This is when a hypothesis is scientifically tested. In a controlled experiment, an independent variable (the cause) is systematically manipulated, and the dependent variable (the effect) is measured; any extraneous variables are controlled.
The researcher can operationalize (i.e., define) the studied variables so they can be objectively measured. The quantitative data can be analyzed to see if there is a difference between the experimental group and the control group.
In This Article
What is the control group?
In experiments scientists compare a control group and an experimental group that are identical in all respects, except for one difference – experimental manipulation.
Unlike the experimental group, the control group is not exposed to the independent variable under investigation and so provides a baseline against which any changes in the experimental group can be compared.
Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.
Randomly allocating participants to independent variable groups means that all participants should have an equal chance of participating in each condition.
The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.
What are extraneous variables?
The researcher wants to ensure that the independent variable’s manipulation has changed the changes in the dependent variable.
Hence, all the other variables that could affect the dependent variable to change must be controlled. These other variables are called extraneous or confounding variables.
Extraneous variables should be controlled were possible, as they might be important enough to provide alternative explanations for the effects.
In practice, it would be difficult to control all the variables in a child’s educational achievement. For example, it would be difficult to control variables that have happened in the past.
A researcher can only control the current environment of participants, such as time of day and noise levels.
Why conduct controlled experiments?
Scientists use controlled experiments because they allow for precise control of extraneous and independent variables. This allows a cause-and-effect relationship to be established.
Controlled experiments also follow a standardized step-by-step procedure. This makes it easy for another researcher to replicate the study.
Key Terminology
Experimental Group
The group being treated or otherwise manipulated for the sake of the experiment.
Control Group
They receive no treatment and are used as a comparison group.
Ecological validity
The degree to which an investigation represents real-life experiences.
Experimenter effects
These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
Demand characteristics
The clues in an experiment that lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).
Independent variable (IV)
The variable the experimenter manipulates (i.e., changes) – is assumed to have a direct effect on the dependent variable.
Dependent variable (DV)
Variable the experimenter measures. This is the outcome (i.e., the result) of a study.
Extraneous variables (EV)
All variables that are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.
Confounding variables
Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.
Random Allocation
Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of participating in each condition.
The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.
Order effects
Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:
(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;
(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.
