A variable is anything that can vary, i.e. changed or be changed, such as memory, attention, time taken to perform a task etc.
Variable are given a special names that only apply to experimental investigations. One is called the dependant variable (DV) and the other the independent variable (IV). In an experiment, the researcher is looking for the possible effect on the dependant variable that might be caused by changing the independent variable.
• Independent variable (IV): Variable the experimenter manipulates (i.e. changes) – assumed to have a direct effect on the dependent variable.
• Dependent variable (DV): Variable the experimenter measures, after making changes to the IV that are assumed to affect the DV.
For example, we might change the type of information (e.g. organised or random) given to participants to see what affect this might have on the amount of information remembered.
In this particular example the type of information is the independent variable (because it changes) and the amount of information remembered is the dependent variable (because this is being measured).
When we conduct experiments there are other variables that can affect our results, if we do not control them. The researcher wants to make sure that it is the manipulation of the independent variable that has changed the changes in the dependant variable. Hence, all the other variables that could affect the DV to change must be controlled. These other variables are called extraneous or confounding variables.
It is very important in psychological research to clearly define what you mean by both your IV and DV. Operational Definitions (or operationalising variables) refers to how you will define and measure a specific variable as it is used in your study.
For example, if we are concerned with the effect of media violence on aggression then we need to be very clear what we mean by the different terms. In this case, we must state what we mean by the terms “media violence” and “aggression” as we will study them. So, you could state that “media violence” is operationally defined (in your experiment) as ‘exposure to a 15 minute film showing scenes of physical assault’; “aggression” is operationally defined as ‘levels of electrical shocks administered to a second ‘participant’ in another room’.
For example, “Young participants will have significantly better memories than old participants” is not operationalised. How do we define "young", “old” or "memory"? "Participants aged between 16 - 30 will recall significantly more nouns from a list if twenty than participants aged between 55 - 70" is operationalised.
The key point here is that we have made it absolutely clear what we mean by the terms as they were studied and measured in our experiment.
If we didn’t do this then it would be very difficult (if not impossible) to compare the findings of different studies into the same behaviour.
Operationalisation has the great advantage that it generally provides a clear and objective definition of even complex variables.
Extraneous variables – These are all variables, which are not the independent variable, but could affect the results (e.g. DV) of the experiment. Extraneous variables should be controlled were possible. They might be important enough to provide alternative explanations for the effects.
1. Situational variables – These are aspects of the environment that might affect the participant’s behaviour e.g. noise, temperature, lighting conditions etc. Situational variables should be controlled so they are the same for all participants.
2. Participant / Person variables – This refers to the ways in which each participant varies from the other, and how this could effect the results e.g. mood, intelligence, anxiety, nerves, concentration etc. For example, if a participant that has performed a memory test was tired, dyslexic or had poor eyesight, this could affect their performance and the results of the experiment. The experimental design chosen can have an affect on participant variables.
Suppose I wanted to measure the effects of Alcohol (IV) on driving ability (DV) I would have to try to ensure that extraneous variables did not affect the results. These variables could include:
• Familiarity with the car: Some people may drive better because they have drove this make of car before.
• Familiarity with the test: Some people may do better than others because they know what to expect in the test.
• Used to drinking. The effects of alcohol on some people may be less than on others because they are used to drinking.
• Full stomach. The effect of alcohol on some subjects may be less than on others because they have just had a big meal.
If these extraneous variables are not controlled they may become confounding variables, because they could go on to affect the results of the experiment.
Confounding variables – variables that do actually have an affect on the DV. A confounding variable could be an extraneous variable that has not been controlled.
There are two types of confounding variables:
1. Participant Expectations - This is where the participant may try to figure out what the experiment is about.
2. Experimenter Expectations - The experimenter unconsciously conveys to participants how they should behave - this is called experimenter bias.
Much psychological research involves people. This makes the conduct of research more complex than work in the natural sciences. If you mix copper sulphate and sulphuric acid the molecules do not sit in the test-tube wondering why you have done this and what you are hoping to prove. If you deprive a plant of light it doesn’t think “A-ha!...photosynthesis experiment. What say we do this time?” People are reflexive – they consider what you are doing and why.
Researchers are people too: some are nice and some are not so nice; some rate highly on attractiveness scales and some do not; some follow procedures exactly and some do not. All these things can affect the result of an experiment.
Some of the many confounding variables in a psychology experiment stem from the fact that a psychology experiment (and interviews, observations, case studies etc.) is a social situation in which neither the participants nor the experimenters are passive, inanimate objects but are active, thinking human beings. Imagine you've been asked to take part in a psychology experiment. Even if you didn't study psychology, you would be trying to work out what the experimenter expected to find out. Experimenters too have expectations about what their results are likely to be.
If the participant guesses the aims of the study they typically change their behaviour to either help or hinder results.
o Positive results due to the “please you effect”. This occurs when participants try to help produce the desired experimental findings.
o Negative results due to the "screw you effect”. Though rare, a participant may attempt to undermine the results of a research study.
As I've just said, participants have certain expectations concerning any experiment. Orne (1962) calls these demand characteristics. Participants are not like a mechanical measuring instrument, they are motivated to find out the purpose of the experiment and maybe respond in a way which supports the hypothesis being tested. Demand characteristics are all the clues in an experiment which convey to the participant the purpose of the research. Participants will be affected by: (i) their surrounding; (ii) the researcher’s characteristics; (iii) the researcher’s behaviour (e.g. non-verbal communication), and (iv) their interpretation of what is going on in the situation. Experimenters should attempt to minimise these factors by keeping the environment as natural as possible, carefully following standardised procedures. Finally, perhaps different experimenters should be used to see if they obtain similar results.
The experimenter unconsciously conveys to participants how they should behave - this is called experimenter bias. The experimenter is often totally unaware of the influence which s/he is exerting and the cues may be very subtle indeed but they have an influence nevertheless.
Rosenthal (1966) is famous for demonstrating how powerful these experimenter effects can be. He used several hundred of his students as experimenters and told one group that they would be studying a strain of maze-bright' rats (bred from intelligent stock) and the other half that they would be studying 'maze-dull' rats. In fact there was no great difference between the rats and they had been randomly assigned to the groups. Nevertheless, the supposedly brainy rats did learn to run the maze more quickly!
In another of his studies Rosenthal found that male researchers were far more likely to smile at female participants than at male participants. Since this is likely to elicit a smile from the female participant, it means that any study on sex differences in co-operation or friendliness is liable to be spoilt.
Experimenters can bias the results by (i) failing to follow standardised procedures, (ii) miss recording results, (ii) and by giving unintentional clues to the participants about what the experiment is about and how they expect them to behave. Also, the personal attributes (e.g. age, gender, accent, manner etc.) of the experiment can affect the behaviour of the participants.
Back to Homepage