Стратегии на образователната и научната политика

2024/3s, стр. 105 - 128

APPLICATION OF THE МАTHEMATICAL FUNCTIONS IN THE ECONOMIC ANALYSIS OF THE ENTERPRISE

Резюме:

Ключови думи:

1. Nature of the function

The process of managing a firm is related to the manifestation of a number of functions, one of which is the analysis of the economic processes in the course of its activities. The application of functions in economic analysis is a prerequisite for the realization and study of the economic, technical-economic and socioeconomic processes in the firm. It follows that analysis is a subjective human activity of exploring and studying the processes and phenomena of business activities in particular.

Thus, for example, if there are two sets А and В and the elements of set А are denoted by х, аnd the elements of set В by у, when written it will be in the form of:

А → х; В→ у

А В

Х
У

Figure 1. Sets of a function

It is then said that there is a set function when for an element x of the defined area A, according to a certain rule, is referred to one or several elements у of set B.

In general a function is set in the following way: y = f (x). The main attributes of the main function y = f (x) are as follows:

y – dependent variable (value of the function) or just function;

х – independent variable (argument);

А – domain of a function or a domain of the permissible values of the argument;

В – domain of the permissible values of the function (Boyadzhiev, Kamenov 2002; Dimitrova 2002).

There are several types of functions:

– one-to-one – if to any element x A corresponds exactly one element y B

– many-to-one – if to any element x A correspond several elements y B 2. Correspondence of a function

From a mathematical point of view the concept of “correspondence” is also present as “image”. Through correspondence it can easily be seen whether a certain image is a function or not. By image is meant any correspondence among the elements of two sets – А and В. There are the following types of images:

Surjective – correspondence where each element y B is the image of at least (i.е. at most) one element x A. With surjective all elements of set В are covered.

Injective correspondence where each element y B is the image of (at most) one corresponding element x A;

Bijective correspondence where each element y B is the image exactly of one element x A. With bijective there is surjective, and injective.

ABABnotincorrespondencesurjective

Figure 2. Examples of correspondence of one function

BBAinjectivebijectiveA

Figure 3. Injective, Bijective

3. Setting of functions (Avramov 2000; Aleksandrova 2017; Boyadzhiev, Kamenov 2002; Chukov & Ivanova 2017).

We can say that a function has been set when its components are known. There are several ways in which a function can be set:

3.1. Analytical setting of a function

– Formulaic setting – the connection between argument and function is set through a formula, i.е. in the correspondence y = f(x), which is set with a formula, the actions (algorithms), which need to applied to х in order to get у, are given (written down). With these algorithms we calculate the values of the function at any point in the domain.

Example: y = , x ≠ ± 2

– Explicit presentation (explicit function) the function is solvable in relation to a certain variable and value у can be calculated right away for the defined argument х. It is set with the equation y = f(x), i.е. it is solved in relation to у. If we take, for example, function:

y = x2

then f(x) can be expressed by х.

– Implicit presentation (implicit function) the function is not solvable in relation to any of the two variables, i.е. the definitive equation of the function у is not solved in relation to у but in relation to:

у = f(x,y) = 0

For example, if an equation is set for a circle with a radius 1, then: x2 + y2 – 1 =

0. In many cases it is possible for an implicit presentation to be transformed into an explicit one, for example:

x2 + y2 – 1 = 0

However, such transformation from implicit to explicit form is not always possible. To make such transformation possible, the definition equation must be transformed from unsolved in relation to у to solved in relation to у.

Parametric setting – it stands for the possibility when a function through an intermediate argument is presented in explicit form. Such type of setting has an application in economics, geometry, mechanics and other areas. It is written down in the following way:

where: and are given functions of variable t, called parameter, which is most often used to denote time.

3.2. Tabular setting – the tabular form is most often used for presenting the different values of the independent variable х and the respective values of function y (Aleksandrova 2017; Dellago 2010).

Table 1. Tabular form of setting a function

xx1x2x3xnyy1y2y3yn

– verbally – function of Dirichlet that is defined as: f(x) is equal to 0 for each irrational value of the argument and to 1 for each rational value, i.е:

fx�� �0, if "х" is irrational, 1, if "х" is rational.

3.3. Graphical setting of a function

From a mathematical and economic point of view a function can be presented graphically as it is shown in Figure 4. In general, it is important to observe how the object under study changes along the horizontal x-axis where the time factor is most often observed (denoted by t). Along the vertical у-axis are plotted, for example, volume sold (as number of products) or their value in a specific currency (BGN, EUR, USD, etc.). Graphic presentation of functions is widely used in technical analysis. It is very important to interpret correctly what the plotted function shows in order to make accurate forecasts about the expected fluctuations of currencies or other valuable goods. This is essential for people who trade on the currency market. It is a well-known fact that the environment is highly dynamic and an incorrectly interpreted graph could lead to big financial losses.

Figure 4. Graphic image of a function

4. Properties of functions(Hristov 2018; Kirkorov, Bonev 1980; Dellago 2010)1:

4.1. Domain – it consists of the quantity of all arguments for which the function is defined. If we take the domain of real numbers R only then can we distinguish between the following intervals:

Open interval:

(а,b) = {x R | a < x < b}

Close interval:

[а,b] = {x R | a ≤ x ≤ b}

4.2. Even and odd function, zero position

If function f(x) is set and is defined within an interval of the (-l, +l) type, where l>0 then for each х of that interval we get:

even function f(x) = f(-x)

Even functions are for example: х2; х4; x2n, etc.

odd function

f(x) = -f(-x)

Odd functions are for example: х3; х5; x2n-1, etc.

It is important to point out that most functions are neither even nor odd. There is a theorem which says that each function f(x) can be presented as the sum of an even and an odd function, i.е:

f(x) = φ(x) + Ψ (x), where: φ(x) – even function

Ψ (x) – odd function

zero position

A function y = f(x) has a zero position at x0, when f(x0) = 0. If we obtain, for example, as the answer to a given function respectively for: х1= - 0,5 and for х2 = + 0,5, then the function at х1 and х2 has zero positions.

Function f(x0) = 0 is the only function, which is even and odd at the same time, i.е., if it is plotted, its graph is the horizontal axis, which is symmetric to Оу, and to the origin О.

It is important to be noted that there exist periodic functions, as well as inverse functions with greater application in mathematics rather than in economics but they are not the object of study of the present paper.

4.3. Monotonicity

When there is a difference between:

∆у = f(x2) f(x1), where: x1 and x2 are respectively two values of the argument of the domain then there is an increase of function f(x). The difference between x1 and x2 is called argument increase. It has the following form:

∆х = x2 x1

Monotonically increasing function – if х1 and х2 are any points of D, for which х1 < х2, and if f (х1) ≤ f (х 2) follows from it we say that the given function is monotonically increasing at D.

Increasing (strictly increasing) function – if we have the strict equation f (х1) < f (х2), a function is called increasing and also strictly increasing.

According to some authors the types of monotonic functions are (Grifell & Knox Lovell 2015)2:

Strictly monotonically increasing:

Monotonically increasing:

Monotonically decreasing:

Strictly monotonically decreasing:

Figure 5. Monotonicity

Figure 6. Monotonically decreasing functions

Fig. 6 shows a monotonically decreasing and a strictly monotonically decreasing function with the following characteristics:

Monotonically decreasing:

f(x1) ≥ f(x2 )

Strictly monotonically decreasing:

f(x1) > f(x2 )

Fig. 7 shows a monotonically decreasing and a strictly monotonically decreasing function with the following characteristics:

Strictly monotonically increasing:

f(x1) < f(x2 )

Monotonically increasing:

f(x1) ≤ f(x2 )

Figure 7. Monotonically increasing functions

Fig. 8 shows all types of monotonic functions – both decreasing and increasing.

Figure 8. Monotonically decreasing and increasing functions

In Fig. 8 the monotonic functions are as follows:

1 – strictly monotonically decreasing; 2 – monotonically decreasing; 3 – monotonically increasing; 4 – strictly monotonically increasing.

4.4. Extremum, minimum and maximum of a function

We say there is an extremum of a function at a certain point when the value of that function is a maximum or a minimum at that point.

If there is a function f(x), which is set in the interval (a,b) and х0 (a,b), then it is said that function f(x) will have a maximum f(х0) at point х0, and if there is an environment P of point х0, for which the following is true:

f(x) ≤ f (x0) | x P.

therefore, there will be:

a strict maximum

f(x) < f (x0) | x P, x ≠ x0

a minimum

f(x) ≥ f (x0) | x P

a strict minimum

f(x) > f (x0) | x P, x ≠ x0

5. Main functions applicable in economics

5.1. Linear function

The function is set as follows:

f(x) = kx + b,

where: к – slope coefficient b – intercept.

If it is given as a simple equation,

y = (±) kx + b,

then it can be said that the slope can be both positive and negative. It has a special application in plotting a trend, i.е., if it is set for a group of goods of the type:

y = -1,2x + 141,8

we draw the conclusion that there is a negative trend and vice versa if we have the equation

y = 1128,2х + 36111,

the trend (tendency) will be positive.

With such an equation or function the sign of the coefficient is important. Depending on what it is we come to the respective conclusions.

There are special linear functions – such are the identity function: y = x, and the constant function: y = b

Therefore, on order to say that there is a rising trend, there must be at least two points, which are connected and each following value is greater than the previous one. For a falling trend two or more points must be connected and each following value must be smaller than the previous one.

Figure 9. Linear function

The figure above shows that к is the angle between the graph of the function and the horizontal axis (Ох), while b shows the ordinate coordinates of the point where the graph crosses the horizontal axis (Oy).

5.2. Power function

Power xn is the product of n equal factors:

хn = x.x.x….xn,

where х is called basis(base), and n exponent. With this function n is a random real number. When they accept different values, we get different power functions.

5.3. Exponential function

The exponential function is seen as a function equal to its own derivative. It is denoted by ex, where е is Euler’s number with the following value: е = 2.718281828. What is characteristic of it is that it has a proportional rate of change, i.е. if there is a change in the fixed value of the independent variable then there is proportional change (it can be a percentage increase or decrease) in the value of the function itself.

The exponential function has the form of:

f(x) = ax

There the real positive number а is the base, аnd х is the exponent.

It is the exponential function that defines the е base through a power series with an infinite number of members:

1 �  � 2! 3! � � !

It can be defined as:

ехlim1���

An exponential function with base е is often written in the following way: f(x)=exp(x)

5.4. Logarithmic function

Graphically it can be plotted as a mirror image of the exponential function at an angle of 45 degrees. The logarithm is written to the base а of the number х as:

loga(x)

The logarithm of the number х to base а is such a number to which а must be raised in order to obtain х.

y = loga(x) ay = x

5.5. Polynomial function

Polynomial function is obtained when the value of a polynom.

A polynom is for example:

P(x) = anxn + an-1xn-1 + ….+ a1x + a0

We can draw the conclusion that there are the following types of functions, which can be used in economic and technical analysis: linear, power, exponential, logarithmic and polynomial. Each of these has its advantages and disadvantages. The easiest of them to use in economic analysis is the linear function because of its clarity and ease of use. The other types of functions can also be used for interpreting a trend but are more complicated, аnd the exponential function is more widely used in technical than in economic analysis.

6. Types of functions applicable to economic analysis of an industrial firm

6.1. Costs, revenue, profit

function of the revenue:

R(x) /R – revenue/

function of the costs:

C(x) /C – costs/

function of the profit:

P(x) /P – profit/

In order to calculate the profit we need to write the equation in the following way:

P(x) = R(x) – C(x),

where: х is the volume of the products.

There is a profit when P > 0 (R > C) and a loss when P < 0 (R < C).

Economic analysis makes use of optimization models whose application aims to achieve:

maximum value of the profit;

maximum value of the revenue;

minimum value of the costs.

6.2. Functions of two or more variables

If the variables x,y and z are given x and y are not related but z is considered to be dependent on them, i.е. to be their function and z is defined as an aggregate of the two variables (x,y). Z will be called a function of the two variables x and y, when a certain value of z corresponds to each pair of numbers (x,y) from set D. It is denoted by:

z = f (x,y)

For example, if an industrial company produces laptops (x) and mobile phones (y) it is known that the constant daily costs for х and у are respectively:

x = 700 EUR;

y = 300 EUR.

The variable costs for a unit of production for х and у respectively are:

x = 120 EUR;

y = 170 EUR.

Therefore, for the daily production the function of the costs would look as:

C (x,y) = 700 + 120x + 300 + 170y = 1000 + +120x + 170y

C (x,y) = 1000 + 120x + 170y

7. Moving average (Grifell & Knox Lovell 2015)1

The moving average value has an application in technical analysis rather than in economic analysis.

The moving average is by its nature a statistical function. It includes the average values of a certain series which have been calculated. These average values are values of different subsets of values from a certain set. It is employed mostly in time series for analysis of changing trends.

It can be employed in economic analysis if there is the need to study the average of products sold over a time period t. It is also possible to use several moving average functions, each of them set for a particular time period. The crossing point of the moving averages shows the change in the trend.

8. Coefficient of determination in economic analysis

The coefficient of determination is a very important part of an economic or statistic analysis, especially when some relationship between the objects of the analysis is studied or must be found. From the perspective of functions it will refer to the relation and the effect х has on у or vice versa - the relation and the effect у has on х.

The coefficient of determination (Кdet=R),2 is equal to the square of the coefficient of correlation and describes the so called explained dispersion. It usually varies within the range of 0 ≤ R2 ≤ 1. Through the coefficient of determination a check is made about the availability of linear relation between x and y. It shows what part of the Y variation is due to the differences between the values of Х, i.е. the impact of the studied factor. If it is multiplied by 100, it expresses the force of the impact of the dependent variable and then we obtain limits in percentage: 0% ≤ R2 ≤ 100%. In scientific literature the coefficient of determination is also present as “coefficient of definiteness“. The coefficient of definiteness (determination) and indefiniteness are added to get one (100%). If we haveR=2 70 %, and К2 = 30% then we get:

R2 + К2 = 70% + 30% = 100 %

As limits of the coefficient of correlation are given two scales which are formed from the scales of the coefficient of correlation (R) (Aleksandrova 2017; Kirkorov, Bonev 1980; Grifell, Knox Lovell 2015):

Table 2. Values of the coefficient of correlation (R)

Variant 1RInterpretation - RVariant 2R0 < R < 0,3weak correlation0 – 0,20,3 < R < 0,5moderate correlation0,2 – 0,40,5 < R< 0,7significant correlation0,4 – 0,60,7 < R < 0,9high correlation0,6 – 0,80,9 < R < 1very high correlation0,8 - 1

Table 3. Values of the coefficient of correlation (R2)

Variant 1R2Interpretation – R2Variant 2R20% < R2< 9%weak correlation0% – 4%9% < R2< 25%moderate correlation4% – 16%25%< R2< 49%signicant correlation16% – 36%49%< R2< 81%high correlation36% – 64%81%<R2< 100%Very high correlation64% - 100%

The calculations are made in the following way:

If we take as the coefficient of correlation the value of R = 0,3 in order to obtain the coefficient of determination (R2) we must square the value of the coefficient of correlation and multiply it by 100 in order to obtain the number in %, i.е.:

R = 0,3 => R2 = (0,3)2 * 100% = 9%

9. Practical application of the functions in economics. Drawing a trend and its interpretation

The object of study is an industrial company, which produces 2 types of items, respectively “А” – contactors and “B”- relays. The sales of the two products are presented (Angelova, Borisova 2019) in Table 4:

Table 4. Sales of items “А”and “B”

MonthItemΣ(А+В)А [number]В [number]11001202202951302253110100210412514026551351302656120140260712015027081001402409130140270101351302651114015029012120140260Σ143016103040

The total number of products “А” sold for the whole year is 1430 and of “B”1610.

The graph below shows sales of product “А” and the trend is obtained through the use of the different types of functions. In a similar way the graph for product “B” can be drawn.

9.1. Exponential function

Figure 10. Exponential fuction

y = 102,66e0,0218x R2 = 0,3649

We have obtained an equation, which is not with a negative sign and that means that the trend is positive, i.е. if the sales have similar values the firm will have a good profit and will not have any losses. There is a moderate correlation between the values.

It is necessary to pay attention to the fact that the values for each month are interlinked with previous months and future periods as in a system there is the impact of both direct and indirect factors. Figure 11 illustrates the impact of the external and internal factors. The ellipsis shows the external environment of the firm. The numbers 1,2 and 3 stand for the volume of sales and the size of the circle demonstrates whether sales have decreased or increased as compared to the previous period. The arrows pointing to the inside of the ellipsis show how external factors penetrate the internal environment of the firm, аnd the triangles (∆) denote internal factors. External factors can be, for example political and legal changes, inflation, etc. Internal factors can be problems within the enterprise itself such as: lack of assembly elements for a specific item or an abrupt deterioration of its financial situation, insufficient workforce and as a result of these factors reduction in orders. That is why it is necessary to seek and study a “hidden” relation between the values in order for the enterprise to be able to respond adequately in a certain situation.

Figure 11. External and internal factors of an enterprise

9.2. Linear function

Figure 12. Linear function

y = 2,5175x + 102,8

R2 = 0,3637

With the linear function there is also positive trend with moderate correlation.

The linear function is one of the most widely used functions for interpretation in economic analysis. That advantage is manifested by the fact of the easy calculation and interpretation of the obtained equation and with its graphic image. It is important to note the slope of the line if one is not capable of dealing with equations. In that particular case the line is with a positive slope, therefore, we can come to the conclusion that the trend (tendency) is positive. If we have to come up with a more accurate interpretation we can say that the tendency is moderately positive because as it can be seen from the graph there is not a strictly expressed slope of the line to the х axis, i.е. the angle coefficient has a small positive value. The interpretation of the line can be made even as an analogue to the different types of monotonic functions.

9.3. Logarithmic function

Figure 13. Logarithmic function

y = 13,095ln(x) + 97,355

R2 = 0,4325

With the logarithmic function we again have a positive trend. The coefficient of determination is within moderate limits.

Here the trend is shown by means of a natural logarythm – ln. It is a logarythm with a base of the number e = 2,718 281 828 459 045 235 360 287 471 35… The е number is called Napier’s number.

9.4.Polynomial function

Figure 14. Polynomial function y = 0,3322x2 + 6,8357x + 92,727 R2 = 0,4228

As this is a polynomial function, respectively the function is obtained through polynoms, which are used for interpolation and extrapolation. In that particular case we also have positive values, the trend is a positive value, аnd the coefficient of determination is moderate.

9.5. Power function

Figure 15. Power function y = 97,792x0,1141 R2 = 0,4291

The power function is with a positive value like the other functions and tendency with the same coefficient of determination, i.е. it is with a moderate value.

With the exponential, logarithmic, polynomial and power functions the way of interpreting them is the same as with the linear function, but unlike the linear function, they are more difficult to interpret in view of the obtained equations and images. They are not straight lines and that further makes their interpretation more difficult. That is why it is recommended that the linear graph is used in economic and technical analyses.

Based on the above data, it can be stated that the determination coefficient is in relatively close limits for the linear and exponential functions – in interval [0,3637; 0,3649] or the average value is 0,3643.

The same inference can be done for the rest of the functions – logarithmic, polynomial and power. The determination coefficient is in the interval [0,4228; 0,4325] with an average value – 0,4281. The deviation between the mean values of the coefficient of determination between the individual functions is 0,0638.

9.6 Moving average1

Table 5 shows a moving average plotted on the basis of average values by quarters using the data in Table 4.

Table 5. Average sales of products “А” and “В”

MonthItemΣ (А+В)AВ100021021172193000400051271372646000700081171432609000100001113214027212000Σ4785371015

On fig. 17 is applied moving average between two periods:

Figure 17. Moving average according to Table 4

Figure 18. Moving average

Using the moving average plotted in Fig. 16 we can come to the conclusion that there is a change in trend in the third quarter as the graph has a V-imaged bottom. It is further noted that the trend will be positive as there is a slight positive slope between the third and the fourth quarter.

Fig. 17 shows what, with the same average values, a trend will look like if it is plotted using a linear function. It can again be seen that it is positive, both visually, and from the interpretation of the analytically set function.

Figure 19. Linear function of the trend at averaged values

y = 8x + 99,5 R2 = 0,6095 10. Recommended research methodology

Based on the mentioned functions, the following methodology can be proposed for performing the analysis:

1) Selection of the object/subject of research;

2) Preparation for data collection, for example – whether it will be intervalgrouped data or individual independent quantities, etc.;

3) Before data collection, a control check is made of the selected data collection tools for final processing and analysis;

4) Carrying out a test-check;

5) Carrying out the site survey and data collection;

6) On-site review of the processed data for possible omissions and/or errors;

7) Selection of the type of function to be used according to the available data; (When selecting multiple features, this should be pre-ordered from most significant to least significant.)

8) Entering the data in a given software product;

9) Obtaining a result to be interpreted;

10) Conclusion.

If several functions are used for the same study, it should be monitored what they show, whether the previous one is confirmed or a different result is obtained. As in any one separate field, several functions may indicate approximately the same thing, but one of them gives a more complete picture of the particular study. From an investment point of view, most practitioners prefer, especially when tracking price movements, to apply an exponential function, as it can show the expected trend much more accurately than a linear one.

Conclusion

The authors present six functions and their practical application in economic analysis by means of establishing trends and their interpretation. On the basis of the study that was carried out we can come to the conclusion that the function with the greatest application in economic analysis is the linear one when there are sequential data for a certain period of time t. It is the function that provides clear and accurate picture of the dynamics of the resulting indicator on the basis of more than one period of study. When we deal with averaged values it is appropriate to use the moving average function. We need to point out that with averaged values we can also obtain information about a trend from a linear function.

It is a matter of judgement on behalf of the experts whether to use an exponential, logarithmic, polynomial or power function in their future financial-economic analyses.

Acknowledgements

The authors would like to thank the Research and Development Sector at the Technical University of Sofia for the financial support.

NOTES

1. https://www.matematika.bg/algebra/functions.html.

2. https://bg.wikipedia.org/wiki/Funktsiya#Vidove_funktsii; https://www.matematika.bg/algebra/functions.html.

3. Ibid.

4. https://www.matematika.bg/algebra/functions.html.

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ВЛИЯНИЕ НА ОБРАЗОВАНИЕТО И ЧОВЕШКИЯ КАПИТАЛ ВЪРХУ ФОРМАЛНАТА И НЕФОРМАЛНАТА ИКОНОМИКА

Проф. д-р Стефан Петранов, доц. д-р Стела Ралева, доц. д-р Димитър Златинов

DETERMINANTS AFFECTING ACADEMIC STAFF SATISFACTION WITH ONLINE LEARNING IN HIGHER MEDICAL EDUCATION

Dr. Miglena Tarnovska, Assoc.Prof.; Dr. Rumyana Stoyanova, Assoc.Prof.; Dr. Angelina Kirkova-Bogdanova; Prof. Rositsa Dimova

Книжка 1s
CHALLENGES FACED BY THE BULGARIAN UNIVERSITIES IN THE CONTEXT OF SCIENCE – INDUSTRY RELATIONS

Dr. Svetla Boneva, Assoc. Prof., Dr. Nikolay Krushkov, Assoc. Prof.

INVENTING THE FUTURE: CAN BULGARIAN UNIVERSITIES FULFILL THEIR MISSION AS CATALYSTS FOR ECONOMIC GROWTH AND SUSTAINABILITY?

Dr. Ralitsa Zayakova-Krushkova, Assist. Prof., Dr. Alexander Mitov, Assoc. Prof.

AN INNOVATIVE MODEL FOR DEVELOPING DIGITAL COMPETENCES OF SOCIAL WORKERS

Prof Dr. Lyudmila Vekova, Dr. Tanya Vazova, Chief Assist. Prof., Dr. Penyo Georgiev, Chief Assist. Prof., Dr. Ekaterina Uzhikanova-Kovacheva

BUSINESS ASPECTS OF ACADEMIC PUBLISHING

Dr. Polina Stoyanova, Chief Assist. Prof.

THE ECONOMIC IMPACT OF MUSIC STREAMING

Dr. Dimiter Gantchev, Assist. Prof.

FILM INCENTIVE SCHEME IN THE REPUBLIC OF BULGARIA

Dr. Ivan Nachev, Assist. Prof.

PATENT PROTECTION OF DIGITAL TWINS

Dr. Vladislava Pаcheva, Chief Assist. Prof.

Книжка 1

МНОГОСТРАНЕН ПОДХОД ЗА ИЗСЛЕДВАНЕ РАВНИЩЕТО НА ДИГИТАЛИЗАЦИЯ В ПОДГОТОВКАТА НА БЪДЕЩИ УЧИТЕЛИ

Доц. д-р Бистра Мизова, проф. д-р Румяна Пейчева-Форсайт Проф. д-р Харви Мелър

2024 година
Книжка 6s
DISRUPTIVE TECHNOLOGIES RISK MANAGEMENT

Dr. Miglena Molhova-Vladova, Dr. Ivaylo B. Ivanov

THE DUAL IMPACT OF ARTIFICIAL INTELLIGENCE: CATALYST FOR INNOVATION OR THREAT TO STABILITY

Prof. Diana Antonova, Dr. Silvia Beloeva, Assist. Prof., Ana Todorova, PhD student

MARKETING IN TOURISM: PRACTICAL EVIDENCES

Dr. Fahri Idriz, Assoc. Prof.

DEVELOPMENT OF THE INFORMATION ECONOMY CONCEPT AND THE TRANSITION TO INDUSTRY 5.0

Dr. Dora Doncheva, Assist. Prof., Dr. Dimitrina Stoyancheva, Assoc. Prof.

THE GLOBAL MARKET AS A PROJECTION OF THE INFORMATION ECONOMY

Dr. Vanya Hadzhieva, Assist. Prof. Dr. Dora Doncheva, Assist. Prof.

ACADEMIC ENTREPRENEURSHIP: PRACTICAL RESULTS AND TRAINING

Prof. Nikolay Sterev, DSc., Dr. Daniel Yordanov, Assoc. Prof.

Книжка 6
AN INTEGRATIVE APPROACH TO ORGANIZING THE FORMATION OF STUDENTS’ COGNITIVE INDEPENDENCE IN CONDITIONS OF INTENSIFICATION OF LEARNING ACTIVITIES

Dr. Albina Volkotrubova, Assoc. Prof. Aidai Kasymova Prof. Zoriana Hbur, DSc. Assoc. Prof. Antonina Kichuk, DSc. Dr. Svitlana Koshova, Assoc. Prof. Dr. Svitlana Khodakivska, Assoc. Prof.

ИНОВАТИВЕН МОДЕЛ НА ПРОЕКТНО БАЗИРАНО ОБУЧЕНИЕ НА ГИМНАЗИАЛНИ УЧИТЕЛИ: ДОБРА ПРАКТИКА ОТ УниБИТ

Проф. д-р Жоржета Назърска, доц. д-р Александър Каракачанов, проф. д-р Магдалена Гарванова, доц. д-р Нина Дебрюне

Книжка 5s
КОНЦЕПТУАЛНА РАМКА ЗА ИЗПОЛЗВАНЕ НА ИЗКУСТВЕНИЯ ИНТЕЛЕКТ ВЪВ ВИСШЕТО ОБРАЗОВАНИЕ

Акад. д.н. Христо Белоев, проф. д.н. Валентина Войноховска, проф. д-р Ангел Смрикаров

ИЗКУСТВЕНИЯТ ИНТЕЛЕКТ В БИЗНЕСА – ФИНАНСОВИ, ИКОНОМИЧЕСКИ И МАРКЕТИНГОВИ АСПЕКТИ

Проф. д-р Андрей Захариев, доц. д-р Драгомир Илиев Гл. ас. д-р Даниела Илиева

RECENT TRENDS AND APPLICATIONS OF THE ARTIFICIAL INTELLIGENCE IN THE EDUCATION

Prof. Dr. Plamen Zahariev, Prof. Dr. Georgi Hristov, Prof. Dr. Ivan Beloev

COMPARATIVE ANALYSIS OF UTILIZING POPULAR INTELLIGENT COMPUTER SYSTEMS IN EDUCATION

Dr. Galina Ivanova, Assoc. Prof. Dr. Aleksandar Ivanov, Assoc. Prof.

CONCEPTUAL MODEL OF TRAINING IN REMOTE VIRTUAL SUPERVISION IN SOCIAL WORK

Dr. Silviya Beloeva, Assist. Prof. Dr. Nataliya Venelinova, Assist. Prof.

ИЗСЛЕДВАНЕ ПРИЛОЖИМОСТТА НА БЛОКОВИ ВЕРИГИ ОТ ПЪРВО НИВО (L1) В СИСТЕМА ЗА ЕЛЕКТРОННО ОБУЧЕНИЕ

Андриан Минчев, проф. Ваня Стойкова, гл. ас. д-р Галя Шивачева Доц д-р Анелия Иванова

DIGITAL DISCRIMINATION RISKS IN THE TRANSFORMATION OF HIGHER EDUCATION

Dr. Silviya Beloeva, Assist. Prof. Dr. Nataliya Venelinova, Assist. Prof.

OPPORTUNITIES, CHALLENGES AND SOLUTIONS FOR DIGITAL TRANSFORMATION OF THE EDUCATIONAL PROCESSES THROUGH 3D TECHNOLOGIES

Prof. Georgi Hristov, Prof. Plamen Zahariev, Dr. Diyana Kinaneva, Assist. Prof., Georgi Georgiev, Assist. Prof.

ДИГИТАЛНОТО ПОКОЛЕНИЕ VS. СЛЯТОТО, ПОЛУСЛЯТОТО И РАЗДЕЛНОТО ПИСАНЕ

Доц. д-р Владислав Маринов, ас. Анита Тодоранова

OPPORTUNITIES AND CHALLENGES FOR THE EDUCATION OF STUDENTS WITH SPECIAL EDUCATIONAL NEEDS IN THE DIGITAL ENVIRONMENT: THE NEW NORMAL

Prof. Julia Doncheva, DSc., Dr. Galina Ivanova, Assoc. Prof. Dilshod Tojievich Oblokulov

ИЗГРАЖДАНЕ НА КОМПЕТЕНЦИИ ЗА РАЗРАБОТВАНЕ НА STEM ОБУЧИТЕЛНИ РЕСУРСИ У БЪДЕЩИ УЧИТЕЛИ ПО ПРИРОДНИ НАУКИ

Доц. д-р Евгения Горанова, проф. д.н. Валентина Войноховска, проф. д-р Ангел Смрикаров

APPLICATION OF ZSPACE TECHNOLOGY IN THE DISCIPLINES OF THE STEM CYCLE

Boyana Ivanova, Assist. Prof. Dr. Kamelia Shoilekova, Assoc. Prof. Dr. Desislava Atanasova, Assoc. Prof. Dr. Rumen Rusev, Assoc. Prof.

TEACHERS' ADAPTATION TO CHANGES IN AN INCREASINGLY COMPLEX WORLD THROUGH THE USE OF AI

Prof. Zhanat Nurbekova, Kanagat Baigusheva, Kalima Tuenbaeva, Bakyt Nurbekov Prof. Tsvetomir Vassilev

АТОСЕКУНДНОТО ОБУЧЕНИЕ – МЕТАФОРА НА ДНЕШНОТО ОБРАЗОВАНИЕ

Проф. д.н. Юлия Дончева, Денис Асенов, проф. д-р Ангел Смрикаров проф. д-р Цветомир Василев

APPLICATION AND ASSESSMENT OF DIGITAL RESOURCES IN THE EDUCATION OF FUTURE PEDAGOGUES

Dr. Galina Ivanova, Assoc. Prof., Dr. Milena Velikova, Assist. Prof.

IDENTIFYING PLAYER TYPES IN THE CLASSROOM FOR EFFECTIVE GAMIFICATION

Dr. Desislava Atanasova, Assoc. Prof., Viliana Molnar

DEVELOPMENT AND INTEGRATION OF AUDIO AND VISUAL MICRO-RESOURCES IN THE LEARNING PROCESS THROUGH THE USE OF ARTIFICIAL INTELLIGENCE SYSTEMS

Dr. Petya Stefanova, Assist. Prof., Dr. Assist. Elitsa Ibryamova, Assist. Prof., Prof. Angel Smrikarov, Dr. Galina Ivanova, Assoc. Prof.

АНАЛИЗ НА ПРОГРАМНИТЕ МОДЕЛИ ЗА АВТОМАТИЗИРАНЕ НА КОГНИТИВНИ ПРОЦЕСИ

Доц. д-р Валентин Атанасов Доц. д-р Анелия Иванова

Книжка 5
MANAGING A POSITIVE AND LIFE-SKILLS DEVELOPMENT IN THE SCHOOL-BASED CURRICULA: A LITERATURE REVIEW ON THE SUSTAINABLE EDUCATION

Dr. Lindita Durmishi, Assoc. Prof., Dr. Ardian Durmishi Prof. Milena Filipova Dr. Silva Ibrahimi

APPLICATION OF THE COMPETENCY MODEL IN BUSINESS ADMINISTARATION HIGHER EDUCATION IN HORIZON 2030

Prof. Nadya Mironova, Dr. Tatyana Kicheva, Assoc. Prof., Dr. Miglena Angelova, Assoc. Prof.

Книжка 4s
THE EDUCATION AND RESEARCH IN THE QUADRUPLE HELIX AND THE REGIONAL INNOVATION PROSPECTS

Prof. Dr. Milen Baltov Dr. Stela Baltova, Assoc. Prof. Dr. Vilyana Ruseva, Assoc. Prof.

Книжка 4
ATTITUDES OF STUDENTS – FUTURE TEACHERS, FOR THE APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE

Assoc. Prof. Nikolay Tsankov, DSc. Dr. Ivo Damyanov, Assist. Prof.

EDUCATIONAL NEEDS OF THE JUDICIAL ADMINISTRATION IN THE CONTEXT OF DIGITALIZATION

Dr. Diana Dimitrova, Dr. Darina Dimitrova, Assoc. Prof., Dr. Velina Koleva

MANAGERIAL ASPECTS OF COOPERATION AMONG HIGHER EDUCATION INSTITUTIONS AND THEIR STAKEHOLDERS

Prof. Olha Prokopenko, DSc. Dr. Svitlana Perova, Assoc. Prof. Prof. Tokhir Rakhimov, DSc.

APPLICATION OF EDUCATIONAL STRATEGIES IN STUDYING THE DYNAMICS OF STATE POWER STRUCTURES: IMPLEMENTATION OF FORMAL AND INFORMAL MECHANISMS OF INFLUENCE

Prof. Stoyan Denchev, DSc. Dr. Miriyana Pavlova, Assist. Prof. Dr. Steliana Yordanova, Assist. Prof.

ДИАГНОСТИКА НА ФОРМИРАНАТА ПРОФЕСИОНАЛНА КОМПЕТЕНТНОСТ НА БЪДЕЩИ ИНЖЕНЕРИ ПО ЕНЕРГЕТИКА

Гл. ас. д-р Надя Илиева Доц. д-р Елена Бояджиева Ивалина Маринова

Книжка 3s
A MODEL FOR CALCULATING THE INDIRECT ADDED VALUE OF AI FOR BUSINESS

Dr. Petya Biolcheva, Assoc. Prof., Prof. Nikolay Sterev, DSc.

AI EFFECTIVENESS AND RISK ASSESSMENT OF INVESTMENTS IN HIGH-RISK START-UPS

Sotir Ivanov, PhD Student, Dr. Petya Biolcheva, Assoc. Prof.

COMPETITIVENESS OF TEXTILE PRODUCERS IN DIGITAL BUSINESS ERA

Prof. Nikolay Sterev, DSc., Dr. Vyara Milusheva, Assoc. Prof.

CHALLANGES OF USING ARTIFICIAL INTELLIGENCE IN MANAGEMENT DECISION MAKING

Dr. Bozhana Stoycheva, Assist. Prof. Dr. Pavel Vitliemov, Assoc. Prof.

THE SIGNIFICANCE OF ERASMUS+ MOBILITY IN BUSINESS EDUCATION: AN EXAMINATION OF A SUCCESSFUL BULGARIAN-MEXICAN COLLABORATION

Dr. Lyudmila Mihaylova, Assoc. Prof. Dr. Emil Papazov, Assoc. Prof. Dr. Diana E. Woolfolk Ruiz

Книжка 3
ИГРОВИ ПОДХОДИ В ОБУЧЕНИЕТО: УНИВЕРСИТЕТСКИ КОНТЕКСТ

Проф. д.н. Цветан Давидков Силвия Тонева, докторант

Книжка 2
FORMATION OF PROFESSIONAL SKILLS OF AGRICULTURAL ENGINEERS DURING LABORATORY PRACTICE WHEN STUDYING FUNDAMENTAL SCIENCE

Dr. Ivan Beloev, Assoc. Prof. Dr. Oksana Bulgakova, Assoc. Prof., Dr. Oksana Zakhutska, Assoc. Prof., Dr. Maria Bondar, Assoc. Prof. Dr. Lesia Zbaravska, Assoc. Prof.

ИМИДЖ НА УНИВЕРСИТЕТА

Проф. д.п.н. Галя Христозова

Книжка 1s
COMPETITIVENESS AS A RESULT OF CREATIVITY AND INNOVATION

Dr. Nikolay Krushkov, Assoc. Prof. Dr. Ralitza Zayakova-Krushkova

INNOVATION, TECHNICAL PROGRESS AND ECONOMIC DEVELOPMENT

Dr. Aleksandar Aleksandrov, Assist. Prof.

ENHANCING ECONOMIC SECURITY THROUGH INTELLECTUAL PROPERTY

Dr. Dimiter Gantchev, Assist. Prof.

INTELLECTUAL PROPERTY AND SECURITY IN THE INTEGRATED CIRCUITS INDUSTRY

Dr. Ivan Nachev, Dr. Yuliana Tomova, Iskren Konstantinov, PhD student, Marina Spasova, student

GREEN TRADEMARKS AND SUSTAINABILITY

Dr. Silviya Todorova, Assist. Prof.

ARTIFICIAL INTELLIGENCE AND ITS PROTECTION AS AN INVENTION

Dr. Vladislava Pаcheva, Assist. Prof.

Книжка 1
PROBLEMS AND PERSPECTIVES FOR SOCIAL ENTREPRENEURSHIP IN HIGHER EDUCATION

Prof. Dr. Milena Filipova Prof. Dr. Olha Prokopenko Prof. Dr. Igor Matyushenko, Dr. Olena Khanova, Assoc. Prof. Dr. Olga Shirobokova, Assoc. Prof. Dr. Ardian Durmishi

RESEARCH OF USING THE SYSTEM APPROACH TO INCREASE PROFESSIONAL COMPETENCE OF STUDENTS IN THE PROCESS OF STUDYING NATURAL SCIENCES

Dr. Ivan Beloev, Assoc. Prof. Dr. Іnna Savytska, Assoc. Prof., Dr. Oksana Bulgakova, Assoc. Prof. Prof. Iryna Yasinetska, Dr. Lesia Zbaravska, Assoc. Prof.

2023 година
Книжка 6s
TRANSFORMING MARITIME EDUCATION FOR A DIGITAL INDUSTRY

Dr. Christiana Atanasova, Assist. Prof.

DEVELOPMENT OF A COMMON INFORMATION SYSTEM TO CREATE A DIGITAL CAREER CENTER TOGETHER WITH PARTNER HIGHER SCHOOLS

Prof. Dr. Yordanka Angelova, Dr. Rossen Radonov, Assoc. Prof. Vasil Kuzmov, Assist. Prof. Stela Zhorzh Derelieva-Konstantinova

DRAFTING A DIGITAL TRANSFORMATION STRATEGY FOR PROJECT MANAGEMENT SECTOR – EMPIRICAL STUDY ON UAE

Mounir el Khatib, Shikha al Ali, Ibrahim Alharam, Ali Alhajeri Dr. Gabriela Peneva, Assist. Prof., Prof. Jordanka Angelova, Mahmoud Shanaa

VOYAGE OF LEARNING: CRUISE SHIPS WEATHER ROUTING AND MARITIME EDUCATION

Prof. Svetlana Dimitrakieva, Dr. Dobrin Milev, Assist. Prof., Dr. Christiana Atanasova, Assist. Prof.

RESEARCH ON THE SUSTAINABLE DEVELOPMENT COMPETENCES OF THE LANDSCAPE ARCHITECT IN PRACTICE

Land. arch. Elena Dragozova, Assoc. Prof., Dr. Stanislava Kovacheva, Assoc. Prof.

STUDY OF THE KEY FACTORS INFLUENCING THE EFFECTIVE PLANNING AND UTILIZATION OF PRODUCTION FACILITIES IN THE INDUSTRIAL ENTERPRISE

Dr. Tanya Panayotova, Assoc. Prof., Dr. Krasimira Dimitrova, Assoc. Prof., Neli Veleva, PhD student

SIMULATOR TRAINING – UNIQUE POWERFUL INSTRUMENT FOR EDUCATING, SKILLS CREATING, MITIGATING SKILLS AND RESILIENCE CREATING

Prof. Dimitar Dimitrakiev, Vencislav Stankov, Assist. Prof., Dr. Christiana Atanasova, Assist. Prof.

СТРУКТУРНИ ПРОМЕНИ В ОБУЧЕНИЕТО НА МЕНИДЖЪРИ ЗА ИНДУСТРИЯ 5.0

Доц. д-р Недко Минчев, доц. д-р Венета Христова, гл. ас. д-р Иван Стоянов

RESEARCH OF THE INNOVATION CAPACITY OF AGRICULTURAL PRODUCERS

Dr. Siya Veleva, Assoc. Prof.; Prof. Dr. Eng. Margarita Mondeshka Dr. Anka Tsvetanova, Assoc. Prof.,

Книжка 6
Книжка 5s
ПРЕСЕЧНАТА ТОЧКА НА СПОРТА, СИГУРНОСТТА И КРИПТО ФЕН ТОКЕНИТЕ

Полк. доц. Георги Маринов Доц. Милена Кулева

ВИДОВЕ ТРАВМИ В ПАРАШУТИЗМА И ПРЕВЕНЦИЯТА ИМ

Капитан III ранг Георги Калинов

ОБУЧЕНИЕ В ХОДЕНЕ С ПОМОЩНИ СРЕДСТВА – РИСКОВЕ И СИГУРНОСТ ЗА ПАЦИЕНТА

Атанас Друмев Доц. д-р Данелина Вачева, доц. д-р Искра Петкова

Книжка 5
ПОДХОДИ ЗА ПСИХОСОЦИАЛНА ПОДКРЕПА НА УНИВЕРСИТЕТСКИ ПРЕПОДАВАТЕЛИ В УСЛОВИЯ НА КРИЗА

Доц. д.н. Цветелина Търпоманова, доц. д.н. Веселина Славова

Книжка 4s
DETERMINING THE DEGREE OF DIGITALIZATION OF A HIGHER EDUCATION INSTITUTION

Acad. DSc. Hristo Beloev, Prof. Dr. Angel Smrikarov, Assoc. Prof. DSc. Valentina Voinohovska, Assoc. Prof. Dr. Galina Ivanova

A STUDY ON THE POSSIBILITIES TO INTEGRATE THE MODERN 3D TECHNOLOGIES IN THE SCIENTIFIC ACTIVITIES OF THE HIGHER EDUCATION INSTITUTIONS

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev, Assist. Prof. Dr. Diyana Kinaneva, Assist. Prof. Georgi Georgiev

THE ROLE OF THE UNIVERSITIES AS ACCELERATORS FOR THE INTEGRATION OF THE STEM LEARNING METHODS IN THE PRIMARY AND SECONDARY SCHOOLS

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev, Assist. Prof. Georgi Georgiev

ОТ STEM КЪМ BEST: ДВА СТАНДАРТА, ЕДНА ЦЕЛ

Проф. д-р Андрей Захариев, проф. д-р Стефан Симеонов, гл. ас. д-р Таня Тодорова

ВЪЗМОЖНОСТИ ЗА ПРИЛОЖЕНИЕ НА БЛОКЧЕЙН ТЕХНОЛОГИЯТА В ОБРАЗОВАНИЕТО

Докторант Андриан Минчев, доц. д-р Ваня Стойкова

ПРЕДИЗВИКАТЕЛСТВА НА ДИГИТАЛНАТА ТРАНСФОРМАЦИЯ В ОБРАЗОВАНИЕТО – СРАВНИТЕЛЕН АНАЛИЗ НА СТУДЕНТСКОТО МНЕНИЕ

Гл. ас. д-р Мирослава Бонева, доц. д-р Антон Недялков, проф. д.н. Милена Кирова

CHALLENGES, REQUIREMENTS, OPPORTUNITIES AND SOLUTIONS FOR THE DIGITAL TRANSFORMATION OF THE TRANSPORT EDUCATION

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev

Книжка 4
EFFECT OF RESILIENCE ON BURNOUT IN ONLINE LEARNING ENVIRONMENT

Dr. Radina Stoyanova, Prof. Sonya Karabeliova, Petya Pandurova, Dr. Nadezhda Zheckova Dr. Kaloyan Mitev

STATE AND PROSPECTS OF DEVELOPMENT OF ACADEMIC MOBILITY IN THE SYSTEM OF TRAINING A SPECIAL EDUCATION SPECIALIST

Dr. Tetiana Dokuchyna, Assoc. Prof., Prof. Dr. Svitlana Myronova, Dr. Tetiana Franchuk, Assoc. Prof.

Книжка 3s
STRATEGIES AND POLICIES TO SUPPORT THE DEVELOPMENT OF AI TECHNOLOGIES IN EUROPE

Assoc. Prof. Miglena Molhova, Assoc. Prof. Petya Biolcheva

BULGARIA'S TECHNOLOGICAL DEVELOPMENT THROUGH THE PRISM OF HIGHER EDUCATION POLICIES

Assoc. Prof. Ivaylo B. Ivanov, Assoc. Prof. Miglena Molhova

INTELLIGENT ANIMAL HUSBANDRY: FARMER ATTITUDES AND A ROADMAP FOR IMPLEMENTATION

Prof. Dr. Dimitrios Petropoulos, Koutroubis Fotios Assoc. Prof. Petya Biolcheva Evgeni Valchev

EFFECTIVE MANAGEMENT OF HUMAN RESOURCES IN TOURISM THROUGH MOTIVATION

Assoc. Prof. Fahri Idriz Assoc. Prof. Marin Geshkov

Книжка 3
САМООЦЕНКА НА ОБЩООБРАЗОВАТЕЛНИТЕ И РЕСУРСНИТЕ УЧИТЕЛИ ЗА РАБОТА В ПАРАДИГМАТА НА ПРИОБЩАВАЩОТО ОБРАЗОВАНИЕ

Проф. д.н. Милен Замфиров, проф. Емилия Евгениева, проф. Маргарита Бакрачева

STUDY OF THE DEVELOPMENT OF THE USE OF COMMUNICATIVE TECHNOLOGIES IN THE EDUCATIONAL PROCESS OF ENGINEERS TRAINING

Assoc. Prof. Ivan Beloev, Assoc. Prof. Valentina Vasileva Assoc. Prof. Sergii Bilan, Assoc. Prof. Maria Bondar, Assoc. Prof. Oksana Bulgakova, Assoc. Prof. Lyubov Shymko

SAFETY THROUGH ARTIFICIAL INTELLIGENCE IN THE MARITIME INDUSTRY

Assoc. Prof. Petya Biolcheva Evgeni Valchev, PhD student

Книжка 2
РАЗПОЛОЖЕНИЕ НА ВИСШИТЕ УЧИЛИЩА В БЪЛГАРИЯ В КОНТЕКСТА НА ФОРМИРАНЕ НА ПАЗАРА НА ТРУДА

Гл. ас. д-р Цветелина Берберова-Вълчева, доц. д-р Камен Петров, доц. д-р Николай Цонков

CHARACTERISTICS AND COMPONENTS OF THE CYBER HYGIENE AS A SUBCLASS OF CYBER SECURITY IN MILITARY ENVIRONMENT AND EDUCATIONAL ISSUES

Prof. Boyan Mednikarov, DSc. Prof. Yuliyan Tsonev Dr. Borislav Nikolov, Prof. Andon Lazarov, DSc.

Книжка 1
MODERNIZATION OF THE CONTENT OF THE LECTURE COURSE IN PHYSICS FOR TRAINING FUTURE AGRICULTURAL ENGINEERS

Dr. Ivan Beloev, Assoc. Prof., Dr. Valentina Vasileva, Assoc. Prof. Prof. Vasyl Shynkaruk, DSc., Assoc. Prof. Oksana Bulgakova, Assoc. Prof. Maria Bondar Assoc. Prof. Lesia Zbaravska, Assoc. Prof. Sergii Slobodian

THE NEW PANDEMIC NORMAL THROUGH THE EYES OF BULGARIAN STUDENTS

Prof. Vyara Stoilova, Assoc. Prof. Todorka Kineva

2022 година
Книжка 6
ORGANIZATION OF AN INCLUSIVE EDUCATIONAL ENVIRONMENT FOR THE STUDENTS WITH SPECIAL NEEDS

Prof. Halyna Bilavych Prof. Nataliia Bakhmat Prof. Tetyana Pantiuk, Prof. Mykola Pantiuk Prof. Borys Savchuk

ДИГИТАЛИЗАЦИЯ НА ОБРАЗОВАНИЕТО В БЪЛГАРИЯ: СЪСТОЯНИЕ И ОБЩИ ТЕНДЕНЦИИ

Д-р Теодора Върбанова, проф. д-р Албена Вуцова, доц. д-р Николай Нетов

СКРИНИНГ НА ЗРЕНИЕТО – ПРОФИЛАКТИКА И ЕЛЕМЕНТ ОТ ПРАКТИКАТА НА СТУДЕНТИ И ОБУЧЕНИЕТО НА УЧЕНИЦИ

Руска Драганова-Христова, д-р Славена Стойкова, доц. д-р Снежана Йорданова

Книжка 5
ПРАВОТО НА ИЗБОР В ЖИВОТА НА ДЕЦАТА В РЕПУБЛИКА БЪЛГАРИЯ

Проф. д.п.н. Сийка Чавдарова-Костова, гл. ас. д-р Даниела Рачева, ас. Екатерина Томова, доц. д-р Росица Симеонова

SUSTAINABLE PROFESSIONAL DEVELOPMENT THROUGH COACHING: BENEFITS FOR TEACHERS AND LEARNERS

Assoc. Prof. Irina Ivanova, Assoc. Prof. Penka Kozhuharova, Prof. Rumyana Todorova

SELF-ASSESSMENT – A COMPONENT OF THE COMPETENCE-BASED TRAINING IN THE PROFESSION “APPLIED PROGRAMMER”

Assoc. Prof. Ivaylo Staribratov, Muharem Mollov, Rosen Valchev Petar Petrov

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BENCHMARKING FOR DEVELOPMENT OF SPEED AND POWER CHARACTERISTICS

Assist. Prof. Dr. Darinka Ignatova Assoc. Prof. Dr. Alexander Iliev

DIAGNOSIS AS A TOOL FOR MONITORING THE EFFECTIVENESS OF ADDICTION PREVENTION IN ADOLESCENTS

Prof. O.A. Selivanova Assoc. Prof. N.V. Bystrova, Assoc. Prof. I.I. Derecha, Assoc. Prof. T.S. Mamontova, Assoc. Prof. O.V. Panfilova

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ПУБЛИЧНОТО РАЗБИРАНЕ НА НАУКАТА В МРЕЖОВИЯ СВЯТ

Д-р Светломир Здравков, д-р Мартин Й. Иванов, д-р Петя Климентова

ОБРАЗОВАНИЕ ЗА УСТОЙЧИВО РАЗВИТИЕ – ПРАКТИКО-ПРИЛОЖНИ АСПЕКТИ

Гл. ас. д-р Златка Ваклева Проф. д-р Тоня Георгиева

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PREPARATION OF PRIMARY SCHOOL TEACHERS FOR COMMUNICATIVE AND RHETORICAL ACTIVITY IN SCHOOL IN THE CONTEXT OF THEIR PRACTICAL TRAINING

Prof. Halyna Bilavych Prof. Nataliia Bakhmat Prof. Tetyana Pantyuk, Prof. Mykola Pantyuk Prof. Borys Savchuk

ПРОЛЕТНА КОНФЕРЕНЦИЯ НА СЪЮЗА НА МАТЕМАТИЦИТЕ В БЪЛГАРИЯ

(Трявна, 5 – 9 април 2022) Гл. ас. д-р Албена Симова

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ДИГИТАЛНАТА ИНТЕРАКЦИЯ ПРЕПОДАВАТЕЛ – СТУДЕНТ В ОНЛАЙН ОБУЧЕНИЕТО В МЕДИЦИНСКИТЕ УНИВЕРСИТЕТИ

Д-р Миглена Търновска, д-р Румяна Стоянова Доц. Боряна Парашкевова, проф. Юлияна Маринова

2021 година
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ЕДНА РЕКАПИТУЛАЦИЯ НА ИЗСЛЕДВАНИЯ ВЪРХУ ИНТЕРКУЛТУРНИТЕ ОТНОШЕНИЯ. КАКВО СЛЕДВА ОТ ТОВА ЗА ОБРАЗОВАНИЕТО?

Давидков, Ц., 2019. Изследвания върху културите. Културни ориентири на управлението. София: СУ „Св. Климент Охридски“, ISBN 978-954-9399-52-3 Проф. Пламен Макариев

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RECOGNITION OF FAKE NEWS IN SPORTS

Colonel Assoc. Prof. Petko Dimov

SIGNAL FOR HELP

Ina Vladova, Milena Kuleva

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PREMISES FOR A MULTICULTURAL APPROACH TO EDUCATION

Dr. Anzhelina Koriakina, Assoc. Prof., Prof. Lyudmila Amanbaeva, DSc.

ПОЗИТИВНА ПСИХОЛОГИЯ: ПРОБЛЕМНИ ОБЛАСТИ И ФОРМИРАНЕ НА ЛИЧНОСТТА

Доц. д-р Стоил Мавродиев, Любомира Димитрова

КНИГА ЗА ИСТОРИЯТА НА БЪЛГАРСКОТО ВИСШЕ ИНЖЕНЕРНО ОБРАЗОВАНИЕ

Сгурев, В., Гергов, С., Иванов, Г., 2019. Положителните науки с приложение към индустрията. История на висшето техническо образование в България. София: Изд. на БАН „Проф. Марин Дринов“, Изд. „Захарий Стоянов“. ISBN 978-619-245-004-5, ISBN 978-954-09-1387-2.

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ENTREPRENEURSHIP AND INTERDISCIPLINARY EDUCATION – SEMIOTIC ASPECTS

Prof. Dr. Christo Kaftandjiev Dr. Diana Kotova

THE PRACTICAL IMPORTANCE OF ACCOUNTING EDUCATION FOR FUTURE MANAGERS

Nataliia Radionova, DSc. Dr. Radostina Stoyanova, Assist. Prof.

ЗА ОБРАЗОВАТЕЛНАТА ИНТЕГРАЦИЯ И ЗАЛОЗИТЕ НА НАСТОЯЩЕТО

Нунев, Й., 2020. Мониторинг на процесите на приобщаване и образователна интеграция и модели за десегрегация на ромското образование. Пловдив: Астарта, ISBN 978-954-350-283-7

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METHODOLOGY OF SAFETY AND QUALITY OF LIFE ON THE BASIS OF NOOSPHERIC EDUCATION SYSTEM FORMATION

Nataliia Bakhmat Nataliia Ridei, Nataliia Tytova, Vladyslava Liubarets, Oksana Katsero

ОБРАЗОВАНИЕ В УСТОЙЧИВО РАЗВИТИЕ И ВЗАИМОДЕЙСТВИЕ „ДЕТЕ – СРЕДА“

Стоянова, М. (2020). Образование в устойчиво развитие и взаимодействие „дете – среда“ София: Авангард принт. ISBN 978-954-337-408-3

2020 година
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HIGHER EDUCATION AS A PUBLIC GOOD

Yulia Nedelcheva, Miroslav Nedelchev

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НАСЪРЧАВАНЕ НА СЪТРУДНИЧЕСТВОТО МЕЖДУ ВИСШИТЕ УЧИЛИЩА И БИЗНЕСА

Добринка Стоянова, Блага Маджурова, Гергана Димитрова, Стефан Райчев

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THE STRATEGY OF HUMAN RIGHTS STUDY IN EDUCATION

Anush Balian Nataliya Seysebayeva Natalia Efremova Liliia Danylchenko

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ПОМОЩНИ СРЕДСТВА И ТЕХНОЛОГИИ В ПРИОБЩАВАЩОТО ОБРАЗОВАНИЕ

Янкова, Ж. (2020). Помощни средства и технологии за деца и ученици със специални образователни потребности в приобщаващото образование.

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МИГРАЦИЯ И МИГРАЦИОННИ ПРОЦЕСИ

Веселина Р. Иванова

SOCIAL STATUS OF DISABLED PEOPLE IN RUSSIA

Elena G. Pankova, Tatiana V. Soloveva, Dinara A. Bistyaykina, Olga M. Lizina

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ETHNIC UPBRINGING AS A PART OF THE ETHNIC CULTURE

Sholpankulova Gulnar Kenesbekovna

ЗА СВЕТЛИНАТА, КОЯТО ИЗЛЪЧВА… В ПАМЕТ НА ПРОФ. Д.П.Н. АСЕМГУЛ МАЛДАЖАНОВА

Нашата редколегия загуби един все- отдаен и неповторим колега и приятел – проф. д.п.н. Асемгул Малдажанова. Пе- дагог по призвание и филолог по мисия! Отиде си от нас нашият приятел, коле- га и член на редколегията на списанието – професор д.п.н. Асемгул Малдажанова – първи заместник-ректор на Евразийския

2019 година
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EMOTIONAL COMPETENCE OF THE SOCIAL TEACHER

Kadisha K. Shalgynbayeva Ulbosin Zh.Tuyakova

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„ОБРАЗОВАТЕЛНИ КИНОХОРИЗОНТИ“ В ПОЛЕТО НА МЕДИА ОБРАЗОВАНИЕТО

(2018). Образователни кинохоризонти. Международен сборник с научни публи- кации по проект „Естетически и образователни проекции на кинодидактиката“. Бургас: Проф. д-р Асен Златаров. Съставител: Маргарита Терзиева. ISBN 978-954-471-496-3

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ВИСШЕТО МОРСКО ОБРАЗОВАНИЕ В КОНКУРЕНТНА СРЕДА

Бакалов, Я. (2019). Висше морско образование. Лидиране в конкурентна среда. Варна: Стено. ISBN 978-619-241-029-2

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УЧИЛИЩЕТО НА БЪДЕЩЕТО

Наталия Витанова

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КНИГА ЗА УСПЕШНИТЕ НАУЧНИ ПУБЛИКАЦИИ

Кожухаров, А. (2018). Успешните научни публикации. Варна: Тера Балканика. ISBN 978-619-90844-1-0

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POST-GRADUATE QUALIFICATION OF TEACHERS IN INTERCULTURAL EDUCATIONAL ENVIRONMENT

Irina Koleva, Veselin Tepavicharov, Violeta Kotseva, Kremena Yordanova

ДЕЦАТА В КОНСТИТУЦИОННИТЕ НОРМИ НА БЪЛГАРИЯ

Румен Василев, Весела Марева

СЪСТОЯНИЕ НА БЪЛГАРСКОТО ОБРАЗОВАНИЕ

Анелия Любенова Любомир Любенов

ИНТЕРКУЛТУРНИЯТ ТРЕНИНГ КАТО ЧАСТ ОТ СТРАТЕГИЯТА ЗА ГЛОБАЛИЗАЦИОННА ИНТЕГРАЦИЯ

Хубенова, М. (2018). Значение на междукултурната комуникация за направления: политически науки, право, икономика и бизнес. София: Издателски комплекс УНСС. ISBN 978-619-232-072-0

ЕДИН НОВ УЧЕБНИК

Дончева, Ю. (2018). Теоретични и методически основи на запознаване с околния свят в детската градина. Русе: Лени Ан

2018 година
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СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXVI / VOLUME 26, 2018 ANNUAL CONTENTS / ГОДИШНО СЪДЪРЖАНИЕ СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 120 КНИЖКА 2 / NUMBER 2: 121 – 224 КНИЖКА 3 / NUMBER 3: 225 – 336 КНИЖКА 4 / NUMBER 4: 337 – 448 КНИЖКА 5 / NUMBER 5: 449 – 560 КНИЖКА 6 / NUMBER 6: 561 – 664

ДИСКУСИОННО / DISCUSSION 211 – 216: Процедурата за назначаване на ръководител на катедра като причина за вло- шаващото се качество на обучението и микроклимата във висшите учи лища у нас [The Procedure for Appointing a Head of Department as a Reason for the Deteriorating Quality of Education and the Microclimate in the Higher School] / Александър Димит- ров / Alexander Dimitrov

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A NEW AWARD FOR PROFESSOR MAIRA KABAKOVA

The staff of the Editorial board of the journal “Strategies for Policy in Science and Education” warmly and sincerely congratulates their Kazakhstan colleague -

ПРОДЪЛЖАВАЩАТА КВАЛИФИКАЦИЯ НА УЧИТЕЛИТЕ – НОРМАТИВЕН И ИЗСЛЕДОВАТЕЛСКИ ОБЗОР

(научно-теоретично обобщение върху проведени обучения на учители)

ЕТНОЦЕНТРИЗМЪТ И ИНЕРЦИИТЕ ОТ МИНАЛОТО – СЕРИОЗНИ ПРОБЛЕМИ В БЪЛГАРСКАТА ОБРАЗОВАТЕЛНА СИСТЕМА

(Eтнопедагогически аспекти на основното и средното образование) Веселин Тепавичаров

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ХРИСТО БОТЕВ И ПОЗНАВАТЕЛНИЯТ КРЪГОЗОР НА СЪВРЕМЕННИТЕ СТУДЕНТИ ЗА ЕВРОПА

Изследователски разказ за един познавателен подвиг и за една познавателна недостатъчност

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BLENDED EDUCATION IN HIGHER SCHOOLS: NEW NETWORKS AND MEDIATORS

Nikolay Tsankov Veska Gyuviyska Milena Levunlieva

ВЗАИМОВРЪЗКАТА МЕЖДУ СПОРТА И ПРАВОТО

Ивайло Прокопов, Елица Стоянова

НАДНАЦИОНАЛНИ И МЕЖДУПРАВИТЕЛСТВЕНИ МЕТОДИ НА ИНТЕГРАЦИЯ В ОБЛАСТТА НА ПРАВОСЪДИЕТО И СИГУРНОСТТА

(Формиране на обща миграционна политика: парадигми и образователни аспекти) Лора Махлелиева-Кларксън

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ВЪЗПРИЯТИЯ И НАГЛАСИ НА УЧЕНИЦИТЕ ПО ВАЖНИ ОБЩЕСТВЕНИ ВЪПРОСИ

(Данни от Международното изследване на гражданското образование – ICCS 2016)

2017 година
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ЗНАЧИМОСТТА НА УЧЕНЕТО: АНАЛИЗ НА ВРЪЗКИТЕ МЕЖДУ ГЛЕДНИТЕ ТОЧКИ НА УЧЕНИЦИ, РОДИТЕЛИ И УЧИТЕЛИ

Илиана Мирчева, Елена Джамбазова, Снежана Радева, Деян Велковски

ВЪЗПРИЯТИЯ И НАГЛАСИ НА УЧЕНИЦИТЕ ПО ВАЖНИ ОБЩЕСТВЕНИ ВЪПРОСИ

(Данни от Международното изследване на гражданското образование – ICCS 2016)

СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXV / VOLUME 25, 2017 ANNUAL CONTENTS / ГОДИШНО СЪДЪРЖАНИЕ

СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 112 КНИЖКА 2 / NUMBER 2: 113 – 224 КНИЖКА 3 / NUMBER 3: 225 – 336 КНИЖКА 4 / NUMBER 4: 337 – 448 КНИЖКА 5 / NUMBER 5: 449 – 552 КНИЖКА 6 / NUMBER 6: 553 – 672

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ОРГАНИЗАЦИОННА КУЛТУРА В УЧИЛИЩЕ

Ивайло Старибратов, Лилия Бабакова

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КОУЧИНГ. ОБРАЗОВАТЕЛЕН КОУЧИНГ

Наталия Витанова, Нели Митева

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ТЕХНОХУМАНИЗМЪТ И ДЕЙТЪИЗМЪТ – НОВИТЕ РЕЛИГИИ НА БЪДЕЩЕТО

Harari, Y. N. (2016). Homo Deus. A Brief History of Tomorrow. Harvill Secker. ISBN-10: 1910701874

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РЕФОРМИТЕ В ОБРАЗОВАНИЕТО – ПЕРСПЕКТИВИ И ПРЕДИЗВИКАТЕЛСТВА

Интервю с Габриела Миткова, началник на Регионалното управление на образованието – Силистра

ЕМПАТИЯ И РЕФЛЕКСИЯ

Нели Кънева, Кристиана Булдеева

2016 година
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СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXIV / VOLUME 24, 2016 ANNUAL CONTENT / ГОДИШНО СЪДЪРЖАНИЕ

СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 120 КНИЖКА 2 / NUMBER 2: 121 – 232 КНИЖКА 3 / NUMBER 3: 233 – 344 КНИЖКА 4 / NUMBER 4: 345 – 456 КНИЖКА 5 / NUMBER 5: 457 – 568 КНИЖКА 6 / NUMBER 6: 569 – 672

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2014 година
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КОХЕРЕНТНОСТ НА ПОЛИТИКИ

Албена Вуцова, Лиляна Павлова

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ОБРАЗОВАНИЕТО ПО ПРАВАТА НА ЧОВЕКА ПРЕЗ ПОГЛЕДА НА ДОЦ. ЦЕЦКА КОЛАРОВА

Цецка Коларова. (2013). Образование по правата на човека. София: Авангард Прима. ISBN 978-619-160-234-6

USING THE RESULTS OF A NATIONAL ASSESSMENT OF EDUCATIONAL ACHIEVEMENT

Thomas Kellaghan Vincent Greaney T. Scott Murray Chapter 4 Translating Assessment Findings Into Policy And Action Although the primary purpose of a system of national assessment is to describe students’ learning, its role is not limited to description. To justify the effort and expenditure involved, the information that an assessment provides about the achievements of students, their strengths and weaknesses, and how they are distributed in the population (for example, by gender or location

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PROFESSIONAL DEVELOPMENT OF UNIVERSITY FACULTY: А SOCIOLOGICAL ANALYSIS

Gulnar Toltaevna Balakayeva Alken Shugaybekovich Tokmagambetov Sapar Imangalievich Ospanov

ЗА ПО-ХУМАНИСТИЧНА ТРАДИЦИОННО- ИНОВАЦИОННА ОБРАЗОВАТЕЛНО-ВЪЗПИТАТЕЛНА СТРАТЕГИЯ У НАС

(КОНЦЕПТУАЛНА РАЗРАБОТКА В ПОМОЩ НА ПОДГОТОВКАТА НА НОВ ЗАКОН ЗА ОБРАЗОВАНИЕТО)

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РЕФЛЕКСИЯТА В ИНТЕГРАТИВНОТО ПОЛЕ НА МЕТОДИКАТА НА ОБУЧЕНИЕТО ПО БИОЛОГИЯ

Иса Хаджиали, Наташа Цанова, Надежда Райчева, Снежана Томова

USING THE RESULTS OF A NATIONAL ASSESSMENT OF EDUCATIONAL ACHIEVEMENT

Thomas Kellaghan Vincent Greaney T. Scott Murray Chapter 1 Factors affecting the use and nonuse of national assessment fi ndings The main objectives of a national assessment, as set out in volume 1 of this series, Assessing National Achievement Levels in Education, are to determine (a) how well students are learning in the education system (with reference to general expectations, aims of the curriculum, and preparation for further learning and for life); (b) whether there is evidence of par

2013 година
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QUESTIONNAIRE DEVELOPMENT

ÎÖÅÍßÂÀÍÅÒÎ

РОССИЙСКАЯ СИСТЕМА ОЦЕНКИ КАЧЕСТВА ОБРАЗОВАНИЯ: ГЛАВНЫЕ УРОКИ

В. Болотов / И. Вальдман / Г. Ковалёва / М. Пинская

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MASS MEDIA CULTURE IN KAZAKHSTAN

Aktolkyn Kulsariyeva Yerkin Massanov Indira Alibayeva

РОССИЙСКАЯ СИСТЕМА ОЦЕНКИ КАЧЕСТВА ОБРАЗОВАНИЯ: ГЛАВНЫЕ УРОКИ

В. Болотов / И. Вальдман / Г. Ковалёва / М. Пинская

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ОЦЕНЯВАНЕ НА ГРАЖДАНСКИТЕ КОМПЕТЕНТНОСТИ НА УЧЕНИЦИТЕ: ПРЕДИЗВИКАТЕЛСТВА И ВЪЗМОЖНОСТИ

Светла Петрова Център за контрол и оценка на качеството на училищното образование

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Уважаеми читатели,

вет, както и от международния борд за предоставените статии и студии, за да могат да бъдат идентифицирани в полето на образованието пред широката аудитория от педа- гогически специалисти във всички степени на образователната ни система. Благодаря за техния всеотдаен и безвъзмезден труд да създават и популяризират мрежа от научни съобщества по профила на списанието и да насърчават научните изследвания. Благодаря на рецензентите от национално представените висши училища, на- учни институции и

METHODS FOR SETTING CUT SCORES IN CRITERION – REFERENCED ACHIEVEMENT TESTS

ÎÖÅÍßÂÀÍÅÒÎ COMPARATIVE ANALYSIS OF THE QUALITY OF THE SEPARATE METHODS

ПУБЛИКАЦИИ ПРЕЗ 2012 Г.

СПИСАНИЕ „БЪЛГАРСКИ ЕЗИК И ЛИТЕРАТУРА“

2012 година
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DEVELOPMENT OF SCIENCE IN KAZAKHSTAN IN THE PERIOD OF INDEPENDENCE

Aigerim Mynbayeva Maira Kabakova Aliya Massalimova

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СИСТЕМАТА ЗА РАЗВИТИЕ НА АКАДЕМИЧНИЯ СЪСТАВ НА РУСЕНСКИЯ УНИВЕРСИТЕТ „АНГЕЛ КЪНЧЕВ“

Христо Белоев, Ангел Смрикаров, Орлин Петров, Анелия Иванова, Галина Иванова

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ПРОУЧВАНЕ НА РОДИТЕЛСКОТО УЧАСТИЕ В УЧИЛИЩНИЯ ЖИВОТ В БЪЛГАРИЯ

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