=Paper=
{{Paper
|id=Vol-2917/paper6
|storemode=property
|title=Activating the Process of Educational Services Using Independent Computing Resources to Manage and Monitor the Quality of Learning
|pdfUrl=https://ceur-ws.org/Vol-2917/paper6.pdf
|volume=Vol-2917
|authors=Nadiia Pasieka,Nelly Lysenko,Oleksandra Lysenko,Vasyl Sheketa,Mykola Pasieka,Mariana Varvaruk
|dblpUrl=https://dblp.org/rec/conf/momlet/PasiekaLLSPV21
}}
==Activating the Process of Educational Services Using Independent Computing Resources to Manage and Monitor the Quality of Learning==
https://ceur-ws.org/Vol-2917/paper6.pdf
Activating the Process of Educational Services Using
Independent Computing Resources to Manage and Monitor the
Quality of Learning
Nadiia Pasieka1, Nelly Lysenko1, Oleksandra Lysenko1, Vasyl Sheketa2, Mykola Pasieka2
and Mariana Varvaruk1
1
Vasyl Stefanyk Precarpathian National University, Ivano-Frankivsk, 76000, Ukraine,
2
National Tech. University of Oil & Gas, Ivano-Frankivsk, 76068, Ukraine
Abstract
The educational and methodological systems and methods aimed at enhancing the educational
process are analyzed. These methods and techniques are designed to effectively solve
problems, the quality and training of specialists on the basis of integrated methods, as well as
improving the content, forms and methods of organizational educational process,
implementing current trends. Based on these results, scientific research and practical research
on the effectiveness of software application on independent computing structures showed many
positive aspects, that is, this method has broad prospects for the construction of distributed
information systems. The use of an independent computing structure allows the application
software to be used around the clock without worrying about its working condition, since this
task was outsourced to a third party when used. However, this way of organizing the
management and monitoring of the educational process has its drawbacks, that is, the necessary
level of protection of personal data on such independent platforms is not studied. Since the
information database is located on an independent computing platform, the owner of the
educational platform cannot guarantee the security of the process of external intervention. In
addition, the use of information technology has been calculated and analyzed to prove and
improve the model of enhancing the learning process, thereby improving the learning process
and enhancing the quality of education.
Keywords 1
higher school, learning, quality of education, information technologies, management of higher
education institution.
1. Introduction
With the rapid development of information and communication technologies, the expansion of free
cloud services is becoming relevant to the application and introduction of the latest information services
in industrial use on the basis of common use of competitive technologies. Taking this into account,
there is an urgent need to outsource information and communication technologies – cloud services (IT-
services) in the development. [2, 8, 17] The concept of "IT-outsourcing" provides the transfer of any IT
process (program, function, work) or a certain part of a third party organization, which provides
professional IT-services on an independent computer platform, it supports the functioning of
information and reference, expert systems, information security databases and databases of enterprises,
storage and processing of significant amounts of data, provision of hardware resources. Outsourcing
MoMLeT+DS 2021: 3rd International Workshop on Modern Machine Learning Technologies and Data Science, June 5, 2021, Lviv-Shatsk,
Ukraine
EMAIL: pasyekanm@gmail.com (N. Pasieka); nelli.lysenko@gmail.com (N. Lysenko); lysenkowa@gmail.com (O. Lysenko);
vasylsheketa@gmail.com (V. Sheketa); pms.mykola@gmail.com (M. Pasieka); varvaruk.mariana@gmail.com (M. Varvaruk)
ORCID: 000-0002-4824-2370 (N. Pasieka); 0000−0002−1029−7843 (N. Lysenko); 0000−0002−1029−7843 (O. Lysenko);
0000−0002−1318−4895 (V. Sheketa); 0000−0002−3058−6650 (M. Pasieka); 0000-0002-9606-9146 (M. Varvaruk)
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
solves the issue of reducing the financial and time costs of implementation, support and modernization
of IT-infrastructure. It ensures the convergence of information and communication media, namely, the
convergence of various electronic technologies to increase business requirements for stability and
availability of IT- services. [11]
To develop a software system using cloud technologies, the development team must develop a
structural scheme that defines the main functional properties of the software system, their interrelation
and purpose. The functionality of a software system is understood as the components of the system
elements, devices, functional groups, functional links. Building a structural scheme, which is designed
to reflect the overall structure of the project (task in hand), is the development of its main blocks, nodes,
parts and formation of the main links between them. From the structural scheme of software
development of the system with the use of cloud technologies it should be clear how the system works
in the main modes of operation and how its parts interact. The designations of the structural scheme
elements can be chosen arbitrarily, though the generally accepted rules of scheme execution should be
observed as much as possible. [13, 26]
Cloud computing is a free way to access external information and communication resources in the
form of various Internet services. The term “cloud computing” was proposed by Ramnath K. Chellappa,
who noted it as a computational paradigm in which the boundaries of computational elements will
depend on the economic feasibility, not only on technical limitations [25]. The appearance of the first
technology, which provided access to applications through the site, namely the software systems as a
service (Software as a Service [SaaS]).
The urgency of development of distributed software systems on the basis of cloud technology lies
in the fact that the need for modern high-performance systems is constantly growing and the methods
of their correct development and algorithms of supporting computational work on independent
computing platforms at the peak moments of the load are very few. [5, 6, 16] The study focuses on the
most controversial modern challenges in the development of software systems based on cloud
technology, faced by architects of such systems, namely, the algorithms of moving the load between
the computing nodes and the architectures of software organization within the framework of business
logic of enterprises. The use of the proposed technique on independent computing platforms for the
development of fault-tolerant software systems based on cloud technology allows us to expand the
worldview approaches to the construction of productive mechanisms of distribution of computational
load between the nodes of the corresponding system. [1, 4, 9, 10, 12] Taking into account the
insufficient research of this subject area we understand that the successful algorithm of the mechanism
of transferring the computational load which promotes the effective modification of this resource within
the framework of the task in hand is the main criterion in the choice of program technologies by the
architect of program systems (Figure 1).
Figure 1: The model of fault-tolerant distributed software system based on cloud technologies
Methods: System analysis, logical mathematical approach to assessing the level of difficulty of test
questions for an objective analysis of their complexity, analysis of publications on the topic,
comparison, generalization of cognitive and negative features of similar approaches and critical testing
of the proposed development, cluster analysis of test questions, reasoning based on precedents.
2. Practical deploying educational services on a cloud platform to
management and monitoring the quality of learning
With the rapid development of information technologies, other models of provision and use of cloud
services on independent computing platforms were further developed (Figure 2) [31].
Figure 2: The model of cloud services on independent computing platforms
The evolutionary development of existing service models in particular:
• Hardware as a Service (HaaS) - hardware;
• Security as a Service (SECaaS) - providing security;
• Backend as a Service (BaaS) – “backend”;
• Recovery as a Service (RaaS) - recovery of programs and data;
• Data as a Service (DaaS) - data acquisition and processing;
• Logging as a Service (LaaS) - authorization and identification;
• Network as a Service (NaaS) - network technologies;
• Platform as a Service (PaaS) - computing platform;
• Desktop as a Service (DaaS) - desktop;
• Storage as a Service (STaaS) - storages and databases;
• API as a Service (APIaaS) - API (application programming interface).
Some of the listed services provided by independent computing platforms are aimed at using a
limited number of specialists as developers and administrators, while others are successfully used by
consumers in a wide range of their activities. [23]
Development of software systems using cloud technologies refers not only to software modules, but
also to ensuring their effective delivery of the developed software module as a component of the
software system to interested users, and at the same time contains the stages of deployment and
maintenance of software modules. However, the service-oriented architecture does not consider how
the developed application should be delivered to the interested users or how independent providers of
computing services will efficiently manage the software modules during their execution. Cloud
computing on independent platforms can help SOSE deliver software modules efficiently by ensuring
that they can be easily deployed and maintained by cloud service providers through virtualization, using
a standardized interface for easy access by interested users and using software modules as part of a
developed cloud-based software system.
Challenges for software development
Today's paradigms in software development using independent computing platforms require
innovative approaches to providing efficient virtualization and interaction between the layers of SaaS,
PaaS and IaaS. The essence of this approach calls for a rethinking of urgent issues in software
engineering, but some of them are not new, and at the same time they require more serious attention in
the context of providing computing services on cloud platforms. We noted seven critical areas in the
development that create serious obstacles to the development of software modules using SOSE.
Confidentiality and data integrity
By using independent cloud computing platforms, interested users have limited control over the
processing and storage of data streams, i.e. on remote computing nodes owned and operated by various
cloud service providers. Since these data streams are not encrypted, there is a significant risk that cloud
service providers or malware may disclose or alter their content. While there are many methods to protect
your privacy, all of them cannot fully guarantee it, but when applying a certain model of protection to
cloud services and systems, you must remember that they are only designed to protect your data flows
from malicious attacks outside the system [14]. Cloud services and software on independent platforms
have different providers of these services within the virtual system.
Reliability and availability of cloud platforms as services
Stakeholders rely heavily on independent cloud service providers for business logic solutions. There
are growing concerns in the information space about how these information threats can affect the
reliability and availability of cloud platforms as a service - from the uncertain economic climate of
society as a whole, and of the service provider in particular, to natural and man-made disasters and
cyberattacks - can have a significant impact on the service, and therefore on the business, of the cloud
user. To minimize these information threats, independent cloud service users must test their data backup
plan, system reliability, disaster recovery and disaster recovery plans. To minimize these information
threats, independent cloud service users must verify their data backup plan, overall system reliability,
emergency exit and software system recovery plans, end-of-service support, and event history
documentation before deciding to use certain services. [20, 21, 28] Today, a variety of cyberattacks are
an extremely critical threat. Independent cloud computing services and systems provide fast and flexible
computing resources to meet the business needs of interested users. For the business community, the
computing capabilities and resources of independent cloud service providers often seem unlimited, as
they are available at any time and in any volume. However, information-cyberattack software can also
buy significant amounts of cloud computing resources that enable them to launch more powerful
cyberattacks. Attackers have already used the Amazon EC2 and Google App Engine cloud computing
platforms. To solve this problem, both for the services themselves and for independent cloud service
providers, innovative and effective software tools are needed to monitor and detect harmful actions
against users, as well as to strictly authenticate users and control their access.
Security in a multitasking cloud
In the developed software systems with the use of cloud technologies on independent computing
platforms in a multifunctional device one copy of the software module runs on the server, which can
have several users or tenants at the same time. In the multilayer architecture the software system is
developed practically separates its information data and configuration, where each interested user works
with an individual sample of the virtual software module.
Services and systems of cloud computing on independent computing platforms have a multi order,
because many interested users repeatedly use the software module and a set of hardware for processing
information flows. The main problem with cloud data flow protection platforms and developed software
systems is the vulnerability to cyberattacks. To provide the necessary level of protection, service
providers use a hypervisor that controls access between virtual machines and hardware and software.
However, some hardware and software tools, such as processor caches and graphics processors, are not
designed to provide strong insulation properties for multilayer architecture. Even virtual machine
hypervisors, which are provided by an independent cloud service provider, may have some flaws that
allow the virtual machine of one interested user to gain unauthorized control over other tasks and data
flows. More recently, cybercriminals have exploited multiple hypervisor vulnerabilities to affect other
users' computing operations or to gain unauthorized access to data sets. Therefore, addressing these
vulnerabilities requires innovative methods of developing software systems to provide multilayer
architectures for cloud-based services, such as virtual machine isolation and monitoring.
Cloud risk profile
Cloud-based software systems developed on independent computing platforms have limited access
to services and cloud computing, as well as information on internal system architecture, software module
versions, configuration, operations and related security practices of these service providers. This limited
access for interested users can increase usability, but it also has serious limitations for operational risk
management. Risk management in software engineering ensures that module developers initially identify
and analyse threats to the software module business process and use appropriate strategies to minimize
and control risks. Namely, how the failure to complete projects within the specified time schedules and
budget constraints, as well as not fully meet the requirements of interested users. Since software
developers using cloud technology lack information about the internal organization of the system under
the layer of virtual abstraction, they may not be able to conduct appropriate research on risk management.
To solve this problem, software developers should turn to independent cloud service providers and
consider three steps:
partial or full disclosure of software design and infrastructure information;
Disclosure of relevant logs and data such as network intrusion logs, anomaly logs and security
logs;
Disclosure of security policy details and enforcement mechanisms.
Taking a professional look at these steps will not completely eliminate the risk, but the information
obtained will provide much more effective business risk management.
Monitoring the quality of cloud service delivery
Independent providers of cloud platforms as services and management of various QoS software
requirements are extremely difficult to manage, as numerous software module developers dynamically
create services in networks to form several computing workflows, and different cloud technology
providers with different methods and policies manage services in different ways. As a result, the QoS
functions of all cloud services are closely linked and there are trade-offs between them.
Thus, the functions responsible for the bandwidth and latency of a particular service rely on the
distribution of information resources of the developed software system during the execution of the
module. Often, a single server hosts multiple services that compete for CPU time, memory and server
bandwidth. In addition, service compositions, the status of server resources, workflow priorities and QoS
requirements usually change dynamically during cloud computing. So, meeting QoS requirements for
multiple computing processes requires effective methods of adaptive allocation of system resources for
each cloud service. Managing multiple QoS properties for such developed software, services and cloud
computing systems requires situational awareness, context analysis and QoS assessment, as well as
optimal hardware and software resource allocation. [18, 22]
Internet Things as Cloud Services Delivery Systems
When developing software systems using cloud technology, the main criterion is the network,
because users or software systems are located on different hardware devices, namely: desktops, laptops,
smartphones, tablets and personal computers, that is, they can access network services at any time and
in any place with the help of standard protocols of information exchange. Since identity theft and service
theft are major threats, mobile services and computing providers in independent cloud platforms require
rigorous software development techniques to provide unrestricted access to computing data services. [3]
Cloud platform legislation
Users who use cloud computing services and systems on independent platforms do not know the
exact physical and geographical location of their data because they have often processed and stored data
in undefined locations, both domestic and foreign. However, legally, each territory has a different
legislative jurisdiction, and independent cloud service providers in foreign countries cannot always
guarantee compliance with regulatory and legal requirements. This can be, for example, protection of
privacy, backup of information data or the provision of audits and the like. Thus, independent cloud
service providers may not be prepared to take responsibility for security incidents, failure to comply with
data backup requirements, and the provision of audits. They may also not be able to protect intellectual
property according to compliance standards.
While computing services and cloud computing have great potential, there are some criticisms of
meeting the increasing demands for dynamic development and use of software modules, and the full
realization of this potential requires a change in the structure of software development.
3. Practical deploying educational services on a cloud platform to management
and monitoring the quality of learning
3.1. Information support of the learning process and its management
The problem of effective or assured functioning of integrated systems of organizational and production
direction is related to both technological components and the ability of personnel to make decisions. That
is, the level of professional training of operators of different authority ranks is one of the decisive criteria
for the functioning of the integrated hierarchical information management system of a higher educational
institution.
The professional level of pedagogical and production personnel is based on the knowledge base obtained
in school, so it is developed on the basis of subject-oriented theoretical knowledge obtained in higher
education and in the process of special training or mobile trainings. As practice of work of the personnel in
various conditions (extreme, marginal) shows, not all cope with technological tasks for a number of reasons
(physiological, mental, cognitive), that is such workers in extreme conditions cannot effectively use the
acquired knowledge given some features of thinking or behavior [33, 36, 38].
The analysis showed that for an effective management strategy it is necessary to consider, in addition to
technological requirements, the ability of administrative personnel to make decisions in different situations
[32, 37]. This ability is closely related to intelligence, psychology, professional training, the level of mental
and intellectual stability and way of thinking in making decisions with appropriate information support.
Types of thinking in terms of levels of cognition (sensory and rational) can be reflected in the following
order:
philosophical theoretical thinking at the verbal-logical level;
generation of ideas and hypotheses regarding problem-solving schemes;
visual (figurative) thinking - action thinking, in which the solution of problems is carried out by real
transformation of the situation in the target with the observation of the motor act;
visual-imaginative thinking - is associated with the representation of situations and their changes as
a result of activity, taking into account the acting factors and completing the various characteristics
of objects;
analytical (logical) thinking, its dynamics and structuring are determined by the hierarchy of levels
of goal orientation, a real assessment of the situation, effective purposeful search for a scheme of
problem solving;
heuristic as an egocentric disoriented inner thinking of a person.
Thus, information support for the learning and management process of the university is a process of
determining the strategic content, search, collection, processing and presentation of necessary information
in an informative form. The use of information technology ensures the intensification of the learning
process and provides an opportunity to improve the effectiveness of the educational level of the specialist
[29].
3.2. Software service of the learning management process
To prove the effectiveness of using computer services on independent computing platforms to monitor
and manage the learning process we deploy a specialized software application whose work is shown in
(Figure 3-6). This specialized computer application can be used both for students (trainees) and teachers
[19, 30]. It allows you to interactively select from an information database only the information you need
at the moment.
Figure 3: An example of a robot program: “Information about students”
Figure 4: An example of a robot program: “Information about students”
Figure 5: An example of a robot program: “By date interval”
Figure 6: An example of a robot program: “In the context of the subjects studied”
Besides, at the further expansion of functionality of the given software application with use of
storehouses of the data where the information on all listeners and teachers for the certain interval of time
will be stored, there will be a possibility of analytical processing of these data for support of acceptance of
administrative decisions for the purpose of improvement of ways of delivering the educational content and
thereby to provide possibility to influence improvement of quality of rendering of educational services.
4. Logical and mathematical model for assessing the level of difficulty of test
tasks to enhance the learning process
Let the test consist of m different tasks, and n students perform the test. Denote by xi,j, j the numerical
score of the success of the j-th task and the i-th student. If the j-th student performed j-th task, then xi,j = 1
to 100 points for the task. Test results in the form of a matrix of results x, which has size [n] [m], are shown
in Table 1: where - i = 1, n - number of students who participated in the test; j = 1, m - number of questions
posed to students.
Table 1
The result of the test of students in relation to question numbers
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
St. 1 84 50 92 87 91 77 94 90 98 100 96 97 86 94 85 42 79 100 88 91 86
St. 2 80 48 80 77 88 74 78 92 69 98 77 80 84 88 83 64 69 98 84 88 80
St. 3 90 93 87 92 93 75 94 100 78 89 84 82 92 95 97 52 93 100 94 96 91
St. 4 77 65 58 75 72 84 81 66 71 67 83 98 74 85 88 79 83 100 77 86 78
St. 5 66 60 63 54 72 65 80 65 63 61 74 80 70 84 78 69 67 100 74 68 71
St. 6 55 51 64 67 72 68 83 55 39 64 67 64 69 85 77 57 65 90 65 57 69
St. 7 80 52 88 87 92 79 94 92 90 94 90 92 84 90 84 68 79 92 85 89 82
St. 8 77 76 84 75 82 74 83 90 74 90 80 77 86 84 85 76 82 89 83 86 82
St. 9 88 90 85 88 90 78 92 96 76 86 88 83 87 90 90 77 92 96 92 92 88
St. 10 82 74 66 82 76 88 84 69 78 87 83 80 86 88 84 85 81 74 68 82 78
St. 11 77 69 74 65 72 78 86 63 69 79 76 74 78 82 69 78 84 97 87 83 77
St. 12 69 71 72 74 74 70 81 65 77 84 82 68 72 64 61 76 70 95 71 67 76
Graphical representation of the results of the test in relation to the quality of the questions is shown in
(Figure 7).
Figure 7: Visualization of the quality of the questions posed to determine the level of knowledge
of students
∑𝑚 𝑋𝑖𝑗
By calculating 𝑝𝑖 = 𝑗=1 𝑚
(the proportion of correct answers of the i-th student for all test items and
𝑞𝑖 = 1 − 𝑝𝑖 – the proportion of incorrect answers), you can determine the initial logit of each student's
knowledge level (that is, the initial score of the knowledge level i-th student in the logit scale):
𝛳𝑖0 = ln (𝑝𝑖 /𝑞𝑖 ), 𝑖 = 𝑙, 𝑛. (1)
∑𝑚
𝑗=1 𝑋𝑖𝑗
By calculating 𝑝𝑗 = (the proportion of correct answers of all students in the group to the j-th
𝑚
task and 𝑞𝑗 = 1 − 𝑝𝑗 – the proportion of incorrect answers), we can determine the initial logit of task
difficulty (that is, the initial estimate of the level of difficulty of the j-th task on the logit scale):
𝛿𝑗0 = lm (𝑝𝑗 /𝑞𝑗 ), 𝑗 = 𝑙, 𝑚. (2)
This stage of parameter estimation is the initial one. After its completion each of the parameters will be
expressed in an interval scale, but with different values of the mean and different standard deviations. At
the next stage we translate the value of 𝛳𝑖0 and 𝛿𝑗0 into one interval scale, having previously calculated the
average value of the initial logits of students' knowledge level:
𝛳 = 𝛳𝑖0 + ⋯ + 𝛳𝑛0 , (3)
And the standard deviation V of the distribution of the initial values of the parameter:
2
∑𝑛 (𝛳0 − 𝛳)
𝑉 = √ 𝑖=1 𝑖 , (4)
𝑛−1
We get the formula for calculating the logit complexity of the j-th problem:
𝛿𝑗 = 𝛳 + 𝑌 ∗ 𝛿𝑗0 , 𝑗 = 1, 𝑚; (5)
Where
1/2
𝑉2
𝑌 = (1 + ) . (6)
2,89
Similarly, calculating:
2 1/2
𝛿10 + ⋯ + 𝛿𝑚
0 ∑𝑚 0
𝑗=1(𝛿𝑗 − 𝛿) 𝑊2
𝛿= ,…𝑊 = , 𝑋 = (1 + ) . (7)
𝑚 𝑚−1 2,89
We get a formula to calculate the logit level of knowledge i-th student:
𝛳𝑖 = 𝛿 + 𝑋 ∗ 𝛳𝑖0 , 𝑖 = 1, 𝑛. (8)
This estimation of the parameter 𝛿𝑗 makes it possible to assess the level of difficulty of all tasks,
regardless of the level of students' proficiency.
Given the values obtained, we can determine the level of students' knowledge by the difficulty level of
the test tasks. If 𝛳𝑖 − 𝛿𝑗 – is a negative value and large in modulo, then the task difficulty is too hard for a
student with the level of knowledge 𝛿𝑗 and it will not be useful for assessing the level of knowledge 𝛳𝑖 of
the i-th student. If this difference is positive and large modulo, then the problem is too easy, the student
learned the question a long time ago. If 𝛳𝑖 − 𝛿𝑗 so, then the probability that the student will complete the
task correctly is 0.5.
After estimating the values of 𝛳𝑖 − 𝛿𝑗 in the logit scale, calculate the probability 𝑃(𝛳) of different
students completing the jth test item correctly:
𝑒 1,7∗(𝛳−𝛿𝑗)
𝑃𝑗 (𝛳) = (9)
1 + 𝑒 1,7∗(𝛳−𝛿𝑗)
Where
𝛳 = (𝛳1 , 𝛳2 , … , 𝛳𝑛 ). (10)
The probability of 𝑃𝑗 correctly completing j-th the test assignment is a rising function of the variable 𝛳𝑖 .
Obviously, the higher a student's level of knowledge, the greater the probability that he or she will correctly
complete j-th the test task.
By introducing the conditional probability 𝑃𝑗 of different students correctly completing j-th the task, we
can proceed to construct a curve: j-th test task (Figure 8).
Figure 8: Characteristic curve of the j-th task
The characteristic curve j-th of the test task shows the relationship between the values of the independent
variable and the values 𝑃𝑗 . The inflection point of the curve: corresponds to the value 𝛳 = 𝛿𝑗 , and at
this 𝛳 = 𝛿𝑗 point equals 0.5. Thus, a student with a level of knowledge corresponding to the difficulty of
j-th test item will answer it correctly with probability 0.5.
For students with a level of knowledge much higher than 𝛿𝑗 , the probability of a correct answer to this
task approaches unity. If, however, the value of is placed far enough away from the value 𝛳 = 𝛿𝑗 and to
the left of the inflection point, then the probability of correctly completing the j-th task will approach zero.
The characteristic curves corresponding to tasks of different difficulty levels do not overlap. An increase
in the difficulty of the j-th test item by the constant C (C> 0) will cause the characteristic curve to shift to
the right. With the previous probability, the student with proficiency level 𝛳 + 𝐶 will answer this problem.
Since 𝛳 − 𝛿 = (𝛳 + 𝐶) − (𝛿 + 𝐶), the value of the function 𝑃𝑗 (𝛳) does not change. So, if a difficult
problem is taken, the student whose level of proficiency changes by the same constant as the level of
difficulty of the problem will answer it with the same probability.
The fundamental difference of testing system based on adaptive tests is that the assessment of students'
knowledge level does not depend on the difficulty of the test, that is, it is objective. Assessment of students'
knowledge level can be effectively used to solve problems of optimization of the educational process -
evaluation of the effectiveness of innovative technology, monitoring, intelligence of students and teachers.
Conclusion
The analysis of educational and methodological systems and methods to improve the educational
process aimed at effective solution of the problems of competence, quality of training specialists was
carried out. Based on the results obtained, a scientific and practical study of the effectiveness of software
application on independent computing structures was conducted, which showed a number of positive
points, namely: this approach to the construction of distributed information systems has significant
prospects for the future. The use of independent computing structures makes it possible to use application
software around the clock without worrying about its working condition, because this task is transferred to
third parties during such use. However, this approach to organizing the management and monitoring of the
educational process has its disadvantages, namely: the required level of personal data protection on such
independent platforms has not yet been investigated. Since the information database is located on an
independent computing platform, the owner of the educational platform cannot guarantee security with
respect to external intervention processes. In addition, a computational analysis in terms of the use of
information technology was conducted, which resulted in the justification and improvement of the test
analysis model, which improved the learning process and the quality of education. The application of the
method of analysis to improve the educational process on the basis of information technology was
substantiated. The use of information and communication technologies provides intensification of specialist
training, as a result of which the objectives are achieved, that is, the maximum amount of professional
training for the minimum possible time of processing educational material.
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