Step 4: Identifying Extraneous (Confounding) Variables

Instructions: Click on the sections below to see the explanations.

Internal Validity (Click)

To receive high marks, your experiment must have high internal validity, meaning that it must constitute a reliable test of the research hypothesis that isolates the potential influence of the independent variable on the dependent variable.  

Concretely, this means that you have to identify and find ways to control (avoid, nullify, or decreasing the risks of) “extraneous” (or “confounding” variables), which are factors that are not the independent variable (they are “extraneous”) but that could affect the behavior of participants (the dependent variable) and thus the findings of the experiment (they are “confounding” and create confusion).

To identify relevant extraneous (confounding) variables in the context of your experiment, you can start by looking at those addressed in the “Participants and Procedures” section of your original study. However, you should also review the list below and ask yourself if they apply to your experiment (keeping in mind whether it will be conducted in person or online).

Participant Variables (Click)

Participant variables are individual characteristics that are not the independent variable, but could affect the behavior of the participants (the dependent variable.) This may affect your findings if these individual differences are not equally distributed across conditions, so that participants are not comparable in terms of relevant characteristics.

Examples include:

  • Age, gender, race, native language, life experiences, personal opinions or preferences, background knowledge, underlying skills, etc. 
  • However, you should only focus on the ones that are relevant to your experiment, i.e., the ones that might affect the dependent variable.
Task / Stimulus Effects and Variables (Click)

Task/stimulus effects and variables are characteristics of the task(s) that participants have to perform and/or of the stimulus on which they have to perform these task(s) that are not the independent variable, but that could affect the behavior of the participants (the dependent variable). This may affect your findings if these characteristics are different in the experimental and control conditions, or if they  affect them or certain participants differently.

Examples include:

  • Task(s) and stimulus that differ in nature or in difficulty 
  • Ceiling effect: When the task(s) and/or stimulus is so hard that differences in performance (the dependent variable) become unnoticeable.
  • Order effects: When performance on successive tasks (or on successive parts of a task) improves through practice, deteriorates because of fatigue or boredom, or is affected by primacy and recency effects.
Situational Variables (Click)

Situational variables are characteristics of the experimental environment that are not the independent variable, but that might affect the behavior of the participants (the dependent variable). This may affect your findings if the environment is different in the experimental and control conditions or if it  affects them or certain participants differently.

Examples include:

  • Time: Participants’ behavior might be affected by the time in the day or week when the experiment is conducted.
  • Place: Participants’ behavior might be affected by the location where the experiment is conducted (e.g., noise level), or by their position in the room, etc.
Researcher Biases (Click)

Researcher biases are ways in which the researchers’ behavior affects the findings of the study apart from their manipulation of the independent variable. This can be due to an unconscious effort to confirm their research hypothesis or to other biases. This may affect your findings if the researchers’ behavior is different in the experimental and control conditions or if it  affects them or certain participants differently.

Examples include:

  • Biases in the conduction of the experiment (presentation of the study, explanation of instructions, treatment of participants, involuntary cues, etc.)
  • Biases in the collection and/or interpretation of data (scoring, etc.)
Participant Biases (Click)

Participant biases are changes in participants’ behavior that are due to the experimental context (their participation in an experiment), but not to the manipulation of the independent variable.

Examples include:

  • Demand characteristics: When participants respond to the researchers’ unconscious demands (cues) to behave a certain way.
  • Good and bad participant effects: When participants behave so as to make the experiment “work” or “fail”, i.e., so as to conform to or deviate from what they think the research hypothesis is.
  • Audience effect: When people’s behavior is affected by their awareness (or belief) that they are being observed and evaluated.

QUESTIONS: Click on the question below to see the worked example.

Answer the question below on your individual Experiment Creation Form.

Question 10: Explain potential extraneous (confounding) variables in your experiment. (Click)

Your answer should include:

  • A systematic review and description of all potential extraneous (confounding) variables that are relevant to your experiment
  • An explanation of their relevance: why might they influence the dependent variable and the findings of the experiment.

Table 7: Example of Explained Extraneous (Confounding) Variable