Test: Experimental variables and ways to control them. Types of variables in the experiment

The researcher should strive to operate in the experiment only as an independent variable. An experiment where this condition is met is called a pure experiment. But most often in the course of the experiment, by varying one variable, the experimenter changes at the same time a number of others. This change can be caused by the action of the experimenter and is due to the relationship of two variables.

For example, in an experiment on developing a simple motor skill, he punishes the test subject for failures with an electric shock. The amount of punishment can act as an independent variable, and the speed of skill development as a dependent variable. Punishment not only reinforces appropriate reactions in the subject, but also gives rise to situational anxiety in him, which affects the results - it increases the number of errors and reduces the speed of skill development.

The central problem in conducting an experimental study is the selection of an independent variable and its isolation from other variables.

As independent variables in a psychological experiment may perform:

1) characteristics of tasks;

2) features of the situation (external conditions);

3) controlled features (states) of the subject.

The latter are often referred to as "body variables". Sometimes isolated fourth kind variables - constant characteristics of the subject (intelligence, gender, increase, etc.), but, in my opinion, they are additional variables, since they cannot be influenced, but their level can only be taken into account when forming the experimental and control groups.

A task characteristic is something that the experimenter can manipulate more or less freely. According to the tradition coming from behaviorism, it is believed that the experimenter only varies the characteristics of stimuli ( stimulus variables), but he has many more options at his disposal.

The experimenter can:

* vary stimuli or task material,

* change the type of response of the subject (verbal or non-verbal response),

* change the rating scale, etc.

*He can vary the instruction, changing the goals that the subject must achieve in the course of the task.

* The experimenter can vary the means that the subject has for solving the problem, and put obstacles in front of him.

*He can change the system of rewards and punishments during the course of the task, etc.

The peculiarities of the situation include those variables that are not directly included in the structure of the experimental task performed by the subject. This may be the temperature in the room, the situation, the presence of an external observer, etc.

Example. Experiments on identifying the effect of social facilitation (gain) were carried out according to the following scheme: the subject was given some sensorimotor or intellectual task. He first performed it alone, and then in the presence of another person or several people (the sequence, of course, varied in different groups). The change in the productivity of the subjects was assessed. In this case, the task of the subject remained unchanged, only the external conditions of the experiment changed.

What can the experimenter vary?

Firstly, these are the physical parameters of the situation: the location of the equipment, the appearance of the room, the illumination, sounds and noises, temperature, the placement of furniture, the color of the walls, the time of the experiment (time of day, duration, etc.). That is, all the physical parameters of the situation that are not incentives.

Secondly, these are socio-psychological parameters: isolation - work in the presence of the experimenter, work alone - work with a group, etc.

Thirdly, these are the features of communication and interaction between the subject (s) and the experimenter.

Judging by the publications in scientific journals, the number of experimental studies in which the variation of external conditions is used has increased dramatically in recent years.

TO "organism variables”, or uncontrollable characteristics of the subjects, include:

* physical,

* biological,

* psychological,

* socio-psychological and

*social signs.

Traditionally, they are referred to as "variables", although most of them are unchanged or relatively unchanged throughout life. The influence of differential psychological, demographic and other constant parameters on the behavior of an individual is studied in correlation studies. However, the authors of most textbooks on the theory of the psychological method, such as M. Matlin, include these parameters among the independent variables of the experiment.

As a rule, in a modern experimental study, the differential psychological characteristics of individuals, such as intelligence, gender, age, social position (status), etc., are taken into account as additional variables that are controlled by the experimenter in a general psychological experiment. But these variables can turn into a "second main variable" in a differential psychological study, and then a factorial design is used.

In order to find out its effect on the dependent variable.

Dependent variable- in a scientific experiment, a measured variable, changes in which are associated with changes in the independent variable.

The independent variable, for example, in a psychological experiment, can be considered the intensity of the stimulus, and the dependent variable is the ability of the subject to feel this stimulus.

Types of relationship between variables

1. The dependent variable is not sensitive to changes in the independent variable.
2. Monotonically increasing dependence: an increase in the values ​​of the independent variable corresponds to a change in the dependent variable.
3. Monotonically decreasing dependence: an increase in the values ​​of the independent variable corresponds to a decrease in the level of the independent variable.
4. Non-linear dependence of the U-shaped type - found in most experiments in which features of the mental regulation of behavior are highlighted
5. Inverted U-shaped dependence - obtained in numerous experiments and correlation studies.
6. Complex quasi-periodic dependence of the level of the dependent variable on the level of the independent.

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See what "Independent variable" is in other dictionaries:

Independent variable- Some aspect of the experimental situation that is under the direct control of the experimenter, who observes its possible influence on the behavior of the participants (see Dependent variable). For example, dividing participants into groups that are given ... ... Great Psychological Encyclopedia

INDEPENDENT VARIABLE, see VARIABLE... Scientific and technical encyclopedic dictionary

Independent variable- - see Function Argument... Economic and Mathematical Dictionary

independent variable- — [Ya.N. Luginsky, M.S. Fezi Zhilinskaya, Yu.S. Kabirov. English Russian Dictionary of Electrical Engineering and Power Industry, Moscow, 1999] Electrical engineering topics, basic concepts EN independent variable ... Technical Translator's Handbook

Independent variable- (independent variabile) - a variable that is controlled experimentally or for the purpose of observing its impact on other, dependent variables. For example, the speed limit on the roads is an independent variable, and the number ... ... Encyclopedic Dictionary of Psychology and Pedagogy

INDEPENDENT VARIABLE- (independent variable) a variable that is controlled experimentally or for the purpose of observing its impact. For example, some roads may systematically limit the speed of traffic, and the effect is measured in terms of statistics ... ... Big explanatory sociological dictionary

independent variable- nepriklausomasis kintamasis statusas T sritis automatika atitikmenys: engl. independent variable vok. unabhangige variable, f rus. independent variable, fpranc. grandeur indépendante, f … Automatikos terminų žodynas

independent variable- nepriklausomasis kintamasis statusas T sritis fizika atitikmenys: engl. independent variable vok. unabhängige Veränderliche, f rus. independent variable, fpranc. variable independante, f … Fizikos terminų žodynas

independent variable- Variable used to predict values, explanation, dependent variable. Synonyms: predictor, explanatory variable. See also dependent variable... Dictionary of Sociological Statistics

Independent variable- - a variable that causes a change in another (dependent) variable ... Social Work Dictionary

A variable is something that can be changed, such as a certain characteristic or value within a study. In psychology, variables are used to determine whether changes in one factor lead to changes in another.

Dependent and independent variables

In experimental psychology, there are two types of variables:

• Independent variable is a factor controlled by the authors of the study. For example, in an experiment investigating the impact of sleep deprivation on performance, sleep deprivation is the independent variable.
• Dependent variable- a phenomenon that experimenters fix and measure. In our example, the performance test results are just the dependent variable.

Extraneous and distorting factors

It is important to note that independent and dependent variables are not the only variables present in experiments. In some cases, extraneous factors can have a noticeable effect on the relationship between the independent and dependent variable (and therefore on the results of the experiment). For example, in our example, such factors include the age and gender of the subjects.

There are two main kinds of extraneous variables:

• subject variables. These are extraneous variables associated with the individual characteristics of each of the participants, which can affect how they react to the conditions of the experiment. These may include gender and age characteristics, origin, mood, anxiety, intelligence, awareness, etc.
• situational variables. These are extraneous variables associated with environmental phenomena that can affect the response of the participants. For example, if a participant is tested in a cool room, the cold temperature is considered an extraneous variable. Some participants may not respond to coolness, some may be distracted and annoyed.

In most cases, extraneous variables are also controlled within the experiment: the researchers themselves can select participants according to certain criteria or set other conditions.

Definition of variables

Before conducting an experiment, it is important to give the operating parameters of the variables - scientists determine the independent and dependent variables, decide in what framework they should be kept and how they will be measured.

For example, in our experiment on the effect of lack of sleep on performance, we must create working definitions for variables. If our hypothesis sounds like “students who experience lack of sleep will perform worse on tests”, then, first, we need to decide who we mean by “students”. Next, we need to define the "lack of sleep" variable. In our example, this would be, say, less than five hours of sleep the night before the test. And finally, we must decide on the "test". Let this be a little theory test...

Dependent variable- a variable (any mental phenomenon, characteristic), changes in which are considered as a consequence of changes in the experimental impact. Simply put, these are the so-called reactions or responses to experimental influence.

Psychologists deal with the behavior of the subject, so the parameters of verbal and non-verbal behavior are chosen as the dependent variable. These include: the number of errors that the rat made while running the maze; the time spent by the subject in solving the problem, changes in his facial expressions when watching an erotic film; time of motor reaction to a sound signal, etc.

The choice of a behavioral parameter is determined by the initial experimental hypothesis. The researcher should specify it as much as possible, i.e. to ensure that the dependent variable was operationalized - succumbed to registration during the experiment.

Behavior parameters can conditionally be divided into formal-dynamic and meaningful. Formal-dynamic (or spatio-temporal) parameters are quite easy to register with apparatus. Parameter examples:

a) Accuracy. The most frequently logged parameter. Since most of the tasks presented to the subject in psychological experiments are achievement tasks, then accuracy or the opposite parameter - the fallacy of actions - will be the main recorded parameter of behavior.

b) Latency. Mental processes proceed secretly from an external observer. The time from the moment the signal is presented to the choice of the answer is called the latent time. In some cases, latent time is the most important characteristic of the process, for example, when solving mental problems.

c) Duration, or speed, of execution. It is a performance characteristic. The time between the choice of an action and the end of its execution is called the speed of the action (in contrast to the latent time).

d) The pace, or frequency, of action. The most important characteristic, especially in the study of the simplest forms of behavior.

e) Productivity. The ratio of the number of errors or the quality of the execution of actions to the execution time. Serves as the most important characteristic in the study of learning, cognitive processes, decision-making processes, etc.

The dependent variable must be valid and reliable. Variable Reliability manifests itself in the stability of its recordability when the experimental conditions change over time. Validity of dependent variable determined only under specific experimental conditions and in relation to a certain hypothesis.

Three types of dependent variables can be distinguished: 1) simultaneous; 2) multidimensional; 3) fundamental. In the first case, only one parameter is recorded, and it is this parameter that is considered a manifestation of the dependent variable (there is a functional linear relationship between them), as, for example, when studying the time of a simple sensorimotor reaction. In the second case, the dependent variable is multidimensional. For example, the level of intellectual productivity is manifested in the time of solving a problem, its quality, and the difficulty of the problem solved. These parameters can be fixed independently. In the third case, when the relationship between the individual parameters of a multidimensional dependent variable is known, the parameters are considered as arguments, and the dependent variable itself is considered as a function.

There is another important property of the dependent variable, namely - sensitivity (sensitivity) dependent variable to changes in the independent. The bottom line is that the manipulation of the independent variable affects the change in the dependent.

The first thing to decide when planning an experiment is how many levels of the independent variable will be and what they will be. The levels of an independent variable are its specific values. They can be set in any measurement scale, i.e. can be both quantitative and qualitative.

The independent variable necessarily has at least two levels that reflect the features of its impact on the dependent variable. Otherwise, it simply ceases to be a variable. In the problem solving example, the independent variable has two quality levels specified in the naming scale: 1 - stuffy room; 2 - ventilated room. If the researcher wants to trace more subtle, quantitative relationships between how much the air in the room is saturated with oxygen and the level of intellectual activity of the subjects, he can express his independent variable on a stronger scale, determining, for example, different values ​​of the oxygen content per 1 m 3 of air.

If a researcher discovers a difference in the success of solving problems in a stuffy and ventilated room, then he has some reason to believe that stuffiness affects the quality of problem solving. In any case, the first two conditions of causal inference are satisfied. In other words, a change in the dependent variable in accordance with a change in the independent variable allows us to talk about the influence of the independent variable on the dependent.

Experimental designs with an independent variable that has two levels are called single-level - probably because one of the levels of the independent variable reflects the normal, usual state of affairs, which is characterized by the absence of exposure (in our example, this state corresponds to a ventilated room). The impact on the subjects, leading to a deterioration in problem solving, is exerted by another level of the independent variable, reflecting the abnormal state of affairs (in our example, a stuffy room).

The independent variable can have more than two levels. Experimental designs in which the independent variable has more than two levels are called multilevel. For example, if we are interested in whether who the child walks with on the playground influences what games the child prefers to play, then in this case the researcher controls one independent variable with four levels: 1 - walks alone, 2nd babysitter , 3 - with parents, 4 friends. And if, for example, a child walking with a nanny prefers to play catch-up (rather than other games) for much longer, then the researcher has reason to believe that this factor determines the interests of the child in preferring this game.

Note that if the experimenter's task is not just to note the influence of one variable on another, but also to find out the nature of such a relationship, he must use precisely multilevel independent variables. Otherwise, the nature of the connection will not be established. So, for example, a researcher who studies the psychophysical relationships between different concentrations of an odorous substance and the corresponding sensations must take several such concentrations in order to understand whether the desired relationship is described by a logarithmic or power law. A single-level plan will not provide him with such an opportunity.

When designing an experiment, the researcher must clearly define how many levels the independent variable has and how exactly, according to his hypothesis, they affect the dependent variable. The question then becomes how to most reliably distinguish different levels of a variable from each other. The better different levels of the independent variable are divorced, i.e. the clearer their differences are, the clearer their effect on the dependent variable will be. If the levels of the independent variable can hardly be distinguished from each other, then their effect on the dependent variable will be less noticeable. In this case, the researcher runs the risk of missing a result that is important for confirming the hypothesis, passing by his discovery.

In addition, the researcher must decide how many independent variables he uses in his research. If there is only one independent variable, we speak of single-factor experimental designs. Depending on the number of levels of the independent variable, single-factor plans can be either single-level or multi-level.

If the researcher uses two or more independent variables that together affect the same dependent variable, such plans are called multifactorial. Multivariate designs can include either single-level or multi-level explanatory variables. For example, a researcher is testing the hypothesis that the approximately equal success of boys and girls in completing an intelligence test is due to the fact that boys are much better at solving arithmetic tasks, and girls are much better at solving anagrams. This would be an example of a multivariate design where the first variable (sex) has two levels (boys and girls) and the second variable (task type) also has two levels (arithmetic tasks and anagrams).

If the researcher is interested in how the quality of problem solving changes in people with different daily regimens ("owls" and "larks"), then he will build an experiment with one single-level and one multilevel variables: the first variable (day regimen) has two levels (" owls" and "larks"), the second variable (time of day) has four levels (morning, afternoon, evening and night). In this case, the dependent variable in both cases will be the quality of problem solving.

Thus, the independent variable plays a key role in planning an experimental study, and even before proceeding with practical actions, the researcher must clearly understand how many independent variables will be in his study, which ones, how many levels each will have and how these levels he will be recorded in the study.