Organization of scientific research. Conducting scientific research in modern conditions Methods and means of research

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In the course of the development of science are developed and improved funds knowledge :

- material,

- mathematical,

- brain teaser,

- language,

- informational.

All means of cognition are specially created means. In this sense, material, informational, mathematical, logical, linguistic means of cognition have a common property: they are designed, created, developed, substantiated for certain cognitive purposes (Figure 4.6).

Material resources knowledge is, first of all, instruments for scientific research. In history, the emergence of material means of cognition is associated with the formation of empirical research methods - observation, measurement, experiment. These funds are directly aimed at the objects under study, they play the main role in the empirical testing of hypotheses and other results of scientific research, in the discovery of new objects, facts. The use of material means of cognition in science in general - a microscope, a telescope, a synchrophasotron, satellites of the Earth, etc. - has a profound influence on the formation of the conceptual apparatus of the sciences, on the ways of describing the subjects studied, the methods of reasoning and representations, on the generalizations, idealizations and arguments used.

Figure 4.6 - Research tools

Information tools knowledge. The mass introduction of computer technology, information technology, and telecommunications is fundamentally transforming research activities in many branches of science, making them the means of scientific knowledge. In particular, in recent decades, computer technology has been widely used to automate experiments in physics, biology, technical sciences, etc., which allows hundreds, thousands of times to simplify research procedures and reduce data processing time. In addition, information tools can significantly simplify the processing of statistical data in almost all branches of science. And the use of satellite navigation systems greatly increases the accuracy of measurements in geodesy, cartography, etc.

Mathematical tools knowledge. The development of mathematical means of knowledge has an increasing influence on the development modern science, they also penetrate into the humanities and social sciences. Mathematics, being the science of quantitative relations and spatial forms abstracted from their specific content, has developed and applied specific means of abstracting form from content and formulated the rules for considering form as an independent object in the form of numbers, sets, etc., which simplifies, facilitates and accelerates the process of cognition, allows you to more deeply reveal the connection between objects from which the form is abstracted, to isolate the initial positions, to ensure the accuracy and rigor of judgments. Mathematical tools make it possible to consider not only directly abstracted quantitative relations and spatial forms, but also logically possible, that is, those that are deduced according to logical rules from previously known relations and forms. Under the influence of mathematical means of cognition, the theoretical apparatus of the descriptive sciences undergoes significant changes. Mathematical tools make it possible to systematize empirical data, to identify and formulate quantitative dependencies and patterns. Mathematical tools are also used as special forms of idealization and analogy (mathematical modeling).

logical means knowledge. In any study, the scientist must decide logical tasks:

- what logical requirements should satisfy the reasoning, allowing to make objectively true conclusions; how to control the nature of these reasoning?

– what logical requirements should satisfy the description of empirically observed characteristics?

– how to logically analyze the initial systems of scientific knowledge, how to coordinate some knowledge systems with other knowledge systems (for example, in sociology and closely related psychology)?

- how to build a scientific theory that allows you to give scientific explanations, predictions, etc.?

The use of logical means in the process of constructing reasoning and evidence allows the researcher to separate controlled arguments from intuitive or uncritically accepted, false from true, confusion from contradictions.

Language tools knowledge. An important linguistic means of cognition are, among other things, the rules for constructing definitions of concepts (definitions). In any scientific research, the scientist has to clarify the introduced concepts, symbols and signs, to use new concepts and signs. Definitions are always associated with language as a means of cognition and expression of knowledge.

The rules for using languages, both natural and artificial, with the help of which the researcher builds his reasoning and evidence, formulates hypotheses, draws conclusions, etc., are the starting point for cognitive actions. Knowledge of them has a great influence on the effectiveness of the use of linguistic means of cognition in scientific research.

Along with the means of cognition are the methods of scientific cognition (methods of research).

Under research methods the very methods of studying phenomena, obtaining scientific information in order to establish regular connections, relationships, and the construction of scientific theories are understood.

In research work, a master student, as a rule, uses well-known methods of psychological, pedagogical, sociological and economic research. The choice of research methods depends on the definition of the topic, problem, hypothesis, purpose and objectives of the study. This issue has been adequately covered in the specialized literature. However, it makes sense to briefly describe the main methods.

All research methods can be divided into theoretical, empirical and mathematical (statistical and econometric).

Methods of theoretical research(theoretical methods) are needed to identify problems, formulate hypotheses, and evaluate the facts collected.

Theoretical analysis- this is the selection and consideration of individual aspects, signs, features, properties of phenomena. Analysis is manifested in the mental division of the whole (phenomenon, property, process or relationship between objects) into its constituent parts, performed in the process of cognition, and allows you to obtain information about the structure of the object of study.

Analysis is accompanied by synthesis and allows you to penetrate into the essence of the issue under study.

Synthesis - the process (usually purposeful) of connecting or combining previously disparate things or concepts into something qualitatively new, whole or representing a set. In addition to analysis, the synthesis method allows you to get an idea of the relationships between the components of the object of study.

inductive method- a method of cognition built on induction, involving the movement of thought (the process inference) from particular judgments to general ones.

deductive method – a method of constructing scientific theories based on the use of deductive techniques (deduction) - a system of logical conclusions from general judgments to a particular conclusion. The beginning (premises) of deduction are axioms, postulates, or simply hypotheses that have the character of general statements, and the end is consequences from premises, theorems, conclusions. If the premises of the deduction are true, then so are its consequences. Deduction is the main means of proof.

Comparison– a method of cognition that underlies judgments about the similarity or difference of objects. With the help of comparison, qualitative and quantitative characteristics of objects are revealed.

Generalization– a method of cognition leading to the selection and meaning of relatively stable properties of an object. In term papers, they often resort to using this method when generalizing concepts - a logical operation, through which, as a result of the exclusion of a specific feature, a concept of a wider scope, but less content, is obtained.

abstraction – this is a method of cognition, which is a mental selection of the essential properties and connections of an object and a distraction from its other properties and connections, recognized as private, insignificant. This theoretical generalization allows reflecting the main patterns of the objects or phenomena under study, studying them, as well as predicting new, unknown patterns. We can say that abstraction allows you to mentally abstract from the non-essential properties of an object and highlight the essential, basic properties, features, connections.

Specification– filling a schematized cognitive picture of an object with particular features, due to which it is possible to move from one scheme to another, more optimal for solving specific problems.

Systematization– the method of unification, the reduction of groups of units that are homogeneous according to certain characteristics (parameters, criteria) to a certain hierarchized unity for functional purposes based on the links existing between them and / or complementary links with the outside world.

Classification– method of grouping objects of study or observation in accordance with their common features. As a result of the developed classification, a classified system (classification) is created.

Modeling- the study of any objects on their models(from lat. modis, fr. modele - sample), that is, on conditional images, diagrams or physical structures similar to the object under study, using the methods of analogy and similarity theory when conducting and processing experimental data. Modeling is used when for some reason it is difficult or impossible to study an object in natural conditions, or when it is necessary to facilitate the process of studying an object.

The model reflects the main, from the point of view of the problem being solved, properties of the modeling object in a simpler, reduced form. At the same time, the model reflects the structure, properties, relationships and relationships between the elements of the object under study. The object under study, in relation to which the model is made, is called original, sample, prototype.

In sociological research, modeling is carried out with the help of signs, symbols, drawings (diagrams).

Theoretical methods are associated with the study and analysis of the relevant literature, which makes it possible to find out which problems in the field under study and in what aspects have already been sufficiently studied, on which scientific discussions are ongoing, what is outdated, and what issues have not yet been resolved.

Literature work includes methods such as:

compiling a bibliography a list of sources selected for work in connection with the problem under study;

summarizing - a concise transcription of the main content of one or more works on a general topic;

note-taking- maintaining more detailed records, the basis of which is the selection of the main ideas and provisions of the work;

annotation - a summary of the general content of the book or article;

citation - verbatim record of expressions, whether actual digital data contained in a literary source.

empirical methods – this is research methods based on facts, practical activities, really emerging experience of organizing something (without subsequent conclusions and theoretical generalizations, since these are already theoretical research methods).

Conversation- is carried out according to a predetermined plan with the allocation of questions that need to be clarified, but improvisation is allowed, that is, a slight deviation from the plan, so the conversation is conducted in a free form without recording the answers of the respondents.

Interview(is a kind of conversation) - the researcher adheres to pre-planned and recorded questions asked in a certain sequence, and fixes the answers of the respondents.

Questionnaire- a method of mass collection of material using a questionnaire in which questions are presented to respondents in writing. When questioning, you can use both questionnaires developed by other authors, and your own, independently developed.

Studying documentation- a research method in which various documentation of an organizational and practical nature, regulatory and instructive-methodical documents are studied. At the same time, generalizations, conclusions are made, attention is drawn to the structure of the document, the main provisions relevant to this study, etc.

scientific observation– a general scientific method of collecting primary information by direct registration by the researcher of events, phenomena and processes occurring under certain conditions. Obtaining empirical information occurs with the use of human senses, various kinds of scientific instruments and operational means for fixing and quantifying incoming information. Scientific observation is distinguished by the clarity of the goal, systematic, if necessary - the use of instruments. This method also includes the study and generalization of experience.

Experiment- a method of scientific research, with the help of which, in natural or artificially created conditions (controlled and managed), a phenomenon, process is investigated, a new, more effective way to solve a problem is searched. An experiment is a specially organized test of one or another method, the reception of a specialist's work. It involves active intervention in the real system, so its essence is to change the conditions in which the object under study is located, and main function – to test the effectiveness (or ineffectiveness) of this intervention. At the same time, control and management of all experimental factors is carried out systematically, the effects (positive or negative) of changes in the object must be measured using reasonable qualimetric tools and scientifically interpreted. Let us note the leading difference between experiment and observation. During the experiment, the researcher introduces new factors into the process and observes, fixes and describes the consequences of his intervention, and in the course of observation, the researcher only observes, captures and describes what is happening in reality without any intervention. The experimental method is aimed at studying the cause-and-effect relationships between the objects under study. It contains features that are characteristic of theoretical knowledge: highlighting the side of the object (phenomenon) that interests the researcher, and abstracting from its other sides. In the process of cognition, experiment and theory interact: experiment confirms or refutes a theory that is at the stage of hypothesis, provides material for its development.

The dissertation must:

- introduce experiment program (to develop a research methodology and an experiment plan, methods for collecting and processing the results obtained);

- conduct and describe ascertaining experiment (the current state of the object of study is studied, the real state of affairs is established in order to obtain primary material for further understanding and organizing a formative experiment);

- if necessary, carry out trial (pilot) experiment , allowing you to check individual aspects and readiness for the main (forming, transforming) experiment , during which the hypothesis put forward, its introduced conditions and their influence on the object of study, expediency will be tested;

– conduct, describe and evaluate the main experiment, if necessary, conduct and evaluate the delayed experiment.

The results and description of the main experiment, quantitative and qualitative analysis, interpretation of the obtained facts, formulation of conclusions and practical recommendations are an obligatory element of the dissertation.

Statistical Methods or, in other words, methods of statistical data processing of experimental work, are used to process the data obtained by survey and experiment methods, as well as to establish quantitative relationships between the studied phenomena (see Table 1).

If a new subject of the tourism industry is developed in the master's thesis (for example, a new tourism product), then the effectiveness of its implementation is checked using econometric methods(see Table 2).

Table 1 - Table statistical methods summary and processing of the results of the experiment

	Name scale	Ordinal scale	Interval scale
Methods of primary processing of the results of the experiment	· registration · ranking · frequency · mode	· registration · ranking · frequency · mode · median	Registration Ranking Frequency Mode Median Mean Variance Coefficient of variation
Methods for secondary processing of experimental results	association coefficient c² test McNamara test	· Spearman coefficient · Kandel coefficient · c² test · sign test · median test · Wilcoxon-Mann-Whitney test · Kolmogorov-Smirnov test	linear correlation (according to Pearson) c² test Fisher's test Student's test Wilcoxon test

Table 2 - Table of econometric methods for summarizing and processing experimental results

Let us give a brief description of the second group of mathematical methods - econometric ones.

Expert review - method of carrying out an intuitive-logical analysis of the problem. It includes: Delphi methods, heuristic methods, "brainstorming", the method of "collective notebook", the method of synectics.

Detailing -

Detailing - the breakdown of summary indicators into their constituent factors that affect the formation of the overall magnitude of the process or phenomenon. Produced by time, specific gravity, place. In service and tourism, it allows you to establish the influence of seasonality on the level of costs; create a calculation of the cost of production; other

Accounting - this is documentation, inventory, accounting or financial reporting. Allows you to: conduct continuous monitoring of business processes, for example, fix the time of work; compare values, resources, obligations, etc. with credentials; generalize information about the economic activity of the enterprise.

Quantitative-value expression - digitized volume of demand, supply, prospects for the development of a process or phenomenon.

SWOT analysis - abbreviation for the first letters of English words: strength, weakness, opportunities, threats. Allows you to conduct a detailed study of the internal and external environment of the enterprise. Identified with this method signals are the basis for the development and adoption of managerial decisions.

Building predictive scenarios - method of successive removal of uncertainty. It is possible to implement only when using intelligent information systems within the framework of neural network technologies. A scenario should be understood as a hypothetical picture of the sequential development of events in space and time. This is some possible assessment of the development of the system, reflected by the trajectory of parameters, states, conditions of its existence. The methodology for constructing forecasts includes two stages: preparatory and scenario. They include: the development of a hypothesis, a systematic description of the forecasting object, the definition of a "tube" of possible trajectories, the development of matrices "situations-factors", calculations according to basic scenarios, the promotion of development alternatives, the execution of the final document.

Graphical reflection of the dynamics of the process under study(bar or line chart, histogram) is an illustration of the results of the study (the point of intersection of supply and demand curves, etc.).

Causal Analysis - a method of removing uncertainty, identifying a symptom of a problem. To solve a problem, it is necessary to eliminate its cause (axiom). The results of identifying and eliminating causes are displayed on the consequences screen. During the implementation of the method, the concepts of "input" into the problem and "output" from it are used.

Guide control - observation from the beginning of practical activity to its end. It includes: measurement, comparison of actual data, goals, plotting.

Filter control - differs from preliminary, guiding and subsequent. It is implemented if there is a deviation of the observed data from those planned by the plan.

Performance measurement - in other words, the effectiveness of any process, the success of its organizers and performers, profitability. Economic efficiency is the ratio of results to costs. Social - the degree of satisfaction of consumer demand for goods or services. In the socio-cultural sphere, social performance assessment prevails, however, the best way to fully measure the result is to measure social and economic, as well as environmental, legal and ethical performance. You can evaluate the effectiveness of the final results of the process. The means of its description should be quantitative and qualitative indicators. Performance measurement criteria: quantity and quality of goods or services; production culture; activity, initiative, ingenuity of the staff.

Functional cost analysis (FSA) - a method of comprehensive study of the functions of an object at all stages of its life cycle, aimed at assessing the minimum costs. A function is an activity, duty, work, appointment, role, external manifestation of the properties of an object. Cost analysis - cost analysis. FSA: analysis of functions, analysis of costs, analysis of the resource for performing functions. Methodological basis method is a functional approach as part of a system-functional approach. FSA stages: preparatory, informational, analytical, creative, research, advisory, implementation and control of results. The most effective reflection of FSA results is the FAST chart. The FAST technique allows you to answer the questions: what functions are the object of analysis, what is supposed to be done to implement this function, what affects the function, who performs it, etc.

"Tree" of decisions - a schematic representation of a system of solutions hierarchically ordered within the framework of the base coordinate system. The main structural elements are "branches", "nodes". "Branches" are options for decisions, possible consequences of decisions. "Nodes" are places where and when decisions must be made. The method of constructing a coordinate system with logical-temporal or spatial ordering of solutions is used.

It should be noted that there are practically no publications that systematically disclose the means and methods of activity. The material about them is scattered across various sources. Therefore, we decided to consider this issue in sufficient detail and try to build the means and methods of scientific research in a certain system. In addition, the means and most of the methods relate not only to scientific, but also to practical activities, to educational activities, etc.

Means of scientific research (means of knowledge). In the course of the development of science are developed and improved means of knowledge: material, mathematical, logical, linguistic. Besides, in recent times to them, obviously, it is necessary to add information means as a special class. All means of cognition are specially created means. In this sense, material, informational, mathematical, logical, linguistic means of cognition have a common property: they are designed, created, developed, substantiated for certain cognitive purposes.

Material resources knowledge is, first of all, instruments for scientific research. In history, the emergence of material means of cognition is associated with the formation of empirical research methods - observation, measurement, experiment.

These funds are directly aimed at the objects under study, they play the main role in the empirical testing of hypotheses and other results of scientific research, in the discovery of new objects, facts. The use of material means of cognition in science in general - a microscope, a telescope, a synchrophasotron, satellites of the Earth, etc. - has a profound influence on the formation of the conceptual apparatus of the sciences, on the ways of describing the subjects studied, the methods of reasoning and representations, on the generalizations, idealizations and arguments used.

Information tools knowledge. The mass introduction of computer technology, information technology, and telecommunications is fundamentally transforming research activities in many branches of science, making them the means of scientific knowledge. In particular, in recent decades, computer technology has been widely used to automate experiments in physics, biology, technical sciences, etc., which allows hundreds, thousands of times to simplify research procedures and reduce data processing time. In addition, information tools can significantly simplify the processing of statistical data in almost all branches of science. And the use of satellite navigation systems greatly increases the accuracy of measurements in geodesy, cartography, etc.

Mathematical tools knowledge. The development of mathematical means of cognition has an ever greater influence on the development of modern science; they also penetrate into the humanities and social sciences.

Maths, being the science of quantitative relations and spatial forms abstracted from their specific content, has developed and applied specific means of abstracting form from content and formulated the rules for considering form as an independent object in the form of numbers, sets, etc., which simplifies, facilitates and speeds up the process of cognition makes it possible to reveal more deeply the connection between objects from which the form is abstracted, to isolate the initial positions, to ensure the accuracy and rigor of judgments. Mathematical tools make it possible to consider not only directly abstracted quantitative relations and spatial forms, but also logically possible ones, that is, those that are deduced according to logical rules from previously known relations and forms.

Under the influence of mathematical means of cognition, the theoretical apparatus of the descriptive sciences undergoes significant changes. Mathematical tools make it possible to systematize empirical data, to identify and formulate quantitative dependencies and patterns. Mathematical tools are also used as special forms of idealization and analogy (mathematical modeling).

logical means knowledge. In any study, the scientist must decide logical tasks:

- what logical requirements should satisfy the reasoning, allowing to make objectively true conclusions; how to control the nature of these reasoning?

– what logical requirements should satisfy the description of empirically observed characteristics?

- how to build a scientific theory that allows you to give scientific explanations, predictions, etc.?

Language tools knowledge. An important linguistic means of cognition are, among other things, the rules for constructing definitions of concepts (definitions). In any scientific research, the scientist has to clarify the introduced concepts, symbols and signs, to use new concepts and signs. Definitions are always associated with language as a means of cognition and expression of knowledge.

Along with the means of cognition are the methods of scientific cognition (methods of research).

Methods of scientific research. An essential, sometimes decisive role in the construction of any scientific work is played by the applied research methods.

Research methods are divided into empirical(empirical - literally - perceived through the senses) and theoretical(see Table 3).

Regarding research methods, the following circumstance should be noted. In the literature on epistemology, methodology, there is a sort of double division, separation scientific methods in particular, theoretical methods. So, the dialectical method, theory (when it acts as a method - see below), the identification and resolution of contradictions, the construction of hypotheses, etc. It is customary to call them, without explaining why (at least, the authors of such explanations could not be found in the literature), methods of cognition. And such methods as analysis and synthesis, comparison, abstraction and concretization, etc., that is, the main mental operations, are methods of theoretical research.

A similar division takes place with empirical research methods. So, V.I. Zagvyazinsky divides empirical research methods into two groups:

1. Working, private methods. These include: the study of literature, documents and results of activities; observation; interview(oral and written); peer review method; testing.

2. Complex, common methods which are based on the application of one or more private methods: survey; monitoring; study and generalization of experience; experimental work; experiment.

Scientific research methods

THEORETICAL	EMPIRICAL
operation methods	action methods	operation methods	action methods
¨ analysis ¨ synthesis ¨ comparison ¨ abstraction ¨ concretization ¨ generalization ¨ formalization ¨ induction ¨ deduction ¨ idealization ¨ analogy ¨ modeling ¨ thought experiment ¨ imagination	¨ dialectics (as a method) ¨ scientific theories tested by practice ¨ proof ¨ method of knowledge systems analysis ¨ deductive (axiomatic) method ¨ inductive-deductive method ¨ identification and resolution of contradictions ¨ problem setting ¨ hypothesis building	¨ study of literature, documents and results of activities ¨ observation ¨ measurement ¨ survey (oral and written) ¨ peer review ¨ testing	¨ object tracking methods: survey, monitoring, study and generalization of experience ¨ object transformation methods: experimental work, experiment

It is possible to resolve this double division both in relation to theoretical and empirical methods from the standpoint of the structure of activity.

We consider methodology as a doctrine of the organization of activities. Then, if scientific research is a cycle of activity, then its structural units are directed actions. As is known, action- a unit of activity, the distinguishing feature of which is the presence of a specific goal. The structural units of action are operations correlated with the objective-objective conditions for achieving the goal. The same goal, correlated with action, can be achieved in different conditions; an action can be implemented by different operations. However, the same operation can be included in different actions (A.N. Leontiev).

Based on this, we distinguish (see Table 3):

– methods-operations;

– action methods.

This approach does not contradict the definition method, which gives the Encyclopedic Dictionary:

- firstly, a method as a way to achieve a goal, solve a specific problem - a method-action;

- secondly, the method as a set of techniques or operations of practical or theoretical development of reality - a method-operation.

Thus, in the future we will consider research methods in the following grouping:

Theoretical methods:

- methods - cognitive actions: identifying and resolving contradictions, posing a problem, building a hypothesis, etc.;

– methods-operations: analysis, synthesis, comparison, abstraction and concretization, etc.

Empirical methods:

- methods - cognitive actions: examination, monitoring, experiment, etc.;

– methods-operations: observation, measurement, questioning, testing, etc.

Theoretical methods (methods-operations). Theoretical methods-operations have a wide field of application, both in scientific research and in practice.

Theoretical methods - operations are determined (considered) according to the main mental operations, which are: analysis and synthesis, comparison, abstraction and concretization, generalization, formalization, induction and deduction, idealization, analogy, modeling, thought experiment.

Analysis- this is the decomposition of the whole under study into parts, the allocation of individual features and qualities of a phenomenon, process or relations of phenomena, processes. Analysis procedures are an integral part of any scientific research and usually form its first phase, when the researcher moves from an undivided description of the object under study to the identification of its structure, composition, properties and features.

One and the same phenomenon, process can be analyzed in many aspects. A comprehensive analysis of the phenomenon allows you to consider it deeper.

Synthesis- the connection of various elements, sides of the subject into a single whole (system). Synthesis is not a simple summation, but a semantic connection. If we simply connect phenomena, no system of connections will arise between them, only a chaotic accumulation of individual facts is formed. Synthesis is opposed to analysis, with which it is inextricably linked. Synthesis as a cognitive operation appears in various functions of theoretical research. Any process of formation of concepts is based on the unity of the processes of analysis and synthesis. Empirical data obtained in a particular study are synthesized during their theoretical generalization. In theoretical scientific knowledge, synthesis acts as a function of the relationship of theories related to the same subject area, as well as a function of combining competing theories (for example, the synthesis of corpuscular and wave representations in physics).

Synthesis also plays an important role in empirical research.

Analysis and synthesis are closely related. If the researcher has a more developed ability to analyze, there may be a danger that he will not be able to find a place for details in the phenomenon as a whole. The relative predominance of synthesis leads to superficiality, to the fact that details essential for the study, which may have great importance to understand the phenomenon as a whole.

Comparison is a cognitive operation that underlies judgments about the similarity or difference of objects. With the help of comparison, quantitative and qualitative characteristics of objects are revealed, their classification, ordering and evaluation are carried out. Comparison is comparing one thing with another. In this case, an important role is played by the bases, or signs of comparison, which determine the possible relationships between objects.

Comparison makes sense only in a set of homogeneous objects that form a class. Comparison of objects in a particular class is carried out according to the principles essential for this consideration. At the same time, objects that are comparable in one feature may not be comparable in other features. The more accurately the signs are estimated, the more thoroughly the comparison of phenomena is possible. Analysis is always an integral part of comparison, since for any comparison in phenomena, it is necessary to isolate the corresponding signs of comparison. Since comparison is the establishment of certain relationships between phenomena, then, naturally, synthesis is also used in the course of comparison.

abstraction- one of the main mental operations that allows you to mentally isolate and turn into an independent object of consideration certain aspects, properties or states of the object in its pure form. Abstraction underlies the processes of generalization and concept formation.

Abstraction consists in isolating such properties of an object that do not exist by themselves and independently of it. Such isolation is possible only in the mental plane - in abstraction. So, geometric figure the body itself does not really exist and cannot be separated from the body. But thanks to abstraction, it is mentally singled out, fixed, for example, with the help of a drawing, and independently considered in its special properties.

One of the main functions of abstraction is to highlight the common properties of a certain set of objects and fix these properties, for example, through concepts.

Specification- a process opposite to abstraction, that is, finding a holistic, interconnected, multilateral and complex. The researcher initially forms various abstractions, and then, on their basis, through concretization, reproduces this integrity (mental concrete), but at a qualitatively different level of cognition of the concrete. That's why dialectics distinguishes in the process of cognition in the coordinates "abstraction - concretization" two processes of ascent: ascent from the concrete to the abstract and then the process of ascent from the abstract to the new concrete (G. Hegel). The dialectic of theoretical thinking consists in the unity of abstraction, the creation of various abstractions and concretization, the movement towards the concrete and its reproduction.

Generalization- one of the main cognitive mental operations, consisting in the selection and fixation of relatively stable, invariant properties of objects and their relationships. Generalization allows you to display the properties and relationships of objects, regardless of the particular and random conditions of their observation. Comparing objects of a certain group from a certain point of view, a person finds, singles out and designates with a word their identical, common properties, which can become the content of the concept of this group, class of objects. Separating general properties from private ones and designating them with a word makes it possible to cover the entire variety of objects in an abbreviated, concise form, reduce them to certain classes, and then, through abstractions, operate with concepts without directly referring to individual objects. One and the same real object can be included in both narrow and wide classes, for which the scales of common features are built according to the principle of genus-species relations. The function of generalization consists in ordering the variety of objects, their classification.

Formalization- displaying the results of thinking in precise terms or statements. It is, as it were, a mental operation of the “second order”. Formalization is opposed to intuitive thinking. In mathematics and formal logic, formalization is understood as the display of meaningful knowledge in a symbolic form or in formalized language. Formalization, that is, the abstraction of concepts from their content, ensures the systematization of knowledge, in which its individual elements coordinate with each other. Formalization plays an essential role in the development of scientific knowledge, since intuitive concepts, although they seem clearer from the point of view of ordinary consciousness, are of little use for science: in scientific knowledge it is often impossible not only to solve, but even to formulate and pose problems until the structure of the concepts related to them will be clarified. True science is possible only on the basis of abstract thinking, consistent reasoning of the researcher, flowing in a logical language form through concepts, judgments and conclusions.

In scientific judgments, links are established between objects, phenomena or between their specific features. In scientific conclusions, one judgment proceeds from another; on the basis of already existing conclusions, a new one is made. There are two main types of inference: inductive (induction) and deductive (deduction).

Induction- this is a conclusion from particular objects, phenomena to a general conclusion, from individual facts to generalizations.

Deduction- this is a conclusion from the general to the particular, from general judgments to particular conclusions.

Idealization- mental construction of ideas about objects that do not exist or are not feasible in reality, but those for which there are prototypes in the real world. The process of idealization is characterized by abstraction from the properties and relations inherent in the objects of reality and the introduction into the content of the formed concepts of such features that, in principle, cannot belong to their real prototypes. Examples of concepts that are the result of idealization can be the mathematical concepts of "point", "line"; in physics - "material point", "absolutely black body", "ideal gas", etc.

Concepts that are the result of idealization are said to be thought of as idealized (or ideal) objects. Having formed concepts of this kind about objects with the help of idealization, one can subsequently operate with them in reasoning as with really existing objects and build abstract schemes of real processes that serve for a deeper understanding of them. In this sense, idealization is closely related to modeling.

Analogy,modeling. Analogy is a mental operation when the knowledge obtained from the consideration of any one object (model) is transferred to another, less studied or less accessible for study, less visual object, called the prototype, the original. It opens up the possibility of transferring information by analogy from model to prototype. This is the essence of one of the special methods of the theoretical level - modeling (building and researching models). The difference between analogy and modeling lies in the fact that if analogy is one of the mental operations, then modeling can be considered in different cases both as a mental operation and as an independent method - a method-action.

Model- an auxiliary object, selected or transformed for cognitive purposes, giving new information about the main object. Modeling forms are diverse and depend on the models used and their scope. By the nature of the models, subject and sign (information) modeling are distinguished.

Object Modeling conducted on a model that reproduces certain geometric, physical, dynamic, or functional characteristics of the object of modeling - the original; in a particular case - analog modeling, when the behavior of the original and the model is described by common mathematical relationships, for example, by common differential equations. At iconic modeling models are diagrams, drawings, formulas, etc. The most important type of such modeling is math modeling(see more details below).

Simulation is always used together with other research methods, it is especially closely related to the experiment. The study of any phenomenon on its model is a special kind of experiment - model experiment, which differs from the usual experiment in that in the process of cognition an “intermediate link” is included - a model that is both a means and an object of experimental research that replaces the original.

A special kind of modeling is thought experiment. In such an experiment, the researcher mentally creates ideal objects, correlates them with each other within the framework of a certain dynamic model, mentally imitating the movement and those situations that could take place in a real experiment. At the same time, ideal models and objects help to identify “in pure form” the most important, essential connections and relationships, to mentally play out possible situations, to weed out unnecessary options.

Modeling also serves as a way of constructing a new one that did not exist earlier in practice. Researcher studying character traits real processes and their tendencies, searches for their new combinations on the basis of the leading idea, makes their mental redesign, that is, models the required state of the system under study (just like any person and even an animal, builds its activity, activity on the basis of the initially formed “model of the required future "- according to N.A. Bernshtein). At the same time, models-hypotheses are created that reveal the mechanisms of communication between the components of the studied, which are then tested in practice. In this understanding, modeling has recently become widespread in the social and human sciences - in economics, pedagogy, etc., when different authors offer different models of firms, industries, educational systems, etc.

Along with the operations of logical thinking, theoretical methods-operations can also include (possibly conditionally) imagination as a thought process to create new ideas and images with its specific forms of fantasy (creation of implausible, paradoxical images and concepts) and dreams(as the creation of images of the desired).

Theoretical methods (methods - cognitive actions). general philosophical, general scientific method knowledge is dialectics- the real logic of meaningful creative thinking, reflecting the objective dialectic of reality itself. The basis of dialectics as a method of scientific knowledge is the ascent from the abstract to the concrete (G. Hegel) - from general and content-poor forms to dissected and richer content, to a system of concepts that allow one to comprehend an object in its essential characteristics. In dialectics, all problems acquire a historical character, the study of the development of an object is a strategic platform for cognition. Finally, dialectics is oriented in cognition to the disclosure and methods of resolving contradictions.

Laws of dialectics: the transition of quantitative changes into qualitative ones, the unity and struggle of opposites, etc.; analysis of paired dialectical categories: historical and logical, phenomenon and essence, general (universal) and singular, etc. are integral components of any well-structured scientific research.

scientific theories,proven by practice: any such theory, in essence, acts as a method in the construction of new theories in this or even other areas of scientific knowledge, as well as in the function of a method that determines the content and sequence of the researcher's experimental activity. Therefore, the difference between scientific theory as a form of scientific knowledge and as a method of cognition in this case is functional: being formed as a theoretical result of past research, the method acts as a starting point and condition for subsequent research.

Proof- method - a theoretical (logical) action, during which the truth of a thought is substantiated with the help of other thoughts. Any proof consists of three parts: the thesis, arguments (arguments) and demonstration. According to the method of conducting evidence, there are direct and indirect, according to the form of inference - inductive and deductive. Evidence Rules:

1. The thesis and arguments must be clear and precise.

2. The thesis must remain identical throughout the proof.

3. The thesis should not contain a logical contradiction.

4. The arguments given in support of the thesis must themselves be true, not subject to doubt, must not contradict each other and be a sufficient basis for this thesis.

5. The proof must be complete.

In the totality of methods of scientific knowledge, an important place belongs to knowledge systems analysis method(see, for example,). Any scientific knowledge system has a certain independence in relation to the reflected subject area. In addition, knowledge in such systems is expressed using a language whose properties affect the attitude of knowledge systems to the objects being studied - for example, if any sufficiently developed psychological, sociological, pedagogical concept is translated into, say, English, German, French - Will it be unequivocally perceived and understood in England, Germany and France? Further, the use of language as a carrier of concepts in such systems presupposes one or another logical systematization and logically organized use of linguistic units to express knowledge. And, finally, no system of knowledge exhausts the entire content of the object under study. In it, only a certain, historically concrete part of such content always receives a description and explanation.

The method of analysis of scientific knowledge systems plays an important role in empirical and theoretical research tasks: when choosing an initial theory, a hypothesis for solving a chosen problem; when distinguishing between empirical and theoretical knowledge, semi-empirical and theoretical solutions to a scientific problem; when substantiating the equivalence or priority of the use of certain mathematical tools in various theories related to the same subject area; when studying the possibilities of disseminating previously formulated theories, concepts, principles, etc. to new subject areas; substantiation of new possibilities for the practical application of knowledge systems; when simplifying and clarifying knowledge systems for training, popularization; to harmonize with other knowledge systems, etc.

– deductive method(synonym - axiomatic method) - a method of constructing a scientific theory, in which it is based on some initial provisions axioms(synonym - postulates), of which all other provisions of this theory ( theorems) are deduced in a purely logical way by means of a proof. The construction of a theory based on the axiomatic method is usually called deductive. All concepts of the deductive theory, except for a fixed number of initial ones (such initial concepts in geometry, for example, are: point, line, plane) are introduced by means of definitions expressing them through previously introduced or derived concepts. The classic example of a deductive theory is the geometry of Euclid. Theories are built by the deductive method in mathematics, mathematical logic, theoretical physics;

- the second method has not received a name in the literature, but it certainly exists, since in all other sciences, except for the above, theories are built according to the method, which we will call inductive-deductive: first, an empirical basis is accumulated, on the basis of which theoretical generalizations (induction) are built, which can be built into several levels - for example, empirical laws and theoretical laws - and then these generalizations obtained can be extended to all objects and phenomena covered by this theory (deduction ) – see Fig. 6 and Fig. 10. The inductive-deductive method is used to construct most of the theories in the sciences of nature, society and man: physics, chemistry, biology, geology, geography, psychology, pedagogy, etc.

Other theoretical research methods (in the sense of methods - cognitive actions): identifying and resolving contradictions, posing a problem, building hypotheses, etc. up to the planning of scientific research, we will consider below in the specifics of the time structure of research activity - the construction of phases, stages and stages of scientific research.

Empirical methods (methods-operations).

Literature study,documents and results of activities. The issues of working with scientific literature will be considered separately below, since this is not only a research method, but also an obligatory procedural component of any scientific work.

A variety of documentation also serves as a source of factual material for research: archival materials in historical research; documentation of enterprises, organizations and institutions in economic, sociological, pedagogical and other studies, etc. Performance learning plays an important role in pedagogy, especially when studying the problems of professional training of pupils and students; in psychology, pedagogy and sociology of labor; and, for example, in archeology, during excavations, an analysis of the results of people's activities: according to the remains of tools, utensils, dwellings, etc. allows you to restore their way of life in a particular era.

Observation- in principle, the most informative method of research. This is the only method that allows you to see all aspects of the phenomena and processes under study, accessible to the perception of the observer - both directly and with the help of various instruments.

Depending on the goals that are pursued in the process of observation, the latter can be scientific and non-scientific. Purposeful and organized perception of objects and phenomena of the external world, associated with the solution of a certain scientific problem or task, is commonly called scientific observation. Scientific observations involve obtaining certain information for further theoretical understanding and interpretation, for the approval or refutation of a hypothesis, etc.

Scientific observation consists of the following procedures:

Definition of the purpose of observation (for what, for what purpose?);

Choice of object, process, situation (what to observe?);

Choice of method and frequency of observations (how to observe?);

The choice of methods for registering the observed object, phenomenon (how to record the information received?);

Processing and interpretation of the information received (what is the result?) - see, for example,.

Observed situations are divided into:

natural and artificial;

Controlled and not controlled by the subject of observation;

Spontaneous and organized;

Standard and non-standard;

Normal and extreme, etc.

In addition, depending on the organization of observation, it can be open and hidden, field and laboratory, and depending on the nature of fixation, it can be ascertaining, evaluating and mixed. According to the method of obtaining information, observations are divided into direct and instrumental. According to the scope of the studied objects, continuous and selective observations are distinguished; by frequency - constant, periodic and single. A special case of observation is self-observation, which is widely used, for example, in psychology.

Observation is necessary for scientific knowledge, since without it science would not be able to obtain initial information, would not have scientific facts and empirical data, therefore, the theoretical construction of knowledge would also be impossible.

However, observation as a method of cognition has a number of significant drawbacks. The personal characteristics of the researcher, his interests, and finally, his psychological state can significantly affect the results of observation. The objective results of observation are even more subject to distortion in those cases when the researcher is focused on obtaining a certain result, on confirming his existing hypothesis.

To obtain objective results of observation, it is necessary to comply with the requirements intersubjectivity, that is, the observational data should (and/or can) be obtained and recorded, if possible, by other observers.

Replacing direct observation with instruments indefinitely expands the possibilities of observation, but also does not exclude subjectivity; evaluation and interpretation of such indirect observation is carried out by the subject, and therefore the subjective influence of the researcher can still take place.

Observation is most often accompanied by another empirical method - measurement

Measurement. Measurement is used everywhere, in any human activity. So, almost every person during the day takes measurements dozens of times, looking at the clock. General definition measurement is: “Measurement is cognitive process, which consists in comparing ... a given quantity with some of its value, taken as a comparison standard ”(see, for example,).

In particular, measurement is an empirical method (method-operation) of scientific research.

You can select a specific dimension structure that includes the following elements:

1) knowing subject, carrying out the measurement with certain cognitive goals;

2) measuring, among which there can be both devices and tools designed by man, and objects and processes given by nature;

3) measurement object, that is, measured magnitude or property to which the comparison procedure is applicable;

4) adapted measurement method, which is a set of practical actions, operations performed using measuring instruments, and also includes certain logical and computational procedures;

5) measurement result, which is a named number expressed using the corresponding names or signs.

The epistemological substantiation of the measurement method is inextricably linked with scientific understanding ratio of qualitative and quantitative characteristics of the studied object (phenomenon). Although only quantitative characteristics are recorded using this method, these characteristics are inextricably linked with

Scientific knowledge is impossible without a certain conscious and unconscious use of the historically established means of cognition. In our time, when science is becoming a direct productive force, and the scientific and technological revolution is gaining wider scope, the study and development of these means is urgent task epistemology and philosophy of science. The means of scientific knowledge are the language of science, special scientific equipment(devices) and methods through which science discovers and studies its objects.

For the purposes of science, to describe the objects it studies, ordinary, natural language turns out to be inadequate. As is known, ordinary language, having such advantages as universality, expressiveness, high combinatoriality, etc., is not free at the same time from a number of features that prevent its canonical use. These include the ambiguity of words and expressions, the bulkiness and immensity of some turns, the fuzziness of syntactic and semantic rules, the diversity and uncertainty of pragmatics. The language of science, on the other hand, is constructed in such a way as to overcome or minimize some of the above features of natural language.

The language of science can be divided into specialized languages and special formalized languages. Specialized languages the sciences achieve precision (i.e., unambiguity and quantitative certainty) through scientific definitions and the application of mathematics. So, the dictionary of any science (specialized language), including its main terms, can be divided into two unequal parts. The first is a small number of so-called basic "words", with the help of which all other, derived terms are defined. The latter are almost completely unambiguous. For example, in the dictionary of classical kinematics, "path", denoted by the symbol s, and "time" - t, are taken as initial undefined terms. They are enough to build the rest of the terms ("speed", "acceleration", etc.). At the same time, in connection with the requirement of compactness, visibility and elegance of the language of science, newly introduced derivative terms, whenever possible, are defined not through the original, but through the nearest derivative terms (for example, “acceleration” is defined through “speed”, and not through “way " and time"). The terms “equals”, “add”, “divide”, etc., which are widely used in kinematics, physics in general and other sciences, are defined in the dictionary of mathematics and play a kind of auxiliary role in the definitions and statements of special sciences.

The language of mathematics differs from the natural one in that the transition from one expression to another is carried out according to some pre-established and strictly defined rules. Moreover, mathematics (especially its variables) allows you to abstract (abstract) from the subject content of your linguistic expressions and focus on operations, connections and relations of expressions used in mathematics. Mathematics has formal rules for transforming some mathematical expressions to others, but the connections and relationships of mathematical expressions ultimately reflect the connections and relationships of objects and phenomena of objective reality. In terms of language, the transformation of mathematical expressions is based on a general semiotic phenomenon - synonymy, and in the transitivity (transitivity) of mathematical expressions, the continuity of thinking and the continuity of meaning (meaning) are manifested.

In its abstractness and formality of the rules for constructing and transforming expressions formalized languages go beyond mathematics. These specially created artificial languages differ from natural ones not only in the special character of their signs, but also in a very special syntax. When constructing a formalized language, its dictionary, or alphabet, containing characters of a certain kind, is first precisely established. Then the rules for constructing sentences from alphabetic characters that are considered meaningful or correct in the given language are indicated. And, finally, the transformation rules are formulated and listed, allowing one to derive others from some correct sentences. In such a fully formalized language there is no place for linguistic intuition, no obscure, implied rules.

The advantage of formal sign systems is the possibility of carrying out within their framework the study of cognizable objects in a purely formal way (operating with signs) without direct appeal to real objects. However, it should be taken into account that formalized sign systems represent (represent) certain provisions of the theory. Consequently, in the final analysis, such systems (formalisms) do not completely lose their connection with reality, with empiricism. Formalisms must have an empirical interpretation, and not necessarily the only one. The latter circumstance testifies to the heuristic possibilities of formalized systems. And the construction and use of such systems in cognition are called formalization method. It was with the help of the formalization method, with the help of Maxwell's mathematical equations, that such a kind of matter as a field was theoretically discovered (we have already mentioned this).

Modern science, especially natural science, is inconceivable without such material means of cognition as appliances, with the help of which decisive facts are obtained and the truth of scientific theories is proved. Devices enhance the cognitive power of the senses, allow a person to go far beyond his natural capabilities. With the help of instruments, a person began to penetrate into such areas of the world that are inaccessible without them. First of all, it is a micro- and mega-world. So, with the help of automatic interplanetary stations "Mars", "Mariner" and "Phoenix", scientists over the past few decades have learned more about Mars than in the entire previous history of civilization.

With the complication of the cognitive process, scientific instruments become more complex. This is natural and natural. However, it is important that in connection with this, the role of the device in cognition changes significantly, and this, in turn, creates certain epistemological difficulties. Previously, devices did not have a significant effect on either the subject or the object. They were to a certain extent external to the cognitive process. This can be represented by such a scheme (Fig. 6), where
S - subject, O - object, P - device:

At present, devices have become true intermediaries between the subject and the object. They are included in the structure of the cognitive process, influencing the subject and object of knowledge. Accordingly, the scheme (Fig. 7) will look like this:

In connection with the essential role of the device in cognition, the problem arises objectivity of knowledge obtained with the instrument. In cases where the effect of the device on the object cannot be neglected, a theory of the interaction between the device and the object is developed. And by calculating the appropriate corrections, they mentally restore the object in the form in which it was before turning on the device. Unfortunately, at present this is feasible only with respect to macroscopic objects. For microscopic objects (elementary particles, individual atoms, etc.), due to the statistical nature of the relationship between theory and experimental data, it is not yet possible to take into account the individual effects of the device on the object. Absolutizing this difficulty, some natural scientists (including such well-known ones as W. Heisenberg and N. Bohr) began to lean towards a special kind of “physical” idealism in interpreting the role of the device in cognition: to “selective” (in the terminology of Eddington), or “ instrumental idealism. Some opponents of materialism even declared the "fundamental uncontrollability" of the impact of the device on micro-objects and that nature (the outside world) is fabricated with the help of the device. In other words, the microworld is created by the will of the observer either as a collection of particles or as a set of waves. It is possible to overcome this form of idealism and obtain a correct philosophical solution to the problem of the relationship between the instrument and the object only on the basis of firstly, to recognize the objectivity and inexhaustibility of the object of study, and, Secondly, on a deep and comprehensive account of the functions of the device in the experiment.

Devices can indeed create an environment for generating object properties that appear only when it interacts with the device. These are the so-called dispositional properties. Academician V.A. Fock notes that the electron contains the properties of being a particle or a wave not in reality (actually), but only in the possibility. Depending on what type of device is chosen for observation, either one or the other possibility is realized. But these possibilities are objective. They are defined nature, the structural organization of the object. Strictly speaking, there is no sour, sweet, etc. in nature, but there are substances with a certain structural organization, which, when interacting with certain human sense organs, give rise to these properties. It is also undoubted that as our understanding of micro-objects deepens and our technical capabilities expand, more “sensitive” devices will be built, capable of recording the possible properties of objects. And, of course, deeper and more comprehensive theories will be created that take into account specific acts of interaction between the device and the object.

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Samsonov, V.F
From 17 Philosophy: textbook. allowance for universities / V.F. Samsonov. - Chelyabinsk: Chelyab Publishing House. state ped. un-ta, 2010. - 498 p. ISBN 978-5-85716-821-9

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Means and methods are the most important components of the logical structure of the organization of activities. Therefore, they constitute a major section of methodology as a doctrine of the organization of activities.
It should be noted that there are practically no publications that systematically disclose the means and methods of activity. The material about them is scattered across various sources. Therefore, we decided to consider this issue in sufficient detail and try to build the means and methods of scientific research in a certain system. In addition, the means and most of the methods relate not only to scientific, but also to practical activities, to educational activities, etc.
Means of scientific research (means of knowledge). In the course of the development of science, means of cognition are developed and improved: material, mathematical, logical, linguistic. In addition, in recent times, it is obviously necessary to add information tools to them as a special class. All means of cognition are specially created means. In this sense, material, informational, mathematical, logical, linguistic means of cognition have a common property: they are designed, created, developed, substantiated for certain cognitive purposes.
Material means of cognition are, first of all, instruments for scientific research. In history, the emergence of material means of cognition is associated with the formation of empirical methods of research - observation, measurement, experiment.
These funds are directly aimed at the objects under study, they play the main role in the empirical testing of hypotheses and other results of scientific research, in the discovery of new objects, facts. The use of material means of cognition in science in general - a microscope, a telescope, a synchrophasotron, satellites of the Earth, etc. - has a profound influence on the formation of the conceptual apparatus of sciences, on the ways of describing the subjects studied, the methods of reasoning and ideas, on the generalizations, idealizations and arguments used.
Information means of knowledge. The mass introduction of computer technology, information technology, and telecommunications is fundamentally transforming research activities in many branches of science, making them the means of scientific knowledge. In particular, in recent decades, computer technology has been widely used to automate experiments in physics, biology, technical sciences, etc., which allows hundreds, thousands of times to simplify research procedures and reduce data processing time. In addition, information tools can significantly simplify the processing of statistical data in almost all branches of science. And the use of satellite navigation systems greatly increases the accuracy of measurements in geodesy, cartography, etc.
Mathematical means of knowledge. The development of mathematical means of cognition has an ever greater influence on the development of modern science; they also penetrate into the humanities and social sciences.
Mathematics, being the science of quantitative relations and spatial forms abstracted from their specific content, has developed and applied specific means of abstracting form from content and formulated the rules for considering form as an independent object in the form of numbers, sets, etc., which simplifies, facilitates and accelerates the process of cognition, allows you to more deeply reveal the connection between objects from which the form is abstracted, to isolate the initial positions, to ensure the accuracy and rigor of judgments. Mathematical tools make it possible to consider not only directly abstracted quantitative relations and spatial forms, but also logically possible ones, that is, those that are deduced according to logical rules from previously known relations and forms.
Under the influence of mathematical means of cognition, the theoretical apparatus of the descriptive sciences undergoes significant changes. Mathematical tools make it possible to systematize empirical data, to identify and formulate quantitative dependencies and patterns. Mathematical tools are also used as special forms of idealization and analogy (mathematical modeling).
Logical means of knowledge. In any study, the scientist has to solve logical problems:
- what logical requirements must satisfy the reasoning, allowing to make objectively true conclusions; how to control the nature of these reasoning?
- what logical requirements should satisfy the description of empirically observed characteristics?
- how to logically analyze the original systems of scientific knowledge, how to coordinate some knowledge systems with other knowledge systems (for example, in sociology and closely related psychology)?
- how to build a scientific theory that allows you to give scientific explanations, predictions, etc.?
The use of logical means in the process of constructing reasoning and evidence allows the researcher to separate controlled arguments from intuitive or uncritically accepted, false from true, confusion from contradictions.
Language means of knowledge. An important linguistic means of cognition are, among other things, the rules for constructing definitions of concepts (definitions). In any scientific research, the scientist has to clarify the introduced concepts, symbols and signs, to use new concepts and signs. Definitions are always associated with language as a means of cognition and expression of knowledge.
The rules for using languages, both natural and artificial, with the help of which the researcher builds his reasoning and evidence, formulates hypotheses, draws conclusions, etc., are the starting point for cognitive actions. Knowledge of them has a great influence on the effectiveness of the use of linguistic means of cognition in scientific research.
Along with the means of cognition are the methods of scientific cognition (methods of research).
Methods of scientific research. An essential, sometimes decisive role in the construction of any scientific work is played by the applied research methods.
Research methods are divided into empirical (empirical - literally - perceived through the senses) and theoretical (see Table. 3).
Regarding research methods, the following circumstance should be noted. In the literature on epistemology and methodology, there is a kind of double division, a division of scientific methods, in particular, theoretical methods, everywhere. Thus, the dialectical method, theory (when it acts as a method - see below), the identification and resolution of contradictions, the construction of hypotheses, etc. It is customary to call them, without explaining why (at least, the authors of such explanations could not be found in the literature), methods of cognition. And such methods as analysis and synthesis, comparison, abstraction and concretization, etc., that is, the main mental operations, are methods of theoretical research.
A similar division takes place with empirical research methods. So, V.I. Zagvyazinsky divides empirical research methods into two groups:
1. Working, private methods. These include: the study of literature, documents and results of activities; observation; survey (oral and written); method of expert assessments; testing.
2. Complex, general methods, which are based on the use of one or more private methods: survey; monitoring; study and generalization of experience; experimental work; experiment.

However, the name of these groups of methods is probably not entirely successful, since it is difficult to answer the question: "private" - in relation to what? Similarly, "general" - in relation to what? The distinction, most likely, goes on a different basis.
It is possible to resolve this double division both in relation to theoretical and empirical methods from the standpoint of the structure of activity.
We consider methodology as a doctrine of the organization of activities. Then, if scientific research is a cycle of activity, then its structural units are directed actions. As you know, an action is a unit of activity, the distinguishing feature of which is the presence of a specific goal. The structural units of action are operations correlated with the objective-objective conditions for achieving the goal. The same goal, correlated with action, can be achieved in different conditions; an action can be implemented by different operations. At the same time, the same operation can be included in different actions (A.N. Leontiev).
Based on this, we distinguish (see Table 3):
- methods-operations;
- action methods.
This approach does not contradict the definition of the method, which gives the Encyclopedic Dictionary:
- firstly, a method as a way to achieve a goal, solve a specific problem - a method-action;
- secondly, the method as a set of techniques or operations of practical or theoretical mastering of reality is a method-operation.
Thus, in the future we will consider research methods in the following grouping:
Theoretical methods:
- methods - cognitive actions: identifying and resolving contradictions, posing a problem, building a hypothesis, etc.;
- methods-operations: analysis, synthesis, comparison, abstraction and concretization, etc.
Empirical methods:
- methods - cognitive actions: examination, monitoring, experiment, etc.;
- methods-operations: observation, measurement, questioning, testing, etc.
Theoretical methods (methods-operations). Theoretical methods-operations have a wide field of application, both in scientific research and in practice.
Theoretical methods - operations are defined (considered) according to the main mental operations, which are: analysis and synthesis, comparison, abstraction and concretization, generalization, formalization, induction and deduction, idealization, analogy, modeling, thought experiment.
Analysis is the decomposition of the whole under study into parts, the selection of individual features and qualities of a phenomenon, process or relations of phenomena, processes. Analysis procedures are an integral part of any scientific research and usually form its first phase, when the researcher moves from an undivided description of the object under study to the identification of its structure, composition, properties and features.
One and the same phenomenon, process can be analyzed in many aspects. A comprehensive analysis of the phenomenon allows you to consider it deeper.
Synthesis is the combination of various elements, aspects of an object into a single whole (system). Synthesis is not a simple summation, but a semantic connection. If we simply connect phenomena, no system of connections will arise between them, only a chaotic accumulation of individual facts is formed. Synthesis is opposed to analysis, with which it is inextricably linked. Synthesis as a cognitive operation appears in various functions of theoretical research. Any process of formation of concepts is based on the unity of the processes of analysis and synthesis. Empirical data obtained in a particular study are synthesized during their theoretical generalization. In theoretical scientific knowledge, synthesis acts as a function of the relationship of theories related to the same subject area, as well as a function of combining competing theories (for example, the synthesis of corpuscular and wave representations in physics).
Synthesis also plays an important role in empirical research.
Analysis and synthesis are closely related. If the researcher has a more developed ability to analyze, there may be a danger that he will not be able to find a place for details in the phenomenon as a whole. The relative predominance of synthesis leads to superficiality, to the fact that details essential for the study, which can be of great importance for understanding the phenomenon as a whole, will not be noticed.
Comparison is a cognitive operation that underlies judgments about the similarity or difference of objects. With the help of comparison, quantitative and qualitative characteristics of objects are revealed, their classification, ordering and evaluation are carried out. A comparison is a comparison of one with another. In this case, an important role is played by the bases, or signs of comparison, which determine the possible relationships between objects.
Comparison makes sense only in a set of homogeneous objects that form a class. Comparison of objects in a particular class is carried out according to the principles essential for this consideration. At the same time, objects that are comparable in one feature may not be comparable in other features. The more accurately the signs are estimated, the more thoroughly the comparison of phenomena is possible. Analysis is always an integral part of comparison, since for any comparison in phenomena, it is necessary to isolate the corresponding signs of comparison. Since comparison is the establishment of certain relationships between phenomena, then, naturally, synthesis is also used in the course of comparison.
Abstraction is one of the main mental operations that allows you to mentally isolate and turn individual aspects, properties or states of an object in its pure form into an independent object of consideration. Abstraction underlies the processes of generalization and concept formation.
Abstraction consists in isolating such properties of an object that do not exist by themselves and independently of it. Such isolation is possible only in the mental plane - in abstraction. Thus, the geometric figure of the body does not really exist by itself and cannot be separated from the body. But thanks to abstraction, it is mentally singled out, fixed, for example, with the help of a drawing, and independently considered in its special properties.
One of the main functions of abstraction is to highlight the common properties of a certain set of objects and fix these properties, for example, through concepts.
Concretization is a process opposite to abstraction, that is, finding a holistic, interconnected, multilateral and complex. The researcher initially forms various abstractions, and then, on their basis, through concretization, reproduces this integrity (mental concrete), but at a qualitatively different level of cognition of the concrete. Therefore, dialectics distinguishes in the process of cognition in the coordinates "abstraction - concretization" two processes of ascent: ascent from the concrete to the abstract and then the process of ascent from the abstract to the new concrete (G. Hegel). The dialectic of theoretical thinking consists in the unity of abstraction, the creation of various abstractions and concretization, the movement towards the concrete and its reproduction.
Generalization is one of the main cognitive mental operations, consisting in the selection and fixation of relatively stable, invariant properties of objects and their relationships. Generalization allows you to display the properties and relationships of objects, regardless of the particular and random conditions of their observation. Comparing objects of a certain group from a certain point of view, a person finds, singles out and designates with a word their identical, common properties, which can become the content of the concept of this group, class of objects. Separating general properties from private ones and designating them with a word makes it possible to cover the entire variety of objects in an abbreviated, concise form, reduce them to certain classes, and then, through abstractions, operate with concepts without directly referring to individual objects. One and the same real object can be included in both narrow and wide classes, for which the scales of common features are built according to the principle of genus-species relations. The function of generalization consists in ordering the variety of objects, their classification.
Formalization - displaying the results of thinking in precise terms or statements. It is, as it were, a mental operation of the “second order”. Formalization is opposed to intuitive thinking. In mathematics and formal logic, formalization is understood as the display of meaningful knowledge in a sign form or in a formalized language. Formalization, that is, the abstraction of concepts from their content, ensures the systematization of knowledge, in which its individual elements coordinate with each other. Formalization plays an essential role in the development of scientific knowledge, since intuitive concepts, although they seem clearer from the point of view of ordinary consciousness, are of little use for science: in scientific knowledge it is often impossible not only to solve, but even to formulate and pose problems until the structure of the concepts related to them will be clarified. True science is possible only on the basis of abstract thinking, consistent reasoning of the researcher, flowing in a logical language form through concepts, judgments and conclusions.
In scientific judgments, links are established between objects, phenomena or between their specific features. In scientific conclusions, one judgment proceeds from another; on the basis of already existing conclusions, a new one is made. There are two main types of inference: inductive (induction) and deductive (deduction).
Induction is a conclusion from particular objects, phenomena to a general conclusion, from individual facts to generalizations.
Deduction is a conclusion from the general to the particular, from general judgments to particular conclusions.
Idealization is the mental construction of ideas about objects that do not exist or are not feasible in reality, but those for which there are prototypes in the real world. The process of idealization is characterized by abstraction from the properties and relations inherent in the objects of reality and the introduction into the content of the formed concepts of such features that, in principle, cannot belong to their real prototypes. Examples of concepts that are the result of idealization can be the mathematical concepts of "point", "line"; in physics - "material point", "absolutely black body", "ideal gas", etc.
Concepts that are the result of idealization are said to be thought of as idealized (or ideal) objects. Having formed concepts of this kind about objects with the help of idealization, one can subsequently operate with them in reasoning as with really existing objects and build abstract schemes of real processes that serve for a deeper understanding of them. In this sense, idealization is closely related to modeling.
Analogy, modeling. Analogy is a mental operation when the knowledge obtained from the consideration of any one object (model) is transferred to another, less studied or less accessible for study, less visual object, called the prototype, the original. It opens up the possibility of transferring information by analogy from model to prototype. This is the essence of one of the special methods of the theoretical level - modeling (building and researching models). The difference between analogy and modeling lies in the fact that if analogy is one of the mental operations, then modeling can be considered in different cases both as a mental operation and as an independent method - a method-action.
Model - an auxiliary object, selected or transformed for cognitive purposes, giving new information about the main object. Modeling forms are diverse and depend on the models used and their scope. By the nature of the models, subject and sign (information) modeling are distinguished.
Object modeling is carried out on a model that reproduces certain geometric, physical, dynamic, or functional characteristics of the object of modeling - the original; in a particular case - analog modeling, when the behavior of the original and the model is described by common mathematical relationships, for example, by common differential equations. In sign modeling, diagrams, drawings, formulas, etc. serve as models. The most important type of such modeling is mathematical modeling (see more details below).
Simulation is always used together with other research methods, it is especially closely related to the experiment. The study of any phenomenon on its model is a special kind of experiment - a model experiment, which differs from a conventional experiment in that in the process of cognition an "intermediate link" is included - a model that is both a means and an object of experimental research replacing the original.
A special kind of modeling is a thought experiment. In such an experiment, the researcher mentally creates ideal objects, correlates them with each other within the framework of a certain dynamic model, mentally imitating the movement and those situations that could take place in a real experiment. At the same time, ideal models and objects help to identify “in pure form” the most important, essential connections and relationships, to mentally play out possible situations, to weed out unnecessary options.
Modeling also serves as a way of constructing a new one that did not exist earlier in practice. The researcher, having studied the characteristic features of real processes and their tendencies, looks for new combinations of them on the basis of the leading idea, makes their mental redesign, that is, models the required state of the system under study (just like any person and even an animal, he builds his activity, activity on the basis of initially formed "model of the required future" - according to N.A. Bernshtein). At the same time, models-hypotheses are created that reveal the mechanisms of communication between the components of the studied, which are then tested in practice. In this understanding, modeling has recently become widespread in the social and human sciences - in economics, pedagogy, etc., when different authors offer different models of firms, industries, educational systems, etc.
Along with the operations of logical thinking, theoretical methods-operations can also include (possibly conditionally) imagination as a thought process for creating new ideas and images with its specific forms of fantasy (creation of implausible, paradoxical images and concepts) and dreams (as the creation of images of the desired).
Theoretical methods (methods - cognitive actions). The general philosophical, general scientific method of cognition is dialectics - the real logic of meaningful creative thinking, reflecting the objective dialectics of reality itself. The basis of dialectics as a method of scientific knowledge is the ascent from the abstract to the concrete (G. Hegel) - from general and content-poor forms to dissected and richer content, to a system of concepts that make it possible to comprehend an object in its essential characteristics. In dialectics, all problems acquire a historical character, the study of the development of an object is a strategic platform for cognition. Finally, dialectics is oriented in cognition to the disclosure and methods of resolving contradictions.
The laws of dialectics: the transition of quantitative changes into qualitative ones, the unity and struggle of opposites, etc.; analysis of paired dialectical categories: historical and logical, phenomenon and essence, general (universal) and singular, etc. are integral components of any well-structured scientific research.
Scientific theories verified by practice: any such theory, in essence, acts as a method in the construction of new theories in this or even other areas of scientific knowledge, as well as in the function of a method that determines the content and sequence of the researcher's experimental activity. Therefore, the difference between scientific theory as a form of scientific knowledge and as a method of cognition in this case is functional: being formed as a theoretical result of past research, the method acts as a starting point and condition for subsequent research.
Proof - method - theoretical (logical) action, during which the truth of a thought is substantiated with the help of other thoughts. Any proof consists of three parts: the thesis, arguments (arguments) and demonstration. According to the method of conducting evidence, there are direct and indirect, according to the form of inference - inductive and deductive. Evidence Rules:
1. The thesis and arguments must be clear and precise.
2. The thesis must remain identical throughout the proof.
3. The thesis should not contain a logical contradiction.
4. The arguments given in support of the thesis must themselves be true, not subject to doubt, must not contradict each other and be a sufficient basis for this thesis.
5. The proof must be complete.
In the totality of methods of scientific knowledge, an important place belongs to the method of analyzing knowledge systems (see, for example,). Any scientific knowledge system has a certain independence in relation to the reflected subject area. In addition, knowledge in such systems is expressed using a language whose properties affect the relationship of knowledge systems to the objects being studied - for example, if any sufficiently developed psychological, sociological, pedagogical concept is translated into, say, English, German, French - Will it be unequivocally perceived and understood in England, Germany and France? Further, the use of language as a carrier of concepts in such systems presupposes one or another logical systematization and logically organized use of linguistic units to express knowledge. And, finally, no system of knowledge exhausts the entire content of the object under study. In it, only a certain, historically concrete part of such content always receives a description and explanation.
The method of analysis of scientific knowledge systems plays an important role in empirical and theoretical research tasks: when choosing an initial theory, a hypothesis for solving a chosen problem; when distinguishing between empirical and theoretical knowledge, semi-empirical and theoretical solutions to a scientific problem; when substantiating the equivalence or priority of the use of certain mathematical tools in various theories related to the same subject area; when studying the possibilities of disseminating previously formulated theories, concepts, principles, etc. to new subject areas; substantiation of new possibilities for the practical application of knowledge systems; when simplifying and clarifying knowledge systems for training, popularization; to harmonize with other knowledge systems, etc.
Further, the theoretical methods-actions will include two methods of constructing scientific theories:
- deductive method (synonym - axiomatic method) - a method of constructing a scientific theory, in which it is based on some initial provisions of the axiom (synonym - postulates), from which all other provisions of this theory (theorem) are derived purely logically through proof. The construction of a theory based on the axiomatic method is usually called deductive. All concepts of the deductive theory, except for a fixed number of initial ones (such initial concepts in geometry, for example, are: point, line, plane) are introduced by means of definitions expressing them through previously introduced or derived concepts. The classic example of a deductive theory is the geometry of Euclid. Theories are built by the deductive method in mathematics, mathematical logic, theoretical physics;
- the second method has not received a name in the literature, but it certainly exists, since in all other sciences, except for the above, theories are built according to the method, which we will call inductive-deductive: first, an empirical basis is accumulated, on the basis of which theoretical generalizations (induction) are built, which can be built into several levels - for example, empirical laws and theoretical laws - and then these obtained generalizations can be extended to all objects and phenomena covered by this theory (deduction) - see Fig. 6 and Fig. 10. The inductive-deductive method is used to construct most of the theories in the sciences of nature, society and man: physics, chemistry, biology, geology, geography, psychology, pedagogy, etc.
Other theoretical research methods (in the sense of methods - cognitive actions): identifying and resolving contradictions, posing a problem, building hypotheses, etc., up to the planning of scientific research, we will consider below in the specifics of the temporal structure of research activity - building phases, stages and stages scientific research.
Empirical methods (methods-operations).
The study of literature, documents and results of activities. The issues of working with scientific literature will be considered separately below, since this is not only a research method, but also an obligatory procedural component of any scientific work.
A variety of documentation also serves as a source of factual material for research: archival materials in historical research; documentation of enterprises, organizations and institutions in economic, sociological, pedagogical and other research, etc. The study of performance results plays an important role in pedagogy, especially in studying the problems of professional training of pupils and students; in psychology, pedagogy and sociology of labor; and, for example, in archeology, during excavations, an analysis of the results of people's activities: based on the remains of tools, utensils, dwellings, etc., makes it possible to restore their way of life in a particular era.
Observation is, in principle, the most informative research method. This is the only method that allows you to see all aspects of the phenomena and processes under study, accessible to the perception of the observer - both directly and with the help of various instruments.
Depending on the goals that are pursued in the process of observation, the latter can be scientific and non-scientific. Purposeful and organized perception of objects and phenomena of the external world, associated with the solution of a certain scientific problem or task, is commonly called scientific observation. Scientific observations involve obtaining certain information for further theoretical understanding and interpretation, for the approval or refutation of a hypothesis, etc.
Scientific observation consists of the following procedures:
- determination of the purpose of observation (for what, for what purpose?);
- choice of object, process, situation (what to observe?);
- choice of method and frequency of observations (how to observe?);
- choice of methods for registering the observed object, phenomenon (how to record the information received?);
- processing and interpretation of the information received (what is the result?) - see, for example,.
Observed situations are divided into:
- natural and artificial;
- controlled and not controlled by the subject of observation;
- spontaneous and organized;
- standard and non-standard;
- normal and extreme, etc.
In addition, depending on the organization of observation, it can be open and hidden, field and laboratory, and depending on the nature of fixation, it can be ascertaining, evaluating and mixed. According to the method of obtaining information, observations are divided into direct and instrumental. According to the scope of the studied objects, continuous and selective observations are distinguished; by frequency - constant, periodic and single. A special case of observation is self-observation, which is widely used, for example, in psychology.
Observation is necessary for scientific knowledge, since without it science would not be able to obtain initial information, would not have scientific facts and empirical data, therefore, the theoretical construction of knowledge would also be impossible.
However, observation as a method of cognition has a number of significant drawbacks. The personal characteristics of the researcher, his interests, and finally, his psychological state can significantly affect the results of observation. The objective results of observation are even more subject to distortion in those cases when the researcher is focused on obtaining a certain result, on confirming his existing hypothesis.
To obtain objective results of observation, it is necessary to comply with the requirements of intersubjectivity, that is, observation data must (and / or can) be obtained and recorded, if possible, by other observers.
Replacing direct observation with instruments indefinitely expands the possibilities of observation, but also does not exclude subjectivity; evaluation and interpretation of such indirect observation is carried out by the subject, and therefore the subjective influence of the researcher can still take place.
Observation is most often accompanied by another empirical method - measurement
Measurement. Measurement is used everywhere, in any human activity. So, almost every person during the day takes measurements dozens of times, looking at the clock. The general definition of measurement is as follows: “Measurement is a cognitive process that consists in comparing ... a given quantity with some of its value, taken as a comparison standard” (see, for example,).
In particular, measurement is an empirical method (method-operation) of scientific research.
You can select a specific dimension structure that includes the following elements:
1) a cognizing subject that carries out measurement with certain cognitive goals;
2) measuring instruments, among which there can be both devices and tools designed by man, and objects and processes given by nature;
3) the object of measurement, that is, the measured quantity or property to which the comparison procedure is applicable;
4) method or measurement method, which is a set of practical actions, operations performed using measuring instruments, and also includes certain logical and computational procedures;
5) the measurement result, which is a named number, expressed using the appropriate names or signs.
The epistemological substantiation of the measurement method is inextricably linked with the scientific understanding of the ratio of qualitative and quantitative characteristics of the object (phenomenon) being studied. Although only quantitative characteristics are recorded using this method, these characteristics are inextricably linked with the qualitative certainty of the object under study. It is thanks to the qualitative certainty that it is possible to single out the quantitative characteristics to be measured. The unity of the qualitative and quantitative aspects of the object under study means both the relative independence of these aspects and their deep interconnection. The relative independence of quantitative characteristics makes it possible to study them during the measurement process, and use the measurement results to analyze the qualitative aspects of the object.
The problem of measurement accuracy also refers to the epistemological foundations of measurement as a method of empirical knowledge. Measurement accuracy depends on the ratio of objective and subjective factors in the measurement process.
These objective factors include:
- the possibility of identifying certain stable quantitative characteristics in the object under study, which in many cases of research, in particular, social and humanitarian phenomena and processes is difficult, and sometimes even impossible;
- the capabilities of measuring instruments (the degree of their perfection) and the conditions in which the measurement process takes place. In some cases, finding the exact value of the quantity is fundamentally impossible. It is impossible, for example, to determine the trajectory of an electron in an atom, etc.
The subjective factors of measurement include the choice of measurement methods, the organization of this process, and a whole range of cognitive capabilities of the subject - from the qualifications of the experimenter to his ability to correctly and competently interpret the results.
Along with direct measurements, the method of indirect measurement is widely used in the process of scientific experimentation. With indirect measurement, the desired value is determined on the basis of direct measurements of other quantities associated with the first functional dependence. According to the measured values of the mass and volume of the body, its density is determined; the resistivity of a conductor can be found from the measured values of resistance, length and cross-sectional area of the conductor, etc. The role of indirect measurements is especially great in cases where direct measurement is impossible under objective reality. For example, the mass of any space object (natural) is determined using mathematical calculations based on the use of measurement data of other physical quantities.
Special attention should be paid to the discussion of measurement scales.
Scale - a numerical system in which the relationships between the various properties of the studied phenomena, processes are translated into the properties of a particular set, as a rule, a set of numbers.
There are several types of scales. Firstly, we can distinguish between discrete scales (in which the set of possible values of the estimated value is finite - for example, the score in points - "1", "2", "3", "4", "5") and continuous scales (for example, mass in grams or volume in liters). Secondly, there are relationship scales, interval scales, ordinal (rank) scales and nominal scales (name scales) - see Fig. 5, which also reflects the power of the scales - that is, their "resolution". The power of the scale can be defined as the degree, the level of its ability to accurately describe phenomena, events, that is, the information that the ratings in the corresponding scale carry. For example, a patient's condition can be assessed on a scale of names: "healthy" - "sick". great information will carry measurements of the state of the same patient in a scale of intervals or ratios: temperature, blood pressure, etc. You can always switch from a more powerful scale to a “weaker” one (by aggregating - compressing - information): for example, if you enter a “threshold temperature » at 37 C and consider that the patient is healthy if his temperature is less than the threshold and sick otherwise, then you can go from the relationship scale to the name scale. The reverse transition in the example under consideration is impossible - the information that the patient is healthy (that is, that his temperature is less than the threshold) does not allow us to say exactly what his temperature is.

Consider, following mainly, the properties of the four main types of scales, listing them in descending order of power.
The relationship scale is the most powerful scale. It allows you to evaluate how many times one measured object is greater (less) than another object, taken as a standard, unity. For ratio scales, there is a natural reference point (zero). Ratio scales measure almost all physical quantities - linear dimensions, areas, volumes, current strength, power, etc.
All measurements are made with some degree of accuracy. Measurement accuracy - the degree of closeness of the measurement result to the true value of the measured quantity. Measurement accuracy is characterized by measurement error - the difference between the measured and the true value.
A distinction is made between systematic (constant) errors (errors) due to factors that act in the same way when measurements are repeated, for example, a malfunction of a measuring device, and random errors caused by variations in measurement conditions and / or threshold accuracy of the measurement tools used (for example, devices).
It is known from probability theory that with a sufficiently large number of measurements, the random measurement error can be:
- greater than the standard error (usually denoted by the Greek letter sigma and equal to the square root of the variance - see definition below in section 2.3.2) in about 32% of cases. Accordingly, the true value of the measured value is in the interval of the mean value plus / minus the standard error with a probability of 68%;
- more than twice the mean square error only in 5% of cases. Accordingly, the true value of the measured value is in the interval of the mean value plus/minus twice the standard error with a probability of 95%;
- more than triple the mean square error only in 0.3% of cases. Accordingly, the true value of the measured value is in the interval of the average value plus / minus three times the standard error with a probability of 99.7%
Therefore, it is extremely unlikely that the random measurement error will be greater than three times the root mean square error. Therefore, as the range of the "true" value of the measured value, the arithmetic mean plus/minus three times the standard error (the so-called "rule of three sigma") is usually chosen.
It must be emphasized that what has been said here about the accuracy of measurements refers only to the scales of ratios and intervals. For other types of scales, the situation is much more complicated and requires the reader to study special literature (see, for example,).
The interval scale is used quite rarely and is characterized by the fact that there is no natural reference point for it. An example of an interval scale is the Celsius, Réaumur, or Fahrenheit temperature scale. The Celsius scale, as you know, was set as follows: the freezing point of water was taken as zero, its boiling point as 100 degrees, and, accordingly, the temperature interval between freezing and boiling water was divided into 100 equal parts. Here already the statement that the temperature of 30C is three times more than 10C will be incorrect. The interval scale stores the ratio of interval lengths (differences). We can say: a temperature of 30C differs from a temperature of 20C twice as much as a temperature of 15C differs from a temperature of 10C.
The ordinal scale (rank scale) is a scale, with respect to the values of which it is no longer possible to talk about how many times the measured value is greater (less) than another, nor how much it is greater (less). Such a scale only arranges objects by assigning certain points to them (the result of measurements is simply the ordering of objects).
For example, the Mohs mineral hardness scale is constructed in this way: a set of 10 reference minerals is taken to determine the relative hardness by scratching. Talc is taken as 1, gypsum as 2, calcite as 3, and so on up to 10 as diamond. A certain hardness can be unambiguously assigned to any mineral. If the studied mineral, for example, scratches quartz (7), but does not scratch topaz (8), then, accordingly, its hardness will be equal to 7. The Beaufort wind force and Richter earthquake scales are similarly constructed.
Order scales are widely used in sociology, pedagogy, psychology, medicine, and other sciences that are not as precise as, say, physics and chemistry. In particular, the ubiquitous scale of school marks in points (five-point, twelve-point, etc.) can be attributed to the order scale.
A special case of the ordinal scale is the dichotomous scale, in which there are only two ordered gradations - for example, “entered the institute”, “did not enter”.
The scale of names (nominal scale) is actually no longer associated with the concept of “value” and is used only to distinguish one object from another: telephone numbers, state registration numbers of cars, etc.
The measurement results must be analyzed, and for this it is often necessary to build derivative (secondary) indicators on their basis, that is, to apply one or another transformation to the experimental data. The most common derived indicator is the averaging of values - for example, the average weight of people, average height, average per capita income, etc. The use of one or another measurement scale determines the set of transformations that are acceptable for measurement results in this scale (for more details, see publications on measurement theory).
Let's start with the weakest scale - the scale of names (nominal scale), which distinguishes pairwise distinguishable classes of objects. For example, in the scale of names, the values of the attribute "gender" are measured: "male" and "female". These classes will be distinguishable no matter what different terms or signs are used to designate them: "female" and "male", or "female" and "male", or "A" and "B", or "1" and "2", or "2" and "3", etc. Therefore, for the naming scale, any one-to-one transformations are applicable, that is, preserving a clear distinguishability of objects (thus, the weakest scale - the naming scale - allows the widest range of transformations).
The difference between the ordinal scale (rank scale) and the naming scale is that classes (groups) of objects are ordered in the rank scale. Therefore, it is impossible to change the values of features arbitrarily - the ordering of objects (the order in which one object follows another) must be preserved. Therefore, for an ordinal scale, any monotonic transformation is admissible. For example, if the score of object A is 5 points, and object B is 4 points, then their ordering will not change if we multiply the number of points by a positive number that is the same for all objects, or add it to some number that is the same for all, or square it and etc. (for example, instead of "1", "2", "3", "4", "5" we use "3", "5", "9", "17", "102" respectively). In this case, the differences and ratios of the “points” will change, but the ordering will remain.
For the interval scale, not any monotonic transformation is allowed, but only one that preserves the ratio of the differences in estimates, that is, a linear transformation - multiplication by a positive number and / or adding a constant number. For example, if 2730C is added to the temperature value in degrees Celsius, then we get the temperature in Kelvin, and the difference of any two temperatures in both scales will be the same.
And, finally, in the most powerful scale - the scale of relations - only similarity transformations are possible - multiplication by a positive number. Substantially, this means that, for example, the ratio of the masses of two objects does not depend on the units in which the masses are measured - grams, kilograms, pounds, etc.
We summarize what has been said in Table. 4, which reflects the correspondence between the scales and the allowed transformations.

As noted above, the results of any measurements, as a rule, refer to one of the main (listed above) types of scales. However, obtaining measurement results is not an end in itself - these results must be analyzed, and for this it is often necessary to build derived indicators on their basis. These derived indicators can be measured on other scales than the original ones. For example, a 100-point scale can be used to assess knowledge. But it is too detailed, and, if necessary, it can be rebuilt into a five-point scale ("1" - from "1" to "20"; "2" - from "21" to "40", etc.), or a two-point scale (for example , positive score - everything above 40 points, negative - 40 or less). Consequently, the problem arises - what transformations can be applied to certain types of source data. In other words, the transition from which scale to which is correct. This problem in measurement theory is called the problem of adequacy.
To solve the problem of adequacy, one can use the properties of the relationship between the scales and the transformations allowed for them, since by no means any operation in the processing of initial data is acceptable. So, for example, such a common operation as calculating the arithmetic mean cannot be used if the measurements are obtained in an ordinal scale. The general conclusion is that it is always possible to move from a more powerful scale to a less powerful one, but not vice versa (for example, based on the ratings obtained on the ratio scale, you can build scores on the ordinal scale, but not vice versa).
Having completed the description of such an empirical method as measurement, let us return to the consideration of other empirical methods of scientific research.
Interview. This empirical method is used only in the social and human sciences. The survey method is divided into oral survey and written survey.
Oral survey (conversation, interview). The essence of the method is clear from its name. During the survey, the questioner has personal contact with the respondent, that is, he has the opportunity to see how the respondent reacts to a particular question. The observer can, if necessary, set various additional questions and thus obtain additional data on some unexplored issues.
Oral surveys give concrete results, and with their help you can get comprehensive answers to complex questions of interest to the researcher. However, the respondents answer the questions of a “delicate” nature in writing much more frankly and give more detailed and thorough answers.
The respondent spends less time and energy on a verbal response than on a written one. However, this method also has its negative sides. All respondents are in different conditions, some of them can get additional information through leading questions of the researcher; facial expression or some gesture of the researcher has some effect on the respondent.
Questions used for interviews are planned in advance and a questionnaire is drawn up, where space should also be left for recording (recording) the answer.
Basic requirements for writing questions:
1) the survey should not be random, but systematic; at the same time, questions that are more understandable to the respondent are asked earlier, more difficult - later;
2) questions should be concise, specific and understandable for all respondents;
3) questions should not contradict ethical standards.
Survey Rules:
1) during the interview, the researcher should be alone with the respondent, without extraneous witnesses;
2) each oral question is read from the question sheet (questionnaire) verbatim, unchanged;
3) exactly adheres to the order of the questions; the respondent should not see the questionnaire or be able to read the questions following the next one;
4) the interview should be short - from 15 to 30 minutes, depending on the age and intellectual level of the respondents;
5) the interviewer should not influence the respondent in any way (indirectly prompt the answer, shake his head in disapproval, nod his head, etc.);
6) the interviewer may, if necessary, if this answer is unclear, ask additionally only neutral questions (for example: “What did you mean by that?”, “Explain a little more!”).
7) answers are recorded in the questionnaire only during the survey.
The responses are then analyzed and interpreted.
Written survey - questioning. It is based on a pre-designed questionnaire (questionnaire), and the answers of respondents (interviewees) to all positions of the questionnaire constitute the desired empirical information.
The quality of empirical information obtained as a result of a survey depends on such factors as the wording of the questionnaire questions, which should be understandable to the interviewee; qualifications, experience, conscientiousness, psychological characteristics of researchers; the situation of the survey, its conditions; emotional condition respondents; customs and traditions, ideas, everyday situation; and also - the attitude to the survey. Therefore, when using such information, it is always necessary to make allowance for the inevitability of subjective distortions due to its specific individual “refraction” in the minds of the respondents. And when it comes to fundamentally important issues, along with the survey, they also turn to other methods - observation, expert assessments, and analysis of documents.
Particular attention is paid to the development of a questionnaire - a questionnaire containing a series of questions necessary to obtain information in accordance with the objectives and hypothesis of the study. The questionnaire must meet the following requirements: be reasonable in relation to the purposes of its use, that is, provide the required information; have stable criteria and reliable rating scales that adequately reflect the situation under study; the wording of the questions should be clear to the interviewee and consistent; Questionnaire questions should not cause negative emotions in the respondent (respondent).
Questions can be closed or open-ended. A question is called closed if it contains a complete set of answers in the questionnaire. The respondent only marks the option that coincides with his opinion. This form of the questionnaire significantly reduces the time of filling out and at the same time makes the questionnaire suitable for processing on a computer. But sometimes there is a need to find out directly the opinion of the respondent on a question that excludes pre-prepared answers. In this case, open-ended questions are used.
When answering an open question, the respondent is guided only by his own ideas. Therefore, such a response is more individualized.
Compliance with a number of other requirements also contributes to the increase in the reliability of answers. One of them is that the respondent should be provided with the opportunity to evade the answer, to express an uncertain opinion. To do this, the rating scale should provide for answer options: “it is difficult to say”, “I find it difficult to answer”, “it happens in different ways”, “whenever”, etc. But the predominance of such options in the answers is evidence of either the incompetence of the respondent, or the unsuitability of the wording of the question to obtain the necessary information.
In order to obtain reliable information about the phenomenon or process under study, it is not necessary to interview the entire contingent, since the object of study can be numerically very large. In cases where the object of study exceeds several hundred people, a selective survey is used.
Method of expert assessments. In essence, this is a kind of survey associated with the involvement in the assessment of the phenomena under study, the processes of the most competent people, whose opinions, complementing and rechecking each other, make it possible to fairly objectively evaluate the researched. The use of this method requires a number of conditions. First of all, this is a careful selection of experts - people who know the area being assessed, the object under study well and are capable of an objective, unbiased assessment.
The choice of an accurate and convenient system of assessments and appropriate measurement scales is also essential, which streamlines judgments and makes it possible to express them in certain quantities.
It is often necessary to train experts to use the proposed scales for an unambiguous assessment in order to minimize errors and make assessments comparable.
If experts acting independently of each other consistently give identical or similar estimates or express similar opinions, there is reason to believe that they are approaching objective ones. If the estimates differ greatly, then this indicates either an unsuccessful choice of the grading system and measurement scales, or the incompetence of experts.
Varieties of the expert assessment method are: the commission method, the brainstorming method, the Delphi method, the heuristic forecasting method, etc. A number of these methods will be discussed in the third chapter of this work (see also).
Testing is an empirical method, a diagnostic procedure consisting in the application of tests (from the English test - a task, a test). Tests are usually given to the test subjects either in the form of a list of questions requiring short and unambiguous answers, or in the form of tasks, the solution of which does not take much time and also requires unambiguous solutions, or in the form of some short-term practical work of the test subjects, for example, qualifying trial work in a professional education, labor economics, etc. Tests are divided into blank, hardware (for example, on a computer) and practical; for individual and group use.
Here, perhaps, are all the empirical methods-operations that the scientific community has at its disposal today. Next, we will consider empirical methods-actions, which are based on the use of methods-operations and their combinations.
Empirical methods (methods-actions).
Empirical methods-actions should, first of all, be divided into two classes. The first class is the methods of studying an object without its transformation, when the researcher does not make any changes, transformations in the object of study. More precisely, it does not make significant changes to the object - after all, according to the principle of complementarity (see above), the researcher (observer) cannot but change the object. Let's call them object tracking methods. These include: the tracking method itself and its particular manifestations - examination, monitoring, study and generalization of experience.
Another class of methods is associated with the active transformation of the object being studied by the researcher - let's call these methods transforming methods - this class will include such methods as experimental work and experiment.
Tracking, often, in a number of sciences is, perhaps, the only empirical method-action. For example, in astronomy. After all, astronomers can not yet influence the studied space objects. The only possibility is to track their state through methods-operations: observation and measurement. The same, to a large extent, applies to such branches of scientific knowledge as geography, demography, etc., where the researcher cannot change anything in the object of study.
In addition, tracking is also used when the goal is to study the natural functioning of an object. For example, when studying certain features of radioactive radiation or when studying the reliability of technical devices, which is checked by their long-term operation.
Survey - as a special case of the tracking method - is the study of the object under study with one or another measure of depth and detail, depending on the tasks set by the researcher. A synonym for the word "examination" is "inspection", which means that the examination is basically the initial study of an object, carried out to familiarize itself with its condition, functions, structure, etc. Surveys are most often used in relation to organizational structures - enterprises, institutions, etc. - or in relation to public entities, for example, settlements, for which surveys can be external and internal.
External surveys: survey of the socio-cultural and economic situation in the region, survey of the goods and services market and labor market, survey of the state of employment of the population, etc. Internal surveys: surveys within the enterprise, institutions - survey of the state of the production process, surveys of the contingent of employees, etc. .
The survey is carried out through the methods-operations of empirical research: observation, study and analysis of documentation, oral and written survey, involvement of experts, etc.
Any survey is carried out according to a detailed program developed in advance, in which the content of the work, its tools (compilation of questionnaires, test kits, questionnaires, a list of documents to be studied, etc.), as well as criteria for evaluating the phenomena and processes to be studied, are planned in detail. This is followed by the following stages: collecting information, summarizing materials, summing up and preparing reporting materials. At each stage, it may be necessary to adjust the survey program when the researcher or a group of researchers conducting it is convinced that the collected data is not enough to obtain the desired results, or the collected data does not reflect the picture of the object under study, etc.
According to the degree of depth, detail and systematization, surveys are divided into:
- Pilot (reconnaissance) surveys carried out for preliminary, relatively surface orientation in the object under study;
- specialized (partial) surveys conducted to study certain aspects, aspects of the object under study;
- modular (complex) examinations - for the study of whole blocks, complexes of questions programmed by the researcher on the basis of a sufficiently detailed preliminary study of the object, its structure, functions, etc.;
- system surveys - conducted already as full-fledged independent studies on the basis of isolating and formulating their subject, purpose, hypothesis, etc., and involving a holistic consideration of the object, its system-forming factors.
At what level to conduct a survey in each case, the researcher or the research team decides, depending on the goals and objectives of scientific work.
Monitoring. This is constant supervision, regular monitoring of the state of the object, the values of its individual parameters in order to study the dynamics of ongoing processes, predict certain events, and also prevent undesirable phenomena. For example, environmental monitoring, synoptic monitoring, etc.
Study and generalization of experience (activity). When conducting research, the study and generalization of experience (organizational, industrial, technological, medical, pedagogical, etc.) is used for various purposes: to determine the existing level of detail of enterprises, organizations, institutions, the functioning of the technological process, to identify shortcomings and bottlenecks in practice a particular field of activity, studying the effectiveness of the application of scientific recommendations, identifying new patterns of activity that are born in the creative search of advanced leaders, specialists and entire teams. The object of study can be: mass experience - to identify the main trends in the development of a particular sector of the national economy; negative experience - to identify typical shortcomings and bottlenecks; advanced experience, in the process of which new positive findings are identified, generalized, become the property of science and practice.
The study and generalization of best practices is one of the main sources for the development of science, since this method allows you to identify relevant scientific problems, creates the basis for studying the patterns of development of processes in a number of areas of scientific knowledge, primarily in the so-called technological sciences.
Best Practice Criteria:
1) Novelty. It can manifest itself in varying degrees: from the introduction of new provisions in science to the effective application of already known provisions.
2) High performance. Best practices should deliver above average results for the industry, group of similar facilities, etc.
3) Compliance with modern achievements of science. Achieving high results does not always indicate the correspondence of experience to the requirements of science.
4) Stability - maintaining the effectiveness of the experience under changing conditions, achieving high results for a sufficiently long time.
5) Replicability - the ability to use experience by other people and organizations. Best practices can be made available to other people and organizations. It cannot be associated only with the personal characteristics of its author.
6) Optimal experience - achieving high results with a relatively economical expenditure of resources, and also not to the detriment of solving other problems.
The study and generalization of experience is carried out by such empirical methods-operations as observation, surveys, the study of literature and documents, etc.
The disadvantage of the tracking method and its varieties - survey, monitoring, study and generalization of experience as empirical methods-actions - is the relatively passive role of the researcher - he can study, track and generalize only what has developed in the surrounding reality, without being able to actively influence what is happening. processes. We emphasize once again that this shortcoming is often due to objective circumstances. This shortcoming is deprived of object transformation methods: experimental work and experiment.
The methods that transform the object of study include experimental work and experiment. The difference between them lies in the degree of arbitrariness of the researcher's actions. If the experimental work is a non-strict research procedure, in which the researcher makes changes to the object at his own discretion, based on his own considerations of expediency, then the experiment is a completely strict procedure, where the researcher must strictly follow the requirements of the experiment.
Experimental work is, as already mentioned, a method of making deliberate changes to the object under study with a certain degree of arbitrariness. So, the geologist himself determines where to look, what to look for, by what methods - to drill wells, dig pits, etc. In the same way, an archaeologist, paleontologist determines where and how to excavate. Or in pharmacy, a long search for new drugs is carried out - out of 10 thousand synthesized compounds, only one becomes a drug. Or, for example, experienced work in agriculture.
Experimental work as a research method is widely used in the sciences related to human activities - pedagogy, economics, etc., when models are created and tested, as a rule, copyright: firms, educational institutions etc., or various author's methods are created and tested. Or an experimental textbook, an experimental preparation, a prototype are created and then they are tested in practice.
Experimental work is in a sense similar to a thought experiment - both here and there, as it were, the question is posed: “what happens if ...?” Only in a mental experiment the situation is played out “in the mind”, while in experimental work the situation is played out by action.
But, experimental work is not a blind chaotic search through “trial and error”.
Experimental work becomes a method of scientific research under the following conditions:
1. When it is put on the basis of data obtained by science in accordance with a theoretically justified hypothesis.
2. When accompanied by deep analysis, conclusions are drawn from it and theoretical generalizations are made.
In experimental work, all methods-operations of empirical research are used: observation, measurement, analysis of documents, peer review, etc.
Experimental work occupies, as it were, an intermediate place between object tracking and experiment.
It is a way of active intervention of the researcher in the object. However, experimental work gives, in particular, only the results of the effectiveness or inefficiency of certain innovations in a general, summary form. Which of the factors of implemented innovations give a greater effect, which less, how they influence each other - experimental work cannot answer these questions.
For a deeper study of the essence of a particular phenomenon, the changes occurring in it, and the reasons for these changes, in the process of research, they resort to varying the conditions for the occurrence of phenomena and processes and the factors influencing them. Experiment serves this purpose.
An experiment is a general empirical research method (method-action), the essence of which is that phenomena and processes are studied under strictly controlled and controlled conditions. The basic principle of any experiment is a change in each research procedure of only one of some factors, while the rest remain unchanged and controllable. If it is necessary to check the influence of another factor, the following research procedure is carried out, where this last factor is changed, and all other controlled factors remain unchanged, and so on.
During the experiment, the researcher deliberately changes the course of some phenomenon by introducing a new factor into it. The new factor introduced or changed by the experimenter is called the experimental factor, or independent variable. Factors that have changed under the influence of the independent variable are called dependent variables.
There are many classifications of experiments in the literature. First of all, depending on the nature of the object under study, it is customary to distinguish between physical, chemical, biological, psychological experiments, etc. According to the main goal, experiments are divided into verification (empirical verification of a certain hypothesis) and search (collection of the necessary empirical information to build or refine the put forward conjecture , ideas). Depending on the nature and variety of the means and conditions of the experiment and the methods of using these means, one can distinguish between direct (if the means are used directly to study the object), model (if a model is used that replaces the object), field (in natural conditions, for example, in space), laboratory (under artificial conditions) experiment.
Finally, one can speak of qualitative and quantitative experiments, based on the difference in the results of the experiment. Qualitative experiments, as a rule, are undertaken to identify the impact of certain factors on the process under study without establishing an exact quantitative relationship between characteristic quantities. To ensure the exact value of the essential parameters that affect the behavior of the object under study, a quantitative experiment is necessary.
Depending on the nature of the experimental research strategy, there are:
1) experiments carried out by the method of "trial and error";
2) experiments based on a closed algorithm;
3) experiments using the "black box" method, leading to conclusions from knowledge of the function to knowledge of the structure of the object;
4) experiments with the help of an “open box”, which allow, based on knowledge of the structure, to create a sample with given functions.
In recent years, experiments have become widespread, in which the computer acts as a means of cognition. They are especially important when real systems do not allow either direct experimentation or experimentation with the help of material models. In a number of cases, computer experiments dramatically simplify the research process - with their help, situations are “played out” by building a model of the system under study.
In talking about experiment as a method of cognition, one cannot fail to note one more type of experimentation, which plays an important role in natural science research. This is a mental experiment - the researcher operates not with concrete, sensual material, but with an ideal, model image. All knowledge gained in the course of mental experimentation is subject to practical verification, in particular in a real experiment. Therefore, this type of experimentation should be attributed to the methods of theoretical knowledge (see above). P.V. Kopnin, for example, writes: “Scientific research is really experimental only when the conclusion is drawn not from speculative reasoning, but from sensory, practical observation of phenomena. Therefore, what is sometimes called a theoretical or thought experiment is not actually an experiment. A thought experiment is ordinary theoretical reasoning that takes on the external form of an experiment.
The theoretical methods of scientific knowledge should also include some other types of experiment, for example, the so-called mathematical and simulation experiments. “The essence of the method of mathematical experiment lies in the fact that experiments are not carried out with the object itself, as is the case in the classical experimental method, but with its description in the language of the corresponding section of mathematics ". A simulation experiment is an idealized study by simulating the behavior of an object instead of actual experimentation. In other words, these types of experimentation are variants of a model experiment with idealized images. More details about mathematical modeling and simulation experiments are discussed below in the third chapter.
So, we have tried to describe the research methods from the most general positions. Naturally, in each branch of scientific knowledge, certain traditions have developed in the interpretation and use of research methods. Thus, the method of frequency analysis in linguistics will refer to the tracking method (method-action) carried out by the methods-operations of document analysis and measurement. Experiments are usually divided into ascertaining, training, control and comparative. But all of them are experiments (methods-actions) carried out by methods-operations: observations, measurements, tests, etc.

NON-STATE AUTONOMOUS NON-PROFIT

EDUCATIONAL ORGANIZATION

INSTITUTE OF THE FASHION INDUSTRY

LECTURE COURSE

"Methods and means of research"

Moscow 2009

INTRODUCTION

The course of lectures is written according to the program of this course. This discipline has been introduced into the curriculum of all mechanical and technological specialties of institutes.

The objective of this course is to teach students how to use mathematical and statistical methods to obtain statistical mathematical models.

LECTURE #1

Research work and preparation for its implementation.

Research works are divided into theoretical, experimental and theoretical-experimental. The combination of theoretical and experimental parts of the research work contributes to a deeper solution of the research problem.

According to the direction of research work in the textile industry are divided into the following types:

1. Theoretical and experimental work revealing regularities technological processes and determining the optimal mode of operation of machines and mechanisms.

2. Experimental work on testing newly created textile machines in order to determine the reliability and durability of the operation and arrangement of mechanisms.

3. Exploratory research aimed at developing new technological processes based on more effective use types of energy known and widely used in industry.

4. Research work aimed at creating new textile materials, work on the rational use of natural and chemical fibers, yarn and threads.

5. Research work to study the factors that determine the quality and performance properties of products, as well as work to improve methods for testing materials.

6. Works aimed at developing new methods for studying technological processes and tools for measuring the parameters that characterize the process.

2. Stages of research work (R&D).

Research work consists of a number of stages. Each stage has independent meaning and is the object of planning.

Theoretical and experimental work in the textile industry usually includes the following steps:

1. Choice and justification of the topic.

2. Preparatory stage.

3. Theoretical analysis of the technological process.

4. Preparation and conduct of a preliminary experiment.

5. Carrying out a systematic basic experiment.

6. Analysis of the results of theoretical and experimental studies, conclusions and proposals for working with an economic justification.

Experimental work on testing textile machines contains all of the above steps, except for the first.

Exploratory research work may include the following steps:

1. Preparatory stage.

3. Testing models and making adjustments to the design and technology.

4. Design and manufacture of stands (models).

5. Preparation and conduct of a preliminary experiment.

6. Carrying out a systematic experiment.

7. Analysis of test results, conclusions and suggestions.

The above sequence of stages of search work assumes a successful solution of the problem.

Research projects that involve the development of technological conditions for the rational use of raw materials and a new range of textile materials usually have the following typical stages:

1. Preparatory stage.

2. Development of the theoretical part of the topic.

3. Preparation and conduct of a preliminary experiment.

4. Carrying out a systematic experiment.

5. Analysis of the results, development of the optimal technological mode of operation of machines in production, selection of the optimal raw materials and structure of materials.

All stages of research are interconnected.

3. Preparatory stage of research.

The preparatory stage of the research work includes the following works:

2. Preliminary acquaintance with the object of study, its structure and features.

3. Study physical basis technological process.

4. Determining the range of issues to be studied, formulating the objectives of the study and justifying the need to formulate work on the chosen topic.

5. Drawing up methodological and working programs for research.

The list of necessary literature can be compiled by the researcher himself using the "chain" method. The essence of this method lies in the fact that by studying the first article, book, dissertation or research report, one can find references to the literature on the topic, and in subsequent articles - to other sources, etc.

When studying literary sources, the researcher thinks and outlines the direction of his work.

Methodological research program and its content.

The methodological program is the main research document, which is compiled on the basis of a study of the literature and a preliminary acquaintance with the object of study in the laboratory or in production, as well as after a preliminary study of the physical nature of the technological processes carried out in this object.

The methodological program should contain:

1. A clear and exhaustive formulation of the topic of the work.

2. Definition of the purpose of the work, as well as the expected results.

3. The reasons for the formulation of this work, both from scientific and technical, and from economic positions.

4. Summary and critical analysis materials scientific works and literary sources.

5. Building a working model of an object or process.

6. A scheme for the development of this topic in stages, i.e. a list of stages.

7. Conditions, planning matrix and methodology for conducting the experiment, as well as the methodology for testing materials.

8. The method of processing the results, observations and tests, the method of generalizing these results and drawing conclusions.

9. Methodology for calculating the economic efficiency of work.

Depending on the nature of the study, it is necessary to include sections or stages of a theoretical nature in its program, which allow substantiating practical conclusions and recommendations for improving or creating new technological processes, devices, machines, etc. Theoretical development may be preceded by experimental work and vice versa.

Mathematical description of technological processes, mathematical models.

Many technological processes and objects of the textile industry are complex.

They are characterized by a large number of interrelated factors (for example, thread tension and thread length in the loop).

Scientific research is carried out with the aim of:

1. Disclosure of the essence and patterns of the process.

2. Determining the optimal mode of operation of the object (mechanism, machine, unit) to ensure the specified quality of products and high productivity.

3. Determination of the static and dynamic characteristics of the object, etc.

The research results can be presented in the form of tables, graphs and equations, i.e. a mathematical description of the technological process.

The essence of the mathematical description of an object (system) or process is to obtain a mathematical model or relationship that links the characteristics of the material entering the object and the output product, i.e.

Y=A(x), (1.1)

Where Y is a set of output process parameters that determine the physical and Chemical properties output product or technical and economic indicators of the process (object). Often this parameter is called the optimization criterion, the optimization parameter.

x is a set of input parameters (factors) that determine the characteristics of the process (object) and the properties of the input material (raw material, product).

Often the input data is called arguments, input parameters, or external influences on the system; A( ) is a symbol, called an operator, which characterizes the mathematical operation of transforming input functions, i.e. mathematical model object or system.

The mathematical model of an object is usually presented in the form of a block diagram:

X - input parameters (factors)

Y - output parameters.

Object or system (cutting machine, sewing machine, press, etc.)

Knowing the mathematical model of the process or object, it is possible to predict the properties of the outgoing product, to assess the degree of influence of input factors in order to optimize the process.

Methods for obtaining mathematical models.

1. Theoretical.

2. Experimental.

Most often, a combination of theoretical and experimental methods is used.

Passive and active experiment.

With passive In an experiment, information about the parameters of a process or an object is obtained during the normal operation of the object, without introducing any artificial perturbations.

With active In the experiment, information about the process parameters is obtained by artificially introducing perturbations, i.e., changing the input parameters in accordance with a pre-planned program (i.e., planning matrix).

preliminary experiment.

1. Preparation and conduct of a preliminary experiment.

Primary processing of experimental data includes:

1) exclusion of sharply distinguished experimental data;

2) static verification of randomness and independence of measurement results;

3) determination of the numerical characteristics of random variables: average, dispersion or standard deviation, coefficient of variation and type of distribution of random variables;

4) determining the type of distribution of the ordinates of a random function;

5) checking the reproducibility of the process.

Methods for eliminating outlier experimental data.

1) The mean value and variance are determined by the formulas:

(1.3)

2) The calculated value of the Smirnov-Grubs criterion is determined if a sharply distinguished maximum value is suspected.

(1.4)

if a sharply distinguished minimum value is suspected.

(1.5)

Then VRmax and VRmin are compared with the table. VT (App. 1), and, provided that the confidence level of the RD or significance level (a)

a = 1 – RD RD = 0…1

in textiles RD = 0.95 or 95%

If VRmax > VT or VRmin > VT, then sharply distinguished Ui max or Ui min are excluded from further statistical data processing.

Example: when testing sewing threads for breaking, the following values \u200b\u200bare obtained: 199, 239, 214, 229, 224, 234, 219, 300, 224, 218

Using forms. one.

;

VT=2.29

So 300 is a sharp highlight, it is excluded.

LECTURE №2

Preparation for research work (R&D).

In Lecture 1, we identified that the production of knitwear is a multifactorial process. The values of managed (resulting) indicators depend on a large number input factors: from the properties of the yarn and from the setting of the machine regulators. It is often difficult to adjust the entire process in order to get the best result: the required values of areal density, shrinkage of the web or product, etc.

In addition, the production of knitwear is a complex of preparatory and finishing industries. For example, raw materials should be prepared in such a way as to ensure, in addition to the required quality of products, the normal flow of the technological process of knitwear production with the maximum use of modern technology.

The wide range of requirements for raw materials for knitwear is due to the very large variety of the products themselves. For example, the requirement for the structure of the thread is made, starting from nylon monofilaments for thin stockings and ending with woolen and synthetic yarns for outerwear.

In addition, WTO or dyeing and finishing processes have an undeniable influence on the production result. In this case, raw materials, semi-finished products or products are subjected to a complex of physical, mechanical and chemical influences.

As already noted, one of the main input factors of knitwear production is the physical and mechanical properties of threads and yarn.

Let us consider as an example the process of knitting a weave fabric with an eraser on a double-loop circular knitting machine of the KLK type from pure wool yarn.

In order to build a mathematical model of the technological process and be able to control it according to the constructed quantitative dependence, first of all, it is necessary to clearly separate the entire set of factors into control (input factors) and controllable (resulting) indicators.

Then it is necessary to know the methods and means of measuring each control action and the controlled indicator of the product (or fabric), especially measuring the properties of yarn and fabric.

Noticeable difficulties are also created by the absence of accurate and fast tools for the automatic measurement of their values for most parameters.

That. in an experimental study of the technological process of knitwear production, it is necessary to measure and record the values of at least 20 variables (Fig. 1), different, so to speak, in their physical nature.

The latter circumstance entails the use of various research methods. Like n in the first lecture, it should be noted here again that the vast majority of variables are measured not during the knitting process, but before it (yarn properties) or after it (fabric indicators).

Because of this circumstance, the TP of knitwear production as a control object is an open system.

Moreover, the measurement of both the properties of the yarn and the performance of the fabric is made from selected yarn samples and fabric samples. i.e. takes place destructive control raw materials and products.

This is one of the specific aspects of the methods for studying the technological processes of knitwear production.

The second specific side is the conditions for measuring the properties of yarn and web performance. The conditions for carrying out such measurements determine to a very large extent the accuracy of the values of the variables under study.

The requirements for these conditions are set out in sufficient detail in the book Testing Knitwear, M. Legprombytizdat, 1989. In addition, after studying the course Textile Materials Science, you should know these conditions, as well as methods and tools for studying some properties of yarn and fabric indicators.

All textile materials, due to their porosity, have the ability to absorb water vapor from environment and give them back. The process of absorption of water vapor from the environment is called sorption, the process of their return is called desorption.

In textile materials, physical sorption takes place, which is NOT accompanied by the formation of chemical compounds between the absorbent (sorbent) and the absorbed vapors (sorbate).

The processes of sorption and desorption of water vapor proceed at constant values of temperature and humidity until the sorption equilibrium is established. When the external conditions of temperature and air humidity change, these processes resume and proceed until a new equilibrium is established. The equilibrium state is considered to be such a state of the sorbent (for example, a thread) when the absorption of water vapor practically stops and amounts to hundredths of the mass of the sorbent.

The amount of absorbed water vapor and the rate of absorption depend on the type of material and the state of the environment.

Depending on the moisture content in textile materials, their physical and mechanical properties change (for example, the mass of the material, which affects the determination of its consumption, i.e., the final economic indicators).

Therefore, when testing textile materials, it is required to comply with RIGID temperature and humidity standards in testing laboratories and to preliminarily hold the test samples under these conditions for a long time in order to achieve sorption equilibrium.

The standard establishes the following air parameters during research and keeping samples: temperature t = 20 + 20 C and relative humidity 65 + 2%. These conditions are called normal.

Also called the humidity that the material acquires under the specified conditions. The holding time of the studied samples depends on their mass and can be several days.

Normal conditions in the testing laboratories are maintained by air conditioners.

Sampling during testing.

Textile materials are delivered and accepted in batches. A batch is a quantity of material of the same name and type, drawn up by one document certifying its quantity and quality.

A batch consists of packaging units, which can include: containers, bales, bales, bundles, boxes, etc.

A packaging unit consists of individual packages (skein, cob, bobbin, reel, piece, roll, product, etc.), which is the smallest part of the batch.

In order to avoid high material costs (destructive testing) and time for research, the quantitative evaluation of textile materials is carried out by testing a small number of selected packages, the so-called. samples.

For the implementation of random selection (selection of an objective, unbiased) packages, m. b. used a table (or a generator as in lotteries) of random numbers. The application of this (random) sampling method is called RANDOMIZATION.

The number of packaging units and the number of packages taken from the batch for sampling are determined by GOST 8844 - 75; GOST 9173 - 76; GOST 6611.0 - 73. The number of packages for testing is selected depending on the mass of the lot or the number of units or on the number of packages (for example, the number of pieces or products) in the lot. For yarns, threads and finished products, packages are selected separately to determine the physical and mechanical properties and to determine the actual moisture content and lubricant content.

For knitted fabrics, finished products and threads for them, samples for all the tests listed are taken from the same packages. Samples are taken from selected packages.

Preparation for testing.

The outer layer is wound from the packages of threads. Then, cutting, winding or pulling off a layer of threads in approximately equal parts with each, a sample of the required size is taken: n pieces of threads with a length of ℓ each.

From the warping rollers, having previously removed the top layer of threads, they wind bundles threads over the entire width of the roller about 1 m long, and before cutting off each bundle, its ends are fixed (knotted or glued).

Samples are cut out from the selected pieces of canvases at a distance of at least 1.5 m from the end of the piece, the so-called point samples. They are full-width segments 65–75 cm long with an expanded web width of 60–120 cm and 30–35 cm with a web width of more than 120 cm.

After keeping spot samples in normal conditions, they are laid out on the table and marked with a finely sharpened pencil, sharply different from the color of the canvas, using the appropriate templates.

Elementary samples for all tests are cut exactly according to the markup so that the stroke lines remain on the cuts.

The number of tests from one package (piece) of the sample and the sizes of samples for testing for various indicators of knitted fabrics are presented in standards on test methods for each indicator.

An incremental sample taken from the web must be related to the type and number of the machine on which the web is worked out or finished.

In the case of determining the physical and mechanical properties of the PRODUCTS, elementary samples are cut out from the products selected in the sample.

Before and during testing, all elemental samples must be in NORMAL CONDITIONS.

LECTURE №3

Determination of numerical characteristics of a set of random variables.

A complete characteristic of random variables obtained by measuring the properties of products and process parameters of the textile industry is the distribution function (law).

Before determining the main numerical characteristics of random variables, in order to simplify, accelerate and prevent errors in calculations, it is recommended to pre-process selective experimental data. The essence of processing is as follows:

1. If the experimental data represent fractional numbers, then it is necessary to multiply them by some constant value in order to operate further only with integers;

2. If the data represent multi-digit numbers that differ only in one or a few last digits, then it is advisable to discard the constant part of this data.

Example: as a result of the measurement, the following data were obtained: 8.35; 8.09; 8.93; 8.64; 8.37; 8.71; 8.19; 8.24; 8.64; 8.32.

Multiply by 100 and subtract 800, we get:

35; 9; 93; 64; 37; 71; 19; 24; 64; 32.

Having determined the average value, the reverse operation is performed, i.e., add 800 and divide by 100.

The mean value is the center of the distribution of random variables, around which most of them are grouped. This characteristic is an estimate of the true (general) mean.

η = M(y), determined by the general population, where

M(y) is the mathematical expectation of the random variable y.

The scattering pattern of the random variable y near the expansion center y is the variance or standard deviation

The variance S2(y) is an estimate of the true variance σ2(y) of the population. With a small sample size (measurements, m), when m<30 то применяют следующие формулы:

(3.1)

(3.2)

(3.3)

The coefficient of variation is a relative characteristic of the scattering of a random variable. Estimation CV(y) of the true value of the coefficient of variation Y(y) of a random variable of the general population is determined by the formula:

If expressed as a percentage, then this is called quadratic unevenness.

(3.5)

If the sample is large, i.e. m>30, then to simplify the calculations, the “method of products” or “method of counting from conditional zero Y0*” is used. A number of experimental values are divided into classes (intervals)

k is the number of classes.

k = 3.332 loq m + 1 at 50

k = when m>200

Table 3.1.

Then we determine the interval value:

(3.7) pp. 35 – 36

Depending on Δу, class boundaries and the average value of the class are determined, and then, having distributed all m values by class, the frequency of values by class is determined (Table 2)

Using the data in Table 2, find the average value of the sample:

(3.8)

And the standard deviation:

(3.9)

where normalized parameter value;

Conditional zero, i.e., some initial value corresponding most often to the maximum value mi, is the average value of the class.

Table 3.2.

Class boundaries

Class average

Normalized value of random variables

miAti

Ati2

miAti2

- at max mi

Table 3.3.

it's filling it's being calculated

Class boundaries

We find 3.7;3.5;3.8.

LECTURE №4

Comparison of two variances of normal populations.

Comparison of dispersions is carried out when comparing various technological objects in terms of stability (reproducibility) of their work, when choosing a method for measuring process parameters or product properties that has a smaller error. Comparison of variances is also carried out when determining the significance of the difference between the averages of two series of measurements.

Let S1 and S2 be an estimate of the same normal general variance, it is required to test the hypothesis Н0 ; σ12= σ22 with respect to three competing hypotheses: H1; σ12=σ22; H2; σ12>σ22; H3; σ12<σ22.

Since the random variables Y1 and Y2 are distributed according to the normal law, then the quotient of estimates of the variance of the general population is taken as a criterion for comparing two variances

where in the numerator is the larger of the two scatter estimates (so that F is always greater than 1).

The ratio of variances as a statistical characteristic with the correct hypothesis H0 has a Fisher distribution with m1 – 1 and m2 – 1 degrees of freedom.

The calculated value of the Fisher criterion, determined by the formula:

(4.2)

comparing with Fisher's tabular criterion - Ft.

If FR

If FR>Ft, then the hypothesis H0 is rejected, i.e. the two obtained series of measurements are not equivalent.

Example 1. Let the output parameter of an object at one level of the factor be characterized by the variance S12(y) = 2.8 with the number of degrees of freedom f1 = 2 (the number of measurements is 3); for the second level, respectively, S2(y) = 1.6; f2= 12;

FT[ Pd = 0.95; f1 = 2; f2= 12] = 3.885

Because ,

then the hypothesis about the homogeneity (reproducibility) of the dispersion or the equal accuracy of the two series of measurements U1 and U2 is accepted.

active experiment.

Planning an active experiment.

Planning an experiment is the setting up of experiments according to some predetermined scheme, with some optimal properties.

At present, mathematical and statistical methods of planning experiments have been applied.

The task of planning an experiment includes: the choice of experiments necessary for the experiment, i.e., the construction of a planning matrix, and the choice of methods for mathematical processing of the results of the experiment.

The experiment planning matrix is a table that indicates the values of the levels of factors in various series of experiments. The number of experiments is determined by the objectives of the study and the methods of planning the experiment.

There are two types of active experiment planning: traditional (classical) single-factor and multi-factor (factorial).

With one-factor planning, the influence of input parameters (factors) on the output parameter is studied gradually, and in each series of experiments the level of only one factor changes, while all the others remain unchanged.

Number of levels N = 5

Factor planning An experiment is a design in which all factors are simultaneously varied.

In factorial planning of the experiment, randomization of experiments is carried out, which makes it possible to exclude the influence of uncontrolled factors and consider them as random factors.

Output and input parameters of the process.

With any method of planning an experiment, the output parameters of the process and the input parameters are set, i.e. factors that are subject to measurement and research.

output parameters- characterize the object and properties of the resulting product. They can be: technical and technological, economic, statistical, etc.

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