<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Borys Grinchenko Kyiv University</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Bulvarno-Kudriavska Str.</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Ukraine o.hlushak@kubg.edu.ua</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>s.semeniaka@kubg.edu.ua</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>v.proshkin@kubg.edu.ua</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>o.lytvyn@kubg.edu.ua</string-name>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Alfred Nobel University</institution>
          ,
          <addr-line>18 Sicheslavska Naberezhna Str., Dnipro, 49000</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
      </contrib-group>
      <fpage>0000</fpage>
      <lpage>0001</lpage>
      <abstract>
        <p>This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students' self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>1</p>
    </sec>
    <sec id="sec-2">
      <title>Introduction</title>
      <p>
        In the conditions of modern development of the economy of Ukraine, special attention
is paid to solving complex theoretical and applied problems that quantitatively and
qualitatively describe the relationship between different economic objects [
        <xref ref-type="bibr" rid="ref12 ref3">10</xref>
        ]. It
demands the development and study of new areas of economic theory and related
scientific disciplines. First of all, there is a need for the development and
implementation of innovative teaching methods, the usage of which would make it
possible to form for future bachelors new economic thinking and understanding of the
essence of economic processes or phenomena, to obtain appropriate know-how of
regulation and management of these processes at any level of complexity, to predict
their development [
        <xref ref-type="bibr" rid="ref25">23</xref>
        ]. In this regard, the formation and development of competencies
associated with the ability to optimally combine the possibilities of logical analysis with
knowledge not only of the laws of mathematics and economics, but also the basics of
mathematical modeling become important.
      </p>
      <p>
        Mathematical modeling with the maximum usage of its potential makes it possible
to identify and solve professional problems of different nature: to define clearly the
purpose of the research, to find quickly possible ways to achieve it, to develop
appropriate models of economic objects or phenomena and on the basis of these models
to create effective algorithms and programs for optimal solutions to current problems
[
        <xref ref-type="bibr" rid="ref21">19</xref>
        ]. Obviously, mathematics in the system of higher education has outgrown the status
of the general educational subject and should become an integral part of the
professional training, on the basis of intersubject connections with special subjects [
        <xref ref-type="bibr" rid="ref16">14</xref>
        ].
In this regard, it becomes actual to resolve the contradictions between the needs of
highly qualified specialists who effectively use mathematical tools in their professional
activities, and the lack of scientific and methodological support for mathematical
training of students, in particular by means of digital technologies.
      </p>
      <p>
        In Ukraine, the development of educational informatization takes place in
accordance with national and European programs (“Digital agenda of Ukraine – 2020”
[
        <xref ref-type="bibr" rid="ref20">18</xref>
        ], containing priority areas, initiatives, projects of digitalization of Ukraine until
2020, the thesis of the updated recommendations of the European Parliament and the
EU Council for lifelong learning [
        <xref ref-type="bibr" rid="ref9">7</xref>
        ], etc.). Various aspects of educational
informatization in the context of mathematical training of students have become the
subject of research for a number of scientists. Thus, Natalya V. Rashevska [11; 20]
investigated mobile information and communicational technologies of higher
mathematics teaching. Kateryna I. Slovak [21; 22] developed a methodology for the
use of mobile mathematical environments in the process of higher mathematics
teaching for students of economic specialties. Oksana I. Tyutyunnik [
        <xref ref-type="bibr" rid="ref17">15</xref>
        ] described the
usage of computer math systems in the process of linear programming teaching. Mariia
A. Kyslovа [12; 13] presented the development of mobile educational environment of
higher mathematics, Mariia M. Astafieva, Dmytro M. Bodnenko and Volodymyr V.
Proshkin [2; 1] found out the possibilities of the educational environment for the
formation of critical thinking of students in the process of mathematics learning.
Oksana M. Hlushak, Volodymyr V. Proshkin and Oksana S. Lytvyn [
        <xref ref-type="bibr" rid="ref11">9</xref>
        ] revealed the
possibilities of e-learning course (ELC) on “Analytical geometry” in the process of
professional training of students. In these works, the theoretical and methodological
foundations of the usage of electronic educational environment in the process of
professional training of bachelors are revealed, the tendencies of the development of
mathematical educational informatization are indicated. The studies on the use of ICT
in the process of economic and mathematical modeling learning are of particular
interest. So, Dana Országhová [
        <xref ref-type="bibr" rid="ref18">16</xref>
        ] investigated the e-learning approach in
mathematical training of future economists. Dimitros Asteriou, Stephen G. Hall [4, pp.
29–91] and Roberto Pedace [17, pp. 59–134] reviewed the classical linear regression
model.
      </p>
      <p>
        In the above mentioned works the features of formation of qualitative modern
cloud-oriented educational environment in the context of mathematical subjects
learning are presented. In addition, the experience of using e-learning courses
is interesting for our research. Thus Charlotte Brooke, Pamela McKinney and Angie
Donoghue [5] claim that students who take e-learning courses on the distance learning
platform use their own time allocated for training more efficiently. Similar ideas are
found in the works of other scientists (Jana Burgerova, Martina Adamkovičovа [6],
Paul Drijvers, Carolyn Kieran, Maria-Alessandra Mariotti, Janet Ainley, Mette
Andresen, Yip Cheung Chan, Thierry Dana-Picard, Ghislaine Gueudet, Ivy Kidron,
Allen Leung, Michael Meagher [
        <xref ref-type="bibr" rid="ref10">8</xref>
        ] etc.). At the same time, the analysis of scientific
researches testifies the limitation of investigation methodical questions of learning
econometric modeling in combination with ICT.
2
      </p>
    </sec>
    <sec id="sec-3">
      <title>The objective of research</title>
      <p>The purpose of the article is to highlight the areas of the use of digital technologies in
the university training of future bachelors (having been based on the data of
mathematical subjects).
3</p>
    </sec>
    <sec id="sec-4">
      <title>Research methodology</title>
      <p>The usage of appropriate methods such as scientific literature analysis with the aim of
establishing the state of readiness of the studying problem, the definition of categorical
and conceptual apparatus of the research; synthesis, generalization, systematization of
theoretical justification of the use of digital technologies in the educational process at
the university and empirical ones: diagnostic (interview, content analysis, testing),
statistical (Fisher and Student criteria) to test the statistical significance of mathematical
model promoted to achieve the purpose of the research.</p>
      <p>The research was carried out within the framework of the project “Partnership for
mathematics learning and teaching at the university” (PLATINUM) of the EU Erasmus
+ KA203 – Strategic partnership for higher education, 2018-1-NO01-KA203-038887
and the complex scientific theme of the department of computer science and
mathematics of Borys Grinchenko Kyiv University “Theoretical and practical aspects
of the use of mathematical methods and information technologies in education and
science”, SR No. 0116U004625. The experimental base of the research is Borys
Grinchenko Kyiv University and Alfred Nobel University (Dnipro city).
4</p>
    </sec>
    <sec id="sec-5">
      <title>Results and discussion</title>
      <p>We believe that in order to implement the task of high-quality training of students
studying economic and mathematical modeling in “Econometrics”, “Economic and
mathematical modeling” subjects, it is necessary to introduce digital technologies in
two directions: for the organization of educational space and in the process of solving
applied problems at the junction of the branches of economics and mathematics
branches.</p>
      <p>The background for the organization of educational space is the availability of the
necessary material and technical base (computers, software, communication channels)
and informational educational environment, the effectiveness and basis of which are
digital technologies. We believe that the informational and educational environment
can be organized through the activities of the teacher with the use of an e-learning
course of the subjects that are aimed at teaching economic and mathematical modeling,
on the basis of the distance learning platform. The Moodle distance learning platform
has been introduced into the educational process at the Borys Grinchenko Kyiv
University. Therefore, electronic courses of “Econometrics”, “Economic and
mathematical modeling” subjects are presented on the basis of this platform.</p>
      <p>Let us present the advantages of ELC using in the educational process.</p>
      <p>Firstly, it is providing the individualization of the educational process in
accordance with the needs, characteristics and capabilities of students. The basis
for the implementation of this ELC characteristic is clearly structured nature, so that
the placement and sequence of teaching materials corresponds to the logic of the
mathematical subject studying. For example, the ELC can be presented in the form of
a chain: a description of the ELC indicating the educational and professional program;
general information of the academic subject (working curriculum, syllabus, assessment
criteria, sources, glossary, announcements, information about the author); teaching
materials for each module: theoretical material, practical (laboratory, seminar) works,
tasks for individual work of students, modular control, accompanied by video
materials and hyperlinks that allow students to increase the amount of information.
Besides, ELC provides information for the final assessment (advancement questions,
self-assessment test, final test) and contains a list of references and addresses of Internet
sources for the implementation of independent students’ work.</p>
      <p>Indeed, the structure of ELC allows students to choose a convenient time and rate of
assimilation of mathematical material, based on their own rhythm of life, individual
characteristics and abilities. This helps in the best way to realize an individual
educational trajectory consistent with the following principles: education is for
everyone and is lifelong.</p>
      <sec id="sec-5-1">
        <title>Secondly, it is improving the quality and efficiency of the educational process.</title>
        <p>This characteristic is directly correlated with the quality of teaching materials, allowing
to form the mathematical competence of students [3]. The advantage of ELC is the
following one: its content can be constantly updated in accordance with the
development of mathematical science, the latest methods of the educational process. As
a rule, the ELC consists of two types of electronic resources:
─ resources designed to present the content of educational material (lecture notes,
multimedia presentations of courses, audio and video materials, guidelines, etc.);
─ resources that provide the consolidation of the studying material, the formation of
skills, acquisition of competencies, self-assessment and evaluation of educational
achievements of students (tasks, questionnaires, testing, forums, including using of
Web 2.0).</p>
        <p>The ability to receive advice, recommendations and explanations through digital
interaction, for example, in forums, also contributes to the quality of students’
education.</p>
        <p>It should also be noted that the quality of the ELC is also related to the fact that these
resources are created and reviewed by a number of teachers whose mathematical
competence meets the immediate requirements of the time.</p>
      </sec>
      <sec id="sec-5-2">
        <title>Thirdly, it is ensuring systematic monitoring of the education quality. In order</title>
        <p>to implement this characteristic, a clear schedule of the curriculum for implementation
by students has been submitted on the ELC website. There are also opportunities for
interactive communication between teachers and students, as well as students among
themselves. ELC contains a system of monitoring and evaluation of all types of
educational activities of students. Thus, for the self-test, the testing is submitted.
Assessment of tasks is carried out automatically that excludes subjective assessment
from the teacher.</p>
        <p>According to the above mentioned, electronic educational courses of
“Econometrics”, “Economic and mathematical modeling” subjects have the unified
structure (Fig. 1): general information on the subject (curriculum of the subject, plan,
assessment criteria, printed sources and Internet resources, glossary); thematic
modules, which include information about the main topics of the module the theoretical
material in the form of a structured lecture material submitted by means of the lesson,
multimedia presentations of lectures, audio, video learning materials and tests (training
and advancement); laboratory work, which reflect the content of the work, list of
individual tasks and methodical recommendations about performance of work; tasks
for individual work with the guidelines of the performing task, a list of individual tasks
and their assessment criteria; tasks for module test, which provides individual tasks and
criteria of assessment of the work performed.</p>
        <p>Each of these ELC blocks contributes to the implementation of individual tasks.
Thus, the theoretical material is built in such a way that a student who missed classes
could easily master the training material, and a student who was in the audience at the
lesson could systematize the material obtained at the lesson, test himself for
understanding and perception of the topic with the help of tests, which had been built
into the lectures. If students have questions, they have the opportunity to ask them on
the forum discussion on the topic of each content module.
ELC laboratory works are presented in the form of web pages with a common structure:
theme, purpose, tasks, form of result presentation, deadlines and assessment criteria
(Fig. 2). Educational and methodological materials recommended to read are presented
under the laboratory work: these are guidelines for tasks, questions for laboratory work,
preparation step-by-step algorithms for tasks, examples of construction and research of
models. In addition, the block of laboratory works contains instructional videos for
performing tasks according to protocol of the laboratory work.</p>
        <p>For self-test is planned the block of the task for individual work of students which
provides individual tasks for each student, methodical recommendations to their
performance and advancement questions.</p>
        <p>At the end of the study of each module, a modular test work is offered for students
of economic and mathematical specialties. The form of module tests for each content
module is different: a complex test that involves answers to 40 questions of different
types: multivariate, alternative, with a short answer, numerical, questions to establish
compliance, or the construction and research of economic and mathematical models for
an individual set of input data.</p>
        <p>In our opinion, such a methodological approach to supply educational material with
the use of digital technology for building electronic educational environment will
promote student’s motivation for the subject learning, implementation of a systematic
approach to mastering academic content and implementation of the principles of
personality-oriented approach. Therefore, due to the use of this ELC in the educational
process of studying “Econometrics”, “Economic and mathematical modeling” subjects,
the teacher will be able to organize individual, group and frontal form of student work.
To find out the real attitude of students to the use of ELC in economic and mathematical
modeling, we conducted a pedagogical experiment during 2018-2019. The basis of the
experiment was Borys Grinchenko Kyiv University and Alfred Nobel University
(Dnipro city). In total, 125 students of “Finance, banking and insurance”,
“Management”, “Economics”, “Accounting and taxation” specialties took part in the
research. Respondents were asked 10 questions about the usefulness of the ELC with
economic and mathematical modeling with the following answers: “Yes”, “rather Yes
than No”, “rather No than Yes”, “No”. In the research, we were interested only in “Yes”
answer, which we considered as a clear indicator of readiness for the effective use of
ELC in the educational process.</p>
        <p>As a result of the survey, the following results were obtained (see table 1).</p>
        <p>According to the results of the research, students generally express a positive attitude
to the use of ELC with economic and mathematical modeling in the educational
process. Special noticeable dynamics in the evaluation of the following indicators: is
constant communication with the teacher (+7.2%), ability to study mathematics
conveniently (+5.5%), favorable conditions for learning (+3.4%). The following
indicators need to be improved: availability of educational mathematical materials that
meet the requirements of the time; individual approach in teaching; self-expression of
students and development of their creativity in the e-learning process.</p>
        <p>
          The second direction of the introduction of digital technologies in the process of
economic and mathematical modeling teaching of future bachelors is the demonstration
of ICT as a tool for the construction and research of econometric models. Let’s consider
more detailed influence of the following factors on the example of the problem of
dependence of the level of employment of the population of Ukraine:
1. share of employees with higher education in % to the list number;
2. labor productivity growth rate;
3. growth rate of the average wage;
4. capital investment index;
5. export-import coverage ratio.
The statistics for the task are taken from the official website of the State Statistics
Service of Ukraine [
          <xref ref-type="bibr" rid="ref26">24</xref>
          ]. The problem will be solved with the help of general-purpose
application software MS Excel.
        </p>
        <p>The first stage for constructing and researching of an econometric model is the
identification of variables. According to the results of identification we get:
Y – level of employment of the population of Ukraine;
X1 – share of employees with higher education in Ukraine;
X2 – growth rate of labor productivity in Ukraine;
X3 – growth rate of average wages in Ukraine;
X4 – index of capital investments in Ukraine;
X5 – export-import coverage ratio in Ukraine.</p>
        <p>The specification of the model is the second stage of construction, it provides the
choice of the form of f communication between the factor and the resultant variable.
We will carry out the construction of the correlation field depending on the level of
employment of the population from each of the factors using a scatter chart in MS Excel
(Fig. 3). To determine the best type of relationship between the factor and the result,
we will use the trend line. Using the trend line format dialog box, we will display the
coefficient of determination and the equations of the model on the chart (Fig. 4).
Comparing the determination coefficients for each type of corresponding dependencies
R2, we can conclude that the most optimal were the dependencies for which the value
R2 takes the maximum value of possible ones. As a result, on the basis of the above
research, it was established the existence of a linear relationship between the relevant
factors of the econometric model.</p>
        <p>Hence, the theoretical multiple regression equation will take the form
=
+
+
+
+
+
+ ,
(1)
where u – probabilistic component that is not directly determined from the equation.
The next stage of the model construction is the parameterization stage: finding of
parameter estimate ( = 0,5) and constructing of the corresponding regression
equation. This step can be implemented in MS Excel in several ways. The first method
is purely mathematical, and consists in determination of the estimates of parameters
using the least squares method using numerical calculations. To do this, we write down
the vector-column of observations of the dependent (productive) variable and the
matrix of observations of independent (factor) variables and we apply to calculate
estimates of regression coefficients by the formula
= (
)
(2)
where - the vector is a column of estimates of the equation coefficients, – the
transposed matrix to the matrix ., ( ) – inverse matrix to the product of two
. To implement this method, students will be able to multiply matrices, find
transposed and inverse matrices in MS Excel using the mathematical functions
MMULT, TRANSPOSE, MINVERSE.
The second method of finding parameter estimates is implemented through “Analysis
package” add-in and “Regression” tool. After entering a range containing a set of
statistics of the dependent variable (employment rate of the population of Ukraine) –
and a set of observations of independent (factor) variables MS Excel displays the
results, which reflect the estimates of the coefficients (Fig. 5).</p>
        <p>The third way to find parameter estimates is to use LINEST statistical function,
which after entering the known values , , constant and statistics, displays the result
as a table of 5 rows and 6 columns by pressing the combination of Ctrl+Shift+Enter
(table 2).
Hence,
Students are offered to make these calculations in the table 3 and finding the coefficient
of determination by formula.
The first row of the table shows the value of parameter estimates. Thus, the resulting
multiple regression equation will take the form:
Note that the last two methods of finding parameter estimates, in our opinion, is
advisable to use only after familiarizing of students with the first method, which
demonstrates the step-by-step application of the mathematical apparatus for finding
parameter estimates.</p>
        <p>The next stage is the research of the model – check for adequacy, which involves
finding the average value of the relative errors of approximation , which are measured
as a percentage and determined by the formula:
=   </p>
        <p>  ⋅  100%.
=
⋅ ∑
.</p>
        <p>(4)
(5)
We can say that the model is adequate, since the average value of the relative
approximation errors is in the range of 8-10%. The coefficient of determination tends
to 1, and the closer R2 to 1, the more significant is the relationship between these
variables, that is, the change in the resulting variable is largely due to the change in the
factor variable and only a small part of the changes – other factors.</p>
        <p>The last stage of the research of the model is the check of statistical significance. To
check the statistical significance of the results, we offer students two criteria: Fisher
criterion (F-criterion) and Student criterion (t-criterion).</p>
        <p>Checking the statistical significance, we put forward two hypotheses – the null
hypothesis : = 0 and the alternative one to it :   ≠ 0. Next, we calculate the
experimental value according to the formulas of each criteria, find the tabular values of
each of the criteria for a certain number of degrees of freedom and compare the
experimental values. Make appropriate conclusions: if the experimental value exceeds
the table one, the null hypothesis is rejected.</p>
        <p>Students should note that the tabular values for F-criterion) and t-criterion shall be
found using the statistical functions FINV and TINV.</p>
        <p>According to the described calculations we find = 17.479 and = 3.204. Since
&gt; , the null hypothesis is rejected, so the model is statistically significant.
Similar results are obtained by the t-criterion. Thus, t1 = 9.349 and t0 = 2.593. Since
&gt; , the null hypothesis is rejected, so the model is statistically significant.
5</p>
        <p>Conclusions
1. As a result of the analysis of scientific sources it is established that mathematical
modelling with the maximum use of its potential makes it possible to identify and
solve professional problems of different nature: to define clearly the purpose of the
research, to quickly find possible ways to achieve it, to develop appropriate models
of economic objects or phenomena and on the basis of these models to create
effective algorithms and programs for optimal solutions to current issues. It is noted
that in order to implement the task of obtaining high-quality training of future
bachelors on study of build and research of economic and mathematical modelling
within “Econometrics”, “Economic and mathematical modelling” subjects it is to
introduce digital technologies in two directions: for the organization of educational
space and in the process of solving applied problems at the junction of economic
sectors and mathematics.
2. It is established that for the organization of educational space it is advisable to use
e-learning courses of “Econometrics”, “Economic and mathematical modelling”
subjects, which is a complex of teaching materials created for individual and group
learning using digital technologies for teaching mathematical modelling to students.
Based on the indicated possibilities of application of the electronic learning course,
as well as its didactic functions, the structure of the electronic learning course of
“Econometrics”, “Economic and mathematical modelling” subjects on the basis of
Moodle platform is developed and described.
3. The results of a pedagogical experiment regarding the study of attitude of students
to the use of electronic learning courses are presented. It is established that students
in general positively evaluate the use of ELC in the educational process. At the same
time, the following indicators need to be improved: availability of educational
mathematical materials that meet the requirements of the time; individual approach
in teaching; self-expression of students and development of their creativity in the
elearning process.
4. Features of application of MS Excel on an example of a problem of dependence of
employment level of the population of Ukraine on influence of the chosen factors
are considered. Various stages of building and study of the econometric model are
characterized, they are following ones: identification of variables, specification of
the model, parameterization and verification of the statistical significance of the
obtained results.</p>
        <p>We see the prospect of further scientific inquiry in the research of implementing an
interactive approach using electronic learning courses.</p>
        <p>Gratitude. The research, the results of which are presented in the article, was carried
out in the framework of the project “Partnership for teaching and teaching mathematics
at the University” (PLATINUM) of EU Erasmus + KA203 – Strategic partnership for
higher education, 2018-1-NO01-KA203-038887. This article reflects only the views of
the author and the European Commission cannot be responsible for any usage of the
information contained here.</p>
      </sec>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          <source>Workshop Proceedings</source>
          <volume>2387</volume>
          ,
          <fpage>507</fpage>
          -
          <lpage>512</lpage>
          (
          <year>2019</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          <string-name>
            <given-names>Information</given-names>
            <surname>Technologies</surname>
          </string-name>
          and
          <source>Learning Tools</source>
          <volume>71</volume>
          (
          <issue>3</issue>
          ),
          <fpage>102</fpage>
          -
          <lpage>121</lpage>
          (
          <year>2019</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          <source>doi:10.33407/itlt.v71i3.2449</source>
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          <string-name>
            <surname>Kiv</surname>
            ,
            <given-names>A.E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Shyshkina</surname>
            ,
            <given-names>M.P</given-names>
          </string-name>
          . (eds.)
          <source>Proceedings of the 7th Workshop on Cloud Technologies</source>
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          <source>in Education (CTE</source>
          <year>2019</year>
          ), Kryvyi Rih, Ukraine, December
          <volume>20</volume>
          ,
          <year>2019</year>
          , CEUR-WS.org, online
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          (
          <year>2020</year>
          , in press)
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          <string-name>
            <surname>Asteriou</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Hall</surname>
            ,
            <given-names>S.G.</given-names>
          </string-name>
          :
          <article-title>Applied Econometrics, 2nd edn</article-title>
          . Macmillan, New York (
          <year>2011</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          <source>Trends</source>
          <volume>61</volume>
          (
          <issue>3</issue>
          ),
          <fpage>613</fpage>
          -
          <lpage>635</lpage>
          (
          <year>2013</year>
          ). doi:
          <volume>10</volume>
          .1353/lib.
          <year>2013</year>
          .0003
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          7. Council Recommendation of 22 May 2018 on
          <article-title>Key Competences for Lifelong Learning</article-title>
          .
          <source>Official Journal of the European Union</source>
          (
          <year>2018</year>
          ). https://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=
          <source>CELEX:32018H0604%2801%29</source>
          (
          <year>2018</year>
          ).
          <source>Accessed 28 Nov 2019</source>
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          8.
          <string-name>
            <surname>Drijvers</surname>
            ,
            <given-names>P.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kieran</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Mariotti</surname>
            ,
            <given-names>M.A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Ainley</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Andresen</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Chan</surname>
            ,
            <given-names>Y.C.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dana-Picard</surname>
            ,
            <given-names>T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gueudet</surname>
            ,
            <given-names>G.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kidron</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Leung</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Meagher</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          :
          <article-title>Integrating Technology into Mathematics Education: Theoretical Perspectives</article-title>
          . In: Hoyles,
          <string-name>
            <given-names>C.</given-names>
            ,
            <surname>Lagrange</surname>
          </string-name>
          , J.-B. (eds.)
          <source>Mathematics Education and Technology - Rethinking the Terrain</source>
          , pp.
          <fpage>89</fpage>
          -
          <lpage>132</lpage>
          . Springer, Boston (
          <year>2009</year>
          ). doi:
          <volume>10</volume>
          .1007/978-1-
          <fpage>4419</fpage>
          -0146-
          <issue>0</issue>
          _
          <fpage>7</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          9.
          <string-name>
            <surname>Hlushak</surname>
            ,
            <given-names>O.M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Proshkin</surname>
            ,
            <given-names>V.V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Lytvyn</surname>
            ,
            <given-names>O.S.:</given-names>
          </string-name>
          <article-title>Using the e-learning course “Analytic Geometry” in the process of training students majoring in Computer Science and Information Technology</article-title>
          . In: Kiv,
          <string-name>
            <given-names>A.E.</given-names>
            ,
            <surname>Soloviev</surname>
          </string-name>
          , V.N. (eds.)
          <source>Proceedings of the 6th Workshop on Cloud Technologies in Education (CTE</source>
          <year>2018</year>
          ), Kryvyi Rih, Ukraine, December
          <volume>21</volume>
          ,
          <year>2018</year>
          .
          <source>CEUR Workshop Proceedings</source>
          <volume>2433</volume>
          ,
          <fpage>472</fpage>
          -
          <lpage>485</lpage>
          . http://ceur-ws.org/Vol2433/paper32.pdf (
          <year>2019</year>
          ).
          <source>Accessed 10 Sep 2019</source>
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          10.
          <string-name>
            <surname>Kiv</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Semerikov</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Soloviev</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kibalnyk</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Danylchuk</surname>
            ,
            <given-names>H.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Matviychuk</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>Experimental Economics and Machine Learning for Prediction of Emergent Economy Dynamics</article-title>
          . In: Kiv,
          <string-name>
            <given-names>A.</given-names>
            ,
            <surname>Semerikov</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            ,
            <surname>Soloviev</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Kibalnyk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>L.</given-names>
            ,
            <surname>Danylchuk</surname>
          </string-name>
          ,
          <string-name>
            <given-names>H.</given-names>
            ,
            <surname>Matviychuk</surname>
          </string-name>
          ,
          <string-name>
            <surname>A</surname>
          </string-name>
          . (eds.)
          <article-title>Experimental Economics and Machine Learning for Prediction of Emergent Economy Dynamics</article-title>
          ,
          <source>Proceedings of the Selected Papers of the 8th International Conference on Monitoring, Modeling &amp; Management of Emergent Economy (M3E2</source>
          <year>2019</year>
          ), Odessa, Ukraine, May
          <volume>22</volume>
          -24,
          <year>2019</year>
          . CEUR Workshop Proceedings 2422,
          <fpage>1</fpage>
          -
          <lpage>4</lpage>
          . http://ceurws.org/Vol-
          <volume>2422</volume>
          /paper00.pdf (
          <year>2019</year>
          ).
          <article-title>Accessed 1 Aug 2019</article-title>
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          11.
          <string-name>
            <surname>Kiyanovska</surname>
            ,
            <given-names>N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Rashevska</surname>
          </string-name>
          , N.:
          <article-title>Using LMS for supporting training mathematics in higher education</article-title>
          .
          <source>Metallurgical and Mining Industry</source>
          <volume>7</volume>
          (
          <issue>9</issue>
          ),
          <fpage>593</fpage>
          -
          <lpage>598</lpage>
          (
          <year>2015</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          12.
          <string-name>
            <surname>Kyslova</surname>
            ,
            <given-names>M.A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Semerikov</surname>
            ,
            <given-names>S.O.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Slovak</surname>
            ,
            <given-names>K.I.</given-names>
          </string-name>
          :
          <article-title>Development of mobile learning environment as a problem of the theory and methods of use of information and communication technologies in education</article-title>
          .
          <source>Information Technologies and Learning Tools</source>
          <volume>42</volume>
          (
          <issue>4</issue>
          ),
          <fpage>1</fpage>
          -
          <lpage>19</lpage>
          (
          <year>2014</year>
          ). doi:
          <volume>10</volume>
          .33407/itlt.v42i4.
          <fpage>1104</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          13.
          <string-name>
            <surname>Kyslova</surname>
            ,
            <given-names>M.A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Slovak</surname>
            ,
            <given-names>K.I.</given-names>
          </string-name>
          :
          <article-title>Method of using mobile learning environments in teaching mathematics of future electromechanical engineer</article-title>
          .
          <source>Information Technologies and Learning Tools</source>
          <volume>51</volume>
          (
          <issue>1</issue>
          ),
          <fpage>77</fpage>
          -
          <lpage>94</lpage>
          (
          <year>2016</year>
          ). doi:
          <volume>10</volume>
          .33407/itlt.v51i1.
          <fpage>1360</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          14.
          <string-name>
            <surname>Modlo</surname>
          </string-name>
          ,
          <string-name>
            <surname>Ye</surname>
          </string-name>
          .O.,
          <string-name>
            <surname>Semerikov</surname>
            ,
            <given-names>S.O.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Bondarevskyi</surname>
            ,
            <given-names>S.L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Tolmachev</surname>
            ,
            <given-names>S.T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Markova</surname>
            ,
            <given-names>O.M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Nechypurenko</surname>
            ,
            <given-names>P.P.</given-names>
          </string-name>
          :
          <article-title>Methods of using mobile Internet devices in the formation of the general scientific component of bachelor in electromechanics competency in modeling of technical objects</article-title>
          . In: Kiv,
          <string-name>
            <given-names>A.E.</given-names>
            ,
            <surname>Shyshkina</surname>
          </string-name>
          ,
          <string-name>
            <surname>M.P</surname>
          </string-name>
          . (eds.)
          <source>Proceedings of the 2nd International Workshop on Augmented Reality in Education (AREdu</source>
          <year>2019</year>
          ), Kryvyi Rih, Ukraine, March
          <volume>22</volume>
          ,
          <year>2019</year>
          .
          <source>CEUR Workshop Proceedings</source>
          <volume>2547</volume>
          ,
          <fpage>217</fpage>
          -
          <lpage>240</lpage>
          . http://ceur-ws.org/Vol2547/paper16.pdf (
          <year>2020</year>
          ).
          <source>Accessed 10 Feb 2020</source>
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          15.
          <string-name>
            <surname>Mykhalevych</surname>
            ,
            <given-names>V.M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Tyutyunnik</surname>
            ,
            <given-names>O.I.</given-names>
          </string-name>
          :
          <article-title>Design of educational problems on linear programming using systems of computer mathematics</article-title>
          .
          <source>Information Technologies and Learning Tools</source>
          <volume>38</volume>
          (
          <issue>6</issue>
          ),
          <fpage>123</fpage>
          -
          <lpage>137</lpage>
          (
          <year>2013</year>
          ). doi:
          <volume>10</volume>
          .33407/itlt.v38i6.
          <fpage>896</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          16.
          <string-name>
            <surname>Országhová</surname>
            ,
            <given-names>D.:</given-names>
          </string-name>
          <article-title>The Application of Computational Tools of IT in Mathematical Tasks</article-title>
          . In:
          <string-name>
            <surname>Smyrnova-Trybulska</surname>
          </string-name>
          , E. (ed.)
          <source>Effective Development of Teachers' Skills in the Area of ICT</source>
          , pp.
          <fpage>438</fpage>
          -
          <lpage>448</lpage>
          . Studio-Noa for University of Silesia, Katowice-Cieszyn (
          <year>2017</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          17.
          <string-name>
            <surname>Pedace</surname>
          </string-name>
          , R.: Econometrics for Dummies. Wiley, Hoboken (
          <year>2013</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          18.
          <string-name>
            <surname>Proekt</surname>
          </string-name>
          <article-title>Tsyfrova adzhenda Ukrainy - 2020 (“Tsyfrovyi poriadok dennyi”-</article-title>
          <year>2020</year>
          ).
          <article-title>Kontseptualni zasady (versiia 1.0). Pershocherhovi sfery, initsiatyvy, proekty “tsyfrovizatsii” Ukrainy do 2020 roku (Digital Agenda of Ukraine Project -</article-title>
          2020
          <string-name>
            <surname>(“Digital Agenda</surname>
          </string-name>
          ”
          <article-title>-</article-title>
          <year>2020</year>
          ).
          <source>Conceptual principles (version 1.0)</source>
          . Priority areas, initiatives, projects of “digitalization” of Ukraine until
          <year>2020</year>
          ). http://ucci.org.ua/uploads/files/58e78ee3c3922.pdf (
          <year>2016</year>
          ).
          <source>Accessed 28 Nov 2019</source>
        </mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation>
          19.
          <string-name>
            <surname>Pursky</surname>
            ,
            <given-names>O.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dubovyk</surname>
            ,
            <given-names>T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Gamova</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Buchatska</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          :
          <article-title>Computation Algorithm for Integral Indicator of Socio-Economic Development</article-title>
          . In: Ermolayev,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Mallet</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            ,
            <surname>Yakovyna</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Kharchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Kobets</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Korniłowicz</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            ,
            <surname>Kravtsov</surname>
          </string-name>
          ,
          <string-name>
            <given-names>H.</given-names>
            ,
            <surname>Nikitchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            ,
            <surname>Semerikov</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            ,
            <surname>Spivakovsky</surname>
          </string-name>
          ,
          <string-name>
            <surname>A</surname>
          </string-name>
          . (eds.)
          <source>Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI</source>
          ,
          <year>2019</year>
          ), Kherson, Ukraine, June 12-15
          <year>2019</year>
          , vol.
          <source>II: Workshops. CEUR Workshop Proceedings</source>
          <volume>2393</volume>
          ,
          <fpage>919</fpage>
          -
          <lpage>934</lpage>
          . http://ceur-ws.org/Vol2393/paper_267.
          <string-name>
            <surname>pdf</surname>
          </string-name>
          (
          <year>2019</year>
          ).
          <source>Accessed 30 Jun 2019</source>
        </mixed-citation>
      </ref>
      <ref id="ref22">
        <mixed-citation>
          20.
          <string-name>
            <surname>Rashevska</surname>
            ,
            <given-names>N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Tkachuk</surname>
            ,
            <given-names>V.</given-names>
          </string-name>
          :
          <article-title>Using LMS for supporting training mathematics in higher education</article-title>
          .
          <source>Metallurgical and Mining Industry</source>
          <volume>7</volume>
          (
          <issue>9</issue>
          ),
          <fpage>593</fpage>
          -
          <lpage>598</lpage>
          (
          <year>2015</year>
          )
        </mixed-citation>
      </ref>
      <ref id="ref23">
        <mixed-citation>
          21.
          <string-name>
            <surname>Semerikov</surname>
            ,
            <given-names>S.O.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Slovak</surname>
            ,
            <given-names>K.I.</given-names>
          </string-name>
          :
          <article-title>Theory and method using mobile mathematical media in the process of mathematical education higher mathematics students of economic specialties</article-title>
          .
          <source>Information Technologies and Learning Tools</source>
          <volume>21</volume>
          (
          <issue>1</issue>
          ) (
          <year>2011</year>
          ). doi:
          <volume>10</volume>
          .33407/itlt.v21i1.
          <fpage>413</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref24">
        <mixed-citation>
          22.
          <string-name>
            <surname>Slovak</surname>
            ,
            <given-names>K.I.</given-names>
          </string-name>
          :
          <article-title>Methodology of separate components formation of mobile mathematical environment “Higher mathematics”</article-title>
          .
          <source>Information Technologies and Learning Tools</source>
          <volume>30</volume>
          (
          <issue>4</issue>
          ) (
          <year>2012</year>
          ). doi:
          <volume>10</volume>
          .33407/itlt.v30i4.
          <fpage>687</fpage>
        </mixed-citation>
      </ref>
      <ref id="ref25">
        <mixed-citation>
          23.
          <string-name>
            <surname>Soloviev</surname>
            ,
            <given-names>V.N.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Moiseenko</surname>
            ,
            <given-names>N.V.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Tarasova</surname>
            ,
            <given-names>O.</given-names>
          </string-name>
          <article-title>Yu: Modeling of Cognitive Process Using Complexity Theory Methods</article-title>
          . In: Ermolayev,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Mallet</surname>
          </string-name>
          ,
          <string-name>
            <given-names>F.</given-names>
            ,
            <surname>Yakovyna</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Kharchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Kobets</surname>
          </string-name>
          ,
          <string-name>
            <given-names>V.</given-names>
            ,
            <surname>Korniłowicz</surname>
          </string-name>
          ,
          <string-name>
            <given-names>A.</given-names>
            ,
            <surname>Kravtsov</surname>
          </string-name>
          ,
          <string-name>
            <given-names>H.</given-names>
            ,
            <surname>Nikitchenko</surname>
          </string-name>
          ,
          <string-name>
            <given-names>M.</given-names>
            ,
            <surname>Semerikov</surname>
          </string-name>
          ,
          <string-name>
            <given-names>S.</given-names>
            ,
            <surname>Spivakovsky</surname>
          </string-name>
          ,
          <string-name>
            <surname>A</surname>
          </string-name>
          . (eds.)
          <source>Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI</source>
          ,
          <year>2019</year>
          ), Kherson, Ukraine, June 12-15
          <year>2019</year>
          , vol.
          <source>II: Workshops. CEUR Workshop Proceedings</source>
          <volume>2393</volume>
          ,
          <fpage>905</fpage>
          -
          <lpage>918</lpage>
          . http://ceur-ws.org/Vol2393/paper_356.
          <string-name>
            <surname>pdf</surname>
          </string-name>
          (
          <year>2019</year>
          ).
          <source>Accessed 30 Jun 2019</source>
        </mixed-citation>
      </ref>
      <ref id="ref26">
        <mixed-citation>
          24. State Statistics Service of Ukraine. http://www.ukrstat.gov.ua (
          <year>2019</year>
          ).
          <source>Accessed 28 Nov 2019</source>
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>