=Paper=
{{Paper
|id=Vol-1844/10000207
|storemode=property
|title=Integration of Information Technologies’ Dynamic Development into
Academic Teaching Process
|pdfUrl=https://ceur-ws.org/Vol-1844/10000207.pdf
|volume=Vol-1844
|authors=Galyna Chornous,Serhii Rybalchenko
|dblpUrl=https://dblp.org/rec/conf/icteri/ChornousR17
}}
==Integration of Information Technologies’ Dynamic Development into
Academic Teaching Process==
https://ceur-ws.org/Vol-1844/10000207.pdf
Integration of Information Technologies’ Dynamic
Development into Academic Teaching Process
Galyna O. Chornous, Serhii A. Rybalchenko
Taras Shevchenko National University of Kyiv, Faculty of Economics, Department of Eco-
nomic Cybernetics, 03022 Vasylkivska str. 90a, Kyiv, Ukraine
chornous@univ.kiev.ua, sergiy.rybalchenko@gmail.com
Abstract. Modern trends in information technologies related to academic per-
ception are looked upon in this paper. The essence of exponential growth of vol-
umes of information relative to IoT intensification is disclosed. The place and
role of higher education in the process of knowledge spread methods, collection,
storage, processing and transmission of information is defined. Effective prac-
tices of working with students in the "Decision Support Systems" and "Infor-
mation systems and technology in the economy" courses are shown. Elements of
coherent training are implemented. The efficiency of the combination of theoret-
ical, practical and on-line business courses within the normative study is proven.
Keywords: Information systems, self-learning, SAP UA, DSS.
Key Terms: Academia, Integration, TeachingProcess, AgentBasedSystem.
1 Introduction
Economic growth has always been based on resources. From the definition of informa-
tional society and post-industrial economy in 1973 by D. Bell., the weight of infor-
mation as a resource and a factor of production has been steadily increasing. First in-
formation systems emerged as instruments serving the elements of economic activity.
In 1976 SAP company launched MRP-accounting solution for businesses. Over time,
similar solutions have evolved up to full support of comprehensive enterprise with
much less time and material cost. At this point, information has become a driving and
the main factor of production in post-industrial economy. The development of infor-
mation systems was accompanied by formation of new markets and industries. Analyt-
ical solutions, knowledge management systems and artificial intelligence comprise
modern trend of focusing information industries efforts. Information process moved
from the stage of formation and development to the exponential growth of all items:
accumulation (reproduction) and growth (processing).
In those circumstances, future training of qualified personnel depends on ability to
quickly adapt to rapidly changing processes and synthesis of long trends. A steady prac-
tice of academic study is its cyclical changes in regulations and training courses. The
average duration of such cycle is 5-6 years, or the period of preparation of educationally
level of "master". In such a long by modern standards time, emergence of new solutions,
methods and conditions in modern market is natural. This suggests a slow nature and
reduction in efficiency of academic study. At the same time employers’ rankings, QS
World University Rankings, Top 200 Ukraine (IREG) constantly show the need for
higher education professionals in information industries. Moreover, the number of tech-
nical universities is lower compared to classical universities. This means high and
growing relevance of academic study with consideration of the exponential dynamics
of the environment.
The basis for this piece of work is a practical training of 3-5th year students and
simultaneous training of lecturers of the Faculty of Economics of Taras Shevchenko
National University of Kyiv.
Taras Shevchenko National University of Kyiv also is active participant of the global
program SAP University Alliances (SAP UA). Eight-year experience of collaboration
with one of leading software vendors gives an opportunity to do certain conclusions in
relation to IT studies efficiency in the modern fleeting world.
The object of study - effectiveness of the learning process of dynamic IT.
Subject of research - analysis and synthesis method, quantitative method of measur-
ing and comparing, historical method.
The aim - to create effective practices and recommendations of the study of infor-
mation systems and technologies of wide application.
The goal will be revealed through the following objectives:
• Determine the conditions and trends of the environment;
• Outline the main information technology;
• Explain the internal conditions of the learning process of IT;
• Summarize the experience of forming competencies in students;
• Show effective methods of involvement in learning;
• Develop recommendations for intensification of cooperation between external and
internal environments.
2 Dynamics of Products of Informational Solutions for
Economy
The focus of the majority of important conferences and forums with economical and
informational inclination is on discussing the topics on Internet of Things spreading
technology, a new stage of scientific and technological revolution - Industry 4.0 and
Artificial Intelligence. Each of these areas is self-contained and requires separate niche
research. But some features are still worth noting here.
Internet of Things (IoT) - a network consisting of interconnected physical objects
(things) or devices that have built-in sensors and software that allows you to transfer
and exchange data between the physical world and computer systems, through standard
communication protocol [1]. Information about the current state of the object in online
mode is transmitted to the processing means: computers, server, smartphone, etc.
Working on data sets using intellectual systems allows to anticipate problem and im-
prove efficiency, changing working modes of object automatically without human in-
tervention. According to various forecasts the number of such connections by 2020 will
reach 15-24 bln., and investments will amount to $2-5 trillion. Such forecasts are up-
lifting, but they are not decisive. Trend of the generated information growth increases
exponentially. Recently, measuring information in Gigabytes was perfectly normal, but
now even private users are already familiar with Terabyte, and corporate users with
Peta- and Exabyte.
Huge volumes of information require processing and effective solutions [2]. Other-
wise the gap is formed between the primary and processed information flow per unit of
time. As a result, knowledge about the current state will not be complete. According to
Moore's law the number of transistors in a processor, i.e. its’ efficiency, doubles every
24 months.
500000000
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r 400000000
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n 300000000
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t 100000000 486TM DX Pentium 4
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o 4004 8080 8086 286 processor processor
processor
r 0 386TM Pentium II
Pentium
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s processor processor processor
-1E+08 1997 2000 2003
1974 1978 1982 1985 1989 1993
Year
Fig. 1. Number of transistors per a chip processor
As you can see (Fig. 1.) exponential dependence clearly emerges. Popularity of the law
is supported by the fact that it was formed in 1965, and receives constant empirical
evidence despite the regular technological limitations. In the words of Moore himself,
the law will have ceased to be functional by 2007 because of the atomic nature of matter
and the speed limit of light, but the technological development of a quantum computer
can continue by the said exponential curve. For convenience, changing trends in the
exponentially-dynamic ranks are put into charts with a logarithmic scale.
1E+09 Itanium
T Xeon
100000000 Pentium III
r 486TM DX Pentium 4
processor
a 10000000 processor
Pentiumprocessor
II
1000000 Pentium processor
n 286
processor
s 100000 8086 386TM
i 8080 processor
10000 4004
s
t 1000 8008
o 100
r 10
s
1
1974 1978 1982 1985 1989 1993 1997 2000 2003
Year
Fig. 2. Linear measurement of growth in the number of transistors
Figure 2 clearly shows that the increase in geometric progression is not an ideal con-
stant, but still quite close to the dependence of uniform acceleration. That is, it creates
a sense of confidence in long-term empirical means of processing and analyzing grow-
ing volumes of information. But in processing of primary data, new secondary infor-
mation and knowledge are formed, which is also multiplied off of primary data volumes
and processing speed at the k <1 coefficient. With an estimated ratio of 0.2, it means
that the ways of processing and analytics should grow 20-30% faster than exponential
growth of primary data sets. But production of efficient hardware and intelligent means
also affect the economic, social and other spheres of public life.
This result is the transitional effect of these information industry trends into the rest
of the productive sectors of social reproduction.
0
The Web
10
Y Mobile Phone
e 20 PC
a Radio
r 30 Telephone Television
s
40
Electricity
50
1873 1897 1926 1975 1991
Year
Fig. 3. Years to spread the innovations among 1/4 of the US population
Along with the effect of constant growth of innovation and its’ transitive effect there is
a permanent reduction of time for implementation and development of technological
innovation (Fig. 3.). Current conditions in informational systems and technologies are
characterized by rapid dynamics of public importance and complexity of regular instru-
ments. This in turn may make the entry barrier in the growth of new industry profes-
sionals and slowing down the development. Therefore, training should include famil-
iarization of students with these industry turnover and get them onto solving this prob-
lem. It is possible to implement by the team reports with creative scenarios and recom-
mendations. Game simulative effect creates a mood of lightness and increases audi-
ences’ engagement to the problems.
Examples of futuristic scenarios are supplemented with reflections of listeners. One
of these scenarios is the invention of artificial intelligence during 2050-2060 (Fig. 4.)
and its’ consequences. Such a scenario is called "technological singularity".
1E+28 Calculations
C 1E+26 per
P 1E+24 second/$1,0
S 1E+22 y = 5E-258e0,3042x 00
1E+20 R² = 0,9341 One Insect
p 1E+18 Brain
1E+16
e
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1E+10 Brain
1 100000000
0 1000000
10000 One Human
0
Brain
100
0
1
$
0,011900 2000 2100
0,0001 All Human
Brains
0,000001
Year
Fig. 4. Alignment of calculation abilities of PC, man and society [3]
Technological singularity in futurology - hypothetical explosive growth rate of scien-
tific and technological progress, which is likely to come as a result of creation of arti-
ficial intelligence and machines capable of reproduction [4]. One of the expected con-
sequences is the impossibility of understanding the human brain processes that will
complicate significantly.
Another direction of case tasks and reports is the Industry 4.0. It deals with the in-
fluence on contemporary forms of production of automated technology, development
of market of weak buyer as well as close formation of market of week seller. In this
situation, the most powerful driving force of the market is analytical system containing
information on consumer preferences, which provides for their needs, knows the pos-
sibilities and sellers know how to achieve optimum performance. Also considered are
hypothetical new forms of business with the possibility of immediate product configu-
ration for individual order.
3 Proactivity, Cognition and Agent-Based Technologies
Perceived necessity to ensure stability in the functioning of the socio-economic systems
and the ability to implement it in terms not only of present moment, but also the future,
makes imperative of proactivity. Proactivity claims to constantly examine the changing
boundaries of the possible, and within that framework, you attain your goals, including
goals of growth and development.
The pace of social development in the information period requires a proactive way
of thinking, proactive decision-making [5]. The basis of mechanism proactive manage-
ment decisions’ ideology is continuous automation, integration of all information flows
and management functions into one strong unit. Modern DSS [6; 7] must be able to
process large volumes of structured and unstructured data; maintain rational and irra-
tional approach to decision-making; organically combine the two types of intelligence
- human and artificial; use formal and informal techniques of cognitive analysis; sup-
port of proactive production, storage and subsequent use for systematic control cogni-
tive information - knowledge.
Prospects of effectivization in management information systems (IS) are considered
only if they will be intellectual. Moreover, now talking not just about intellectual IS,
but the cognitive systems - the systems in which the internal mechanisms of cognitive
information processing integrated with process of natural intelligence modeling
through artificial intelligence and collective intelligence. Modern DSS should decide
together the classical analytical tasks and the new cognitive tasks connected with pro-
active search of knowledge.
A survey conducted among managers about 6 thousand companies from around the
world (including 129 from Ukraine and CIS) shows that the implementation of cogni-
tive computing and development on this basis of intelligent information systems relate
to technologies that foremost will transform business in the next 3-5 years (Fig. 5).
Understanding current state of information and analytical decision-making support
in the national economy can to create options for improvement and modernization,
which will provide a necessary integration into the global information and economic
space, and to create competitive advantages of the national economy. The search for
such options is one of the important tasks of the study course DSS at the Economics
Faculty of University. So preparation of case-studies for implementation in the class-
room as well as the formation of tasks for individual work of students concerns such
basic provisions.
Firstly, to solve the task of proactive solutions support we need to develop DSS
model, which combines the latest technological achievements such as technology of
information management; data mining technology; modeling technology in real time;
mobile technology; technology of decision support in real time.
5%
Man-machine hybrids 10%
5%
Biotechnology 12%
24%
New energy sources 23%
27%
Advanced production technology 28%
41%
Cognitive computing 37%
45%
Internet of Things 57%
76%
Mobile solutions 61%
70%
Cloud computing and services 63%
0% 50% 100%
Ukraine and CIS World
Fig. 5. Results of the survey of CEOs on the impact of technology on business transformation
(IBM, 2016)
Secondly, the basis for the development of cognitive DSS is set to put a hybrid approach
which combines the advantages of accumulated decision support software, efficiently
synthesizes various approaches to the collection and processing of data, combines var-
ious intellectual methods and models, actively involves the hybrid algorithms.
Thirdly, the need to combine in one model a significant number of tools to collect,
prepare and analyze data and provide with parallel operations, negotiations, distribution
solutions, knowledge management requires the decentralization and the use of network
structure in the DSS.
A promising direction for implementation of DSS is distributed intelligent systems
based on agent-oriented approach. Multi-agent systems (MAS) are a radical concept
that opens an era of networked organizations with the collective interaction of software
agents, providing powerful replace centralized structure completely decentralized,
which gives way the network instead of the hierarchical structure. Chronology of the
concept of agent-oriented approach and the MAS is presented in [8; 9]. Practical im-
plementation of MAS in industries, information and telecommunications, in public and
organizational management presented in [10; 11; 12] and other sources.
The agent-based approach leads to a multilevel combination of hardware, software,
conceptual entities that form the heterogeneous structure of the global information
space, allows you to build very large open, flexible, reliable, productive cognitive sys-
tems, each component of which is completely autonomous, but if necessary coordinates
activity with other systems.
On the bases of great prospects of this approach students are invited to divide in
teams of 7-8 people for realization of the individual projects and to develop the concept
of agent-oriented DSS, which monitors and analyzes the situation in certain particular
socio-economic system and provides for implementation of data mining models.
As a result of this project the students, firstly, get to know the concepts of multi-
agent and agent-oriented systems, and secondly, they involved in the study of the vari-
ous agent platforms - specialized software systems containing a set of software tools
and describing the behavior of agents and the state of the environment.
Due to the fact that agent-oriented approach has great demand both in scientific re-
search as well as for business process management, a lot of agent platforms are devel-
oped, for instance, ABLE, Altreva Adaptive Modeler, AgentBuilder, AgentSheets,
Aglobe, AnyLogic, Ascape, Brahms, Breve, Construct, Cormas, Cougaar, DeX, D-
OMAR, ECHO, ECJ, Eclipse AMP, FAMOJA, Framsticks, GPU Agents, GROWlab,
iGen, JADE, JAS, JASA, Jason, JCA-Sim, jES, jEcho, JESS, LSD, MacStarLogo,
Madkit, MAGSY, MAML, MASON, MAS-SOC, MATLAB, MIMOSE, Moduleco,
MOOSE, NetLogo, OBEUS, Omonia, OpenStarLogo, oRIS, PS-I, Repast, SDML,
SEAS, SeSAm, SimPlusPlus, SimAgent, SimBioSys, SimPack, SME, Soar, StarLogo,
StarLogoT, StarLogoTNG, Sugarscape, Swarm, VisualBots, VSEit, ZEUS.
The students found that almost half of the listed platforms (31 of 65) makes it pos-
sible to simulate MAS for general purpose, but there are special platforms developed
for environmental and biocommunity modeling (Cormas, ECHO, jEcho, SME), social
modeling (MAML, MAS- SOC, MIMOSE, VSEit), organizational processes' modeling
(Brahms, Construct), economic processes (Altreva Adaptive Modeler).
According to software implementation, agent-based platform can be a complete de-
velopment environment (AnyLogic, NetLogo), as well as built-in modules (Repast
Simphony), pluggable libraries (JADE). 40 platforms require knowledge of program-
ming languages (C, C ++, C #, Java), while others use specially developed agents mod-
eling language (Logo in NetLogo, AgentSpeak in Jason). Only 9 platforms come with
open source, another 17 have free license (with different limitations).
Comparative analysis of capabilities of platforms for general purpose with a free
license and low requirements for programming skills, leads to the fact that in most cases
for their further studies students choose software environment NetLogo.
In addition to agent-based platforms, students explore the possibilities and specific
features of the intellectual data analysis software, selecting some tools in one or more
systems, presented in Table 1.
Finally, students learn how to integrate various types of software efficiently for man-
agement based on the existing IT infrastructure through the use of software agents.
Agents are created and destroyed in accordance with the needs of specific tasks, net-
work architecture MAS allows new agents to connect to the "on the fly" (or existing
switched off) without stopping and restarting other structural elements of the system.
Thus students create a conceptual model of a system that can be a part of a global
network environment, its structural link. The requirements imposed on modern DSS: a
high level of flexibility, efficiency and productivity; adaptability to changes in environ-
mental conditions; high potential of integration and interaction with other systems are
specific to agent systems.
Table 1. Samples of Data Mining software
Methods of Mining,
Samples of software
groups of IS
Microsoft SQL Server Data Mining, IBM DB2 Intelligent Miner,
DBMS
Oracle Data Mining, SAP HANA (in-memory analytics)
Oracle Advanced Analytics, IBM SPSS Modeler; PolyAnalyst,
IBM SPSS Predictive Analytics Enterprise, SAP Predictive Anal-
Analytical plat-
Data Mining
ysis, SAS Enterprise Miner, Deductor;
forms
Systems that implement in-memory analytics:
SAP InfiniteInsight, Oracle Exalytics In-Memory Software
Statistical pack- SAS/STAT, SAS Visual Analytics, STATISTICA Data Miner,
ages The R Project for Statistical Computing, Weka
Neural networks: Neuro Pro, NeuralWorks Professional II Plus,
NeuroShell 2, Neuro Оffice, NeuralWorks Professional, Brain-
Special pack-
Maker Pro;
ages
Genetic algorithms: GeneHunter, Auto2Fit3, KnowledgeMiner ;
Fuzzy logic: FuziCalc CubiCalc, Fuzzy Logic Toolbox
Oracle Data Miner, Oracle Endeca Information Discovery,
Visual Mining
IBM Cognos Insight, SAP Lumira, SAS Visual Analytics
SAS Text Miner, STATISTICA Text Miner, TextAnalyst,
Textalytics, SAP BusinessObjects Text Analitycs, Salience En-
Text Mining
gine, WordStat, KnowledgeREADER, DiscoverText, NetOwl,
TextMiner
Students develop the systems composed of many modules connected through infor-
mation and intellectual integration of the various levels of management. Among the
components of such systems can be the situational centers that provide fast and deep
"immersion" into situation for decision-maker and getting of reasonable solution; local
DSS; BI platform; subsystems of corporate information system for local strategic deci-
sion support; local systems operational decisions; analytical platforms and various soft-
ware applications.
Developing a system that creates a proactive solution, each student had hones skills
of effective teamwork and his own competence of proactivity, passes from adaptive
flexible adaptation to environmental conditions to an active, proactive impact on the
environment, to the model of proactive behavior. Collective interaction of software
agents in the created agent-based DSS, along with rational integration of different types
of software and the ability to solve cognitive tasks generates system proactivity com-
petence of the information system because proactivity is the basic property of each
agent, which it gives for a functioning system.
The main advantages of this approach to self-learning, is that it gives a theoretical
possibility to simulate without simplifying decisions of the complex practical problems
that constantly occur the economy; leads to the creation of social self-organizing mod-
els, each element of which is developing, getting information and knowledge from other
elements. The value of this approach is that it allows to create and experiment with
many techniques that adapt to the continuous changes in the composition and structure
of heterogeneous tasks, directs evolution methods of storage, processing, modeling in
a channel defined by the laws of nature, of society and science. It opens the way for
students to synthesize IS capable of solving problems not only today but also those that
provide opportunities for the future to include the most relevant elements and methods
that appear through continuous identification of new, unknown up to this time of the
fundamental laws of development and behavior of socio-economic systems, which are
closely related to nature, man and created equipment and technology.
4 Thinking as Innovation
As an active participant in global program SAP University Alliances, in practical train-
ing, students freely use SAP ERP solution. Besides, those wishing, participate in the
regular activities of SAP InnoJam, where "Design Thinking" technology of innovation
is presented. Elements of this way of creative design space of innovative solutions de-
velopment is implemented in the "Information systems and technology in the economy"
course.
Students are encouraged to split into teams of 3 people and develop software to op-
timize the pressing problems: for example, queues in the student cafeteria, urban traffic
jams, etc. Then during class 2 teams report their results under the "Tournament of young
inventors (physics / mathematics)." The reports are presented by teams one by one.
The average attendance rate of students of 4th year is 53%, but during the report
sessions mentioned above, attendance increases. All the attending students, except
those that were reporting, are involved into evaluating the reports. Results are ranking
in nature, subject to normal distribution, and therefore can be considered objective.
Only 10% of the total participants failed to perform a full report of their own decisions
(Fig. 6).
7
S 6
t 5
u
d 4
e 3
n
t
2
s 1
0
6 7 8 9 10 11 12 13 14 15 16 17 18
Points
Fig. 6. Students’ score distribution for "Design Thinking"
The results developed during the presentations of reports can be used by students in
further research and practice.
5 Cloud Technologies and Self-Learning Opportunities
As described in Section 2, the number of tools, solutions and information systems is
increasing, the students were offered to individually study a certain information system
from the list in Table 2.
Table 2. List of IS for the personal study
Microsoft Dynamics CRM ARIS Express
Salesforce (CRM) StarUML 2
NetSuite CRM SmartDraw
SAP CRM Oracle ERP Cloud
Oracle CRM Decision Lens
SAP Business Objects Cogito
Microsoft SharePoint Microsoft Power BI
Sisense Hyperion Solutions Corporation
Business Intelligence and Reporting
IBM Cognos Business Intelligence
Tools (BIRT) Project
iDashboards FreeCBR
SAS Visual Analytics ManageEngine ServiceDesk Plus
QlikView
After personal study of one of these systems the students delivered their presenta-
tions. Obligatory elements were: to specify a product demo, describe the main functions
and develop a detailed business case and solve it with the use of the product.
According to the results of the final presentation, only 8% of students were unable
to cope with the task. The work was not assessed by rank but as to the availability of
finished assignments and therefore it is not of a normal distribution. 52% of students
completed the task very efficiently and showed great interest.
This form of training allowed to dramatically expand the list of products in which
the students received basic skills. In addition to SAP ERP-solutions, students can study
other modern systems up to the level 10+ user, like Oracle, Microsoft as a part of a
standard course.
The second part of this self-learning program is getting a certificate from any online
course of choice from open.sap.com portal. 96% of students completed the task thanks
to its’ availability and mobility. Of these, 60% did it efficiently (Fig. 7). Compared with
last year's results, the involvement of students in tasks completion increased dynami-
cally by 10-12% on average.
More than 10 online courses for the listeners’ registration were accessible during
studies. But students have demonstrated relative stationarity in a choice. On the whole
only 4 courses studied of own free will by students.
7
S 6
t
5
u
d 4
e 3
n 2
t
1
s
0
3 4 5 6 7 8 9 10
Points
Fig. 7. The score distribution for individual independent study of ISs
Also on Fig.8 we see a result (achievement) got students. Within the framework of
our course the "Information systems and technology in the economy" a student got
points in any case, regardless of online course passing quality. The important fact was
receiving at least a certificate of participation.
14
S 12
t
10
u
d 8
e 6
n
4 Students
t
s 2 90% 65% 78% 0%
0 Achievement
Enterprise Software Design Digital Text Analytics with
Machine Learning for Non-Designers Transformation SAP HANA
in a Nutshell Across the Platform
Extended Supply
Chain – In a
Nutshell
Online courses
Fig. 8. Student distribution among online courses
As students passed studies on online-courses independently, then results within one
type of course between different students had a stationary result also. It testifies for
command work or transitive transfer of correct answers to on-line-tests.
This is seen in Fig.9. A student received a certificate of successful achievement if
the results exceed 50%. In the opposite case - only a certificate of participation. Among
the nine students successfully passing the test, there are three levels of results - 58%,
67% and 72%. To improve the quality and independence of online learning can limit
the student’s free choice by setting a proposed courses range.
100%
A
c 80%
h
i 60%
r
e
a
v 40%
t
e
e
m 20%
e
n 0%
t 1 8 4 2 3 10 6 11 5 7 9 12
Students
Fig. 9. Student’s result distribution for online-course “Software Design for Non-Designers”
In the future it is planned to expand the list portals of quality online education of
information systems issues and practices. It is also planned to attach a simulation of
software industry tasks to the practical tasks.
6 Enhancement of Cooperation with Leading Software Vendors
As the information society imposes significant requirements for level of information
technologies and appropriate training is a necessary condition for the adequacy of the
realities of life, Taras Shevchenko National University of Kyiv has been developing
programs of cooperation with world leaders in the IT sector.
One of cooperation forms is participation in the global program of company SAP –
SAP University Alliances (more than 3,100 member institutions in over 106 countries).
The program exposes students and faculty to the latest SAP technologies and enables
universities to integrate SAP software into their teaching by partnering to build tech-
nology skills [13].
During 8 years of participating in this program such basic possibilities of the pro-
gram were implemented on Faculty of Economics: the teaching of academic disciplines
using SAP ERP, support projects and theses, regular presentations of experts of SAP
and partner company on the latest trends in IT, training in the partner companies of
SAP.
Awareness that a high level of IT training can be achieved only through continuous
professional development of lecturers, lies in the basic pillars of the program. 18 uni-
versity lecturers have been training in SAP Ukraine, SAP Academic Competence Cen-
tre, the Regional Academic SAP Certification Center in Taras Shevchenko National
University of Kyiv. 8 lecturers have international certificates SAP Certified Business
Associate with SAP ERP 6.0 and SAP Certified - Associate Business Foundation &
Integration with SAP ERP 6.0 EHP5, 2 lecturers have certificates SAP Certified Appli-
cation Associate - Human Capital Management with SAP ERP 6.0 EHP4 and SAP Cer-
tified Application Associate - Financial Accounting with SAP ERP 6.0 EHP4.
32 trainees passed the international certification in the Regional Academic SAP Cer-
tification Center in Taras Shevchenko National University of Kyiv, including 15 stu-
dents (SAP Certified - Associate Business Foundation & Integration with SAP ERP 6.0
EHP5).
As noted in Sections 4 and 5, students take part in the intelligent crosses InnoJam
and self-learning programs through free massive open online courses on the SAP
HANA platform, SAP Mobile Platform, design thinking, business network, Industry
4.0, Internet of Things, and more.
Thus the program provides empowerment of the university community on the latest,
most innovative topics from SAP, including to leverage massive open online courses
available on the openSAP platform and running operations in the cloud.
However, in our opinion, the program possibilities are not yet fully implemented in
Ukraine. Our university initiates extension of the program in Ukraine and suggests a
series of actions that will provide improvements in this area.
1. Extension of Ukrainian universities' representation in the SAP UA.
Nowadays, there are only 3 Ukrainian universities which are the active members of
the SAP UA. Considering the possibilities for development that SAP UA gives to uni-
versities and the fact that average of universities from developed countries are 50-150
institutions, it is necessary to intensify efforts to raise awareness about the program and
reduce entry barriers. It is also necessary to develop a minimum set of steps to upload
Ukrainian universities to the program and to perform adaptation of norms and require-
ments of global program to Ukrainian realities.
2. The development of scientific and industrial cooperation between the academic
and business institutions.
It is necessary to define the annual needs of companies in trainees and capacity of
Ukrainian universities - participants of the SAP UA, to develop a set of required com-
petencies of students for effective practical training.
Consistent improvement of educational materials and learning methods creates con-
ditions for scientific outsourcing. We must create a mechanism for coordination be-
tween universities and partner companies for clear delineation of the issues of integra-
tion and development of information systems in economics.
3. Creation of grants for specialized SAP courses’ student training.
The main competences of students on information systems generate during academic
courses according to the curriculum. But the advanced knowledge with subsequent in-
ternational certification is possible only for a fee. A permanent interest of the students
to specialized courses exists, but there is no objective possibility of incurring such costs
simultaneously. It should intensify communication and cooperation with international
grant agencies.
4. Creating of Innovative Research SAP Center in Ukraine.
Full performing of paragraph 2 will formulate a request for the establishment of in-
stitutional cooperation and communication among the market leaders in information
systems and universities in Ukraine.
5. International research cooperation.
The current active academic environment on information systems will allow partic-
ipants to intensify cooperation with the joint work of graduate and doctoral students
from universities in different countries. Mechanisms such studies have been realized
on the basis of several universities in the EU and the US.
6. The functioning of database 'the competent students - reliable employers'.
All students, who were trained on information systems in the universities, which are
participants of the SAP UA, will be entered into a database, showing the existing com-
petencies and grades. The program partners can upload vacancies or projected needs
with a set of required competencies. It is necessary to develop a software mechanism
of division of qualified students between vacancies.
These actions are important not just for the development of the program SAP UA in
Ukraine, they are typical for cooperation with any of the leading software vendors.
Without enhancement of cooperation, successful IT training cannot be provided in the
conditions of dynamic development of technology.
7 Conclusions
Information technology market is growing rapidly, it is a subject to sectorial dichotomy
and it transitively distributes its effects on other markets and spheres of public life. In
the next 5-10 years processing of IoT will become the most promising sector, alongside
with analytical systems market and modeling of artificial intelligence.
Academic teaching process should give possibilities to experiment with a lot of
methods that appear due to the constant discovery of new laws of systems' development,
create social models, self-organizing, each element of which is developing, getting in-
formation and knowledge from other elements.
For quality training in information technology, students’ initiatives should be en-
couraged and the exchange of experience between academic and business spheres
should be intensified. Now when technology is evolving faster than we can adapt for it,
there is an urgent need to enhance cooperation between universities and vendors of
software solutions that allows to keep up with the times both teachers and students.
Therefore, there is necessity of extension of Ukrainian universities' representation in
the programs of cooperation, for example, SAP University Alliances.
Combining classical theoretical learning with practical innovative approaches shows
the effectiveness and focuses students on common features of software solutions and
architectures. Permanent research on the changing boundaries of the possible allows to
develop proactivity competence of student without which today person cannot effec-
tively move forward and achieve goals.
The extent of involvement of business representatives and solution providers to the
cases and tasks is the basis for effective growth of studying. Through a blended learning
model, university should access software, bringing hands-on learning with world-class
enterprise software solutions into the classroom.
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