Connection of needs and motives in human activity. needs and motives. Main theses. Key features of motives

V.V. Nikandrov points out that the achievement main goal experiment - the maximum possible unambiguity in understanding the connections between the phenomena of internal mental life and their external manifestations - is achieved due 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 fixation of the conditions and the process of their occurrence;

4) isolation of some and emphasis on other factors that determine the studied phenomena, which makes it possible to identify the patterns of their existence;

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

6) variation of conditions for quantitative assessments of the revealed regularities.

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

Experiments are of several types. Depending on the way of organizing distinguish laboratory, natural and field experiments. Laboratory The experiment is carried out under special conditions. The researcher deliberately 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 in real conditions. Its advantage lies in the fact that the study of the object is carried out in the context Everyday life, so the data obtained are easily transferred to reality. The subjects are not always informed about their participation in the experiment, so they do not give motivational distortions. Disadvantages - the inability to control all conditions, unforeseen interference and distortion.

Field The experiment is carried out according to the natural scheme. In this case, it is possible to use portable equipment, which makes it possible to more accurately record the received data. The subjects are informed about 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 held on initial stage research, allows you to formulate a hypothesis, identify independent, dependent and secondary variables (see 4.4) and determine how to control them.

Aerobatic An experiment is a trial experiment, the first in a series. It is carried out on a small sample, without strict control of variables. The pilot experiment makes it possible to eliminate gross errors in the formulation of the hypothesis, to specify the goal, and to clarify the methodology for conducting the experiment.

Confirming the experiment is aimed at establishing the form functional connection and refinement of quantitative relationships between variables. It is carried out at the final stage of the study.

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

By influence opportunities experimenter, the independent variable is allocated to the provoked experiment and the experiment to which they refer. provoked An experiment is an experiment 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 the intervention of the experimenter. This type of psychological experiment is resorted to when independent variables affect the subject, significantly extended in time (for example, the education system, etc.). If the impact on the subject can cause a serious negative physiological or psychological disturbance, then such an experiment cannot be carried out. However, there are cases when a negative impact (for example, a brain injury) occurs in reality. Subsequently, such cases can be generalized and studied.

4.3. Structure of a psychological experiment

The main components of any experiment are:

1) the subject (the subject or group under study);

2) experimenter (researcher);

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

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

5) conditions of the experiment (additional to the stimulation of the impact, which can affect the reactions of the subject).

The response of the subject is an external reaction, by which one can judge the processes taking place in his inner, subjective space. These processes themselves are the result of the stimulation and conditions of experience acting on him.

If the response (reaction) of the subject is denoted by the symbol R, and the effects of the experimental situation on him (as a combination of stimulation effects and experimental conditions) - by the symbol S, then their ratio 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 personality of a person. (P). In reality, a person's reaction to a situation is always mediated by the psyche, the personality. Thus, the relationship between the main elements of the experiment can be fixed by the following formula: R = f(R, S).

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

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

Structural relationships are revealed through the system of answers (R1, R2, Rn) to various situations (Sv S2, Sn). Relationships between individual responses are structured into a system that reflects the personality structure (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 revealed through reaction analysis (R1, R2, Rn) of different subjects (P1, P2, pn) for the same situation (S). The scheme of these relations is as follows (Fig. 4).

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

To clarify the ratio of all factors included in the experiment, the concept of "variable" is introduced. There are three types of variables: independent, dependent and additional.

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

The conditions under which the subject's activity is carried out, the characteristics of the tasks the performance of which is required from the subject, the characteristics of the subject himself (age, gender, other differences of the subjects, etc.) emotional states and other properties of the subject or people interacting with him). Therefore, it is customary to single out the following types NP: situational, instructive and personal.

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

Instructional NPs are directly related to the experimental task, its qualitative and quantitative characteristics, as well as the methods of its implementation. The instructive NP can be manipulated more or less freely by the experimenter. It 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 scale of assessment, etc. Great opportunities lie in the way in which the subjects are instructed, informing them about the purpose of the experimental task. The experimenter can change the means that are offered to the subject for completing the task, put obstacles in front of him, use a system of rewards and punishments in the course of completing the task, etc.

Personal NP are controlled features of the subject. Usually, such features are the states of the participant in the experiment, 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 signs which the experimenter cannot control. In some cases, these uncontrolled features 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 different kinds independent variables. Depending on the presentation scale qualitative and quantitative NPs can be distinguished. quality NPs correspond to different gradations of naming scales. For example, the subject's emotional states can be represented by states of joy, anger, fear, surprise, etc. Ways of performing tasks may include the presence or absence of prompts to the subject. quantitative NP correspond to rank, proportional or interval scales. For example, the time allotted to complete the 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 levels of manifestation independent variables distinguish two-level and multi-level NP. Two-level NPs have two levels of manifestation, multilevel- three or more levels. Depending on the number of levels of manifestation of NP, experimental plans of various complexity are built.

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 other psychological characteristics, which can be registered in the course of psychological experiments.

Depending on the the way in which changes can be registered, allocate ZP:

S observed directly;

S requiring physical equipment for measurement;

S requiring a psychological dimension.

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

Depending on the the number of parameters included in the dependent variable, one-dimensional, multidimensional and fundamental RFPs are distinguished. one-dimensional The RFP is represented by the only parameter whose changes are studied in the experiment. An example of a one-dimensional RFP is the speed of a sensorimotor reaction. Multidimensional ZP is represented by a set of parameters. For example, mindfulness can be measured by the amount 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 variable of a complex nature, the parameters of which have some famous relationships between themselves. In this case, some parameters act as arguments, and the dependent variable itself acts as a function. For example, the fundamental measurement 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 ZP is its sensitivity to a change in the level of the independent variable. If the dependent variable does not change when the independent variable changes, 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 the insensitivity of the RFP: the “ceiling effect” and the “floor effect”. The "ceiling effect" is observed, for example, in the case when the task presented is so simple that it is performed by all subjects, regardless of age. The “gender effect”, on the other hand, occurs when the task is so difficult that none of the subjects can cope with it.

There are two main ways of fixing changes in BP in a psychological experiment: immediate and delayed. Direct the method is used, for example, in experiments on short-term memorization. The experimenter, immediately after repeating a series of stimuli, fixes their number reproduced by the subject. The delayed method is used when impact and the effect passes 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 affects his response. The set of DP consists, as a rule, of two groups: external conditions of experience and internal factors. Accordingly, they are usually called external and internal DP. TO external DP refer to the physical environment of the experience (illumination, temperature regime, sound background, spatial characteristics premises), parameters of apparatus and equipment (design of measuring instruments, operating noise, etc.), time parameters of the experiment (start time, duration, etc.), personality of the experimenter. TO internal DP include the mood and motivation of the subjects, their attitude towards the experimenter and experiments, their psychological attitudes, inclinations, knowledge, skills, skills and experience in this type of activity, the level of fatigue, well-being, etc.

Ideally, the researcher seeks 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 external influences; 2) constancy of conditions; 3) balancing; 4) counterbalancing.

Elimination of external influences represents the most radical method of control. It consists in the complete exclusion of external environment any external DP. Conditions are created in the laboratory that isolate the test subject from sounds, light, vibration effects, etc. The most striking example is the sensory deprivation experiment conducted on volunteers in a special chamber that completely excludes any stimuli from the external environment. It should be noted that it is practically 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 way to control is to create constant conditions. The essence of this method is to make the effects of DP constant and the same for all subjects throughout the experiment. In particular, the researcher strives to make constant the spatio-temporal conditions of the experiment, the technique of conducting it, the equipment, the presentation of instructions, etc. With careful application of this method of control, large errors can be avoided, however, the problem of transferring the results of the experiment to conditions that are very different from the experimental ones, 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 in using the control group. The study of the control and experimental groups is carried out under the same conditions, with the only difference 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 DPs, while in the experimental group it is due to the combined action of external additional and independent variables.

If the external DP is known, then balancing consists in 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 the independent variable (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.

In more complex experiments, balancing of several variables can be applied simultaneously.

counterbalancing as a way to control external DP is practiced most often when the experiment includes several series. The subject finds himself in different conditions sequentially, however, previous conditions may 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 a different order. For example, in the first series of the experiment, the first group is presented with the solution of intellectual problems from simpler to more complex, and the second - from more complex to simpler. In the second series, on the contrary, the first group is presented with the solution of intellectual problems from more complex to simpler, and the second - from simpler to more complex. Counterbalancing is used in cases where it is possible to conduct several series of experiments, however, it should be borne in mind that big number attempts causes fatigue of the subjects.

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

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

To equalize the effect of these variables on responses in different samples, 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, a special order of presentation of stimuli is used. This procedure is called "balanced alternating order", when the stimuli different categories are presented symmetrically about the center of the stimulus row. 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 response of the subject anxiety or inexperience, conducting trial or preliminary experiments. Their totals are not taken into account when processing data.

To prevent variability in responses due to accumulation of experience and skills during the experiment, the subject is offered the so-called "exhaustive practice". As a result of this practice, the subject develops stable skills before the start of the actual experiment, and in further experiments, the subject's indicators do not directly depend on the factor of accumulating experience and skills.

In those cases where it is necessary to minimize the influence on the response of the subject fatigue, resort to the "rotation method". Its essence lies in the fact 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 in the presentation to the subjects. Thus, stimuli are presented to the first subgroup in the order ABC, the second - AVB, the third - BAV, the fourth - BVA, the fifth - VAB, the sixth - VBA.

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

The set and motivation of the subjects as internal non-permanent DP must be maintained at the same level during the entire experiment. Installation how the readiness to perceive a stimulus and respond to it in a certain way is created through the instruction that the experimenter gives to the subject. In order for the installation to be exactly what is required for the task of the study, the instruction must be available to the subjects and adequate to the tasks of the experiment. The unambiguity and ease of understanding of the instruction are achieved by its clarity and simplicity. To avoid variability in presentation, it is recommended that instructions be read verbatim or given in writing. The maintenance of the initial set is controlled by the experimenter by constant observation of the subject and is corrected by recalling, if necessary, the appropriate instructions of the instruction.

Motivation The test subject is seen mainly as an interest in the experiment. If interest is absent or weak, then it is difficult to count on the completeness of the subjects' fulfillment of the tasks provided for in the experiment and on the reliability of his answers. Too high interest, "remotivation", is also fraught with inadequacy of the subject's answers. Therefore, in order to obtain an initially acceptable level of motivation, the experimenter must seriously approach the formation of the contingent of subjects and the selection of factors stimulating their motivation. Competitiveness, various types of remuneration, interest in one's performance, professional interest, etc. can serve as such factors.

Psychophysiological states it is recommended not only to keep the subjects at the same level, but also to optimize this level, i.e., the subjects must be in a “normal” state. You should make sure that before the experiment, the subject did not have super-significant experiences for him, he has enough time to participate in the experiment, he is not hungry, etc. During the experiment, the subject should not be unnecessarily excited or suppressed. If these conditions cannot be met, then it is better to postpone the experiment.

From the considered characteristics of variables and ways to control them, the need for careful preparation experiment during planning. In real conditions of experimentation, it is impossible to achieve 100% control of all variables, however, various psychological experiments differ significantly from each other in the degree of control of variables. The following section is devoted to the issue of assessing the quality of an experiment.

For the design and evaluation of experimental procedures, the following concepts are used: an ideal experiment, an experiment of full compliance and an infinite experiment.

The Perfect Experiment is an experiment organized in such a way that the experimenter changes only the independent variable, the dependent variable is controlled, and all other conditions of the experiment remain unchanged. An ideal experiment assumes the equivalence of all subjects, the invariance of their characteristics over time, 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 a characteristic as internal validity. Internal validity indicates the reliability of the results that a real experiment provides compared to an ideal one. The more dependent variables are affected by conditions not controlled by the researcher, the lower the internal validity of the experiment, therefore, the greater the likelihood that the facts found in the experiment are artifacts. High internal validity main feature well done experiment.

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

Factor background(stories) includes events that occur between the pre-measurement and the final measurement and may cause changes in the dependent variable along with the influence of the independent variable. Factor natural development due to the fact that changes in the level of the dependent variable may occur in connection with the natural development of the participants in the experiment (growing up, increasing fatigue, etc.). Factor testing lies in the influence of preliminary measurements on the results of subsequent ones. Factor measurement errors associated with inaccuracy or changes in the procedure or method of measuring the experimental effect. Factor statistical regression manifests itself in the event that subjects with extreme indicators of any assessments were selected for participation in the experiment. Factor non-random selection accordingly, it occurs in those cases when, when forming the sample, the selection of participants was carried out in a non-random manner. Factor sifting manifests itself in the event that the 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 match experiment is an experimental study in which all conditions and their changes correspond to reality. The approximation of a real experiment to a full compliance experiment is expressed in terms of external validity. The degree of transferability of the results of the experiment to reality depends on the level of external validity. External validity, according to the definition of R. Gottsdanker, affects the reliability of the conclusions, which are given by the results of a real experiment compared to 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 (may lead to the fact that the experimental effect can be observed only in these specially organized conditions);

Interference factor of influences (appears when one group of subjects is presented with a sequence of mutually exclusive influences).

Care for the external validity of experiments is especially shown by researchers working in the applied fields of psychology - clinical, pedagogical, organizational, since in the case of an invalid study, its results will not give anything when transferred to real conditions.

Endless Experiment involves an unlimited number of experiments, samples to get more and more accurate results. An increase in the number of samples in an experiment with one subject leads to an increase reliability experiment 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 lies precisely in the fact that, on the basis of a limited number of samples or with the help of a limited group of subjects, to identify causal relationships between phenomena. Therefore, an endless experiment is not only impossible, but also meaningless. To achieve high reliability of the experiment, the number of samples or the number of subjects must correspond to the variability of the phenomenon under study.

It should be noted that with an increase in the number of subjects, 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 mentioned above, the 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. First, these are situations where the individual differences of the subjects can be neglected, i.e., any person can be the subject (if the experiment studies its features, unlike, for example, an animal). In other situations, on the contrary, the subject is a unique object (a brilliant chess player, musician, artist, etc.). There are also situations when the subject is required to have special competence as a result of training or extraordinary life experience (the only survivor in a plane crash, etc.). One test subject is also limited in cases where the repetition of this experiment with the participation of other subjects is impossible. For experiments with one subject, special experimental plans have been developed (for details, see 4.7).

More often experiments are carried out with a group of subjects. In these cases, the sample of subjects should be a model general population, to which the results of the study will then be extended. Initially, the researcher solves the problem of the size of the experimental sample. Depending on the purpose of the study and the possibility 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. To apply statistical processing methods, 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, since some of them or their results will be “rejected” during the experiment.

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

1. Informative. It lies in the fact that the selection of a group of subjects should 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 arbitrary memorization.) It is desirable to create ideal ideas about the object of experimental research and, when forming a group of test subjects, deviate minimally from the characteristics of the ideal experimental group.

2. Criterion of equivalence of subjects. When forming a group of subjects, it is necessary to take into account all significant characteristics object of study, differences in the severity of which can significantly affect the dependent variable.

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

Consider strategies for selecting subjects from a population.

Random Strategy is that each member of the general 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 in the event that the experimental sample must necessarily include subjects with a certain set of characteristics (gender, age, level of education, etc.). The sample is compiled in such a way that the subjects of each stratum (layer) with the given characteristics are equally represented in it.

Stratometric random selection 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 in the case 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 applied approximate modeling. The more accurate the set of criteria that describe the population to which the conclusions of the experiment are supposed to be extended, the higher its external validity.

Sometimes, as an experimental sample, real groups, at the same time, either volunteers participate in the experiment, or all subjects are involved involuntarily. In both cases, external and internal validity are violated.

After the formation of the 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 exposure.

The procedure for selecting equivalent groups and subjects is called randomization. According to a number of authors, the equivalence of groups can be achieved by pairwise selection. In this case, the experimental and control groups are composed of individuals equivalent in terms of side parameters significant for the experiment. Perfect option for pairwise selection - attraction of twin pairs. Randomization with stratification consists in the selection of homogeneous subgroups in which the subjects are equalized in all characteristics, except for the additional variables of interest to the researcher. Sometimes, in order to highlight 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 fall into different groups. The distribution of subjects into experimental and control groups can be carried out and random method. As mentioned above, with a large number of experimental samples, this method gives quite satisfactory results.

Experimental plan is a tactic of experimental research embodied in a specific system of experiment planning operations. The main criteria for classifying plans are:

Composition of participants (individual or group);

Number of independent variables and their levels;

Types of representation scales for independent variables;

Method of collecting experimental data;

Place and conditions of the experiment;

Features of the organization of the experimental impact and the 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 possibility of generalizing the results of the experiment to the population; the possibility of using schemes of intergroup comparisons; saving time; application of methods statistical analysis. The disadvantages of this type of experimental plans include: individual differences between people on the results of the experiment; the problem of the representativeness of the experimental sample; the problem of equivalence of groups of subjects.

Experiments with one test subject- This special case"plans with little N. J. Goodwin points to the following reasons for using such plans: the need for individual validity, since in experiments with large N a problem arises when the generalized data does not characterize any of the subjects. 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 a small N, according to D. Martin, has the following advantages: the absence of complex statistical calculations, the ease of interpreting the results, the possibility of studying unique cases, involving one or two participants, and ample opportunities for manipulating independent variables. It also has some disadvantages, in particular, the complexity of control procedures, the difficulty in generalizing the results; relative uneconomical time.

Consider plans for one subject.

Time series planning. The main indicator of the influence of the independent variable on the dependent one in the implementation of such a plan is the change in the nature of the responses of the subject over time. The simplest strategy: the scheme A– B. The subject initially performs activities under conditions A, and then under conditions B. To control the “placebo effect”, the following scheme is used: A - B - A.(“The placebo effect” is the reactions of the subjects to “empty” stimuli, corresponding to reactions to real stimuli.) In this case, the subject does not need to know in advance which of the conditions is “empty” and which is real. However, these schemes do not take into account the interaction of impacts, therefore, when planning time series, as a rule, regular alternation schemes are used (A - B - A– B), positional adjustment (А – B - B- A) or random alternation. The use of longer "long" time series increases the possibility of detecting the effect, but leads to a number of negative consequences- fatigue of the subject, reduced 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 impact A And IN randomly distributed over time and presented to the subject separately. Then the effects of each of the exposures are compared.

Reverse plan used to study two alternative forms of behavior. Initially, the basic 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 impacts is evaluated.

Criteria Increasing Plan often used in the psychology of learning. Its essence lies in the fact that a change in the behavior of the subject is recorded in response to an increase in exposure. In this case, the next impact is presented only after the subject reaches the given level of the criterion.

When conducting experiments with one subject, it should be taken into account that the main artifacts are practically irremovable. In addition, in this case, as in no other, the influence of the experimenter's attitudes and the relationship that develops between him and the subject is manifested.

R. Gottsdanker proposes to distinguish 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 experimental plans, the levels of the independent variable are presented in interval, rank, or proportional scales, i.e., the levels of severity of a particular condition are used in the experiment.

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

Intragroup and intergroup experimental plans. T.V. Kornilova defines two types of experimental plans according to the criterion of the number of groups and the conditions of the experiment: intragroup and intergroup. TO intragroup include designs in which the influence of variants of 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 intragroup plan are: a smaller number of participants, the elimination of factors of individual differences, a decrease in the total time of the experiment, the possibility of proving the statistical significance of the experimental effect. Disadvantages include non-constancy of conditions and manifestation of the “sequence effect”.

The advantages of the intergroup plan are: the absence of a "consistency effect", the possibility of obtaining more data, reducing the time of participation in the experiment for each subject, reducing the effect of dropping out participants in the experiment. The main disadvantage of the intergroup plan is the non-equivalence of groups.

Designs with one independent variable 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 on them, see p. 120), the experimenter manipulates two or more independent variables, explores all possible options for the interaction of their different levels.

Plans from a series of experiments conducted to gradually exclude competing hypotheses. At the end of the series, the experimenter comes to the verification of one hypothesis.

Pre-experimental, quasi-experimental and true experimental designs. D. Campbell proposed to divide all experimental plans for groups of subjects into the following groups: pre-experimental, quasi-experimental and plans for true experiments. This division is based on the closeness of a real experiment to an ideal one. The fewer artifacts a particular plan provokes and the stricter the control of additional variables, the closer the experiment is to the 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 an illustration, in the practice of scientific research they should be avoided if possible. Quasi-experimental plans are an attempt to take into account the realities of life when conducting empirical research, they are specially created with a deviation from the schemes of true experiments. The researcher must be aware of the sources of artifacts - external additional variables that he cannot control. A quasi-experimental plan is used when a better plan cannot be applied.

Systematized signs of pre-experimental, quasi-experimental plans and plans of true experiments are given in the table below.

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

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

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

The control of external variables and the independent variable is completely absent. In such an experiment, there is no material for comparison. The results can only be compared with ordinary 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:

There is no control group in this plan, so it cannot be argued that changes in the dependent variable (difference between O1 and O2) recorded during testing are caused precisely by the change 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 plan also does not allow control over the effect of natural development and the effect of testing.

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

This plan takes into account the effect of testing by introducing a control group to control 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 for comparing the condition of the subjects on this 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 borne in mind that differences in test results may not be due to experimental exposure, but to differences in the composition of the groups.

Quasi-experimental plans are a kind of compromise between reality and strict framework true experiments. There are the following types of quasi-experimental plans in psychological research: 1) plans for experiments for non-equivalent groups; 2) plans with preliminary and final testing of various randomized groups; 3) plans for discrete time series.

Plan experiment for nonequivalent groups is aimed at establishing a causal relationship between variables, however, it lacks a procedure for equalizing groups (randomization). This plan can be represented by the following diagram:

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

Plan with pre and post testing of various randomized groups differs from the design of a true experiment in that one group passes the preliminary test, and the final test is the equivalent group that was exposed to:

The main disadvantage of this quasi-experimental design is the inability to control the "background" effect - the influence of events that occur along with the experimental exposure in the period between the first and second testing.

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

The plan of discrete time series for one group of subjects is that the initial level of the dependent variable on the group of subjects is initially determined using a series of consecutive measurements. Then an experimental effect is applied and a series of similar measurements is carried out. Compare the levels of the dependent variable before and after exposure. Schematic of this plan:

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

A modification of this design is a time-series quasi-experiment in which pre-measurement exposure alternates with no pre-measurement exposure. His schema is:

XO1 - O2XO3 - O4 XO5

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 are divided into two sequences and the results of measurements, where there was an impact, are compared with the results of measurements, where it was absent. To compare data, Student's t-test is used with the number of degrees of freedom n– 2, where n is the number of situations of the same type.

Time series plans are often implemented in practice. However, when they are used, the so-called "Hawthorne effect" is often observed. It was first discovered by American scientists in 1939, when they were conducting research at the Hawthorne plant in Chicago. It was assumed that the change in the system of labor organization would increase its productivity. However, during the experiment, any changes in the organization of labor led to an increase in its productivity. As a result, it turned out that participation in the experiment itself increased the 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 scheme of the time series plan for two non-equivalent groups, of which one is not affected, looks like this:

O1O2O3O4O5O6O7O8O9O10

O1O2O3O4O5O6O7O8O9O10

Such a plan allows you to control the "background" effect. It is usually used by researchers when studying real groups in educational institutions, clinics, and in production.

Another specific plan, which is often used in psychology, is called an experiment. ex post facto. It is often used in sociology, pedagogy, as well as in neuropsychology and clinical psychology. The strategy for implementing this plan is as follows. The experimenter himself does not influence the subjects. Some influence is real event from their life. The experimental group consists of "subjects" who have been exposed, while the control group consists of people who have not experienced it. In this case, the groups, if possible, are equalized at the moment of their state before the impact. Then the dependent variable is tested in the representatives of the experimental and control groups. The data obtained as a result of testing are compared and a conclusion is made about the impact of exposure on the further behavior of the subjects. Thus the plan ex post facto simulates the design of the experiment for two groups with their equalization and testing after exposure. His schema is:

If it is possible to achieve group equivalence, then this design becomes the design of a true experiment. It is implemented in many modern research. 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 post-traumatic stress syndrome, their results are compared with the results of the control group, which makes it possible to identify the mechanisms for the occurrence of such reactions. In the neuropsychology of brain injury, lesions of certain structures, considered as "experimental exposure", provide a unique opportunity to identify the localization of mental functions.

Plans for true experiments for one independent variable differ from others as follows:

1) using strategies for creating 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 exposure.

Let us consider in more detail some experimental designs for one independent variable.

Plan for two randomized groups with post-exposure testing. His schema 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 plan is the best because it allows you to control most sources of artifacts. The absence of preliminary testing excludes both the effect of the interaction of the testing procedure and the experimental task, and the effect of testing itself. The plan allows you to control the influence of the composition of groups, spontaneous dropout, the influence of the background and natural development, the interaction of the composition of the group with other factors.

In the considered example, 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.

Plan for two randomized groups with pre and post testing. The outline of the plan looks like this:

R O1 X O2

This plan is used when there is doubt about the results of randomization. The main source of artifacts is the interaction between testing and experimental exposure. In reality, one also has to deal with the effect of testing non-simultaneity. Therefore, it is considered best to conduct testing of members of the experimental and control groups in random order. Presentation-non-presentation of the experimental impact is also best done in a random order. D. Campbell notes the need to control "intragroup events". This experimental design controls well the background effect and the natural development effect.

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

Solomon's plan is a combination of the two previous plans. For its implementation, two experimental (E) and two control (C) groups are required. His schema looks like this:

With this plan, the interaction effect of pre-testing and the experimental exposure effect can be controlled. The effect of experimental exposure is revealed by comparing the indicators: O1 and O2; O2 and O4; O5 and O6; O5 and O3. Comparison of O6, O1 and O3 reveals the effect 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 the independent and dependent variables. His schema looks like this:

When implementing this plan, 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 with such an experimental design.

Factorial Experimental Designs are 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. The factorial design is to ensure that all levels of independent variables are 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 plan 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. Fisher's analysis of variance is used to process the results.

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 the full plan for three independent variables with two or more levels. The principle of the Latin square is that two levels of different variables occur only once in the experimental plan. 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 according to the "Latin square" method will look like this.

In this case, the level of the third independent variable (A, B, C) occurs in each line and in each column once. By combining the 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 of the variables. Application Latin letters A, B WITH It is traditional to designate the levels of the third variable, which is why the method was called the “Latin square”.

"Greco-Latin square". This plan is used when it is necessary to investigate the influence of four independent variables. It is built on the basis of a Latin square for three variables, with a Greek letter attached to each Latin group of the plan, denoting the levels of the fourth variable. The schema for a plan with four independent variables, each with three levels, would look like this:

To process the data obtained in terms of the "Greek-Latin square", the method of variance analysis according to Fisher is used.

The main problem that factorial designs can solve is determining the interaction of two or more variables. This problem cannot be solved by applying several conventional experiments with one independent variable. In the factorial plan, instead of trying to “clear” 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 the relationships between the studied characteristics allows us to reveal 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 plan of the correlation study is simple. The researcher puts forward a hypothesis about the presence of a statistical relationship between several mental properties of an individual. However, the assumption of causal dependence is not discussed.

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

Correlations.“Correlation” literally means ratio. If a change in one variable is accompanied by a change in another, then we speak of the correlation of these variables. The presence of a correlation between two variables is not evidence of the presence of causal relationships between them, but it makes it possible to put forward such a hypothesis. The absence of correlation allows one to refute the hypothesis of a causal relationship of 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 the heterogeneity of the sample (if the sample consists of two heterogeneous groups, then a correlation can be obtained that does not exist in the general population).

Correlations 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 the absence of a connection between variables);

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

Planning a correlation study. The design of the correlation study is a kind of quasi-experimental design in the absence of the influence of the independent variable on the dependent ones. A correlation study is broken down into a series of independent measurements in a group of subjects. When simple correlation study group is homogeneous. When comparative 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. Correlation study data is processed by calculating correlations by rows or columns of the matrix. Row correlation yields a comparison of subjects. Column correlation provides information about the association of measured variables. Temporal correlations are often detected, i.e., changes in the structure of correlations over time.

The main types of correlation research are considered 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 one or another parameter. The mean results of the two groups are compared using Student's t-test. If necessary, Fisher's t-test (see 7.3) can also be used to compare the variances of an indicator between two groups.

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

Correlation study of pairwise equivalent groups. This plan is used in the study of twins by the method of intra-pair 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 for both dizygotic and monozygotic pairs is the same. Dizygotic and monozygotic twins are divided into groups: each contains one twin from a pair. In twins of both groups, the parameter of interest to the researcher is measured. Then the correlations between the parameters are calculated (ABOUT-correlation) and between twins (R-correlation). Comparing the intra-pair correlations of monozygotic and dizygotic twins, it is possible to identify the shares of the influence of the environment and the 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 of several variables. An experimental group is selected, which is tested according to a specific program consisting of several tests. Research data are entered in the table of "raw" data. Then this table is processed, the coefficients of linear correlations are calculated. Correlations are evaluated for statistical differences.

Structural correlation study. The researcher reveals the difference in the level of correlation dependencies between the same indicators measured in representatives of different groups.

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

NATURAL EXPERIMENT, as a method of psychological research, occupies a middle position between the methods of objective observation and laboratory experiment. He strives to combine the naturalness of the conditions of observation with the accuracy and scientific nature of the experiment. A natural experiment allows, while preserving the naturalness of human behavior, to study it experimentally, that is, to call at will various acts this behavior, varying their conditions or repeating the experience in the same situation several times.

For the first time, the method of natural experiment was proposed by the professor of the St. Petersburg Psychoneurological Institute A.F. Lazursky in relation to children. Lazursky's idea was that each type of school activity for a child is based on a certain form of behavior functionally associated with it (psycho, a phenomenon, as Lazursky said). Therefore, on the basis of an analysis of the student's pedagogical activities, it is possible to conclude about his behavior in psychological terms; e.g. good or bad memorization and reproduction of a poem indicates a good or bad memory of the child; the drawing gives grounds for the conclusion about his work, etc. Lazursky, together with his collaborators, gave an appropriate functional analysis of the entire day of school classes, selected the most typical tasks from them, brought them into a system, and thus organized the experiment, calling it natural on the grounds that it takes place in the natural conditions of the school life of children. However, Lazursky did not have the opportunity to fully formulate the methodological side of the natural experiment. In equal measure, the materials of the experiment were developed by him in relation to the pre-revolutionary school. Therefore, in his edition, this method is now significantly outdated.

Lazursky's work was continued by V. A. Artemov, who gave a completely developed method of natural experiment in relation to the modern labor school. According to Artemov, a natural experiment is carried out on the trail. types school work: 1) food processes (for closed institutions); 2) games and gymnastic exercises; 3) meetings, rallies and all kinds of holidays; 4) processes of pictorial and graphic drawing; 5) various types of manual labor; 6) the processes of memorization and reproduction; 7) solving mathematical problems; 8) writing essays; 9) oral storytelling; 10) analysis of the read or listened to story; 11) natural science; 12) social science.

In these classes, the following forms of behavior are explored: 1) instincts, 2) emotional reactions, 3) motor skills, 4) set and inhibition, 5) the formation of conditional connections of reactions and their reproduction, 6) thinking, 7) creative processing of experience. A total of forty various forms behavior.

The material for the experiment was compiled on the basis of the GUS programs. It has for every school group two options - urban and rural, each of which, in turn, is divided into two editions (one for the beginning of the school year, the other for the end). Like any experiment, a natural experiment has three stages of its implementation: preparation for the experiment, its conduct and processing of the results.

Preparation for the experiment consists in preparing the appropriate premises and materials for the experiment. Conducting an experiment consists in offering children experimental tasks and recording their behavior. The latter is carried out using a special protocol, which later serves as the basis for processing the results of the experiment. Registration and processing are carried out with the help of five special stages of development of various forms of behavior. The processing of the results consists in assigning the forms of behavior, on the basis of the results of experience and observation, to the corresponding stage of development. The final results of the experiment are recorded on a special chart, the so-called "asterisk" (see figure).

In the above edition, the natural experiment (hereinafter - EE) has typological tasks. The type of student's behavior is determined by finding the following values: 1) a structural combination of individual forms of behavior; 2) the "total area" of giftedness as a ratio to the conditional average development of a given group; 3) D-values ​​as the difference between the maximum and minimum development of individual forms of behavior; 4) dynamics of development per unit of time (coefficient of development). It should be borne in mind that EE is applicable to the study of any area of ​​individual and collective behavior. From this point of view, EE. is of particular interest to the doctor, since it is possible, according to the type described, to offer a special edition of the EE for various cases of a wedge, studying the behavior of patients in respect of which ordinary observation is not enough, and a laboratory experiment is impossible. Behind Lately there is a whole series of new methodological attempts in German holistic psychology, the so-called Gestaltpsychologie, some of which to a certain extent correspond to natural experiment.
Literature: Artemov V., Natural experiment, M., 1927; he, Modern psychology, Psychology, vol. I, c. 1 - 2, 1928; Basov M., New data for the justification of a natural - experimental study of personality, Questions of studying and educating a personality, 1922, c. 4 - 5; Osipova V., On the method of individual natural experiment, Psychiatry, neurology and expert psychology, 1922, c. 1; Shevaleva E. and Ergolskaya O., Children's team in the light of a collective natural experiment, Sat., dedicated. V. Bekhterev, L., 1926. V. Artemov.

Natural experiment (psychology)

natural experiment, or field experiment, - V psychology it's kind experiment, which is carried out in the conditions of normal life of the subject with a minimum of experimenter intervention in this process.

When conducting a field experiment, it remains possible, if allowed, ethical and organizational considerations, to leave the subject in the dark about their role and participation in the experiment, which has the advantage that the natural behavior of the subject will not be affected fact conducting research.

This method is specific in that the experimenter's ability to control additional variables is limited.

Literature

• Zarochentsev K. D., Khudyakov A. I. Experimental psychology: textbook. - M.: Prospekt, 2005. S. 51.

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