Methods of psychology experiment advantages and disadvantages table. What is a natural experiment in psychology

Psychological experiment- (from Latin experimentum - test, experience), a method of cognition with the help of which phenomena of nature and society are studied under controlled and controlled conditions. One of the main (along with observation) methods scientific knowledge in general, psychological research in particular. It differs from observation by active intervention in the situation on the part of the researcher, carrying out systematic manipulation of one or more variables (factors) and recording accompanying changes in the behavior of the studied object. A correctly designed experiment allows you to test hypotheses about cause-and-effect relationships, without limiting yourself to stating the connection (correlation) between variables.

There are traditional and factorial experimental designs. With traditional planning, only one independent variable changes, with factorial planning - several. In this case, analysis of variance (R. Fisher) is used to statistically process the experimental results. If the area under study is relatively unknown and there is no system of hypotheses, then they talk about a pilot experiment, the results of which can help clarify the direction of further analysis. When there are two competing hypotheses and an experiment allows us to choose one of them, we speak of a decisive experiment. A control experiment is carried out to check any dependencies. The use of experiment, however, encounters fundamental limitations associated with the impossibility in some cases of arbitrarily changing variables. Thus, in differential psychology and personality psychology, empirical dependencies for the most part have the status of correlations (i.e. probabilistic and statistical dependencies) and, as a rule, do not always allow drawing conclusions about cause-and-effect relationships. One of the difficulties of using an experiment in psychology is that the researcher often finds himself involved in a situation of communication with the person being examined (subject) and can unwittingly influence his behavior. Formative, or educational, experiments form a special category of methods of psychological research and influence. They allow you to purposefully form the characteristics of such mental processes as perception, attention, memory, thinking.

The essence of a psychological experiment Wundt sees in a change in a material stimulus causing a change in the mental process directly associated with it, and in the objective, if possible, recording of the external manifestations of the caused mental process. Wundt, from the point of view of the relationship between the mental process, on the one hand, and stimuli and reactions, on the other, distinguished three types of mental experiments: the method of stimulation, the method of expression and the method of reaction. The basic scheme of stimulus-response experiments is also the basic law of behavior. In experimental psychology, verbal instruction is the basis of all experience. With its help, the experimenter creates the desired environment for the subject, evokes the process to be observed, establishes connections, but usually the psychological role of the instruction itself is ignored. The stimulus-response circuit is the basis of any experiment. This means that the common thing that unites all types and forms of mental experiment is a naturalistic approach to human psychology, without opening and overcoming it, which is impossible to find an adequate method for research cultural development behavior. The stimulus-response scheme cannot be applied to the study of higher mental functions and cannot serve as a basis for constructing an adequate method for studying specific human forms of behavior.

Two types of psychological experiments: laboratory and natural. A laboratory psychological experiment takes place in specially created and controlled conditions, usually using special equipment and devices. The initial object of a laboratory experiment in psychology was elementary mental processes: sensations, perceptions, reaction speed. Distinctive feature An experiment in a laboratory is strict adherence to research conditions and the accuracy of the data obtained. Reached great perfection in the use of laboratory experiments cognitive psychology, which studies human cognitive processes. Cognitive processes constituted the main area of ​​laboratory research in human psychology. The scientific objectivity and practical significance of the data obtained in a laboratory experiment is reduced by artificiality created conditions. This is due both to the remoteness of the problems solved in the experiment from the real life conditions of the subject, and to the impossibility of recording the nature of the experimenter’s influence on the subject during the study. Therefore, the problem arises of transferring data obtained in the laboratory to real conditions of human life. In other words, does the experimental situation simulate essential conditions human life? This question always remains open in laboratory psychological research. The use of a laboratory experiment in real legal practice, due to its artificiality, abstractness, and labor intensity, is actually not practiced. A natural psychological experiment removes the noted limitations of a laboratory experiment. Its main difference lies in the combination of experimental research with the naturalness of the conditions. Subjects participating in a natural experiment are unaware that they are being tested.

Rubinstein: the main task of the psychological experiment, conclusion. is to make nouns accessible to objective external observation. features of the internal Ps process; To do this, it is necessary, by varying the environmental conditions, to find a situation in which the external course of the act would adequately reflect its internal Ps content, i.e. The task of experimentally varying conditions in a psychological experiment is, first of all, to reveal the correctness of one single psychological interpretation of an action and deed, excluding the possibility of all others.

Question 11. Method social experiment, its advantages and disadvantages.

Experimental study- this is one of the methods social psychology, which aims to identify the relationship between cause and effect.

By changing one of the variables (independent), the researcher conducting the experiment observes changes in another variable (dependent), which is not manipulated. The data obtained as a result of the experiment shows whether the independent variable is the cause of changes in the dependent variable.

The advantages of the method are:

1) artificially cause phenomena of interest to the experimenter;

2) clearly take into account the influence of conditions on the socio-psychological phenomena being studied;

3) quantitatively change the experimental conditions;

4) change some conditions while keeping others unchanged.

Disadvantages of the experimental method include:

1) the artificiality of the experiment or its remoteness from life, due to the absence of conditions essential for the phenomenon being studied;

2) analyticity and abstractness of the experiment. The experiment is usually carried out in artificial conditions, in connection with which, the features and patterns of the course of socio-psychological processes identified during the experiment, which are often of an abstract nature, do not make it possible to draw direct conclusions about the patterns of the course of these same processes in natural conditions;

3) the complicating role of the influence of the experimenter (Rosenthal effect) - the impossibility of excluding the influence of the experimenter on the course and results of the experiment.

Types of experiments:

1) according to the form:

a) natural experiment - consists of actually influencing a real object for the purpose of diagnosing it;

b) thought experiment - consists of manipulating not with a real object, but with information about it or with its model;

2) according to the conditions:

a) field experiment - organized in natural conditions for the object being diagnosed; can be carried out at all levels of public life. Advantages: a combination of the naturalness of observation methods and the activity of the experiment. Flaws: involve ethical and legal issues;

b) laboratory experiment - takes place in special conditions using special equipment that allows one to strictly record the characteristics of external influences and the corresponding mental responses of people. The actions of the subjects are determined by the instructions. The subjects know that an experiment is being conducted, although they may not fully understand the true meaning of the experiment. Advantages: the possibility of repeated experiments with a large number of subjects, which makes it possible to establish general reliable patterns of development of mental phenomena. Flaws: artificiality of research conditions.

Special types of experimental techniques include instrumental methods carried out using technical devices that make it possible to create a certain significant situation that reveals one or another characteristic of the object being diagnosed, taking readings about the manifestation of the characteristics being studied, recording and partially calculating the diagnostic results.

The hardware is based on the classic “bridge” in electrical engineering. Winston "- four resistances (resistors) connected in the form of a rhombus.

One of the oldest and most popular methods of scientific research in psychology is the natural experiment. Scientists resorted to “his services” thousands of years ago, and in modern conditions he has acquired particular effectiveness.

What is the essence of a natural experiment in psychology?

A natural experiment is also called a field experiment because it is carried out under “field” conditions. The object lives its normal life (albeit, set in a certain direction, desired by the experimenter) and the intervention of the subject is minimal. The latter is actually an observer.

If ethical considerations permit, the subject is not informed about the experiment, and neither he nor other people suspect anything. From the outside it seems that no experiment is being carried out at all. Natural experiment is very often used in psychology, especially in its social section.

Natural experiment in psychology: pros and cons

A natural experiment in psychology has a huge advantage over a laboratory experiment. After all, the familiar conditions in which the subject is located allow him to feel calm. He does not tense up and acts as he naturally does. And this allows the researcher to draw more adequate conclusions.

For a long time it was believed that a natural experiment is inferior to a laboratory experiment in the accuracy of recording the results. After all, organize in field conditions this process It was really difficult. But the key word here is “was.” Today, with the availability of high-tech equipment, it is quite possible to fill this gap and obtain results that are even much more accurate than with a laboratory experiment.

Natural Experiment Techniques

A natural experiment, although very close to observation, is still not one. This method assumes only the appearance of the object's ordinary life. In fact, the experimenter creates certain conditions in which it will take place. And then he observes the behavior of the subject in them.
There are several techniques and forms for creating certain conditions during a natural experiment. Among them:

Introductory tasks - the subject is given one or another task and the experimenter is interested in how the subject will behave.

Formative (or educational) experiment - the object is also given a task. But its goal is to develop certain skills or abilities. And the experimenter observes the process and draws conclusions.

Transformation of the conditions of activity - the structure of activity (for example, professional) changes radically. Emphases are shifted, control levers are placed, new stimuli are introduced, the emotional background is “colored” in unusual shades, and the results of the activities of the group of people under study (or an individual) in new conditions are recorded.

Creating a model - this technique is used in cases where it is impossible to simply conduct a survey, test, experiment or observation in real operating conditions. Then an artificial model is created that repeats the parameters and properties of the natural “field”.

V.V. Nikandrov points out that the achievement main goal experiment - the utmost possible unambiguity in understanding the connections between the phenomena of internal mental life and their external manifestations - is achieved thanks to the following main characteristics of the experiment:

1) the initiative of the experimenter in the manifestation of psychological facts of interest to him;

2) the possibility of varying the conditions for the emergence and development of mental phenomena;

3) strict control and recording of conditions and the process of their occurrence;

4) isolating some and emphasizing other factors that determine the phenomena being studied, which makes it possible to identify the patterns of their existence;

5) the possibility of repeating experimental conditions for multiple verification of the obtained scientific data and their accumulation;

6) varying conditions for quantitative estimates identified patterns.

Thus, a psychological experiment can be defined as a method in which the researcher himself causes the phenomena of interest to him and changes the conditions for their occurrence in order to establish the reasons for the occurrence of these phenomena and the patterns of their development. In addition, the received scientific facts can be repeatedly reproduced due to controllability and strict control of conditions, which makes it possible to test them, as well as to accumulate quantitative data on the basis of which one can judge the typicality or randomness of the phenomena being studied.

There are several types of experiments. Depending on the way of organizing There are laboratory, natural and field experiments. Laboratory the experiment is carried out under special conditions. The researcher plans and purposefully influences the object of study in order to change its state. The advantage of a laboratory experiment can be considered strict control over all conditions, as well as the use of special equipment for measurement. The disadvantage of a laboratory experiment is the difficulty of transferring the obtained data to real conditions. The subject in a laboratory experiment is always aware of his participation in it, which can cause motivational distortions.

Natural The experiment is carried out under real conditions. Its advantage is that the study of the object is carried out in the context Everyday life, so the data obtained is easily transferred to reality. The subjects are not always informed about their participation in the experiment, so they do not give motivational distortions. Disadvantages: inability to control all conditions, unexpected interference and distortion.

Field The experiment is carried out according to the natural scheme. In this case, it is possible to use portable equipment that allows more accurate recording of the received data. The subjects are informed about their participation in the experiment, but the familiar environment reduces the level of motivational distortions.

Depending on the research objectives There are search, pilot and confirmatory experiments. Search the experiment is aimed at finding a cause-and-effect relationship between phenomena. It is carried out at the initial stage of the study, allows you to formulate a hypothesis, identify independent, dependent and secondary variables (see 4.4) and determine ways to control them.

Aerobatic The experiment is a trial experiment, the first in a series. It is conducted on a small sample, without strict control of variables. A pilot experiment allows you to eliminate gross errors in the formulation of a hypothesis, specify the goal, and clarify the methodology for conducting the experiment.

Confirming the experiment is aimed at establishing the type of functional connection and clarifying the quantitative relationships between variables. Conducted at the final stage of the study.

Depending on the nature of influence The test subject is divided into ascertaining, formative and control experiments. Ascertaining an experiment includes measuring the state of an object (a subject or a group of subjects) before active influence on it, diagnosing the initial state, and establishing cause-and-effect relationships between phenomena. Purpose formative experiment is the use of methods for the active development or formation of any properties in subjects. Control An experiment is a repeated measurement of the state of an object (a subject or a group of subjects) and a comparison with the state before the start of the formative experiment, as well as with the state in which the control group was located, which did not receive experimental influence.

By possibilities of influence The experimenter's independent variable is distinguished between the induced experiment and the experiment referred to. Provoked An experiment is an experience in which the experimenter himself changes the independent variable, while the results observed by the experimenter (types of reactions of the subject) are considered provoked. P. Fress calls this type of experiment “classical”. Experiment, which is referred to is an experiment in which changes in the independent variable are carried out without intervention by the experimenter. This type of psychological experiment is resorted to when independent variables have an impact on the subject that is significantly extended over time (for example, the education system, etc.). If the effect on the subject can cause serious negative physiological or psychological impairment, then such an experiment cannot be carried out. However, there are times when a negative impact (such as a brain injury) actually occurs. Subsequently, such cases can be generalized and studied.

4.3. Structure of a psychological experiment

The main components of any experiment are:

1) subject (subject or group being studied);

2) experimenter (researcher);

3) stimulation (the method of influencing the subject chosen by the experimenter);

4) the subject’s response to stimulation (his mental reaction);

5) experimental conditions (in addition to stimulation, influences that can influence the reactions of the subject).

The subject's answer is an external reaction, by which one can judge the processes occurring in his internal, subjective space. These processes themselves are the result of the influence of stimulation and experimental conditions on it.

If the response (reaction) of the subject is denoted by the symbol R, and the influence of the experimental situation on him (as a set of stimulation effects and experimental conditions) is denoted by the symbol S, then their relationship can be expressed by the formula R = =f(S). That is, the reaction is a function of the situation. But this formula does not take into account the active role of the psyche, the human personality (P). In reality, a person’s reaction to a situation is always mediated by the psyche and personality. Thus, the relationship between the main elements of the experiment can be fixed by the following formula: R = f(R, S).

P. Fresse and J. Piaget, depending on the objectives of the study, distinguish three classical types of relationships between these three components of the experiment: 1) functional relationships; 2) structural relations; 3) differential relations.

Functional relationships are characterized by the variability of the responses (R) of the subject (P) with systematic qualitative or quantitative changes in the situation (S). Graphically, these relationships can be represented by the following diagram (Fig. 2).

Examples of functional relationships identified in experiments: changes in sensations (R) depending on the intensity of the impact on the senses (S); memory capacity (R) from the number of repetitions (S); intensity of emotional response (R) on the action of various emotiogenic factors (S); development of adaptation processes (R) in time (S) and so on.

Structural relationships are revealed through a system of responses (R1, R2, Rn) to various situations (Sv S2, Sn). The relationships between individual responses are structured into a system that reflects the structure of personality (P). Schematically it looks like this (Fig. 3).

Examples of structural relationships: a system of emotional reactions (Rp R2, Rn) to the action of stressors (Sv S2, Sn); solution efficiency (R1, R2, Rn) various intellectual tasks (S1, S2, Sn) and so on.

Differential relations are identified through analysis of reactions (R1, R2, Rn) of different subjects (P1, P2, Pn) for the same situation (S). The diagram of these relationships is as follows (Fig. 4).

Examples of differential relations: difference in reaction speed between different people, national differences in the expressive manifestation of emotions, etc.

To clarify the relationship between all factors included in the experiment, the concept of “variable” was introduced. There are three types of variables: independent, dependent and additional.

Independent variables. A factor that can be changed by the experimenter himself is called independent variable(NP).

The NP in an experiment can be the conditions in which the subject’s activity is carried out, the characteristics of the tasks that the subject is required to perform, the characteristics of the subject himself (age, gender, other differences between the subjects, emotional states and other properties of the subject or people interacting with him). Therefore, it is customary to highlight the following types NP: situational, instructive and personal.

Situational NPs most often are not included in the structure of the experimental task performed by the subject. However, they have a direct impact on his activity and can be varied by the experimenter. Situational NPs include various physical parameters, such as illumination, temperature, noise level, as well as the size of the room, furnishings, placement of equipment, etc. The socio-psychological parameters of situational NPs may include performing an experimental task in isolation, in the presence of an experimenter, an external observer or group of people. V.N. Druzhinin points to the peculiarities of communication and interaction between the subject and the experimenter as a special type of situational NP. Much attention is paid to this aspect. In experimental psychology there is a separate direction called “psychology of psychological experiment”.

Instructional NP are directly related to the experimental task, its qualitative and quantitative characteristics, as well as methods of its implementation. The experimenter can manipulate the instructive NP more or less freely. He can vary the material of the task (for example, numerical, verbal or figurative), the type of response of the subject (for example, verbal or non-verbal), the rating scale, etc. Great possibilities lie in the way of instructing the subjects, informing them about the purpose of the experimental task. The experimenter can change the means that are offered to the subject to complete the task, put obstacles in front of him, use a system of rewards and punishments during the task, etc.

Personal NPs represent controllable characteristics of the subject. Typically, such features are the states of the experiment participant, which the researcher can change, for example, various emotional states or states of performance-fatigue.

Each subject participating in the experiment has many unique physical, biological, psychological, socio-psychological and social characteristics that the experimenter cannot control. In some cases, these uncontrollable characteristics should be considered additional variables and control methods should be applied to them, which will be discussed below. However, in differential psychological research, when using factorial designs, uncontrolled personal variables can act as one of the independent variables (for details on factorial designs, see 4.7).

Researchers also distinguish between different kinds independent variables. Depending on the presentation scales Qualitative and quantitative NPs can be distinguished. High quality NPs correspond to different gradations of naming scales. For example, the emotional states of the subject can be represented by states of joy, anger, fear, surprise, etc. Methods of performing tasks may include the presence or absence of prompts for the subject. Quantitative NPs correspond to rank, proportional or interval scales. For example, the time allotted to complete a task, the number of tasks, the amount of remuneration based on the results of solving problems can be used as quantitative NP.

Depending on the number of manifestation levels independent variables distinguish between two-level and multi-level NPs. Two-level NPs have two levels of manifestation, multi-level– three or more levels. Depending on the number of levels of manifestation of NP, experimental plans of varying complexity are constructed.

Dependent Variables. A factor whose change is a consequence of a change in the independent variable is called dependent variable(ZP). The dependent variable is the component of the subject's response that is of direct interest to the researcher. Physiological, emotional, behavioral reactions and others can act as GPs. psychological characteristics, which can be recorded during psychological experiments.

Depending on the the method by which changes can be registered, allocate salary:

S directly observable;

S requiring physical equipment for measurement;

S requiring a psychological dimension.

To the salary, directly observable include verbal and non-verbal behavioral manifestations that can be clearly and unambiguously assessed by an external observer, for example, refusal of activity, crying, a certain statement by the subject, etc. physical equipment for registration, include physiological (pulse, blood pressure, etc.) and psychophysiological reactions (reaction time, latent time, duration, speed of action, etc.). For POs requiring psychological dimension, include such characteristics as the level of aspirations, the level of development or formation of certain qualities, forms of behavior, etc. For psychological measurement of indicators, standardized procedures can be used - tests, questionnaires, etc. Some behavioral parameters can be measured, i.e. i.e. clearly recognized and interpreted only by specially trained observers or experts.

Depending on the number of parameters, included in the dependent variable, there are unidimensional, multidimensional and fundamental PPs. One-dimensional ZP is represented by a single parameter, changes in which are studied in the experiment. An example of a one-dimensional PP is the speed of a sensorimotor reaction. Multidimensional The salary is represented by a set of parameters. For example, attentiveness can be assessed by the volume of material viewed, the number of distractions, the number of correct and incorrect answers, etc. Each parameter can be recorded independently. Fundamental ZP is a complex variable, the parameters of which have certain known relationships with each other. In this case, some parameters act as arguments, and the dependent variable itself acts as a function. For example, the fundamental dimension of the level of aggression can be considered as a function of its individual manifestations (facial, verbal, physical, etc.).

The dependent variable must have such a basic characteristic as sensitivity. Sensitivity FP is its sensitivity to changes in the level of the independent variable. If, when the independent variable changes, the dependent variable does not change, then the latter is non-positive and it makes no sense to conduct an experiment in this case. There are two known variants of the manifestation of non-positivity of the PP: the “ceiling effect” and the “floor effect”. The “ceiling effect” is observed, for example, in the case when the presented task is so simple that all subjects, regardless of age, perform it. The “floor effect,” on the other hand, occurs when a task is so difficult that none of the subjects can cope with it.

There are two main ways to record changes in mental health in a psychological experiment: immediate and delayed. Direct The method is used, for example, in short-term memory experiments. Immediately after repeating a number of stimuli, the experimenter records their number reproduced by the subject. The deferred method is used when between influence and the effect lasts a certain period of time (for example, when determining the influence of the number of memorized foreign words on the success of the text translation).

Additional Variables(DP) is a concomitant stimulation of the subject that influences his response. The totality of DP consists, as a rule, of two groups: external conditions experience and internal factors. Accordingly, they are usually called external and internal DPs. TO external DP include the physical environment of the experiment (lighting, temperature, sound background, spatial characteristics of the room), parameters of the apparatus and equipment (design of measuring instruments, operating noise, etc.), time parameters of the experiment (start time, duration, etc.), experimenter's personality. TO internal DP includes the mood and motivation of the subjects, their attitude towards the experimenter and the experiments, their psychological attitudes, inclinations, knowledge, abilities, skills and experience in this type of activity, level of fatigue, well-being, etc.

Ideally, the researcher strives to reduce all additional variables to nothing or at least to a minimum in order to highlight the “pure” relationship between the independent and dependent variables. There are several main ways to control the influence of external DP: 1) elimination of external influences; 2) constancy of conditions; 3) balancing; 4) counterbalancing.

Elimination of external influences represents the most radical method of control. It consists of complete exclusion from external environment any external DP. In the laboratory, conditions are created that isolate the subject from sounds, light, vibration, etc. The most a shining example An experiment on sensory deprivation conducted on volunteers in a special chamber that completely excludes the entry of any irritants from the external environment can serve as an experiment. It should be noted that it is almost impossible to eliminate the effects of DP, and it is not always necessary, since the results obtained under the conditions of eliminating external influences can hardly be transferred to reality.

The next method of control is to create constant conditions. The essence of this method is to make the effects of DP constant and identical for all subjects throughout the experiment. In particular, the researcher strives to make constant the spatio-temporal conditions of the experiment, the technique of its conduct, equipment, presentation of instructions, etc. With careful application of this method of control, large errors can be avoided, but the problem of transferring the results of the experiment to conditions that are very different from the experimental ones is difficult. remains problematic.

In cases where it is not possible to create and maintain constant conditions throughout the experiment, resort to the method balancing. This method is used, for example, in a situation where the external DP cannot be identified. In this case, balancing will consist of using a control group. The study of the control and experimental groups is carried out under the same conditions with the only difference being that in the control group there is no effect of the independent variable. Thus, the change in the dependent variable in the control group is due only to external DP, while in the experimental group it is due to the combined effect of external additional and independent variables.

If the external DP is known, then balancing consists of the effect of each of its values ​​in combination with each level of the independent variable. In particular, such an external DP as the gender of the experimenter, in combination with an independent variable (the gender of the subject), will lead to the creation of four experimental series:

1) male experimenter - male subjects;

2) male experimenter – female subjects;

3) female experimenter - male subjects;

4) female experimenter - female subjects.

More complex experiments may involve balancing multiple variables simultaneously.

Counterbalancing as a way to control external DP, it is most often practiced when the experiment includes several series. The subject is exposed to different conditions sequentially, but previous conditions can change the effect of subsequent ones. To eliminate the “sequence effect” that arises in this case, experimental conditions are presented to different groups of subjects in different orders. For example, in the first series of the experiment, the first group is presented with solving intellectual problems from simpler to more complex, and the second group - from more complex to simpler. In the second series, on the contrary, the first group is presented with solving intellectual problems from more complex to simpler, and the second group - from simpler to more complex. Counterbalancing is used in cases where it is possible to conduct several series of experiments, but it should be taken into account that big number attempts causes fatigue in the subjects.

Internal DP, as mentioned above, are factors hidden in the personality of the subject. They have a very significant impact on the results of the experiment; their impact is quite difficult to control and take into account. Among the internal DPs we can highlight permanent And fickle. Permanent internal DPs do not change significantly during the experiment. If the experiment is carried out with one subject, then the constant internal DP will be his gender, age, and nationality. This group of factors also includes the subject’s temperament, character, abilities, inclinations, interests, views, beliefs and other components of the general orientation of the individual. In the case of an experiment with a group of subjects, these factors acquire the character of unstable internal DPs, and then, to level out their influence, they resort to special methods of forming experimental groups (see 4.6).

TO fickle internal DP includes the psychological and physiological characteristics of the subject, which can either change significantly during the experiment, or be updated (or disappear) depending on the goals, objectives, type, and form of organization of the experiment. The first group of such factors consists of physiological and mental states, fatigue, addiction, acquisition of experience and skills in the process of performing an experimental task. The other group includes the attitude towards this experience and this research, the level of motivation for this experimental activity, the attitude of the subject towards the experimenter and his role as a test subject, etc.

To equalize the effect of these variables on responses in different tests, there are a number of methods that have been successfully used in experimental practice.

To eliminate the so-called serial effect, which is based on habituation and uses a special order of stimulus presentation. This procedure is called “balanced alternating order,” when stimuli of different categories are presented symmetrically relative to the center of the stimulus series. The scheme of such a procedure looks like this: A B B A, Where A And IN– incentives of different categories.

To prevent influence on the subject's answer anxiety or inexperience, Introductory or preliminary experiments are carried out. Their results are not taken into account when processing data.

To prevent response variability due to accumulation of experience and skills During the experiment, the subject is offered so-called “exhaustive practice.” As a result of such practice, the subject develops stable skills before the start of the experiment itself, and in further experiments the subject’s performance does not directly depend on the factor of accumulation of experience and skills.

In cases where it is necessary to minimize the influence on the subject’s response fatigue, resort to the “rotation method”. Its essence is that each subgroup of subjects is presented with a certain combination of stimuli. The totality of such combinations completely exhausts the entire set of possible options. For example, with three types of stimuli (A, B, C), each of them is presented with the first, second and third place when presented to the subjects. Thus, the first subgroup is presented with stimuli in the order ABC, the second - AVB, the third - BAV, the fourth - BVA, the fifth - VAB, the sixth - VBA.

The presented methods for procedural equalization of internal non-constant DP are applicable for both individual and group experiments.

The attitude and motivation of the subjects, as internal unstable DPs, must be maintained at the same level throughout the entire experiment. Installation how the willingness to perceive a stimulus and respond to it in a certain way is created through the instructions that the experimenter gives to the subject. In order for the installation to be exactly what is required for the research task, the instructions must be accessible to the subjects and adequate to the objectives of the experiment. The unambiguity and ease of understanding of the instructions are achieved by its clarity and simplicity. To avoid variability in presentation, it is recommended that the instructions be read verbatim or given in in writing. Maintenance of the initial setting is controlled by the experimenter through constant observation of the subject and adjusted by reminding, if necessary, the appropriate instructions in the instructions.

Motivation The subject is seen primarily as having an interest in the experiment. If interest is absent or weak, then it is difficult to count on the completeness of the subject’s performance of the tasks provided for in the experiment and on the reliability of his answers. Too much interest, “overmotivation”, is also fraught with inadequacy of the subject’s answers. Therefore, in order to obtain an initially acceptable level of motivation, the experimenter must take the most serious approach to the formation of a contingent of subjects and the selection of factors that stimulate their motivation. Such factors may include competition, various types of remuneration, interest in one’s performance, professional interest, etc.

Psychophysiological conditions It is recommended that subjects not only be maintained at the same level, but also that this level be optimized, i.e., subjects should be in a “normal” state. You should make sure that before the experiment the subject did not have experiences that were extremely significant for him, that he had enough time to participate in the experiment, that he was not hungry, etc. During the experiment, the subject should not be overly excited or suppressed. If these conditions cannot be met, then it is better to postpone the experiment.

From the considered characteristics of the variables and methods of their control, the need for careful preparation of the experiment when planning it becomes clear. In real experimental conditions, it is impossible to achieve 100% control of all variables, but various psychological experiments differ significantly from each other in the degree of control of variables. The next section is devoted to the issue of assessing the quality of the experiment.

The following concepts are used to design and evaluate experimental procedures: ideal experiment, perfect compliance experiment, and infinite experiment.

The perfect experiment is an experiment designed in such a way that the experimenter changes only the independent variable, the dependent variable is controlled, and all other experimental conditions remain unchanged. An ideal experiment assumes the equivalence of all subjects, the invariance of their characteristics over time, and the absence of time itself. It can never be implemented in reality, since in life not only the parameters of interest to the researcher change, but also a number of other conditions.

The correspondence of a real experiment to an ideal one is expressed in such characteristics as internal validity. Internal validity shows the reliability of the results that a real experiment provides compared to an ideal one. The more the changes in the dependent variables are influenced by conditions not controlled by the researcher, the lower the internal validity of the experiment, therefore, the greater the likelihood that the facts discovered in the experiment are artifacts. High internal validity is the main sign of a well-conducted experiment.

D. Campbell identifies the following factors that threaten the internal validity of an experiment: background factor, natural development factor, testing factor, measurement error, statistical regression, non-random selection, screening. If they are not controlled, they lead to the appearance of corresponding effects.

Factor background(history) includes events that occur between the preliminary and final measurement and can cause changes in the dependent variable along with the influence of the independent variable. Factor natural development is due to the fact that changes in the level of the dependent variable may occur due to the natural development of the experiment participants (growing up, increasing fatigue, etc.). Factor testing lies in the influence of preliminary measurements on the results of subsequent ones. Factor measurement errors is associated with inaccuracy or changes in the procedure or method for measuring the experimental effect. Factor statistical regression manifests itself if subjects with extreme indicators of any assessments were selected to participate in the experiment. Factor non-random selection Accordingly, it occurs in cases where, when forming a sample, the selection of participants was carried out in a non-random manner. Factor screening manifests itself when subjects drop out unevenly from the control and experimental groups.

The experimenter must take into account and, if possible, limit the influence of factors that threaten the internal validity of the experiment.

Full Compliance Experiment is an experimental study in which all conditions and their changes correspond to reality. The approximation of a real experiment to a complete correspondence experiment is expressed in external validity. The degree of transferability of the experimental results to reality depends on the level of external validity. External validity, as defined by R. Gottsdancker, affects the reliability of the conclusions that the results of a real experiment provide in comparison with a full compliance experiment. To achieve high external validity, it is necessary that the levels of additional variables in the experiment correspond to their levels in reality. An experiment that lacks external validity is considered invalid.

Factors that threaten external validity include the following:

Reactive effect (consists in a decrease or increase in the susceptibility of subjects to experimental influence due to previous measurements);

The effect of the interaction of selection and influence (consists in the fact that the experimental influence will be significant only for the participants in this experiment);

Factor of experimental conditions (can lead to the fact that the experimental effect can only be observed in these specially organized conditions);

Factor of interference of influences (manifests itself when one group of subjects is presented with a sequence of mutually exclusive influences).

Researchers working in applied areas of psychology - clinical, pedagogical, organizational - are especially concerned about the external validity of experiments, since in the case of an invalid study, its results will not give anything when transferring them to real conditions.

Endless experiment involves an unlimited number of experiments and tests to obtain increasingly accurate results. An increase in the number of trials in an experiment with one subject leads to an increase reliability experimental results. In experiments with a group of subjects, an increase in reliability occurs with an increase in the number of subjects. However, the essence of the experiment is precisely to identify cause-and-effect relationships between phenomena on the basis of a limited number of samples or with the help of a limited group of subjects. Therefore, an endless experiment is not only impossible, but also meaningless. To achieve high reliability of an experiment, the number of samples or the number of subjects must correspond to the variability of the phenomenon being studied.

It should be noted that as the number of subjects increases, the external validity of the experiment also increases, since its results can be transferred to a wider population. To conduct experiments with a group of subjects, it is necessary to consider the issue of experimental samples.

As stated above, an experiment can be carried out either with one subject or with a group of subjects. An experiment with one subject is carried out only in some specific situations. Firstly, these are situations when the individual differences of the subjects can be neglected, i.e., the subject can be any person (if the experiment studies his characteristics in contrast to, for example, an animal). In other situations, on the contrary, the subject is a unique object (a brilliant chess player, musician, artist, etc.). Situations are also possible when the subject is required to have special competence as a result of training or extraordinary life experience (the only survivor of a plane crash, etc.). They are limited to one subject even in cases where repetition of this experiment with the participation of other subjects is impossible. Special experimental designs have been developed for single-subject experiments (see 4.7 for details).

More often, experiments are carried out with a group of subjects. In these cases, the sample of subjects should represent a model general population, to which the results of the study will then be applied. Initially, the researcher solves the problem of the size of the experimental sample. Depending on the purpose of the study and the capabilities of the experimenter, it can range from several subjects to several thousand people. The number of subjects in a separate group (experimental or control) varies from 1 to 100 people. For use statistical methods processing, it is recommended that the number of subjects in the compared groups be at least 30–35 people. In addition, it is advisable to increase the number of subjects by at least 5-10% of the required number, since some of them or their results will be “rejected” during the experiment.

To select a sample of subjects, several criteria must be taken into account.

1. Meaningful. It lies in the fact that the selection of a group of subjects must correspond to the subject and hypothesis of the study. (For example, it makes no sense to recruit two-year-old children into a group of test subjects to determine the level of voluntary memorization.) It is desirable to create ideal ideas about the object experimental research and when forming a group of subjects, deviate minimally from the characteristics of the ideal experimental group.

2. Equivalence criterion for subjects. When forming a group of subjects, one should take into account all significant characteristics of the research object, differences in the severity of which can significantly affect the dependent variable.

3. Representativeness criterion. The group of individuals participating in the experiment must represent the entire part of the population to which the results of the experiment will be applied. The size of the experimental sample is determined by the type of statistical measures and the selected accuracy (reliability) of accepting or rejecting the experimental hypothesis.

Let's consider strategies for selecting subjects from the population.

Random strategy is that each member of the population is given an equal chance of being included in the experimental sample. To do this, each individual is assigned a number, and then an experimental sample is formed using a table of random numbers. This procedure is difficult to implement, since each representative of the population of interest to the researcher must be taken into account. In addition, the random strategy gives good results when forming a large experimental sample.

Stratometric selection is used if the experimental sample must include subjects with a certain set of characteristics (gender, age, level of education, etc.). The sample is compiled in such a way that it includes equally represented subjects from each stratum (layer) with the given characteristics.

Stratometric random sampling combines the two previous strategies. Representatives of each stratum are assigned numbers and an experimental sample is randomly formed from them. This strategy is effective when selecting a small experimental sample.

Representative modeling is used when the researcher manages to create a model of an ideal object of experimental research. The characteristics of a real experimental sample should deviate minimally from the characteristics of an ideal experimental sample. If the researcher does not know all the characteristics of the ideal model of experimental research, then the strategy is used approximate modeling. The more accurate the set of criteria describing the population to which the conclusions of the experiment are supposed to be extended, the higher its external validity.

Sometimes used as an experimental sample real groups, in this case, either volunteers participate in the experiment, or all subjects are recruited forcibly. In both cases, external and internal validity are violated.

After forming an experimental sample, the experimenter draws up a research plan. Quite often, an experiment is carried out with several groups, experimental and control, which are placed in different conditions. The experimental and control groups should be equivalent at the start of the experimental intervention.

The procedure for selecting equivalent groups and subjects is called randomization. According to a number of authors, group equivalence can be achieved by pairwise selection. In this case, the experimental and control groups are composed of individuals who are equivalent in terms of secondary parameters that are significant for the experiment. The ideal option for pairwise selection is to involve twin pairs. Randomization with identification of strata consists in the selection of homogeneous subgroups in which the subjects are equalized for all characteristics, except for additional variables of interest to the researcher. Sometimes, to isolate a significant additional variable, all subjects are tested and ranked according to the level of its severity. The experimental and control groups are formed so that subjects with the same or similar values ​​of the variable are placed in different groups. The distribution of subjects into experimental and control groups can be carried out by random method. As mentioned above, with a large experimental sample, this method gives quite satisfactory results.

Experimental design is a tactics of experimental research, embodied in a specific system of experimental planning operations. The main criteria for classifying plans are:

Composition of participants (individual or group);

Number of independent variables and their levels;

Types of scales for presenting independent variables;

Method of collecting experimental data;

Place and conditions of the experiment;

Features of the organization of experimental influence and method of control.

Plans for groups of subjects and for one subject. All experimental plans can be divided according to the composition of participants into plans for groups of subjects and plans for one subject.

Experiments with group of subjects have the following advantages: the ability to generalize the results of the experiment to the population; the possibility of using intergroup comparison schemes; saving time; application of statistical analysis methods. To the disadvantages of this type experimental designs can include: the influence of individual differences between people on the results of the experiment; the problem of representativeness of the experimental sample; the problem of equivalence of groups of subjects.

Experiments with one subject- this is a special case of “plans with a small N". J. Goodwin points out the following reasons for using such plans: the need for individual validity, since in experiments with a large N A problem arises when the generalized data does not characterize any subject. An experiment with one subject is also carried out in unique cases when, for a number of reasons, it is impossible to attract many participants. In these cases, the purpose of the experiment is to analyze unique phenomena and individual characteristics.

An experiment with small N, according to D. Martin, has the following advantages: the absence of complex statistical calculations, ease of interpretation of results, the ability to study unique cases, the involvement of one or two participants, ample opportunities manipulation of independent variables. It also has some disadvantages, in particular the complexity of control procedures, difficulty in generalizing results; relative time inefficiency.

Let's consider plans for one subject.

Planning time series. The main indicator of the influence of the independent variable on the dependent variable when implementing such a plan is the change in the nature of the subject’s responses over time. The simplest strategy: scheme A– B. The subject initially performs the activity in conditions A, and then in conditions B. To control the “placebo effect”, the following scheme is used: A – B – A.(“The placebo effect” is the reactions of subjects to “empty” influences that correspond to reactions to real influences.) In this case, the subject should not know in advance which of the conditions is “empty” and which is real. However, these schemes do not take into account the interaction of influences, therefore, when planning time series, as a rule, regular alternation schemes are used (A - B – A– B), positional adjustment (A – B – B– A) or random alternation. The use of longer time series increases the possibility of detecting an effect, but leads to a number of negative consequences– fatigue of the subject, decreased control over other additional variables, etc.

Alternative Impact Plan is a development of the time series plan. Its specificity lies in the fact that the effects A And IN are randomly distributed over time and presented to the subject separately. The effects of each intervention are then compared.

Reversible plan used to study two alternative forms of behavior. Initially, a baseline level of manifestation of both forms of behavior is recorded. Then a complex effect is presented, consisting of a specific component for the first form of behavior and an additional one for the second. After a certain time, the combination of influences is modified. The effect of two complex interventions is assessed.

Criteria increasing plan often used in educational psychology. Its essence is that a change in the subject’s behavior is recorded in response to an increase in exposure. In this case, the next impact is presented only after the subject reaches the specified criterion level.

When conducting experiments with one subject, it should be taken into account that the main artifacts are practically unavoidable. In addition, in this case, like no other, the influence of the experimenter’s attitudes and the relationships that develop between him and the subject are manifested.

R. Gottsdanker suggests distinguishing qualitative and quantitative experimental designs. IN quality In plans, the independent variable is presented on a nominative scale, i.e., two or more qualitatively different conditions are used in the experiment.

IN quantitative In experimental designs, the levels of the independent variable are presented on interval, rank or proportional scales, i.e., the experiment uses the levels of expression of a particular condition.

It is possible that in a factorial experiment one variable will be presented in quantitative form and the other in qualitative form. In this case, the plan will be combined.

Within-group and between-group experimental designs. T.V. Kornilova defines two types of experimental plans according to the criterion of the number of groups and experimental conditions: intragroup and intergroup. TO intragroup refers to designs in which the influence of variations in the independent variable and the measurement of the experimental effect occur in the same group. IN intergroup plans, the influence of variants of the independent variable is carried out in different experimental groups.

The advantages of the within-group design are: a smaller number of participants, the elimination of individual differences factors, a reduction in the total time of the experiment, and the ability to prove the statistical significance of the experimental effect. Disadvantages include the non-constancy of conditions and the manifestation of the “sequence effect”.

The advantages of the intergroup design are: the absence of a “sequence effect”, the possibility of obtaining more data, reducing the time of participation in the experiment for each subject, reducing the effect of dropout of experiment participants. The main disadvantage of the between-groups design is the non-equivalence of the groups.

Single independent variable designs and factorial designs. According to the criterion of the number of experimental influences, D. Martin proposes to distinguish between plans with one independent variable, factorial plans and plans with a series of experiments. In the plans with one independent variable the experimenter manipulates one independent variable, which can have an unlimited number of manifestations. IN factorial plans (for details about them, see p. 120), the experimenter manipulates two or more independent variables, explores all possible options for the interaction of their different levels.

Plans with a series of experiments are carried out to gradually eliminate competing hypotheses. At the end of the series, the experimenter comes to verify one hypothesis.

Pre-experimental, quasi-experimental, and true experimental designs. D. Campbell proposed dividing all experimental plans for groups of subjects into the following groups: pre-experimental, quasi-experimental and true experimental plans. This division is based on the proximity of a real experiment to an ideal one. The fewer artifacts a particular design provokes and the stricter the control of additional variables, the closer the experiment is to ideal. Pre-experimental plans least of all take into account the requirements for an ideal experiment. V.N. Druzhinin points out that they can only serve as illustrations; in the practice of scientific research they should be avoided if possible. Quasi-experimental designs are an attempt to take into account the realities of life when conducting empirical research; they are specifically created to deviate from the designs of true experiments. The researcher must be aware of the sources of artifacts - external additional variables that he cannot control. A quasi-experimental design is used when a better design cannot be used.

Systematic features of pre-experimental, quasi-experimental and true experimental designs are given in the table below.

When describing experimental plans, we will use the symbolization proposed by D. Campbell: R– randomization; X– experimental influence; O– testing.

TO pre-experimental designs include: 1) single case study; 2) plan with preliminary and final testing of one group; 3) comparison of statistical groups.

At single case study One group is tested once after the experimental intervention. Schematically, this plan can be written as:

Control of external variables and independent variable is completely absent. In such an experiment there is no material for comparison. The results can only be compared with everyday ideas about reality; they do not carry scientific information.

Plan with preliminary and final testing of one group often used in sociological, socio-psychological and pedagogical research. It can be written as:

This design does not have a control group, so it cannot be argued that changes in the dependent variable (the difference between O1 and O2), recorded during testing, are caused precisely by changes in the independent variable. Between the initial and final testing, other “background” events may occur that affect the subjects along with the independent variable. This design also does not control for the natural progression effect and the testing effect.

Comparison of statistical groups it would be more accurate to call it a two-non-equivalent group design with post-exposure testing. It can be written like this:

This design allows for the testing effect to be taken into account by introducing a control group to control for a number of external variables. However, with its help it is impossible to take into account the effect of natural development, since there is no material to compare the state of the subjects at the moment with their initial state (preliminary testing was not carried out). To compare the results of the control and experimental groups, Student's t-test is used. However, it should be taken into account that differences in test results may not be due to experimental effects, but to differences in group composition.

Quasi-experimental designs are a kind of compromise between reality and the strict framework of true experiments. Exist following types quasi-experimental designs in psychological research: 1) experimental plans for non-equivalent groups; 2) designs with pre-test and post-test of different randomized groups; 3) plans of discrete time series.

Plan experiment for non-equivalent groups is aimed at establishing a cause-and-effect relationship between variables, but it does not have a procedure for equalizing groups (randomization). This plan can be represented by the following diagram:

In this case, two real groups are involved in conducting the experiment. Both groups are tested. One group is then exposed to the experimental treatment while the other is not. Both groups are then retested. The results of the first and second testing of both groups are compared; Student’s t-test and analysis of variance are used for comparison. Difference O2 and O4 indicates natural development and background exposure. To identify the effect of the independent variable, it is necessary to compare 6(O1 O2) and 6(O3 O4), i.e., the magnitude of the shifts in the indicators. The significance of the difference in the increases in indicators will indicate the influence of the independent variable on the dependent one. This design is similar to the design of a true two-group experiment with pre- and post-exposure testing (see page 118). The main source of artifacts is differences in group composition.

Plan with pre- and post-testing of different randomized groups differs from a true experimental design in that one group is pretested and an equivalent group is exposed to the posttest:

The main disadvantage of this quasi-experimental design is the inability to control for background effects—the influence of events that occur alongside the experimental treatment between the first and second testing.

Plans discrete time series are divided into several types depending on the number of groups (one or several), as well as depending on the number of experimental effects (single or series of effects).

The discrete time series design for one group of subjects consists of initially determining the initial level of the dependent variable on a group of subjects using a series of sequential measurements. Then an experimental effect is applied and a series of similar measurements are carried out. The levels of the dependent variable before and after the intervention are compared. The outline of this plan:

The main disadvantage of a discrete time series design is that it does not allow one to separate the effect of the independent variable from the effect of background events that occur during the course of the study.

A modification of this design is a time-series quasi-experiment in which exposure before measurement is alternated with no exposure before measurement. His scheme is as follows:

ХO1 – O2ХO3 – O4 ХO5

Alternation can be regular or random. This option is only suitable if the effect is reversible. When processing the data obtained in the experiment, the series is divided into two sequences and the results of measurements where there was an impact are compared with the results of measurements where there was no impact. To compare data, Student's t-test with the number of degrees of freedom is used n– 2, where n– the number of situations of the same type.

Time series plans are often implemented in practice. However, when using them, the so-called “Hawthorne effect” is often observed. It was first discovered by American scientists in 1939, when they conducted research at the Hawthorne plant in Chicago. It was assumed that changing the labor organization system would increase productivity. However, during the experiment, any changes in the organization of work led to an increase in productivity. As a result, it turned out that participation in the experiment itself increased motivation to work. The subjects realized that they were personally interested in them and began to work more productively. To control for this effect, a control group must be used.

The time series design for two non-equivalent groups, one of which receives no intervention, looks like this:

O1O2O3O4O5O6O7O8O9O10

O1O2O3O4O5O6O7O8O9O10

This plan allows you to control the “background” effect. It is commonly used by researchers when studying real groups in educational institutions, clinics, in production.

Another specific design that is often used in psychology is called an experiment. ex-post-facto. It is often used in sociology, pedagogy, as well as neuropsychology and clinical psychology. The strategy for applying this plan is as follows. The experimenter himself does not influence the subjects. The influence is some real event from their life. The experimental group consists of “test subjects” who were exposed to the intervention, and the control group consists of people who did not experience it. In this case, the groups are, if possible, equalized at the time of their state before the impact. Then the dependent variable is tested among representatives of the experimental and control groups. The data obtained as a result of testing are compared and a conclusion is drawn about the impact of the impact on the further behavior of the subjects. Thus the plan ex-post-facto simulates an experimental design for two groups with their equalization and testing after exposure. His scheme is as follows:

If group equivalence can be achieved, then the design becomes a true experimental design. It is implemented in many modern studies. For example, in the study of post-traumatic stress, when people who have suffered the effects of a natural or man-made disaster, or combatants, are tested for the presence of PTSD, their results are compared with the results of a control group, which makes it possible to identify the mechanisms of such reactions. In neuropsychology, brain injuries, lesions of certain structures, considered as “experimental exposure,” provide a unique opportunity to identify the localization of mental functions.

True Experiment Plans for one independent variable differ from others as follows:

1) using strategies to create equivalent groups (randomization);

2) the presence of at least one experimental and one control group;

3) final testing and comparison of the results of groups that received and did not receive the intervention.

Let's take a closer look at some experimental designs for one independent variable.

Two randomized group design with post-exposure testing. His diagram looks like this:

This plan is used if it is not possible or necessary to conduct preliminary testing. If the experimental and control groups are equal, this design is the best because it allows you to control most sources of artifacts. The absence of pretesting excludes both the interaction effect of the testing procedure and the experimental task, as well as the testing effect itself. The plan allows you to control the influence of group composition, spontaneous attrition, the influence of background and natural development, and the interaction of group composition with other factors.

In the example considered, one level of influence of the independent variable was used. If it has several levels, then the number of experimental groups increases to the number of levels of the independent variable.

Two randomized group design with pretest and posttest. The outline of the plan looks like this:

R O1 X O2

This design is used if there is doubt about the results of randomization. The main source of artifacts is the interaction of testing and experimental manipulation. In reality, we also have to deal with the effect of non-simultaneous testing. Therefore, it is considered best to test members of the experimental and control groups in random order. Presentation-non-presentation of the experimental intervention is also best done in random order. D. Campbell notes the need to control “intra-group events.” This experimental design controls well for the background effect and the natural progression effect.

When processing data, parametric criteria are usually used t And F(for data on an interval scale). Three t values ​​are calculated: 1) between O1 and O2; 2) between O3 and O4; 3) between O2 And O4. The hypothesis about the significance of the influence of the independent variable on the dependent variable can be accepted if two conditions are met: 1) differences between O1 And O2 significant, but between O3 And O4 insignificant and 2) differences between O2 And O4 significant. Sometimes it is more convenient to compare not absolute values, but the magnitude of the increase in indicators b(1 2) and b(3 4). These values ​​are also compared using Student's t test. If the differences are significant, the experimental hypothesis about the influence of the independent variable on the dependent variable is accepted.

Solomon's Plan is a combination of the two previous plans. To implement it, two experimental (E) and two control (C) groups are needed. His diagram looks like this:

This design can control for the pretest interaction effect and the experimental effect. The effect of experimental influence is revealed by comparing the indicators: O1 and O2; O2 and O4; O5 and O6; O5 and O3. Comparison of O6, O1 and O3 allows us to identify the influence of the factor of natural development and background influences on the dependent variable.

Now consider a design for one independent variable and several groups.

Design for three randomized groups and three levels of the independent variable used in cases where it is necessary to identify quantitative relationships between independent and dependent variables. His diagram looks like this:

In this design, each group is presented with only one level of the independent variable. If necessary, you can increase the number of experimental groups in accordance with the number of levels of the independent variable. All of the above statistical methods can be used to process the data obtained using such an experimental design.

Factorial experimental designs used to test complex hypotheses about relationships between variables. In a factorial experiment, as a rule, two types of hypotheses are tested: 1) hypotheses about the separate influence of each of the independent variables; 2) hypotheses about the interaction of variables. A factorial design involves all levels of independent variables being combined with each other. The number of experimental groups is equal to the number of combinations.

Factorial design for two independent variables and two levels (2 x 2). This is the simplest of factorial designs. His diagram looks like this.

This design reveals the effect of two independent variables on one dependent variable. The experimenter combines possible variables and levels. Sometimes four independent randomized experimental groups are used. To process the results, Fisher's analysis of variance is used.

There are more complex versions of the factorial design: 3 x 2 and 3 x 3, etc. The addition of each level of the independent variable increases the number of experimental groups.

"Latin Square". It is a simplification of a complete design for three independent variables having two or more levels. The Latin square principle is that two levels of different variables occur only once in an experimental design. This significantly reduces the number of groups and the experimental sample as a whole.

For example, for three independent variables (L, M, N) with three levels each (1, 2, 3 and N(A, B, C)) the plan using the “Latin square” method will look like this.

In this case, the level of the third independent variable (A, B, C) occurs once in each row and each column. By combining results across rows, columns, and levels, it is possible to identify the influence of each of the independent variables on the dependent variable, as well as the degree of pairwise interaction between the variables. Application of Latin letters A, B, WITH It is traditional to designate the levels of the third variable, which is why the method is called “Latin square”.

"Greco-Latin square". This design is used when the influence of four independent variables needs to be examined. It is constructed on the basis of a Latin square for three variables, with a Greek letter attached to each Latin group of the design, indicating the levels of the fourth variable. A design for a design with four independent variables, each with three levels, would look like this:

To process the data obtained in the “Greco-Latin square” design, the Fisher analysis of variance method is used.

The main problem that factorial designs can solve is determining the interaction of two or more variables. This problem cannot be solved using several conventional experiments with one independent variable. In a factorial design, instead of trying to “cleanse” the experimental situation of additional variables (with a threat to external validity), the experimenter brings it closer to reality by introducing some additional variables into the category of independent ones. At the same time, the analysis of connections between the studied characteristics allows us to identify hidden structural factors on which the parameters of the measured variable depend.

The theory of correlation research was developed by the English mathematician K. Pearson. The strategy for conducting such a study is that there is no controlled impact on the object. The design of a correlational study is simple. The researcher puts forward a hypothesis about the presence of a statistical connection between several mental properties of an individual. In this case, the assumption of causal dependence is not discussed.

Correlation is a study conducted to confirm or refute a hypothesis about a statistical relationship between several (two or more) variables. In psychology, mental properties, processes, states, etc. can act as variables.

Correlation connections.“Correlation” literally means ratio. If a change in one variable is accompanied by a change in another, then we talk about the correlation of these variables. The presence of a correlation between two variables does not indicate the presence of cause-and-effect relationships between them, but makes it possible to put forward such a hypothesis. The lack of correlation allows us to refute the hypothesis about the cause-and-effect relationship of the variables.

There are several types of correlations:

Direct correlation (the level of one variable directly corresponds to the level of another variable);

Correlation due to a third variable (the level of one variable corresponds to the level of another variable due to the fact that both of these variables are due to a third, common variable);

Random correlation (not due to any variable);

Correlation due to heterogeneity of the sample (if the sample consists of two heterogeneous groups, then a correlation may be obtained that does not exist in the general population).

Correlation connections are of the following types:

– positive correlation (an increase in the level of one variable is accompanied by an increase in the level of another variable);

– negative correlation (an increase in the level of one variable is accompanied by a decrease in the level of another);

– zero correlation (indicates that there is no connection between the variables);

– nonlinear relationship (within certain limits, an increase in the level of one variable is accompanied by an increase in the level of another, and for other parameters, vice versa. Most psychological variables have a nonlinear relationship).

Designing a correlational study. A correlational research design is a type of quasi-experimental design in which the independent variable does not influence the dependent variables. A correlation study is divided into a series of independent measurements in a group of subjects. When simple In a correlation study, the group is homogeneous. When comparative In a correlation study, we have several subgroups that differ in one or more criteria. The results of such measurements give a matrix of the form R x O. Data from a correlation study is processed by calculating correlations along the rows or columns of the matrix. Row correlation provides a comparison between subjects. Column correlation provides information about the relationship between measured variables. Temporal correlations are often detected, i.e., changes in the structure of correlations over time.

The main types of correlational research are discussed below.

Comparison of two groups. It is used to establish the similarity or difference between two natural or randomized groups in terms of the severity of a particular parameter. The mean results of the two groups are compared using Student's t test. If necessary, Fisher's t-test can also be used to compare the variances of the indicator in two groups (see 7.3).

Univariate study of one group in different conditions. The design of this study is close to experimental. But in the case of correlation research, we do not control the independent variable, but only note the change in the individual’s behavior under different conditions.

Correlation study of pairwise equivalent groups. This design is used in twin studies using intrapair correlations. The twin method is based on the following provisions: the genotypes of monozygotic twins are 100% similar, and dizygotic twins are 50% similar, the development environment of both dizygotic and monozygotic pairs is the same. Dizygotic and monozygotic twins are divided into groups: each group contains one twin from the pair. The parameter of interest to the researcher is measured in twins of both groups. Then the correlations between the parameters are calculated (ABOUT-correlation) and between twins (R-correlation). By comparing intrapair correlations of monozygotic and dizygotic twins, it is possible to identify the shares of the influence of environment and genotype on the development of a particular trait. If the correlation of monozygotic twins is reliably higher than the correlation of dizygotic twins, then we can talk about the existing genetic determination of the trait, otherwise we talk about environmental determination.

Multivariate correlation study. It is carried out to test the hypothesis about the relationship between several variables. An experimental group is selected and tested according to a specific program consisting of several tests. The research data is entered into a table of “raw” data. This table is then processed and linear correlation coefficients are calculated. Correlations are assessed for statistical differences.

Structural correlation study. The researcher identifies differences in the level of correlations between the same indicators measured in representatives of different groups.

Longitudinal correlational study. It is built according to a time series plan with testing of the group at specified intervals. Unlike a simple longitudinal study, the researcher is interested in changes not so much in the variables themselves as in the relationships between them.

Within the framework of knowledge of the surrounding reality, scientific tools offer many means of empirical, that is, experimental research. The experiment is one of the most effective, since it is based on the principles of repetition and evidence. More importantly, the experimental method allows you to study individual phenomena independently of random factors, which distinguishes it from traditional observation.

as research tools

Compared to practical knowledge through observations, an experiment is organized as a prepared study, which is given a specific task with pre-established parameters for interpreting the result. Important feature is also the participation of the researcher in the process of such cognition. In addition, the method of scientific experiment, precisely due to the possibility of organizing its repeated conduct under the same conditions, is distinguished by accuracy and more reliable information. In this way, it is possible to establish causal connections between individual elements of the experiment, identifying other properties with patterns in a particular phenomenon.

When organizing experiments, measuring instruments and technical equipment are often used to ensure the correctness of the data. A classic experiment can be presented as a laboratory research process, since it is completely controlled by the author, but there are other concepts of this method of understanding reality, which will be discussed below.

Experimental models

Typically, perfect and random experiments are distinguished. The first includes a model of organization, which for one reason or another cannot be implemented in practice, that is, under conditions of scientific observation. This technique not only helps to complete the task set regarding the study of the object, but also helps to improve the experimental method by identifying individual errors. Regarding the model random experiment, then it is built on the concept of random experience, which may correspond to a real test, but its result will be unpredictable. The random experimental method requires compliance with a wide range of requirements. For example, the prepared mathematical research model in it must adequately describe the experiment. Also, when setting up a problem, researchers precisely determine the model within which the initial mathematical data for the experiment and the results obtained will be compared.

What types of experimental method is divided into?

In practice, physical, computer, mental and critical experiments are most often used. Most common physical experiment which is the knowledge of nature. Thanks to such experiments, in particular, erroneous hypotheses of physics that were studied within the framework of theoretical research. connected to the computer process. During testing, specialists process initial data about a specific object, resulting in information about the identified properties and characteristics. The thought experiment method can affect various fields of study, including physics and philosophy. Its fundamental difference is the reproduction of the conditions of reality not in practice, but in the imagination. In turn, critical experiments are not aimed at studying specific objects or phenomena, but at confirming or refuting a certain hypothesis or theory.

Features of psychological experiments

A separate group of experiments is represented by the psychological sphere, which determines its specificity. The main subject of study in this direction is the psyche. Accordingly, the conditions for conducting research will be directly determined by the life activity of the subject. And here we can note some contradiction with basic principles the method under consideration as such. Compared to other types of research, one cannot count on complete control and creation of test conditions. One can only proceed from biased data provided by a psychological experiment. The method of psychological research also does not allow us to isolate one of the processes of mental activity, since experimental influences have an impact on the body as a whole. Similar studies can be carried out on both humans and animals. In the first case, the conditions of the test sometimes include initial instruction for the subject.

Natural and laboratory experiments

This division is also included in the concept of Natural research can, to a certain extent, be correlated with scientific observation, since in this case minimal interference in the course of the mental activity of the subject is assumed. By the way, this is where the significant advantage of the natural method comes from. The subject, due to the lack of interference in his life activity during the experiment, can remain in the dark. That is, the fact of conducting the research will not affect it in any way. On the other hand, due to the lack of control, this method of scientific experiment in psychology is considered ineffective. Opposite characteristics also determine the advantages of a laboratory experiment. In such studies, the tester can, if possible, artificially organize the learning process, focusing on specific facts that interest him. But even in this case, the need for close interaction between the researcher and the subject determines the subjectivity of the result obtained.

Advantages of the experimental method

The advantages of this approach in research primarily include the controllability of conditions. The researcher organizes the process in accordance with his capabilities and resources, which greatly facilitates the work. Also, the advantages of the experimental method are determined by the possibility of its repetition, which makes it possible to clarify the data without adjustments for changes in test conditions. On the contrary, flexible process correction capabilities allow you to track the dynamics of changes in certain qualities and properties of an object.

Of course, the main advantage of this technique is the accuracy of the data. This parameter will depend on how correctly the process conditions were prepared, but within the given framework and parameters you can count on high degree reliability. The observation method especially reveals the advantages of such tests in terms of accuracy. Against this background, the experiment is more controllable, which makes it possible to exclude third-party factors of interference in the research process.

Disadvantages of the method

Mostly weak spots experimental methods relate to organizational errors. Here it is also worth making a comparison with observation, which will be extremely correct in terms of conditions. Another question is that, unlike observation, experiment is a fixed process in all respects. In addition, the disadvantages of the experimental method are associated with the impossibility of artificially repeating phenomena and processes. Not to mention that certain areas of technology application require significant material investments in the organization.

Examples of using experiments

One of the very first experiments was carried out by Eratosthenes of Cyrene, who studied physical phenomena. The essence of his research was to calculate the radius of the Earth in a natural way. He used the degree of deviation of the Sun from the Earth during the summer solstice, which allowed, by correlating the parameters with the distance to the point at which there was no deviation at all, to conclude that the radius was 6300 km. The difference with the actual figure is only 5%, which indicates the high accuracy with which the method was performed. Experiments, examples of which are reflected in psychology, cannot claim mathematical accuracy, but they also deserve attention.

So, in 1951, a group of researchers conducted a group experiment, the purpose of which was to study conformity. Participants were asked to answer simple questions regarding the number and location of rods that were supposedly testing vision. At the same time, all but one participant were given the command to give false results - the method was based on identifying this difference. The experiment, examples of which were reproduced many times, ultimately gave disappointing results. Participants who were left alone with a obviously incorrect but dominant opinion, in most cases also agreed with it.

Conclusion

Experimental research undoubtedly expands and deepens a person’s understanding of the world around him. However, this method cannot be used in all areas. Observations, experiments and experiments together provide much more information, complementing each other. There are areas in which research is possible using different methods separately, but in the interests of rationalization, research centers are increasingly using combined approaches. At the same time, it must be recognized that experimental research still plays a fundamental role in the context of developing theories and hypotheses.