him to perform the tasks) come into the module of
accumulation statistics and the learning process con-
trol. If student has any questions, he can use the
feedback form to contact the teacher. At the end of
the section studying, student passes the test. Results
(total score, test time, number of attempts) also
come into the module for further analysis.
Management of the training quality is based on
three-loop diagram (management of the quality of
student’s learning, management of the quality of the
group’s learning and management of the learning
quality of the specific field of training). To assess
effectiveness the system of indicators was devel-
oped. Correction of the process in order to increase
its effectiveness can be performed at each stage of
learning within each control loop. Such factors as a
quality of questions asked, the time for teaching,
quality of responses, speed and regularity of work
can be the criteria for evaluation of effectiveness of
student’s performance. Based on the personal char-
acteristics of the student an individual approach
should be implemented in the proposed system: the
teacher can choose such teaching methods, that will
be effective for this concrete student. Patrick Buck-
ley and Elaine Doyle (2017: 43-55) state in their
paper that it is generally accepted that matching an
individual’s learning style with the appropriate form
of an instructional intervention significantly impacts
upon the performance of the student and his/her
achievements of learning outcomes.
Analyses of statistical data will allow teacher to
determine the reasons for low efficiency. This may
be caused by individual characteristics of a particu-
lar student, by the complexity of the topic in general
or by insufficient quality of the educational content.
In the second case, the teacher may post additional
lookup materials, and in the third case, this will
serve as a signal to the teacher to change educational
content. The results of such studies in a field of user
personalization behavior presented in the paper
(Bent et al., 2017: 456–464), where authors present
the modeling of user behavior in the context of per-
sonalized education. The user behavior data is mod-
eled and sent to the cloud-enabled backend where
detailed analytics are performed to understand dif-
ferent aspects of a student, such as engagement, dif-
ficulties, and preferences.
4.2 Modules Organizing Students’
Training Process
Modules, that allow students to select courses and to
access training content and self-control means are
developed to organize the self-study process. In or-
der to start working in system, student must register
and select courses, which he will study. The main
feature of engineering education is that along with
learning theoretical material, there is a necessity to
acquire practical skills for the future professional
activities. Therefore, the learning content, in addi-
tion to already becoming traditional text, video and
multimedia, contains resources, using modern edu-
cational technologies, that contributes to intensifica-
tion of perception and development of a creative
approach to the practical problems solution (such as
models of real situations and systems, virtual and
augmented reality).
Modelling and simulation allow the student to
see studied process with their own eyes, that has a
positive impact on the learning process. The authors
of research (Wu et al., 2013: 41–49) outline the edu-
cational possibilities of recently developed “aug-
mented reality” (AR), alongside with the problems it
has brought in its wake. Thus, in research (Kesim
and Ozarslan, 2012: 297 – 302) it is suggested that
educationists should collaborate with researchers to
develop extended interfaces of reality. Although the
key role of producing augmented realities is played
by soft- and hardware technologies and there are
engineers for designing them, the educational tech-
nologies are seriously in need of specialists to design
learning activities for augmented reality.
It is shown (Martín-Gutiérrez et. al, 2012: 832 –
839; 2015: 752–761) that one of the AR advantages
consists in saving of instructors’ time on repeat ex-
planations because students can use them for inde-
pendent revision. Furthermore, the effect of these
technologies is twofold: facilitating the teachers’
control of laboratory courses and promoting the stu-
dents’ motivation. Research (Webel et. al, 2013)
describes an experiment of applying AR for training
of technicians in industrial maintenance and assem-
bling operations. The authors emphasize the im-
portance of drilling technicians in new skills due to
increasing complexity of maintenance operations
and demonstrate the superior performance of AR
tools compared to traditional teaching techniques.
Another tool to enhance learning of students is
an ability to conduct tests and experiments in a vir-
tual laboratory. Then he will be more prepared for
this experience in real conditions. The application of
virtual reality technology enhances an intensification
of training. One more tool is a business game in
which students are given an opportunity to demon-
strate personal and professional qualities. In the im-
plementation process of business games, students
will be able to define their role in the team and will
have an opportunity to form teams among the stu-