=Paper=
{{Paper
|id=Vol-1614/paper_18
|storemode=property
|title=University Curricula Modification Based on Advancements in Information and Communication Technologies
|pdfUrl=https://ceur-ws.org/Vol-1614/paper_18.pdf
|volume=Vol-1614
|authors=Yuriy Kondratenko,Dan Simon,Igor Atamanyuk
|dblpUrl=https://dblp.org/rec/conf/icteri/KondratenkoSA16
}}
==University Curricula Modification Based on Advancements in Information and Communication Technologies==
https://ceur-ws.org/Vol-1614/paper_18.pdf
University Curricula Modification Based on Advance-
ments in Information and Communication Technologies
Yuriy Kondratenko1,2, Dan Simon1, Igor Atamanyuk2
1
Department of Electrical Engineering and Computer Science
Cleveland State University, Cleveland, Ohio, USA
y.kondratenko@csuohio.edu, d.j.simon@csuohio.edu
2
Department of Intelligent Information Systems
Petro Mohyla Black Sea State University, 68-th Desantnykiv str. 10,
54003 Mykolaiv, Ukraine
y_kondrat2002@yahoo.com, atamanyuk_igor@mail.ru
Abstract. This paper discusses the main methods for modification of university
curricula for graduate students based on advanced research results in infor-
mation and communication technology (ICT), artificial intelligence, control,
and decision making. Special attention is paid to classifications of the ap-
proaches and their evaluation. Examples from the Washkewicz College of En-
gineering at Cleveland State University, and Black Sea State University, show
the efficacy of the authors’ proposals, approaches, and classification results.
Keywords: computer science, curricula, knowledge transfer
Key Terms: InformationCommunicationTechnology, Educational Process,
KnowledgeEngineeringMethodology, Academia
1 Introduction
Many countries are reforming their science and technology systems to implement
the recent advanced achievements of distinguished researchers from their own coun-
try and abroad in higher education [10, 13, 14]. At the same time, those of us directly
involved in the reform process realize that some countries are deficient in devising
genuine exchange programs, both within the country and abroad.
During the last few decades, university and industry researchers from different
countries have paid much attention to the modification and development of new arti-
ficial intelligence techniques and optimization methods, especially for control and
decision making systems [17, 21, 26, 27, 33, 38, 43]. Many international conferences,
congresses, symposia, and seminars are specifically devoted to the needs of inter-
university and university-industry cooperation [22, 40] in the field of soft computing,
fuzzy systems, evolutionary optimization, and artificial neural networks, which allow
for the solution of many practical tasks that include uncertainty. These research ef-
forts include the development of new theoretical methods, advanced devices and
equipment, joint research projects, joint publications, the incorporation of research
results in university curricula, and so on, and also include the determination of the
ICTERI 2016, Kyiv, Ukraine, June 21-24, 2016
Copyright © 2016 by the paper authors
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most efficient means by which these goals can be achieved. Many publications in the
educational field are devoted to the following topics.
(a) Using modern information and communication technology (ICT) in training
processes [7, 8, 23, 24, 39], and developing new teaching methods, infrastructures,
and software for ICT education and application;
(b) Creating university curricula [29, 30, 31, 32, 42] with balance between theoret-
ical and practical components, and with possibilities for modification in the near fu-
ture according to new requirements and developments;
(c) Developing new teaching methods and tools for on-line learning [13, 14];
(d) Using modeling and simulation techniques [34] for the investigation of the dif-
ferent dynamic and uncertain processes in education.
The optimization of fuzzy algorithms and systems opens up opportunities for co-
operation and collaboration between scientists from different countries. At the same
time, university curricula needs constant modification based on new research results
in the fields of ICT and computer science to improve the quality of student training.
This modification must take into account the dynamics of society’s economic devel-
opment, regional peculiarities, the increasingly intellectual level of technological and
production processes, the complexity of market relations and the labor market, and
the globalization and internationalization of societies and educational systems [1, 2, 3,
6, 25]. Such constant modification is possible by introducing new fundamental and
elective courses, or by content modification of existing courses, taking into account
that the present educational systems in many countries allows for elective courses.
The aim of this paper is to review the analysis and evaluation of modern educa-
tional approaches for creating and modifying university curriculum in the sphere of
ICT, artificial intelligence, evolutionary optimization, automatic control, decision-
making, and intelligent robotics. These educational approaches correspond to the
recent results in research and science, and are based on the authors’ experience in the
Department of Electrical Engineering and Computer Science at Cleveland State Uni-
versity (CSU) in Cleveland, Ohio, USA [44], and the Department of Intelligent In-
formation Systems at Petro Mohyla Black Sea State University (BSSU) in Mykolaiv,
Ukraine [45].
The rest of this paper is organized as follows. Section 2 deals with related works
and section 3 presents a classification approach to advanced scientific and engineering
achievements. Section 4 considers the most efficient methods for curriculum modifi-
cation. Section 5 is devoted to approaches for knowledge transfer, and Section 6 dis-
cusses evaluation. Section 7 provides some concluding remarks.
2 Related Works
Here we consider current research in curriculum development education challenges
[35, 41, 42]. Some research is devoted to the modification of well-known educational
approaches, but some is devoted to the development of new approaches based on the
results in ICT and educational methodology [7, 8, 23, 24]. The overview, analysis,
interconnection, and correlation of general education reform and the computer revolu-
tion is given in [10, 23, 35, 42]. Previous research includes investigations into the role
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of inquiry as an organizing theme for science curricula [1], the anatomy of narrative
curricula [4], the advantages of problem-based curricula [6], the correlation of course
and curriculum design with learning outcome assessment at the course and curricular
levels [5], the suitability, evolution, and impact of online learning, especially in ICT
[13], and the issues, challenges, and opportunities for internet-based curriculum and
individual courses [2].
Particular attention in the scientific literature has been devoted to the problem of
interdisciplinary research and education, the development of integrated engineering
curricula [12] with links between distinct disciplines, new approaches for teaching
ICT to the next generation of students [25], embedding employability into curricula
[16], and efficient approaches to internationalize university curricula [26]. Other re-
search includes investigations into research-based curricula in response to needs from
government agencies and members of the research community [3].
Curriculum modification according to current research is common but different (in
some aspects) among various countries, so it is important to share best practices at the
international level. The education community needs a wide spectrum of approaches
and tools to increase the quality of university graduates and to imbue them with mod-
ern knowledge at each stage of their training, based on the latest theoretical and ex-
perimental research.
3 Research that Significantly Impacts Higher Education
Here we consider several items due to their significant influence on the higher edu-
cation and training of graduate students. These items are all related to scientific and
engineering research, and can be divided in 4 categories.
1. New directions and recent achievements in science and technology:
a) New theoretical results, including methods, models, algorithms, principles,
approaches, etc. [18, 26, 27, 37, 38, 43] (e.g., biogeography-based optimization, inva-
sive weed optimization, and other evolutionary optimization methods; new reliability
assessment methods for critical computer systems; etc.).
b) New experimental results that demonstrate theory or scientific phenomena in
simple and informative ways (e.g., thermoacoustic engines, ecopyrogenesis, intelli-
gent robots, etc.).
2. Recent products of advanced industrial manufacturing:
c) New devices with improved characteristics and properties that allow investi-
gation into scientific phenomena, and that extend the number of experimental modes
for experiments related to hydrodynamics, thermodynamics, electrohydraulics, elec-
tromagnetics, nanotechnology, and others (e.g., NAO humanoid robot, IMS radiation
detection based on gamma ray spectrometry and the Nerva LG robot, etc.).
d) New electronic components, sensors, and materials that can be used to design
next-generation devices (e.g., new slip displacement sensors, FPGA-based controllers
and electronic devices, etc.).
3. New software solutions developed by leading and advanced IT companies:
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e) New computer-aided design (CAD) software, including 2D and 3D CAD
software, that enables new levels of design processes in computer science, computer
engineering, device design, machine design, ship design, and other important manu-
facturing fields (e.g., Active-HDL, Siemens PLM Software, parcel shipping software,
etc.).
f) New information and communication technologies for industrial applications
and domestic use, including IoT - the internet of things (e.g., Verizon IoT Solutions,
Cisco IoT System, etc.).
4. Recent achievements in education based on the modern information and
communication technologies:
g) New software and information technologies for teaching more efficiently,
testing student knowledge, modeling object behavior in uncertain environments, con-
trol, identification, and decision making in education (e.g., e-learning and e-testing
information technologies, etc.).
h) New educational methods using the internet to increase motivation and edu-
cational efficiency, to teach students to train themselves, and to apply current interna-
tional standards to education (e.g., miscellaneous electronics and software - MPLAB
from Microchip – for the course “Embedded Systems”, etc.).
Information about the above items can be obtained by students and teachers from
various sources, including the following.
a) Publications in the scientific literature, including articles in international and
domestic journals, chapters in monographs and edited books, and abstracts in confer-
ence proceedings (e.g., the journals Information Sciences, Kybernetes, etc.).
b) Articles in internet journals with both open access and registration access,
chapters in e-books, electronic textbooks, and e-monographs (e.g., open access jour-
nals in engineering & computer science, Applied Computing and Informatics, etc.),
the journal Sensors & Transducers, Elsevier journals, etc.).
c) Patents from various countries, such as the US, Ukraine, and international
(multi-country) patents, with detailed information about new methods of signal pro-
cessing and new technical solutions for devices in various fields of human activity
(e.g., U.S. Patent No.8467921, 2013; Ukraine Patent No. 106288, 2016; etc.).
d) Presentations at conferences, congresses, symposia, and seminars, which in
many cases include new and first-hand research results and pre-print material (e.g.,
ACC 2016, WConSC 2016, CDC 2016, etc.).
e) Industrial reports about new results and achievements that are obtained from
industry, associations, or industrial consortia (e.g., NAICS Industry Report Collec-
tion, Industrial Report on Samsung Electronics' Processor Exynos, etc.).
f) International and domestic exhibitions of new devices and equipment in var-
ious scientific arenas, including new ICT technologies (e.g., Smart City Expo,
NANOTECH: Advanced Materials & Applications, etc.).
g) International and domestic research projects that are financially supported by
agencies such as the US National Science Foundation, NASA, the Fulbright Program
(USA), the Tempus and Erasmus Programs (European Union), DAAD, DFG (Ger-
many), Ministry of Education and Science (Ukraine), etc. [44, 45].
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h) Newsletters from professional associations with recent information about
new achievements, events, and activities, such as IEEE Spectrum newsletters (Insti-
tute of Electrical and Electronics Engineers), the IFAC Newsletters (International
Federation of Automatic Control), the Sens2B (Sensor to Business) Newsletter, the E-
Letter on Systems, Control, and Signal Processing from the IEEE Control Systems
Society, the Medallion e-Newsletter from the PBD Honor Society for International
Scholars, etc.
i) Web portals of engineering companies, consortia, and professional associa-
tions, such as the smart sensors web portal of the IFSA (Internation-
al Frequency Sensor Association), web portal of Aldec, Inc. (The Design Verification
Company), and others.
4 Research-Based Modification of University Curriculum
Usually a university curriculum consists of a list of year-by-year subjects for student
learning, which includes vertical and horizontal relationships and correlation [44, 45].
For example, curricula for undergraduate study at the Department of Electrical Engi-
neering and Computer Science (EECS) in the Washkewicz College of Engineering
(WCE) at Cleveland State University are shown in Fig.1 (Bachelor of Science in
Computer Science - BSCS) and in Fig. 2 (Bachelor in Electrical Engineering - BEE)
[44]. CSU’s curricula for the BEE, BSCS, and Bachelor in Computer Engineering
(BCE) degrees are approved by the Accreditation Board for Engineering and Tech-
nology (ABET). Fig. 1 and Fig. 2 include different notations for required courses,
core courses, and electives, as well as interrelations between courses, such as Pre-
requisite, Co-/Pre-requisite, and Co-requisite.
Analysis of the possibilities for university curriculum modification according to
new research results allows us to classify and discuss (using CSU examples) the fol-
lowing educational methods and approaches, which are directed to the improvement
of the graduates’ qualifications, and which promise to imbue them with modern
knowledge in the field of science, engineering, and technology.
New specializations for existing Master of Science programs. New specializations
allow CSU to take into account the newest research in science and engineering, and to
specify required courses according to new engineering knowledge. For example, spe-
cializations in the modern science of nanotechnology has been included in the aca-
demic programs of several universities in various countries. The following areas of
specialization are offered for graduate study and research in the Master of Science in
Electrical Engineering (MSEE) program in the Department of Electrical Engineering
and Computer Science (EECS) at CSU.
a) Communication Systems
b) Computer Systems
c) Control Systems
d) Power Electronics and Power Systems
e) Nanobiotechnology
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Fig. 1. The BSCS curriculum at CSU
Fig. 2. The BEE curriculum at CSU
Developing a new Master of Science program. The first example here is the Mas-
ter of Science in Software Engineering (MSSE) program at Cleveland State Universi-
ty, which is the first of its kind in Ohio, USA. The program introduces students to
current and best practices and based on the recent achievements in the engineering of
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software systems. A distinguishing feature of the program is its emphasis on the ar-
chitecture, design, quality, management, and economic aspects of software engineer-
ing. The program exposes students to new technological developments in an advanc-
ing field, and teaches them how to apply their advanced knowledge in the workplace.
Graduates meet the modern demands of industry and the needs of information tech-
nology professionals, in general, and software engineers, in particular. The second
example deals with the computer science track in the Master of Science in Computer
Science (MSCS) program at CSU. This track emphasizes the study of computing
using the latest technologies, and the graduates of the program are prepared for im-
mediate employment in business, industry, and government, or can pursue higher
studies in the discipline. BSSU’s MSCS program is preparing the new specialization
Methods of Artificial Intelligence.
Doctor of Engineering (DRE) Programs and PhD Programs. PhD Programs in
the United States are often theoretical programs which consist mostly of theoretical
courses and research. The PhD thesis is a work with a theoretical hypothesis, pro-
posals, and mathematical theorems that are supported, proven, and confirmed by
modeling and simulation. The DRE thesis usually includes new models and algo-
rithms for solving specific engineering problems. Compared to PhD programs, DRE
programs are more practical, experimental, and industrially oriented.
New elective courses for programs at all educational levels (bachelor, masters,
and doctoral). University curricula usually include required and elective courses, with
a set of alternatives for electives. In particular, the Master of Science in Electrical
Engineering program at CSU includes various sets of elective courses, depending on
the specialization. For example, 10 elective courses are available for the Control Sys-
tems specialization, including Probability & Stochastic Processes, Embedded Sys-
tems, Art and Science of Feedback Control, Advanced Control System Design, Sys-
tem Identification, Nonlinear Systems, Optimal Control Systems, Intelligent Control
Systems, Dynamics and Control of MEMS, and Robot Dynamics and Control. Four-
teen elective courses are available for the Computer Systems specialization, including
Embedded Systems, Software Engineering, Modern Digital Design, Rapid Digital
System Prototyping, Formal Methods in Software Engineering, Software Quality
Assurance, Software Testing, Software Design & Architecture, High Performance
Computer Architecture, Distributed Computing Systems, Computer Networks II,
Parallel Processing Systems, Mobile Computing, Secure and Dependable Computing.
Modification of existing courses with new content and teaching methods based
on modern software. Here we consider the example of adjusting the content of a Con-
trol Systems course by including a new section on Fuzzy Control based on the recent
research results, and using the MATLAB Fuzzy Logic Toolbox (Fig. 3) to model
control system behavior in different modes and with various disturbances. The teach-
ing approach in the EECS department establishes a spiral framework in which key
concepts are revisited at increasing levels of sophistication and interconnection.
New case studies and examples in flexible courses. This approach applies to flex-
ible courses such as Fundamentals of Research Investigations (BSSU, Ukraine), and
Writing in Electrical Engineering (CSU, USA). Many engineering examples can be
used to teach flexible courses, so it is easy for the instructor to consider new modern
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engineering examples while taking into account new achievements in the field of
electrical and computer engineering, intelligent information systems, and robotics.
a) b)
Fig. 3. Design of Mamdani-type fuzzy PID-controller (FPID) using the MATLAB Fuzzy Logic
Toolbox: (a) the structure of the FPID controller; (b) Fuzzy rule editor
New research directions for (a) theses, (b) dissertations, and (c) course projects.
Topics of student theses, dissertations, and course projects at CSU and BSSU deal
with new research in the field of robotics, artificial intelligence, and control systems,
as well as with the current research in the corresponding departments. For example,
the EECS department (CSU) received research grants from the US National Science
Foundation, Cleveland Clinic, Innovative Developments, Ford Motor Company,
American Diabetes Association, and Electronics and Telecommunications Research
Institute. BSSU received research grants from the European Commission for
TEMPUS for the project Model-Oriented Approach and Intelligent Knowledge-Based
System for Evolvable Academia-Industry Cooperation in Electronics and Computer
Engineering (20132016). Thesis and dissertation research topics include Bio-
Inspired Optimization of Ultra-wideband Patch Antennas Using Graphics Processing
Unit Acceleration, Applications of Sliding Mode Controller and Active Disturbance
Rejection Controller to a PMSM Servo System, and Evolutionary Optimization of
Atrial Fibrillation Diagnostic Algorithms.
ICT for lectures and demonstrations. Multi-media plots and program code are ef-
ficient ways for introducing ICT and software. For example, consider the lectures
concerning optimal state estimation methods [37]. MATLAB plots and demonstra-
tions of the pseudo code are presented in Figs. 4 and 5 for the CSU course Optimal
State Estimation.
Teaching and learning in academic consortia. Integrated processes between dif-
ferent universities and colleges is a powerful means for education reforms [10, 34].
Academic consortia allow cross registration (multi-vector) continuous education. The
terms “cross registration” and “multi-vector education” mean that students are offered
the possibility for parallel study at their home University and elective courses accord-
ing at other universities [19]. The objective of multi-vector education is to create con-
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ditions for the study of both foundational courses and elective courses to meet student
inclinations, abilities, aspirations, and desires.
Any curricular innovation based on ICT should be supported by software facilities.
For example, the relationship between disciplines and software in the EECS depart-
ment at CSU can be seen in Table 1, Fig. 1, and Fig. 2.
function DiscreteKFEx1(N)
% Discrete time Kalman filter for position estimation of a Newtonian system.
% This example illustrates the effectiveness of the Kalman filter for state
% estimation. It also shows how the variance of the estimation error
% propagates between time steps and decreases as each measurement is
% processed.
% INPUT: N = number of time steps.
if ~exist('N', 'var')
N = 6;
end
T = 5; % time between measurements
sigma = 30; % position measurement standard deviation
R = sigma^2;
P0 = [100 0 0; 0 10 0; 0 0 1]; % initial state estimate uncertainty
% A = [0 1 0; 0 0 1; 0 0 0]; % continuous-time system matrix
H = [1 0 0];
F = [1 T T*T/2; 0 1 T; 0 0 1]; % state transition matrix
x = [1; 1; 1]; % initial state
xhat = x; % initial state estimate
Q = zeros(3,3);
Q(3,3) = 0.01;
posArray = zeros(1, N);
xhatArray = zeros(3, N);
yArray = zeros(1, N);
Pplus = P0;
Varminus = zeros(1, N);
Varplus = P0(1,1);
KArray = zeros(3, N);
for k = 1 : N
…
Fig. 4: Sample MATLAB code for CSU’s Optimal State Estimation course
5 Efficient Knowledge Transfer
In this section we classify the most efficient ways, according to authors’ point of
view, for knowledge transfer using various combinations: teacher–student, student–
student, student–student team, and teacher group–student group. We consider these
approaches mostly using examples from CSU.
Invitation of visiting professors. Usually, visiting professors present individual
specialties, for example Fuzzy Modeling and Control, Decision Making in Uncertain-
ty, Optimal State Estimation, Intelligent Sensors, Robotics, Biomechanics, Mechatro-
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nics, etc. This is an efficient way to give students new knowledge based on research
results within the framework of regular classes or special classes.
3500
3000
position estimation error variance
2500
2000
1500
1000
500
0
0 10 20 30 40 50 60
time step
Fig. 5. Sample MATLAB output for the CSU Optimal State Estimation course
Students’ participation in research projects and publication with professors.
When students conduct research (in the framework of research grants) with professors
they can obtain a lot of new knowledge. Many CSU students are currently involved in
research on the US NSF projects “Optimal prosthesis design with energy regenera-
tion” ($1.5 million), “The game changer: a new model for password security”
($200,000), Acquisition of a 4G/LTE wireless communications test set” ($252,000),
“A spiral computer engineering lab framework” ($245,000), and others. Students are
heavily involved in the preparation of articles and papers for the publication of re-
search results [17, 27]. This allows faculty to give students knowledge in modern data
information processing and skills in formatting and formulating a goal, introduction,
main idea, conclusion, references, citations, and so on.
Gathering students into a single research team. This approach broadens the per-
spective for knowledge transfer when students with different ICT knowledge can
gather in one team for executing one or several projects. For example, students who
are members of a research team may have various knowledge in using software for
evolutionary optimization (genetic algorithms, partial swarm optimization, multi-
objective invasive weed optimization, etc.), decision making based on Pareto optimi-
zation, sliding mode control, impedance control, fuzzy logic, artificial neural net-
works for parametric identification, pattern recognition, image processing, and so on.
CSU student teams have the possibility to conduct research in laboratories in the
EECS Department such as the Digital Systems Lab, Control Systems Lab, Power
Systems Lab, Computer Networks & Distributed Systems Lab, Communications &
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Table 1. Relationships between disciplines and software in the EECS Department at CSU
Course
Course Title Software
Code
Introduction to Engineering Arduino (an open-source electronics platform
ESC 120
Design based on easy-to-use hardware and software)
EEC 310 Electric Circuits I
PSpice, MATLAB, MultiSim
EEC 311 Electric Circuits II
EEC 312 Electric Circuits Laboratory Agilent IntuiLink software (Agilent scopes
EEC 315 Electronics Laboratory and signal generators, breadboards, passive
EEC 451 Communications Laboratory components, transformers)
EEC 314 Electronics II PSpice, MATLAB/Simulink
EEC 384 Digital Systems Laboratory EDA (electronic design automation) software
EEC 487 Advanced Digital Systems from Altera and Xilinx (FPGA prototyping
EEC 488 Hardware-Software Co-design boards, logic analyzers)
Miscellaneous electronics and Software
EEC 417 Embedded Systems
(MPLAB from Microchip)
EEC 421 Software Engineering Eclipse for Java development
EEC 440 Control Systems PSpice, MATLAB/Simulink
SystemView by Elanix (design and simulate
EEC 450 Communications
communication systems)
(Microsoft Visual C, Quartus II from Altera
EEC 483 Computer Organization
(software), DE0 from Altera (hardware)
Universal software (USRP) from Ettus (hard-
EEC 492 Software Defined Radio ware) and GNU Radio (software), and Lab-
View from National Instruments (software)
Quartus II from Altera (software), DE0 from
EEC 492 Computer Security
Altera (hardware)
EEC 525 Data Mining WEKA, RapidMiner, R (o/s software)
Formal Methods in Software
EEC 622 Model checker SPIN, Visual Studio
Engineering
EEC 623 Software Quality Assurance JUnit, GitHub, SPSS (statistical software)
EEC 624 Software Testing JUnit (open source testing tools)
Java, Mysql, Perl, Python, PHP, Apache, C#,
EEC 626 Software Engineering Project SQL server, ASP.net, development tools:
Eclipse, NetBeans, and, Visual Studio
EEC 683 Computer Networks II Network simulator NS2
EEC Kinect Application Develop-
492/592 ment
Website -
EEC Secure and Dependable Com-
http://academic.csuohio.edu/zhao_w/teaching.
688/788 puting
html
iPhone Application Develop-
EEC 693
ment
EEC 693 Network Security and Privacy Various attack and dense tools
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Electronics Lab, Software Engineering Lab, and Senior Design Lab. Available soft-
ware includes: Altera Quartus II 10.1 SP1, Altera Quartus II 13.1, Cisco Packet Trac-
er, Oracle VM VirtualBox, Microsoft SQL Server 2008, Microsoft Visual Studio
2010, Microsoft Office 2010, Orcad family Release 9.2 lite Edition, ORCAD 16.5
lite, Python 2.7.5, MATLAB R2013b, dSPACE Control Desk 5.1, ModelSim SE
10.0a, Precision Synthesis 2010 a.218, SystemView V6.0, and Agilent Data Capture
Application. BSSU students have the availability of Visual Studio, MS SQL Server,
MS Windows Server, MS Windows 7, MS Access, MS Visio, MS Project, Free Ware,
Moodle, Libre Office, Eclipse, NetBeans IDE, Ubuntu, FreeBSD, Apache, Qt,
OmegaT, VirtualBox, Python, Java, JavaFX, C/C++, PHP, JavaScript, HTML5.
Participation of students in conferences, seminars, and research meetings. The
goal of any conference is the sharing of knowledge and discussion of recent research
results. CSU hosts a weekly Human Motion and Control seminar that includes senior
researchers and students giving presentations (approximately half-and-half) on ad-
vanced research results with participation from the departments of EECS, Mechanical
Engineering, and Engineering Technology. Moreover, every student has the responsi-
bility to report their research achievements on a weekly basis at meetings or seminars
of their separate research team, with additional short presentations on new funding,
new methods, software, technology, sensors, computer components, and so on. The
Annual Research Day of the WCE (CSU) is a scientific event with poster presenta-
tions by master’s and PhD students, including time for discussion and awards for the
best posters.
Cooperation of the university with advanced ICT companies. This approach al-
lows for the possibility of knowledge transfer within the framework of lectures by
ICT company representatives at the university, familiarization by the students with
new ICT company software, student internships (NASA Glenn Research Center,
General Electric, etc.), joint programming projects, certification of students, and crea-
tion of student start-up and spin-off companies [11, 15, 22, 40].
IT for papers, articles, and course work preparation. Students have the possibility
to learn specific software editing of their manuscripts using different LaTeX or MS
Word templates which correspond to specific journal or conference formatting re-
quirements.
Textbooks and manuals for students based on the recent faculty experience.
Courses in the EECS department at CSU are based on the faculty’s own textbooks,
classical / fundamental textbooks, and internet resources. For example, recent re-
search results on optimal state estimation and evolutionary optimization are repre-
sented in faculty textbooks [37, 38] with accompanying MATLAB codes which is
available on the CSU website [44].
User-friendly pseudo code in published articles and research projects. At the
EECS department, every student has free access to pseudo code. Authors and devel-
opers transfer their programming achievements by sharing them with students and the
world-wide research community. CSU’s web site includes pseudo code which is de-
veloped by research teams or individual developers.
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Internet search systems and databases. To increase their level of knowledge based
from recent research results, students can use search systems from databases such as
Scopus, Science Direct, Google Scholar, IEEE Xplore, and others;
Research portals like Research Gate, Linkedln, and others. Students can gain
new knowledge by following recent publications from specific authors, by asking and
answering questions in dialogues with colleagues, and so on.
Memberships in professional societies. Memberships in professional and scien-
tific societies, like IEEE, IFAC, PBD, and others, gives students a wide spectrum of
opportunities for knowledge transfer using the resources of the corresponding society.
6 Evaluation of the Modified University Curricula and
Approaches to Knowledge Transfer
An evaluation of the quality of training processes and of the quality of university
graduates is a feedback from the implementation of the proposal in Section 4, Re-
search-Based Modification of University Curriculum. Here we propose some indica-
tors for evaluation processes:
a) Awards and participation of students in programming Olympiads, and student
research project competitions. For example, a team from CSU’s Washkewicz College
of Engineering took first place at an international student design competition spon-
sored by the American Institute of Aeronautics and Astronautics (AIAA). For their
winning project they designed, built, and tested an engine air particle separator for an
unmanned ariel vehicle using 3D printing technology. BSSU student have been re-
peated winners in the Aldec, Inc. (USA) Olympiad on C++, VHDL and Verilog [20].
b) The level of published articles by students is indicated by databases such as the
Web of Science, Scopus, etc. Other important considerations are the impact factor of
corresponding journals, and the rank of conferences with student presentations (inter-
national, regional, university, college, department, etc.) [14].
c) Grading of student knowledge and erudition using traditional testing approaches
(homework, midterm, term project, final exam) and using advanced software and ICT
[9, 36].
d) Tracking graduates and applicants for PhD or DRE programs illustrates research
aspirations and the desire for conducting continuing research.
e) Successful employment, for example: (1) CSU graduates work in US companies
and industrial corporations such as Rockwell Automation, Phillips, Foundation Soft-
ware, Winncom Technologies, UTC Aerospace Systems, Swagelok Company,
RoviSys, American Railways, United States Postal Service, and others; (2) BSSU
graduates work in Canada, France, Germany, Great Britain, Latvia, Netherlands,
Norway, Poland, UAE, USA, and Ukraine, including companies such as Camo-IT,
Ciklum, eBay, EPAM Systems, GeeksForLess, GlobalLogic, HostingMaks, Linkedln,
Luxof, Microsoft Research, MobiDev, NetCracker, Oracle, TemplateMonster, and
others.
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7 Conclusions
The authors have described research related to the increasing efficiency of univer-
sity graduate training by modification of the curricula in electrical engineering, and
computer science and engineering, based on the latest achievements and advanced
research results in the corresponding fields. Analyzing and classifying the knowledge
transfer and knowledge evaluation methods for examination and verification of the
proposed curriculum modification approach, the authors have presented many educa-
tional examples and successful cases from the Department of Electrical Engineering
and Computer Science at CSU (USA) and the Department of Intelligent Information
Systems at BSSU (Ukraine). Because of the limited space of this paper, only a few
specific use cases have been considered. All discussed approaches can be successfully
implemented for graduate student curricula modification in other universities around
the world, especially those which do not currently use all of the discussed methods.
Acknowledgements. The authors gratefully thank the Fulbright Program (USA) for
providing the possibility to conduct research together in the USA by supporting Prof.
Y. P. Kondratenko with a Fulbright scholarship.
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