Variables in Experimental Method | Nature and Types of Variables

The experimental method originated in the year 1879 when Wilhelm Wundt, a German psychologist set up the first psychology laboratory at Leipzig. Under the influence of Wundt the experimental method developed rapidly and today most of the psychological data are collected through well planned and scientifically conducted experiments.



An experiment is a procedure to create certain stimulating conditions, observe the effects following such changes and explain the same on the basis of already existing knowledge or generate new knowledge. An experimental method therefore, is used lo confirm or expand existing knowledge or to generate new knowledge and fill the gaps. It can be used outside the laboratory as well as inside.

Most of the experiments take place in the laboratory because the experimenter can carefully control conditions in the laboratory and more easily than in a natural situation. A laboratory experiment provides the experimenter with an opportunity to introduce change and manipulate conditions in a short time and under less cost. It also helps him to anticipate new changes and 'study their effect which may not be possible or desirable in a natural setting. An experiment is carried out under well controlled conditions in which there is a systematic variation of one of the conditions.

The experimental method involves creation of certain stimulating conditions or presentation of certain stimuli that evoke or produce a certain response through repeated observations on a number of people. Certain generalizations can be arrived at about the relationships between stimuli and responses.


MAIN FEATURES OF THE EXPERIMENTAL METHOD 


The main features of the experimental method are:

i. We specify the antecedent (stimulus) conditions of an event or behavior that is all the circumstances that come before a behavior so that we can predict the outcome
ii. We manipulate the antecedent conditions to create at least 2 different treatment conditions
iii. The subjects are exposed to different treatment conditions so that we can measure the effects of those conditions on behavior.
iv. Record the responses or behaviors of the subjects under various conditions and then compare them.
v. Assess whether or not the predictions are confirmed. If the behavior changes as the antecedent conditions change, we can say that the differences in the antecedent conditions caused the difference in the behavior i.e. we can also infer a cause and effect relationship between the antecedent treatment conditions and the subject's behavior.

The experimenter must clearly define what is being studied and how so that the experiment can be evaluated and replicated.


VARIABLES: THEIR NATURE AND TYPES 


In an experiment, the experimenter tries to discover the relationship among variables. A variable is that which can be changed or varied or that which changes or varies itself. There are three types of variables in an experiment viz. Independent variables, dependent variable and intervening variables.


Independent variable (I. V.): This is the dimension which is systematically and independently varied (manipulated) by the experimenter to study its impact on the behavior or the organism. It is also called antecedent variable because it occurs before the behavior on response. It is also known as stimulus variable. An independent variable may be an environmental variable like illumination level, a task variable such as level of complexity, mode of presentation and subject variable e.g. age, sex, anxiety, intelligence.

Dependent Variable (D.V.) is also called consequent variable or response variable. It is a change in the response or behavior which follows or accompanies the changes in the independent variable. Its value depends on the value of independent variable. In an experiment when there is one independent variable and the dependent variable it is called Uni-variate experiment. There need not necessarily be only one independent and one dependent variables. In certain experiments there are more than two variables. Such experiments are called Multivariate experiments. In a Multivariate experiment the relationship between two independent variables and one dependent variable or the relationship between one independent and two dependent variables or the relationships between two independent and two dependent variables is investigated. For e.g. Consider the effect of teaching method on learning of science. Here the teaching method (lecture or Discussion) is the independent variable and performance in learning science is the dependent variable. This is the example of uni-variate experiment.

In a Multivariate experiment, the experimenter may have 2 independent variables such as lecture method and discussion method as teaching methods and recall of science as dependent variable. Here in a Multivariate experiment, the experimenter may study one independent variable lecture method of teaching on 2 dependent variables learning ' of science and learning of English prose. If he wants to study 2 independent variables lecture method and Discussion method on 2 dependent variables learning of science and learning of prose, both independent variables and dependent variables must be operationally defined.

Intervening variable: The 3rd set of variables in an experiment which are not deliberately introduced or varied by the experimenter but influence the responses on dependent variables are called intervening variables. They are also called as mediating variables. They intervene and distort the relationship between the independent variable and dependent variable. These are not observable but are present within the subject such as motivation, intelligence, past experience etc. or sometimes present in the outside environment. The exact nature of the intervening variables varies from experiment to experiment depending on the nature of the organism, the nature of independent variable, nature of dependent variable and other factors. Their effect may be in the same direction as the independent variable or in the opposite direction. They cannot be seen nor manipulated by the experimenter but their effect can be inferred from the effect of the  independent variables upon the dependent variables, so very little attention is given to them. When the intervening variables also called extraneous variables result in changes from one condition to another along with the independent variable we have a situation called Confounding. In confounding we can say for sure that the changes in DV is observed are caused by the IV or by the intervening or extraneous variable. Confounding : threatens the internal validity. Hence precautions have to be taken to eliminate the effect of the intervening variables.

In an experimental research, the experimenter has to keep in mind three factors

i. Theoretical consideration: In choosing a particular variable as intervening variable he should know how it interacts with IV for producing change in the DV. He should also know whether it is related to the theory with which he is working.

ii. Design consideration: Depending on the nature of the experimental design, IV, . extraneous an intervening variable should be selected

iii Practical consideration: The financial resources available and the time factor and the number & nature of variables should all be considered. These considerations are useful in increasing the validity of the experimental research.

The experimental method involves a number of dependent methods:

- Methods for the selection of subjects to be studied depending on the nature and purpose of the study.
- Suitable methods have to be devised for controlling extraneous variables.
- Suitable tests and tools have to be devised for the particular purpose.
- Methods for presenting the stimuli and for giving instructions to the subjects have to be developed
- Methods for recording internal bodily changes in the subject must be devised for certain experiments as required.
- In some experiments, introspective report of the subject must be obtained.
- Statistical methods to be used for analyzing and interpreting the data

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