables will systematically bias the results and confound the effect of the independent variable.

   • Example: In a study testing the effectiveness of a new teaching method, researchers would randomly assign students to either the group receiving the new method or the group receiving the traditional method. This helps ensure that pre-existing differences in students’ academic abilities or learning styles are evenly distributed between the two groups, making it more likely that any observed differences in learning outcomes are due to the teaching method itself.

2. Standardization of Procedures: This involves keeping all aspects of the study the same for all participants, except for the manipulated independent variable. This includes standardizing the instructions given to participants, the environment in which the study is conducted (e.g., same lighting, temperature, noise levels), the timing of the interventions or measurements, and the way data is collected. By minimizing situational extraneous variables, researchers can reduce the chance that these factors are influencing the dependent variable in a systematic way.

   • Example: In a study examining the impact of different types of music on concentration, researchers would ensure that all participants perform the concentration task in the same quiet room, receive the same instructions, and listen to the music for the same duration. The only difference between groups would be the type of music they hear (the independent variable). This standardization helps to isolate the effect of the music on concentration levels (the dependent variable) by controlling for other environmental factors.

Example from a Peer-Reviewed, Primary Research Article:

Let’s consider a hypothetical example based on common themes in educational psychology research. Imagine a study investigating the effect of mindfulness meditation (independent variable) on students’ test anxiety levels (dependent variable).

A hypothetical peer-reviewed article titled “The Impact of a Brief Mindfulness Intervention on Test Anxiety in High School Students” might describe the following methods to control extraneous variables:

• Random Assignment: The researchers randomly assigned participating high school students to one of two groups: a mindfulness meditation intervention group and a control group (who engaged in a neutral activity). This helped to distribute pre-existing differences in students’ baseline anxiety levels, academic performance, and personality traits evenly across the two groups. By randomly assigning students, the researchers aimed to minimize the influence of these participant variables on the study’s outcome.