Psychological experiment- an experiment conducted in special conditions to obtain new scientific knowledge about psychology through the targeted intervention of a researcher in the life of the subject.

Various authors interpret the concept of "psychological experiment" ambiguously; often, under the experiment in psychology, a complex of different independent empirical methods is considered ( actual experiment, observation, questioning, testing). However, traditionally in experimental psychology, the experiment is considered an independent method.

As part of psychological counseling, a psychological experiment is a specially created situation designed for a more holistic (in various modalities) experience by the client of his own experience.

The specifics of a psychological experiment

In psychology, experimental research has its own specifics, which makes it possible to consider it separately from research in other sciences. The specifics of the psychological experiment is that:

• The psyche as a construct cannot be directly observed and one can learn about its activity only based on its manifestations, for example, in the form of a certain behavior.
• When studying mental processes, it is considered impossible to single out any one of them, and the impact always occurs on the psyche as a whole (or, from a modern point of view, on the body as a single indivisible system).
• In experiments with humans (as well as some higher animals, such as primates), there is an active interaction between the experimenter and the subject.
• This interaction, among other things, makes it necessary for the subject to have instructions (which, obviously, is not typical for natural science experiments).

General information

In a simplified example, the independent variable can be considered as a relevant stimulus (St(r)), the strength of which is varied by the experimenter, while the dependent variable is the reaction ( R) of the subject, his psyche ( P) on the impact of that relevant stimulus.

However, as a rule, it is precisely the desired stability of all conditions, except for the independent variable, that is unattainable in a psychological experiment, since almost always, in addition to these two variables, there are also additional variables, systematic irrelevant incentives (St(1)) and random stimuli ( St(2)), leading to systematic and random errors, respectively. Thus, the final schematic representation of the experimental process looks like this:

Therefore, three types of variables can be distinguished in the experiment:

1. Additional variables (or external variables)

So, the experimenter is trying to establish a functional relationship between the dependent and independent variable, which is expressed in the function R=f( St(r)), while trying to take into account the systematic error that arose as a result of exposure to irrelevant stimuli (examples of a systematic error include the phases of the moon, time of day, etc.). To reduce the likelihood of the impact of random errors on the result, the researcher seeks to conduct a series of experiments (an example of a random error can be, for example, fatigue or a mote that has fallen into the eye of the test subject).

The main task of the experimental study

The general task of psychological experiments is to establish the existence of a connection R=f( S, P) and, if possible, the form of the function f (there are various types of relationships - causal, functional, correlation, etc.). In this case, R- test subject's response S- the situation and P- the personality of the subject, the psyche, or "internal processes". That is, roughly speaking, since it is impossible to “see” mental processes, in a psychological experiment, based on the reaction of subjects to stimulation regulated by the experimenter, some conclusion is made about the psyche, mental processes or personality of the subject.

Stages of the experiment

Each experiment can be divided into the following stages. The first stage is the formulation of the problem and goal, as well as the construction of an experiment plan. The plan of the experiment should be built taking into account the accumulated knowledge and reflect the relevance of the problem.

The second stage is the actual process of active influence on the world resulting in the accumulation of objective scientific facts. Properly selected experimental technique contributes to obtaining these facts to a large extent. As a rule, the experimental method is formed on the basis of those difficulties that must be eliminated in order to solve the problems posed in the experiment. A technique developed for some experiments may be suitable for other experiments, that is, acquire universal significance.

Validity in a psychological experiment

As in natural science experiments, so in psychological experiments, the concept of validity is considered the cornerstone: if the experiment is valid, scientists can have some confidence that they measured exactly what they wanted to measure. A lot of measures are taken in order to respect all kinds of validity. However, it is impossible to be absolutely sure that in some, even the most thoughtful, study, all the validity criteria can be completely met. A completely flawless experiment is unattainable.

Classifications of experiments

Depending on the conditions for conducting, allocate

• Laboratory experiment - the conditions are specially organized by the experimenter. The main objective is to ensure high internal validity. The allocation of a single independent variable is characteristic. The main way to control external variables is elimination (elimination). External validity is lower than in the field experiment.
• Field, or natural experiment - the experiment is carried out in conditions that the experimenter does not control. The main task is to ensure high external validity. The selection of a complex independent variable is characteristic. The main ways to control external variables are randomization (the levels of external variables in the study correspond exactly to the levels of these variables in life, that is, outside the study) and constancy (make the level of the variable the same for all participants). Internal validity is generally lower than in laboratory experiments.

Depending on the result of the impact,

Ascertaining experiment - the experimenter does not irreversibly change the properties of the participant, does not form new properties in him and does not develop those that already exist.

Formative experiment - the experimenter changes the participant irreversibly, forms in him such properties that did not exist before or develops those that already existed.

Pathopsychological experiment - the purpose of the experiment is the task of qualitative and quantitative assessment of the main processes of thinking; the experimenter, as a rule, is not interested in the immediate results of testing, since research is carried out during the experiment way achieving a result.

depending on the level of awareness

Depending on the level of awareness, experiments can also be divided into

• those in which the subject is given complete information about the goals and objectives of the study,
• those in which, for the purposes of the experiment, some information about him from the subject is withheld or distorted (for example, when it is necessary that the subject does not know about the true hypothesis of the study, he may be told a false one),
• and those in which the subject is unaware of the purpose of the experiment or even of the very fact of the experiment (for example, experiments involving children).

Organization of the experiment

Flawless Experiment

Not a single experiment in any science is able to withstand the criticism of the supporters of the "absolute" accuracy of scientific conclusions. However, as a standard of perfection, Robert Gottsdanker introduced the concept of “perfect experiment” into experimental psychology - an unattainable ideal of an experiment that fully satisfies the three criteria (ideality, infinity, full compliance), to which researchers should strive to approach.

A flawless experiment is a model of experiment that is impracticable in practice and is used as a benchmark by experimental psychologists. This term was introduced into experimental psychology by Robert Gottsdanker, the author of the well-known book "Fundamentals of Psychological Experiment", who believed that the use of such a sample for comparison would lead to a more effective improvement of experimental methods and the identification of possible errors in planning and conducting psychological experiment.

Criteria for a flawless experiment

A flawless experiment, according to Gottsdanker, must satisfy three criteria:

• Ideal experiment (only independent and dependent variables change, there is no influence of external or additional variables on it)
• Infinite experiment (the experiment must continue indefinitely, since there is always the possibility of a manifestation of a previously unknown factor)
• An experiment of full correspondence (the experimental situation must be completely identical to how it would happen "in reality")

Interaction between experimenter and subject

The problem of organizing interaction between the experimenter and the subject is considered one of the main ones, generated by the specifics of psychological science. The instruction is considered as the most common means of direct communication between the experimenter and the subject.

Instruction to the subject

The instruction to the subject in a psychological experiment is given in order to increase the likelihood that the subject adequately understood the requirements of the experimenter, so it gives clear information on how the subject should behave, what he is asked to do. For all subjects within the same experiment, the same (or equivalent) text with the same requirements is given. However, due to the individuality of each subject, in experiments the psychologist is faced with the task of ensuring an adequate understanding of the instruction by the person. Examples of differences between subjects that determine the appropriateness of an individual approach:

• it is enough for some subjects to read the instruction once, for others - several times,
• some subjects are nervous, while others remain cool,
• etc.

Requirements for most instructions:

• The instruction should explain the purpose and significance of the study
• It must clearly state the content, course and details of the experience.
• It should be detailed and at the same time sufficiently concise.

Sampling problem

Another task facing the researcher is the formation of a sample. The researcher first of all needs to determine its volume (number of subjects) and composition, while the sample must be representative, that is, the researcher must be able to extend the conclusions drawn from the results of the study of this sample to the entire population from which this sample was collected. For these purposes, there are various strategies for selecting samples and forming groups of subjects. Very often, for simple (one-factor) experiments, two groups are formed - control and experimental. In some situations, it can be quite difficult to select a group of subjects without creating a selection bias.

Stages of a psychological experiment

The general model for conducting a psychological experiment meets the requirements of the scientific method. When conducting a holistic experimental study, the following stages are distinguished:

1. Initial problem statement
   • Statement of a psychological hypothesis
2. Working with scientific literature
   • Search for definitions of basic concepts
   • Compilation of a bibliography on the subject of the study
3. Refinement of the hypothesis and definition of variables
   • Definition of experimental hypothesis
4. Choice of an experimental tool that allows:
   • Manage independent variable
   • Register dependent variable
5. Planning a Pilot Study
   • Highlighting Additional Variables
   • Choosing an Experimental Plan
6. Formation of the sample and distribution of subjects into groups in accordance with the adopted plan
7. Conducting an experiment
   • Experiment preparation
   • Instructing and motivating subjects
   • Actually experimentation
8. Primary data processing
   • Tabulation
   • Information Form Transformation
   • Data validation
9. Statistical processing
   • Choice of statistical processing methods
   • Converting an Experimental Hypothesis to a Statistical Hypothesis
   • Carrying out statistical processing
10. Interpretation of results and conclusions
11. Recording the research in a scientific report, monograph, letter to the editor of a scientific journal

Advantages of the experiment as a research method

The following main advantages that the experimental method has in psychological research can be distinguished:

• Possibility to choose the start time of the event
• The frequency of the event under study
• Changeability of results through conscious manipulation of independent variables
• Ensures high accuracy of results
• Repeated studies under similar conditions are possible

Control methods

1. Exclusion method (if a certain feature is known - an additional variable, then it can be excluded).
2. Equalization method (used when one or another interfering feature is known, but it cannot be avoided).
3. Randomization method (used if the influencing factor is not known and it is impossible to avoid its impact). A way to retest the hypothesis on different samples, in different places, on different categories of people, etc.

Criticism of the experimental method

Proponents of inadmissibility experimental method in psychology are based on the following provisions:

• The subject-subject relationship violates scientific rules
• The psyche has the property of spontaneity
• The mind is too fickle
• The mind is too unique
• The psyche is too complex an object of study

Psychological and pedagogical experiment

A psychological and pedagogical experiment, or a formative experiment, is a type of experiment that is specific exclusively to psychology, in which active influence experimental situation on the subject should contribute to his mental development and personal growth.

A psychological and pedagogical experiment requires a very high qualification on the part of the experimenter, since unsuccessful and incorrect use psychological methods can lead to negative consequences for the subject.

Psychological and pedagogical experiment is one of the types psychological experiment.

In the course of a psychological and pedagogical experiment, the formation of a certain quality is supposed (that is why it is also called "forming"), usually two groups participate: experimental and control. The participants of the experimental group are offered a certain task, which (according to the experimenters) will contribute to the formation of a given quality. The control group of subjects is not given this task. At the end of the experiment, the two groups are compared with each other to evaluate the results.

The formative experiment as a method appeared thanks to the theory of activity (A.N. Leontiev, D.B. Elkonin, etc.), which affirms the idea of ​​the primacy of activity in relation to mental development. During the formative experiment, active actions are performed by both the subjects and the experimenter. On the part of the experimenter, a high degree of intervention and control over the underlying variables is required. This distinguishes experiment from observation or examination.

natural experiment

A natural experiment, or field experiment, in psychology, is a type of experiment that is carried out under 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 ethical and organizational considerations allow, to leave the subject in the dark about his role and participation in the experiment, which has the advantage that the fact of conducting the study will not affect the natural behavior of the subject.

A laboratory experiment, or an artificial experiment, is carried out in artificially created conditions (within a scientific laboratory) and in which, as far as possible, the interaction of the studied subjects is ensured only with those factors that are of interest to the experimenter. Subjects under study are considered to be subjects or a group of subjects, and the factors of interest to the researcher are called relevant stimuli.

The specificity that distinguishes a psychological laboratory experiment from experiments in other sciences lies in the subject-subject nature of the relationship between the experimenter and the subject, which is expressed in active interaction between them.

A laboratory experiment is set up in cases where the researcher needs to provide the greatest possible control over the independent variable and additional variables. Additional variables are called irrelevant, or irrelevant, and random stimuli, which in natural conditions are much more difficult to control.

Control over additional variables

As a control over additional variables, the researcher should carry out: Finding out all irrelevant factors that can be identified If possible, keeping these factors unchanged during the experiment Tracking changes in irrelevant factors during the experiment

Pathopsychological experiment

The pathopsychological diagnostic experiment has specific differences from the traditional test research method in terms of the research procedure and analysis of the research results in terms of qualitative indicators (no time limit for completing the task, researching how to achieve the result, the possibility of using the experimenter's help, speech and emotional reactions during a task, etc.). Although the stimulus material of the techniques itself may remain classical. This is what distinguishes the pathopsychological experiment from the traditional psychological and psychometric (test) research. Analysis of the protocol of a pathopsychological study is a special technology that requires certain skills, and the "Protocol" itself is the soul of the experiment.

One of the basic principles for constructing experimental techniques aimed at studying the psyche of patients is the principle of modeling ordinary mental activity carried out by a person in work, study, and communication. Modeling consists in isolating the main mental acts and actions of a person and provoking or, better to say, organizing the performance of these actions in unusual, somewhat artificial conditions. The quantity and quality of such models are very diverse; here is analysis, and synthesis, and the establishment of various connections between objects, combination, dismemberment, etc. In practice, most experiments consist in the fact that the patient is offered to do some work, they are offered a series of practical tasks or actions "in the mind", and then carefully record how the patient acted, and if wrong, then what caused and what type of these errors were

Solso R. L., Johnson H. H., Beal M. C. Experimental psychology: a practical course. - St. Petersburg: prime-EVROZNAK, 2001.

Gottsdanker, Robert;"Fundamentals of psychological experiment"; Publishing house: M.: MGU, 1982;

D. Campbell. Models of experiments in social psychology and applied research. M., Progress 1980.

Gottsdanker R. Fundamentals of psychological experiment. M.: MGPPIA, 1982. S. 51-54.

V. V. Nikandrov Observation and experiment in psychology. St. Petersburg: Speech, 2002, p. 78.

When experimenting, even an experienced researcher is not guaranteed against errors and distortions of information. Some of them can be eliminated if we approach the design of the experiment more carefully. The other part is, in principle, irremovable. But taking into account this very possibility, the possibility of errors, allows us to make the necessary corrections.

First of all, something that, in fact, is not an experiment, can be mistakenly called an experiment. When conducting a parallel experiment, it is possible, for example, to change the wage system in one factory team, and not change it in another, and it may turn out that labor productivity has increased in the first team. However, this kind of situation will by no means be experimental unless some important characteristics of both groups are taken into account and put under control: control.

The experimental and control teams should be equal in terms of quantitative composition, type of activity, distribution of production functions, type of leadership, or other important characteristics from the point of view of the hypothesis. If any important group properties cannot be equalized, one should try to somehow neutralize or fix them and take them into account when analyzing the results.

In cases where the sociologist does not do this, he is not at liberty to call the created situation experimental and to explain the change in productivity by changing the wage system, since the change in productivity may be caused by any other random factor, and not change; wages. Before calling a study experimental, the researcher must analyze whether he has a basis for this, in other words, whether he has created the necessary conditions and whether it provided the required level of measurement and control.

When formulating a hypothesis and when moving from a general hypothesis to operational variables, errors may occur related to the logic of reasoning.

As a unifying reason when formulating a hypothesis: the identified mechanisms and relationships may be erroneously identified. This usually happens when studying little-known phenomena, and then the negative results obtained in the experiment are a positive contribution to the development of a theoretical model of the object of observation, since they show that this mechanism or connection does not determine the ongoing processes.

Errors are possible in the transition from the definition of a hypothetical

connection to the description of its empirical indicators. Incorrectly chosen indicators deprive the experiment of any value, regardless of how carefully it was conducted. There may be errors associated with the subjective perception of the situation by both the participants in the experiment and the researcher. The experimenter often has a tendency to overestimate the effect of the variable being investigated, and this leads to the fact that he is inclined to interpret any ambiguous fact in the direction he wants.

The members of the experimental group also have the possibility of a subjective interpretation of the situation: they can perceive certain features of the experimental situation in accordance with their own attitudes, and not in the sense in which they are presented to the experimenter. Such a discrepancy in perception, if it is not taken into account when planning an experiment, will certainly affect the analysis of the results and significantly reduce their reliability.

The weakening of control and the decrease in the degree of "purity" of the experiment increase the possibility of the influence of additional variables or random factors, which at the end of the experiment cannot be taken into account or evaluated. This, in turn, greatly reduces the reliability of the conclusions drawn.

Insufficiently experienced, the researcher is in danger associated with the use of statistical methods, He may apply methods that are not appropriate for the research task. This possibility applies both to the design of the experimental group and to the way the results are analyzed.

The use of an experiment in sociology is associated with a number of difficulties that do not allow achieving the purity of a natural science experiment, since it is impossible to eliminate the influence of relations that exist outside the investigated one, it is impossible to control factors to the extent that it is possible in a natural science experiment, to repeat the course in the same form and results.

An experiment in sociology directly affects a specific person, and this also poses epic problems, naturally, narrows the boundaries of the application of the experiment and requires increased responsibility from the researcher.

Literature for additional reading

Lenin V. R, Great initiative. - Full. coll. cit., vol. 39, p. 1-29.

Afanasiev V. G. Management of society as a sociological problem. - In the book: Scientific management of society. M.: Thought, 1968, no. 2, p. 218-219.

Meleva L. A., Sivokon P. E. Social experiment and its methodological foundations. Moscow: Knowledge 1970. 48 p.

Kuznetsov V.P. Experiment as a method of object transformation. - Vesti. Moscow State University.

Ser. 7. Philosophy, 1975, No. 4, p. 3-10.

Kupriyan A.P. The problem of experiment in the system of social practice M. Nauka, 1981. 168 p.

Lectures on the methodology of specific social research / Ed. G. M. Andreeva. M.: Publishing House of Moscow State University, 1972, p. 174-201.

Mikhailov S. Empirical sociological research. Moscow: Progress, 1975, pp. 296-301.

Fundamentals of Marxist-Leninist sociology. Moscow: Progress, 1972, p. 103-108. The process of social research / Under the general. ed. Yu. E. Volkova. Moscow: Progress 1975, sec. PD II.4.

Panto R., Grawitz M. Methods social sciences. M.: Progress, 1972, pp. 557-562.

Richtarzyk K. Sociology on the Ways of Cognition. M.: Progress, 1981, p. 89-112.

Ruzavin G.I. Methods of scientific research. Moscow: Thought, 1974, p. 64-84.

Shtoff V. A. Introduction to methodology scientific knowledge. L.; Publishing house of Leningrad State University. 1972. 191 p.

Section Four

Experimental technique

An experimental technique is a set of methods and techniques for conducting it. The methodology, which applies to the entire study, is general. For individual experiments within this study, additional private methods can be created. The importance of private methods increases with the increase in the variety of phenomena to be studied.

The methodology of experimental research determines the equipment, the number of experiments, the work plan, the cost of time and money.

The construction of the correct methodology allows, in the shortest possible time and with minimal environmental and labor costs, to obtain the expected result from the experiment and avoid the appearance of unnecessary experimental data, from which no conclusions can be drawn.

The experiment can be carried out in a passive form (observation without interference in the conditions of the development of the phenomenon) and active (creation of certain conditions for the development of the phenomenon).

Passive observation is mainly used for preliminary verification of the general correctness of the working hypothesis and for establishing the direction of development of the phenomenon. During passive observation, the researcher registers various parameters of interest to him, characterizing the phenomenon. Various measuring instruments are used for registration. Passive observation can be alternated with active.

Observation becomes active when the researcher himself determines the conditions for the development of the phenomenon in the desired direction in order to obtain clear patterns.

The first stage of active observation is search experiments. The purpose of the search experiments is to check the individual parts of the developed methodology and the suitability of instruments for the measurements that are determined by the methodology. In the course of exploratory experiments, the factors that determine development are also established or the main factors are selected. Search experiments can also be set in order to find grounds for calculating the number of experiments.

After conducting search experiments, all the factors that cause the phenomena are divided into the main ones, which have the greatest influence on the development of the phenomenon and carry the greatest information about it, and additional factors that affect the development of the phenomenon secondary. When setting up an experiment, only parameters characterizing the main factors are measured.

It should be borne in mind that this division is largely conditional, since when the conditions of the experiment change, additional factors can become the main ones and vice versa.

In order to eliminate or at least reduce the error that appears as a result of the division of factors into basic and additional ones, when, when setting up experiments, it seeks to neutralize additional factors, i.e. to create such conditions under which the effect of additional factors would be as stable and insignificant as possible. In this case, the researcher should strive to make the variables only the main factors. In this way, general principles of research is the constancy of all other factors when the chosen ones change.

There are four basic techniques for neutralizing additional factors.

Method of abrupt change of variable factors with relatively little change in the others. With this method, they try to change the main factor in the widest range of values, and minimize the change in the rest. For example, when taking a pump characteristic Q=f(p), or efficiency=f(p), it is desirable to change the pressure as widely as possible, and secondary factors, such as machine wear, the effect of oil viscosity, temperature repsim, etc. to minimize, for which it is better to carry out the study on equally worn machines (for example, when comparing two different types of machines), to cool the RJ, etc.

Method of control experiments, when changing additional factors simultaneously affect several objects with different gradations of the main factor, one of which is considered the control (standards) and all the others are compared with it. For example, when studying the effect of an additive to oil (lubrication) on bearing wear, an experiment can be carried out for two groups of bearings, of which a lubricant with an additive is used, in the other - without. Since in most cases it is not possible to avoid the influence of changes in temperature, load and speed conditions on bearing wear, two groups are tested simultaneously in such changing conditions, which are the results of wear. There can be much more than two groups of bearings for testing, each of them can use different additives or its different content, and one of the groups is always the control (reference).

The method of "pure" experiments. With this method, they seek to artificially create conditions in which additional factors would not appear or would not affect the changing main factors during experiments. This method is used only in laboratory conditions.

For example, in real operating conditions it is very difficult to study the operation of the hydraulic steering system of a car, because. the moment of resistance to the rotation of the steered wheels is constantly changing due to the presence of roadway irregularities, different coefficients of friction in its various sections, etc. In addition, the value of the moment of resistance to the rotation of the steered wheels during long-term testing will be affected by tire wear, tire pressure, changes in vehicle weight (for example, as a result of refueling), etc. It is extremely difficult to conduct accurate scientific research under such conditions, therefore, when testing a hydraulic steering system, it idealizes its interaction with the external environment, artificially creating in laboratory conditions constant and precisely known values ​​​​of the resistance forces to turn the wheel, or, in other cases, providing changes in the resistance forces according to a certain law . The same method of "partial" experiments will be very suitable for Recreating in laboratory conditions angular vibrations and impacts of the required magnitude on the steerable wheels of a car, simulating the movement of a car on uneven roads. In real road conditions (outside special polygons), it is almost impossible to obtain such disturbances on the system with the required frequency and amplitude.

Method of different signs consists in the fact that the same factor, which cannot be completely eliminated, is first given a positive and then a negative value, so that when calculating the average value, the errors from not taking into account the influence of this factor are mutually canceled out.

For example, when studying the process of braking a car, the angle of the road in the longitudinal direction, as well as the wind speed, can lead to a noticeable error. To eliminate the error from the influence of these factors, experiments are made when the car moves to one and then the other (reverse) side of the same road section, after which the data obtained are averaged.

Experiment planning. The number of experiences.

When determining the required number of experiments, one should be guided by two kinds of provisions.

Firstly, such a number of experiments is needed that would accurately reveal the form of the functional dependence of the two parameters. For example, the position of a straight line is determined by two points, while arcs of constant radius are determined by three. For more complex curves, the number of points is determined by the following rule: considering a complex curve as a combination of straight and simple curves, describe each inflection of the curve with at least three points, and each section close to a straight line - with two. For a more accurate determination of the numerical values ​​of the function, it is recommended to substantiate each inflection of the curve with at least five experiments. In addition, sharp inflections of the curves or an abrupt change in the development of the phenomenon should occur with particular care.

For such a determination of the number of experimental points, the graphs of the regularity of the working hypothesis are used. If the pattern in the development of the phenomenon is not known in advance, the experimental points are evenly distributed along the abscissa. In the course of the experiments, the position of these points can be refined in accordance with the actual places of curve bends.

Secondly, it is necessary to take into account random errors of experience. As is known, to reduce the influence of such errors, the experiments are repeated and the arithmetic mean is taken. Moreover, the number of necessary repetitions depends on the standard deviation of the measurements and the given reliability of the result.

Under reliability experiment will understand the probability of obtaining the same results with new measurements of the same value or with repetition of the experiment under the same conditions.

It is known from the theory of probability that the greater the relative fluctuations of the results and the greater the reliability of the experiment it is desirable to obtain, the more repetitions of the experiment should be made. In the most convenient way for practical use, this dependence was established by V.I. Romanovsky and presented in the form of a table

Required number of experiments (measurements)

	The reliability of R.

In order to find the required number of experiments from this table, it is necessary to set the reliability P and the error A, taken in fractions of the standard deviation σ.

For example, when measuring with a less accurate instrument of any size, the standard deviation is 0.9 mm, and with a more accurate one - 0.15 mm. Let the allowable measurement error with a reliability of 0.95 should be no more than 0.3 mm, which is 1/3σ when measuring with a less accurate tool and 2σ when measuring with a more accurate tool. According to the table, we determine that under these conditions more than 27 measurements are required with a less accurate and only 4 measurements with a more accurate instrument.

If the standard deviation of the measurement result is not known in advance, then such an analysis can be carried out sequentially with experiments according to the following scheme: after each measurement, starting from the third, the mathematical expectation and standard deviation are calculated. As soon as the reliability and calculation of the error in the fraction of the standard σ give the number of measurements that have already been made in the table, the experiments are stopped.

In those cases where there is no necessary data to determine the number of repeated experiments, and search experiments require no less cost than the main ones, triple repetition of experiments is often taken as the minimum.

Planning single-factor and multi-factor experiments.

A factor should be understood as a variable that presumably affects the result of the experiment. The factor can be pressure, flow, viscosity of the RJ, etc.

When planning one-factor experiment, the correct choice of the number and location of experimental points on the function under study is of no small importance. In many cases, it is advisable to choose an experiment design with equal intervals between points. However, depending on the parameter for which an equal interval is taken, the change in its values, the result of the experiment may look different. For example, when examining a fluid on a throttle from its flow rate (), the graphs will look like:

When the controlled variable ν changes at regular intervals Δν, we obtain a graph, the images in Fig. a). In the area of ​​high speeds, there are not enough points, and in the area of ​​low speeds, they are in abundance. On fig. b) the situation is opposite. The most correct option is shown in Fig. c), where the same segments ΔS of the experimental curve are enclosed between the experimental points. However, this approach is difficult to calculate and for its implementation it is necessary to know the nature of the dependence under study before conducting experiments.

When choosing between the options shown in Fig. a) and b) it is better to use the criterion relative accuracy of data in different parts of the function under study. For example, for hydraulic systems, tests performed at low pressure or low power will be the least accurate. From this position, the sections of the curve on which the data are most doubtful are tried to be filled with a large number of points. From this point of view, the version shown in Fig. a) preferred.

When planning multifactorial experiments consider two or more variables. Such experiments are called two-factor, three-factor, etc.

If the experiment determines the dependent variable R, which is a function of several independent variables x, y, z, etc., then the plan of the multivariate experiment is that all independent variables, except for one, are assumed to be constant, and this one variable changes during the entire interval of the value, while the choice of the interval between the values ​​of the variable is made according to one of the rules discussed above. Then another independent variable changes, and all the others are kept constant. Essentially, a multivariate experiment is simply a sequence of single-factor experiments. This approach allows us to find such simple functions as

R=ax n+by m

the design of a two-factor experiment, in which each factor is taken at five levels, can be schematically represented as follows:

variable levels y

levels of re-

exchange x 3 * * * * *

An asterisk indicates the combinations of independents at which the experiment should be carried out.

For more complex functions such as

the above plan will be very limited and will not allow you to determine these dependencies. In this case, several levels of independent variables x and y are considered, for example:

variable levels y

variable levels y

levels of re-

exchange x 3 * * * * *

Or you might have to fill in the whole square and run the experiment for all 25 combinations of x and y.

When planning an experiment, keep in mind that it does not have to be balanced. This means that one can choose ten levels of x and only three levels of y if R's dependence on x is considered to be more important or more complex.

In addition, other plans are possible, more complex than those described above, focused on specific technical processes and built on the basis of a priori information about the nature of the function under study.

General principles for designing experiments

Comparison.

Randomization.

Replication.

Uniformity.

Stratification.

factor levels

Name: General principles experiment planning
Detailed description:

Since its inception, science has been looking for ways to understand the laws of the surrounding world. Making one discovery after another, scientists rise higher and higher up the ladder of knowledge, erasing the border of the unknown and entering new frontiers of science. This way lies through experiment. Consciously limiting the infinite diversity of nature by the artificial framework of scientific experience, we turn it into a picture of the world that is understandable to the human mind.

Experiment like Scientific research It is the form in which and through which science exists and develops. The experiment requires careful preparation before it is carried out. In biomedical research, the planning of the experimental part of the study is especially great importance due to the wide variability of properties characteristic of biological objects. This feature is the main reason for the difficulties in interpreting the results, which can vary significantly from experience to experience.

Statistical problems justify the need to choose such an experimental scheme that would minimize the effect of variability on the scientist's conclusions. Therefore, the purpose of experiment design is to create a design that is necessary to obtain as much information as possible at the lowest cost to carry out the study. More precisely, the planning of an experiment can be defined as the procedure for choosing the number and conditions for conducting experiments that are necessary and sufficient to solve the problem with the required accuracy.

Experimental design originated in agrobiology and is associated with the English statistician and biologist Sir Ronald Aylmer Fisher. At the beginning of the 20th century, at the agrobiological station in Rothamsted (Great Britain), studies began on the effect of fertilizers on the yield of various cereal varieties. Scientists had to take into account both the great variability of the objects of study and the long duration of the experiments (about a year). Under these conditions, there was no other way but to develop a well-thought-out experimental plan to reduce negative impact these factors on the accuracy of the conclusions. Applying statistical knowledge to biological problems, Fisher came to develop his own principles of the theory of statistical inference and laid the foundation for a new science of planning and analyzing experiments.

Ronald Fisher himself explained the basics of planning on the example of an experiment carried out to determine the ability of a certain English lady to distinguish between what was poured into a cup in the first place - tea or milk. It should be noted that for real English ladies it is important that tea is poured into milk, and not vice versa, a violation of the sequence will be a sign of ignorance and spoil the taste of the drink.

The experiment is simple: the lady tastes tea with milk and tries to understand the order in which both ingredients were poured. The design developed for this study has a number of properties.

Comparison. In many studies, it is difficult or impossible to accurately determine the measurement result. So, for example, a lady will not be able to quantify the quality of tea, she will compare it with the standard of a properly prepared drink, the taste of which has been familiar to her since childhood. As a rule, in a scientific experiment, the object is compared either with some predetermined standard or with a control object.

Randomization. This is a very important point in planning. In our example, randomization refers to the order in which the cups are presented for tasting. Randomization is necessary in order to be able to use statistical methods to analyze the results of the study.

Replication. Repeatability is a necessary component of setting up an experiment. It is unacceptable to draw conclusions about the ability to determine the quality of tea from only one cup. The result of each individual measurement (tasting) carries a share of the uncertainty that has arisen under the influence of many random factors. Therefore, several tests are needed to identify the source of variability. The sensitivity of the experiment is related to this property. Fisher noted that until the number of cups of tea exceeds a certain minimum, it is impossible to draw any unambiguous conclusions.

Uniformity. Despite the need to repeat measurements (replication), their number should not be too large so as not to lose homogeneity. The temperature difference of the cups, dullness of taste, etc., when a certain limit number of repetitions is exceeded, can make it difficult to analyze the results of the experiment.

Stratification. Going beyond R. Fisher's example to a more abstract description of the experimental plan, one can additionally indicate such a property as stratification (blocking). Stratification is the distribution of experimental units into relatively homogeneous groups (blocks, layers). The stratification procedure allows minimizing the effect of non-random sources of variability known to us. Within each block, the experimental error is assumed to be smaller relative to the variant with random selection for the experiment of the same number of objects. For example, when researching a new medicinal product we have two levels of the factor - "drug" and "placebo", which are given to men and women. In this case, gender is a blocking factor, according to which the study is divided into subgroups.

The characteristics of an experimental design described above apply in whole or in part to any scientific experiment. However, to get started, it is not enough just to know about general properties research, more careful preparation is needed. It is not possible to create a detailed guide within a single article, so the most general information about the stages of experiment planning.

Any research begins with setting a goal. The choice of problem to study and its formulation will influence both the design of the study and the conclusions that will be drawn from its results. In the simplest case, the problem statement should include the questions “Who?”, “What?”, “When?”, “Why?” And How?".

An illustration of the importance of this planning stage can be found in a study that collects information on traffic accidents. Depending on the goal setting, the work can be directed to the development of a new car or a new road surface. Despite the fact that the same data set is used, the problem statement and conclusions differ significantly depending on the problem formulation.

After choosing the goal of the work, the so-called dependent variables should be determined. These are the variables that will be measured in the study. For example, indicators of the functioning of certain systems of the human body or laboratory animals (heart rate, blood pressure, enzyme levels in the blood, etc.), as well as any other characteristics of the objects of study, the change of which will be informative for us.

Since there are dependent variables, there must also be independent variables. Their other name is factors. The researcher operates with factors in the experiment. This may be the dose of the study drug, the level of stress, the degree physical activity etc. The relationship between a factor and a dependent variable is conveniently represented using a cybernetic system, often called a "black box".

A black box is a system whose mechanism of operation is unknown to us. However, the researcher has information about what happens at the input and output of the black box. The state of the output is functionally dependent on the state of the input. Accordingly, y1, y2, ..., yp are dependent variables, the value of which depends on factors (independent variables x1, x2, ..., xk). Parameters w1, w2, ..., wn are disturbing influences that cannot be controlled or change with time.

In general terms, this can be written as follows: y=f(x1, x2, ..., xk).

Each factor in the experience can take on one of several values. Such values ​​are called factor levels. It may turn out that the factor is capable of taking an infinite number of values ​​(for example, the dose of a drug), but in practice several discrete levels are chosen, the number of which depends on the objectives of a particular experiment.

A fixed set of factor levels defines one of the possible states of the black box. At the same time, these are the conditions for conducting one of the possible experiments. If we enumerate all possible sets of such states, then we will get a complete set of different states of the given system, the number of which will be the number of all possible experiments. In order to calculate the number of possible states, it is enough to raise the number of levels of factors q (if it is the same for all factors) to the power of the number of factors k.

The totality of all possible states determines the complexity of the black box. Thus, a system of ten factors at four levels can be in more than a million different states. Obviously, in such cases it is impossible to carry out a study that includes all possible experiments. Therefore, at the planning stage, the question of how many experiments and which ones need to be carried out to solve the problem is decided.

It should be noted that the properties of the object of study are essential for the experiment. First, we need to have information about the degree of reproducibility of the results of experiments with a given object. To do this, you can conduct an experiment, and then repeat it at irregular intervals and compare the results. If the spread of values ​​does not exceed our requirements for the accuracy of the experiment, then the object satisfies the requirement for reproducibility of results. Another requirement for an object is its manageability. A controllable object is an object on which an active experiment can be carried out. In turn, an active experiment is an experiment in which the researcher has the opportunity to choose the levels of factors that are of interest to him.

In practice, there are no fully managed objects. As mentioned above, both controllable and uncontrollable factors act on a real object, which leads to variability in the results between individual objects. We can separate random changes from regular ones, caused by different levels of independent variables, only with the help of statistical methods.

But statistical methods are effective only under certain conditions. One of these conditions is the requirement of a certain minimum sample size used in the experiment. It is obvious that the wider the range of change in attributes from object to object, the greater should be the repetition of the experiment, i.e., the number of experimental groups.

Because it's unreasonable big number testing will make the study too expensive, and an insufficient sample size may compromise the accuracy of the conclusions, determining the required sample size plays a critical role in experiment design. Methods for calculating the minimum sample size are described in detail in the specialized literature, so it is not possible to present them in the article. However, it should be mentioned that they require a preliminary determination of the average value of the indicator under study and its error. Publications about similar studies can serve as a source of such information. If they have not yet been carried out, then there is a need to perform a preliminary “pilot” study to assess the variability of the trait.

The next step in designing experiments is randomization. Randomization is a process used to group subjects so that each of them has an equal chance of being placed in a control or treatment group. In other words, the selection of study participants must be random so that the study is not biased towards the investigator's "preferred" outcome.

Randomization helps prevent bias due to causes that were not directly addressed in the experimental design. For this, for example, the formation of experimental groups of laboratory animals is carried out randomly. However, complete randomization is not always possible. Thus, patients of a certain age group, with a predetermined diagnosis and severity of the disease, take part in clinical trials, and, therefore, the selection of participants is not random. In addition, randomization is limited by the so-called "block" designs of experiments. These plans imply that selection in each block is carried out in accordance with certain non-random conditions, and random selection of research objects is possible only within blocks. The randomization process is easy to implement using specialized statistical software or special tables.

In conclusion, it is necessary to say about the need to take into account in the research plan, in addition to the requirements of medicine and statistics, also moral and ethical standards. Do not forget that not only people, but also laboratory animals should be involved in the experiment in accordance with ethical principles.

With pedagogical measurements, as with many others, it is impossible to achieve absolute accuracy: we are always dealing with deviations from the absolute value. Therefore, there is always a certain possibility of error in an experiment.

In order for the experiment to give an accurate and reliable answer to the question posed, it is necessary, if possible, to reduce errors to a minimum.

Errors in the experiment can be of two types:

• 1) the researcher builds an objectively correct hypothesis, but as a result of a poorly conducted experiment, the correctness of the hypothesis is not confirmed;
• 2) the researcher builds an incorrect hypothesis, but an incorrectly conducted experiment gives such results, according to which the hypothesis is erroneously recognized as correct.

The sources of most disputes in science are often the inability to correctly take into account and evaluate possible mistakes during the experiment.

During the experiment, sometimes allowed intentional mistakes. They occur when an unscrupulous researcher distorts the course of an experiment and its data in order to "improve" the results.

Sometimes the teachers participating in the experiment have a fear that when evaluating the results of the experiment, their work will be criticized. Hence there is a distortion of the results of the experiment by teachers. For example, in experimental group create "conditions" for displaying more high achievements pupils, give the opportunity to prompt, help them, etc. It should be noted here that any conscious operations that distort real data are a gross violation of the professional ethics of the researcher.

Unconscious Mistakes arise mainly due to insufficient theoretical preparation for the experiment, inept planning, the use of subjective criteria for evaluating the results of the experiment, etc.

unconscious mistakes, are in turn divided into random and systematic. The first appear in one direction or the other. Most of them cancel each other, so their influence on the results of the experiment is negligible. If the number of subjects is large enough, then these errors can be neglected. Random errors can be due, for example, to a different number of children. But with enough in large numbers experimental and control groups are approximately equal in the number of strong, medium and weak students. It should also be taken into account that in pedagogical experiments, the value of additional variables is usually not measured, and therefore it is not always possible to say whether the influence of the deviations caused by them is insignificant (close to zero) or not.

At systematic errors one can always single out a certain direction or trend of accumulation. These errors cause deviations in the results of the experiment, always in a positive or negative direction. Such errors can significantly distort the results of the experiment. For example, studying the effect independent work students to the depth and strength of knowledge. In the experimental class, work is carried out in a well-equipped room. And in the control class, training takes place in a regular class with a limited set of visual aids and multimedia tools. It is clear that the learning conditions in this case are the cause of significant systematic errors.

Systematic errors can be minimized large quantity subjects and clear planning of the experiment. Practice shows that the causes of large systematic errors in the experiment are mainly errors made in the design of the experiment or as a result of the fact that some important factors were not taken into account. One of the main tasks of organizing experimental work is to find the right initial principles for planning an experiment and interpreting its results.

Materials for practical tasks

Program of experiment 1

experiment
Executor experiment	I. V. Razboinikova, master student of YSPU
supervisor experiment	L. V. Baiborodova, professor, doctor pedagogical sciences, Head of Department pedagogical technologies YaGPU
Relevance	One of the main requirements of the federal state educational standard higher vocational education to graduates of pedagogical universities is fluency in Russian for teaching school disciplines. The speech of the teacher should provide a solution to professional problems, as well as act as a model. However, often students and teachers not only make mistakes in oral and writing, but also have shortcomings in sound pronunciation, allow spelling and punctuation errors. In addition, the speech of future teachers is not always logical, consistent, stylistically consistent and intonation-shaped. Many students do not fully master the language as the most important means of communication. At the same time, the methods of solving this problem are not sufficiently presented in the scientific and methodological literature. Thus, there are contradictions: between the needs of society for specialists who are able to speak their own language and the low level of formation of language competence among future teachers; between the need to form future teachers primary school language competence and insufficient development of appropriate pedagogical means for this. To resolve these contradictions, it is necessary to identify and use effective pedagogical tools for the formation of the quality under study.
Experiment Idea	The development of speech in junior schoolchildren- the most important task of the teacher, but its solution depends on the language competence of the teacher himself. Opportunities for the formation of language competence of primary school teachers have philological disciplines. These opportunities are realized if you use special trainings, exercises, techniques, as well as identify the possibilities of research methods and technologies that will effectively improve the quality of students' oral and written speech, reduce the number of orthoepic, spelling, grammatical, punctuation and other errors.

	Pedagogical means the formation of language
experiment	competencies of future primary school teachers
Design of the experiment	Inclusion in Auditory lessons in philological disciplines of speech trainings and exercises, methods, technologies and techniques that form language competence
Object of experimentation	The process of forming the language competence of future primary school teachers
Subject of experimentation	Pedagogical means that effectively influence the formation of the language competence of future primary school teachers
Pedagogical	Fluency in different styles of speech in different situations, skillful use of the word as a means of pedagogical influence and communication, rich vocabulary, speech literacy
Purpose of the experiment	Develop and test pedagogical tools that effectively develop the language competence of future teachers in the classroom in philological disciplines
	1. To develop criteria and indicators for studying the formed language competence of students, as well as methods for measuring them and revealing the effectiveness of the pedagogical tools used. 2. Determine methods, technologies, ways of organizing learning activities, effectively influencing the formation of the language competence of future primary school teachers. 3. Plan classes using identified pedagogical tools. 4. To identify the effectiveness of pedagogical tools used to form language competence in the study of philological disciplines
Hypothesis	The use of research methods and classes conducted in the form of speech trainings, lectures and seminars with elements research work students will increase the level of formed ™ of their language competence
Diagnostic tools	The evaluation of the results of the experiment will be carried out using observation, questioning, testing, the method of analyzing the products of students' activities, performing diagnostic exercises and tasks.
Criteria for evaluating expected results	1. Knowledge of the language and the rules governing speech activity. 2. The ability to express an idea in a word clearly and correctly. 3. The ability to navigate in a communicative situation, to accurately select language means. 4. Literacy of oral speech: - spelling literacy;

Topic	Pedagogical means the formation of language
experiment	competencies of future primary school teachers Timing of the experiment	February - May
Stages of the experiment	1. Development of criteria and indicators for tracking the results of the experiment and identifying the effectiveness of the pedagogical tools used. 2. Diagnosis of the level of formation of the language competence of students. 3. Planning and development of classes within the framework of the training course using methods, forms, technologies, techniques that effectively influence the formation of language competence. 4. Organization of scheduled classes, tracking in the course of the experiment, the effectiveness of the influence of the means used on the intermediate results of the formation of competence. 5. Carrying out a repeated "cut" and determining the dynamics of the formation of language competence. 6. Analysis of the results of the experiment, determination of the effectiveness of the pedagogical tools used for the formation of language competence (methods, forms, technologies, etc.). Making adjustments to the original plans, program training sessions. 7. Discussion of the results of the experiment at a meeting of the department. Preparation of publication and guidelines
Forecast of possible negative consequences	1. Passivity and unwillingness of students to master new forms in the classroom. 2. The occurrence of material and technical difficulties
corrections, compensation negative consequences	Motivating students to master new forms and methods, emphasizing the significance of the experiment for each participant

	Pedagogical means the formation of language
experiment	competencies of future primary school teachers
The composition of the participants in the experiment	Students of the Faculty of Education and teachers of the Department of Methods of Teaching Philological Disciplines in Primary School
Functional responsibilities	Head of the department: includes the experiment in the plan scientific work department, approves the program and plan of the experiment, informs the staff of the department about the experiment, invites colleagues to participate if necessary, helps to solve organizational and methodological issues, helps to determine the basis of the experiment. Master student: draws up the program and plan of the experiment, prepares the necessary teaching materials, coordinates his activities with other teachers, draws up the results of the experiment and presents them at a meeting of the department. Supervisor: provides scientific and methodological assistance, helps in drawing up the program and plan of the experiment, coordinates the base of practice with the head of the department, controls the course of the experiment, the implementation of its program, helps in formalizing the results
Experiment base	Groups of students of the 4th and 5th courses of the Pedagogical Faculty of YSPU
Scale of experiment	The duration of the experiment is 3.5 months. Coverage of students - 76 people; the volume of training sessions - 20 hours of lectures and practical training on the course
Experiment type	Formative
Experiment Status	Collective, within the faculty
The form of presentation of the results of the experiment for mass practice	1. Speech at the "School of Young Scientists" 2. Speech at a scientific and practical conference 3. Publication of the article 4. Drawing up methodological recommendations
Scientific and methodological support of the experiment	Scientific and methodical literature on the topic, scientific advice

Questions for self-control and discussion

• 1. What are the features of the pedagogical experiment?
• 2. What methods are used during the pedagogical experiment?
• 3. What should be considered when organizing an experiment?
• 4. How to ensure reliable results of the experiment?
• 5. What is the relationship between the concepts of "experimental work", "experimental work", "experiment", "innovative activity"?

Practical tasks

• 1. Using the experiment program presented above, characterize it in accordance with the classification of experiments.
• 2. Analyze the program of the experiment proposed above in terms of its requirements.
• 3. Using the table of classification of experiments presented in fig. 3.1, describe the experiment on the topic of your research.
• 4. Make an experiment program on the topic of your research.

• When developing the program, materials from the book were used: Sidorenko A.S., Novikova T.G. Experiment in education. M. : APK i PRO, 2002. S. 47-48.