The “Operating Systems” Course as a Base of Students’ Learning

Activity Parameters Investigation

Oleksandr H. Kolgatin

1 a

, Dmytro Yu. Holubnychyi

1 b

and Larysa S. Kolgatina

2 c

Simon Kuznets Kharkiv National University of Economics, 9a Science Ave., Kharkiv, 61166, Ukraine

H. S. Skovoroda Kharkiv National Pedagogical University, 29 Alchevskykh Str., Kharkiv, 61002, Ukraine

Keywords:

Operating Systems, Students, Learning Activity, Pedagogical Diagnostics, Time Planning, Indicators.

Abstract:

The paper is devoted to the study of students’ learning activity indicators that concern to the time of learning

product submission. There were analysed relations of these indicators with parameters of student model in

context of pedagogical diagnostics and prognosis. The research was based on the course “Operating Systems”

that were studied in traditional blended learning educational process and in distance mode during COVID-

19 pandemic. Empirical work gave possibility to analyse correlation between timeliness of completing the

learning tasks by students and their educational achievements as well as to analyse the structure of students’

time planning at homework. There was shown that students, who completed their educational tasks in time,

have good educational achievement according to test results. But we can not say that all students with high

educational achievements submitted results of their independent work in time. There was analysed the distri-

bution of students activity during a day. There was shown that working time of students at distance learning

is more natural and correspond to business time of day. Some approaches to improve students’ competences

in learning activity self-management were discussed. Recommendations to improve the educational process

have been suggested.

1 INTRODUCTION

1.1 Statement of the Problem

Nowadays, effective educational process is not possi-

ble without active use of information and communica-

tion technologies. New educational environment puts

forward advanced requirements to management of

students’ learning activity that become more indepen-

dent. Such management should be grounded on com-

prehensive models. Theoretical basis of modelling of

the open education organizational systems, theory of

designing such systems have been expounded from

systemic positions in monograph of Bykov (Bykov,

2008). Kiv et al. (Kiv et al., 2019) underline that

Information technologies, especially, cloud technolo-

gies transform education, and have analysed accord-

ing to results of the “Cloud Technology in Education”

scientiﬁc conference modern approaches to manag-

ing students’ learning activity in university educa-

https://orcid.org/0000-0001-8423-2359

https://orcid.org/0000-0003-1719-7586

https://orcid.org/0000-0003-2650-8921

tional environment. Triakina et al. (Triakina et al.,

2018) have described the existing E-learning instru-

ments that was designed by the international orga-

nizations for self-education and have suggested the

ways of this tools implementation into professional

training. Vlasenko et al. (Vlasenko et al., 2019) on

the base of survey, conducted for teachers, suggested

to develop an educational platform – an online envi-

ronment for collaboration of the experienced profes-

sionals, whose joint activities should help in greatly

enhancing their professional skills.

Independent work of students become one of the

most signiﬁcant part of modern educational systems.

It is the demand of the curriculums and necessity to

provide of the dual learning. Therefore, elements of

distance learning are widely used in educational pro-

cess as a form of education and as a form of manage-

ment of students’ independent work. Students’ work

is realised in specialised learning management envi-

ronments without teacher’s personal presence, and the

teacher has no possibility to use traditional forms of

pedagogical observation. The teacher needs in spe-

cial system for management of students’ independent

learning activity instead of traditional intuitive man-

144

Kolgatin, O., Holubnychyi, D. and Kolgatina, L.

The â

AIJOperating Systemsâ

I Course as a Base of Studentsâ

Z Learning Activity Parameters Investigation.

DOI: 10.5220/0012062300003431

In Proceedings of the 2nd Myroslav I. Zhaldak Symposium on Advances in Educational Technology (AET 2021), pages 144-157

ISBN: 978-989-758-662-0

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

agement of learning process.

Learning management systems, for example Moo-

dle, give us various new highly informative tools for

pedagogical diagnostics. Management of students’

learning activity in information and communication

environment should be based on individual pedagogi-

cal prognosis for each student with use of an idealised

student’s achievements model, a model of student’s

real state and a model of available variants of learn-

ing methods (Kolgatin, 2012). The relationship be-

tween parameters of this models and indicators that

can be directly measured in a learning management

system should be studied experimentally and theoret-

ically. The ﬁeld of interest in this paper is system-

aticity of student learning activity as a characteristic

of student’s leaning style and a parameter of student

model in learning management system. Indicators

of systematicity and its inﬂuence on student learning

achievements are in the centre of our attention.

1.2 Analysis of Previous Researches

There are many scientiﬁc work devoted to students’

independent work, its systematicity. But we want

to pay attention to experimental data according to

this problem. In focus of our interest are time plan-

ning and inﬂuence of systematicity of students’ learn-

ing activity on educational achievements. So, Va-

lynuk and Konovalenko (Valynuk and Konovalenko,

2017) pointed on the basis of survey that only 14 %

of students prepare to classes systematically, 8 % –

occasionally, but 78 % of students work at home

only before practical and seminar classes. Klimenko

(Klimenko, 2016) believes that systematic learning

work of students promotes accumulation of knowl-

edge, mastering in skills. But large amount of short

structured tasks leads to obliviousness of educational

material, so special work for systematisation should

be suggested to students periodically. Lavrentieva

et al. (Lavrentieva et al., 2019) draw attention to the

necessity of planning independent work with account-

ing the complexity of its various types and analysing

new methods of organization of students’ independent

study activities together with the use of ICT and tools.

Particularities of students’ independent work dis-

tribution in time were experimentally studied by Kol-

gatin et al. (Kolgatin et al., 2020) with use of learn-

ing management system Moodle for measuring and

collecting data. These results were obtained in tra-

ditional in situ educational process with ICT support

of out of classes independent work. The authors con-

cluded that students, who suggested their reports on

laboratory works in time were more successful in the

assessment at low and sufﬁcient levels.

Very useful investigation of time-related be-

haviours was carried by Boroujeni et al. (Boroujeni

et al., 2016). They have analysed three key dimen-

sions of regularity: intra-course, intra-week and intra-

day. These authors considered two strategies for par-

ticipating in MOOCs: regular scheduling of learn-

ing activities and adaptive scheduling based on daily

work or study schedule.

We can see that researchers consider two aspects

of systematicity: according to the educational mate-

rial structure and according to learning process reg-

ularity. The ﬁrst one correspond to systematicity as

knowledge quality, the second – to stability of the

learning activity pace. More over, researchers differ

systematic and systemic. Systematic work is spread

over the days in small portions, which are logically

selected and organized by content (Klimenko, 2016).

Systematization involves the generalization of knowl-

edge, the establishment of system-forming links to

make knowledge to be systemic. There were sug-

gested formulas to process measurements and some

criteria were built. There was shown positive cor-

relation between the deﬁned regularity measures and

the performance of the student. Students who planed

their learning activities in a regular manner had better

chances of succeeding in the MOOC.

1.3 Objectives

Despite a number of theoretical and empirical studies

in the ﬁeld of modelling the learning process, there is

no integrated model yet. Available models are based

on teacher intuition and personal pedagogical obser-

vation that complicates using such models for peda-

gogical prognosis at managing the learning activity in

Internet-oriented environments. Great work for spec-

iﬁcation of models parameters and its indicators, de-

tection of pedagogical criteria inﬂuence at efﬁciency

of educational process is very actual. In this way the

aim of this paper is to study some indicators of stu-

dent’s time planning in context of their leaning activ-

ity systematicity. We try to ﬁnd correlations between

these indicators and at learning results in course “Op-

erating systems”. Also we try to look at inﬂuence of

students independent work management peculiarities

on regularity of this work.

2 THEORETICAL FRAMEWORK

In the context of mass education, the teacher cannot

pay enough attention to each student to make peda-

gogical forecast for each student on the basis of own

intuition, experience, theoretical and methodological

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145

knowledge. It is necessary to equip the student him-

self as the subject of the educational process with the

skills and appropriate pedagogical forecasting tools

for an independent choice of the appropriate variant

of educational activity. The teacher should manage

this pedagogical diagnostics system and provide the

student with necessary help. Design of the computer-

based pedagogical diagnostic system requires the de-

velopment of a learning objectives model, a student

psychological and pedagogical model (SPPM) and

learning technologies model that would form the ba-

sis of this system. These models should be specially

structured and should contain a limited number of pa-

rameters, which can be directly measured in the edu-

cational process.

Let ﬁx our attention at one of this three major

models in the system of pedagogical diagnostics – the

psychological and pedagogical model of the student

(SPPM) (Kolgatin, 2012). SPPM is built on the ba-

sis of learning objectives model so that the parame-

ters of the student model reﬂect the forthcoming to

the intended learning goal. The SPPM is to allow

comparison of successive academic achievements, re-

ﬂecting the dynamics of learning process. That is,

this model should be dynamic. Based on the anal-

ysis of pedagogical science data in the ﬁeld of edu-

cational achievement modelling (Pustobaev and Sa-

iapyn, 2005; Bespalko, 2002; Lerner, 1978; Raven,

1991; Babansky, 1989), a system of criteria has been

proposed (Kolgatin, 2012) according to such com-

ponents: motivation and target, educational content

mastering, self-management and activity, reﬂection

and prognosis (table 1). Further comprehensive de-

veloping of this model needs in a lot of experimen-

tal data on correspondence between criteria indicators

that can be directly measured in educational process

and real results of students’ educational work. But we

have not enough such data in modern publications as

it was shown above.

Estimation of the parameters that characterise the

educational content criteria is carried out by means

of pedagogical testing based on the concept of the

level of educational achievements in accordance with

the works of Bespalko (Bespalko, 2002) and Lerner

(Lerner, 1978) as well the Ukrainian educational stan-

dards. These works are not modern, but classic. The

ideas of Bespalko correlate with Bloom’s taxonomy

(Bloom et al., 1956), but Bespalko’s approach is more

simple and useful for practical automated pedagogi-

cal measurements. Lerner’s ideas give us possibility

to classify criteria according to indicators than can be

measured directly as it was shown in (Kolgatin, 2012).

The parameter of the lasting of knowledge has not

included to composition of database for model param-

eters (Kolgatin, 2012). According to deﬁnition, last-

ing of knowledge is the permanent ﬁxation in the stu-

dent’s memory of the system of essential knowledge

and methods of their application or the willingness

to derive the necessary knowledge from other based

knowledge (Lerner, 1978). A natural measure of last-

ing of knowledge is the ratio of the appropriate mas-

tering coefﬁcients according to the preliminary and

current testing. If the mathematical model used in the

automated system of diagnostics considers the param-

eters of student’s academic achievements in dynam-

ics (as a function of time), then a separate parameter

“lasting of knowledge” is not needed. It is replaced

by the functional dependence of all other parameters

on the time that, deﬁnitely, carries more information.

The parameters of the student’s psychological

and pedagogical characteristics are determined by the

teacher on the basis of pedagogical observation and

analysis of the products of the student’s educational

activity. The student also takes active part in deter-

mining these parameters by introspection.

A high level of reﬂection on the result of the ac-

tivity indicate the student’s ability to objectively eval-

uate own results of the learning activity and his desire

to complete the task qualitatively, to bring the work to

a logical conclusion. The presence of an appropriate

parameter in the student psychological and pedagog-

ical model (SPPM) gives a reason to offer students,

who have the developed reﬂection to the result of own

activity, educational tasks of a creative nature. Other-

wise, such tasks as projects, creative works etc. can be

ineffective without student’s own reﬂection, because

it is difﬁcult to build an objective and unambiguous

algorithm for its checking.

High importance of the result of learning activ-

ity for the student is expressed in the desire to mas-

ter given knowledge and skills as soon as possible,

to get the result of the activity in the form of a fully

completed task or project, a solved problem, etc. Of

great importance is the student’s sense of satisfaction

from the successful completion of similar tasks in the

past (Raven, 1991). The organization of education of

such students should provide for certain stop points at

which the student can feel the completion of the stage

of work. It is advisable to prevent the unexpected ad-

ditional tasks and complications.

High interest in the process of learning is often

native for students with research abilities, who can

unlimited improve a computer program or laboratory

equipment, collect some data from the Internet and so

on. Modern multimedia tools and intelligent learning

systems help to increase delight of the learning pro-

cess itself. But the interest in certain activities in the

absence of signiﬁcance of the learning result leads to a

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Table 1: Structure of the student psychological and pedagogical model.

Component Criteria

Motivation and target

Signiﬁcance of the result of learning activity for the student

Student’s interest in the educational process, cognitive interest

Conscious adherence to the educational discipline

Educational content mastering

Completeness of knowledge

Promptness of knowledge

Depth of knowledge

Flexibility of knowledge

Systematic of knowledge

Automation of activity

Self-management and activity

Stability of pace of learning activity

Ability of the student to mobilize energy, persistence and will

Reﬂection and prognosis

Student’s reﬂection on the result of activity

Student’s reﬂection on the process of activity

shift in the focus on minor things and reduce the effec-

tiveness of learning. Such students need in regular di-

agnose of the structure of academic achievement and

control the implementation of the curriculum. They

need in systematicity of learning activity according to

curriculum. Such systematicity can be achieved by

direct management of student’s independent work or

by training the student in skills of self-management.

Cognitive interest as a separate parameter of the

student model provides an opportunity to distinguish

features of the student’s motivation for learning activ-

ities. An important element of the emotional setting

for learning activities is the conscious adherence to

the educational discipline (Babansky, 1989), which is

expressed in the self-control of the correspondence of

the learning activity to the work plan and culture of

interaction with other participants of the educational

process (timely completion of tasks, conscious fulﬁl-

ment of requirements, accuracy in visiting classes and

appointed consultations).

The strength and stability of the student’s con-

centration on learning activities in a particular disci-

pline largely depends on the peculiarities of the men-

tal processes and physiological properties of the stu-

dent and determines the style of educational activ-

ity. Therefore, it is important to add to the student

model (SPPM) a parameter that characterizes a stu-

dent’s ability to mobilize persistence and will (Raven,

1991), and a parameter that characterizes the stability

of the pace of student’s academic work (Babansky,

1989).

Activity of the student on introspection, obser-

vation of student’s educational work, analysis of the

style of educational achievements tests passing, anal-

ysis of the order of performance and presentation of

educational products, analysis of the content of prod-

ucts of educational activity – are the sources of the

information for the SPPM. It is advisable to measure

parameters of reﬂection, emotional setting and vo-

litional qualities on a scale of order (low, medium,

high). The application of the equal-interval scale is

problematic, because these parameters are complex

and may include various indicators with signiﬁcantly

non-linear effect. Such measuring becomes a problem

in case of lack of personal interconnection between

student and teacher.

Summarising the above, it should be pointed that

all indicators, which can be measured in some learn-

ing management system, are complex and are con-

nected with several criteria of student’s motivation,

target of education, educational content mastering,

self-management and activity, reﬂection and progno-

sis. We need to understand the main binds of each

indicator with criteria. There will be studied the

time of learning activity products submissions in this

paper. We assume that in-time submission of stu-

dent’s works characterise student’s motivation (crite-

rion: Conscious adherence to the educational disci-

pline), competency in self-managing (criteria: Stabil-

ity of pace of learning activity; Ability of the student

to mobilize energy, persistence and will) and reﬂec-

tion (criterion: Student’s reﬂection on the process of

activity). The time of submission can be directly anal-

ysed in Internet-oriented learning management sys-

tems, such as Moodle. We can see if the learning ac-

tivity product was submitted in-time or not. We can

also see the time of the submission. We can see if the

student worked regular during a week or submitted

the work in the last moment.

In this paper the systematicity of student’s activity

are understood in context of activity by the plan given

by teacher or designed by student in accordance to

curriculum. Correlations of systematicity indicators

with parameters of student psychological and peda-

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gogical model are analysed both hypothetical and ex-

perimental

3 SYSTEMATICITY OF

STUDENTS LEARNING

ACTIVITY IN BLENDED

LEARNING

3.1 Methodology of Empirical Research

Study of features of students learning activity, con-

nection between its systematicity and students’ learn-

ing achievements was conducted in course “Operat-

ing Systems” with use of learning management sys-

tem Moodle. Methods of learning the course “Op-

erating Systems” are not a matter of this paper, but

we should to describe the ground of our empirical

work. In 2019 this course combines theoretical and

practical issues of operating systems concepts, mod-

els of its interconnection with hardware, applied soft-

ware and users (Tanenbaum and Bos, 2014; Allievi

et al., 2022; Bacon and Harris, 2003). The ﬁrst con-

tent module of this course is devoted to history and di-

versity of operating systems according to peculiarities

its application. Students should understand the basic

principles of computer hardware building, in particu-

lar, von Neumann principles, shared bus architecture,

address space, function of the registers, interrupts etc.

One of the main fundamental issues of this module

is to show the deep connection between the hardware

and operating systems architecture. The simple op-

erations in operating systems with use of command

interpreter and graphical user interface were also the

object of students’ educational activity. Second mod-

ule is devoted to detailed study of main abstractions

in the theory of the operating systems: virtual mem-

ory, processes and threads. Students used built in and

third party software as well as the authors’ models to

investigate the peculiarities of internal mechanisms of

multiprogramming realisation, especially of schedul-

ing CPU time and access to slow devices as well as

RAM memory access. The third module covers wide

spectrum of practical issues of booting the operating

systems and logical organisation of disk drives, ﬁle

systems, the structure of executable ﬁles, mechanism

of management of the Windows operating system, se-

curity in operating systems.

Practical component of students’ educational ac-

tivity was dominant. Students of second year, future

bachelors of computer science and software engineer-

ing completed the practical tasks on analysing struc-

ture, functionality, principles of design of some op-

erating systems with use of virtual machines. Spe-

cial software for virtualisation was used for support-

ing educational activity on installing different oper-

ating systems and third party software. Methods of

study operating systems with using of virtualisation

are enough developed in modern pedagogical works.

As an example we can suggest the research of Spirin

and Holovnia (Spirin and Holovnia, 2018). The tasks

that were suggested for students assumed a part of

work to be done in classes and other part was home-

work. There was traditional educational process in

2019 with some components of student independent

work management in Moodle. Personal Learning

System in Moodle contained some theoretical mate-

rials, reference lists, instructions for the laboratory

works. Personal Learning System was used by stu-

dents to submit their reports on laboratory works com-

pletion.

Each student worked according to unique variant

of the tasks, but some steps were very similar for all

students. Each of these task contained both reproduc-

tive and creative steps with problem solving. There

were suggested 11 tasks in 2019 year for every stu-

dent for the semester according to the topics of the

curricular:

• Analysing the ReactOS operating system (in-

stalling and customising the operating system, do-

ing some work in it);

• Analysing the KolibriOS operating system (in-

stalling and customising the operating system, do-

ing some work in it);

• Analysing the Ubuntu operating system (in-

stalling and customising the operating system, do-

ing some work in it);

• Analysing active processes and threads in the

Windows operating system (operating with pro-

cesses and threads, obtaining the information

about the active processes and threads using built-

in and third-party software);

• Analysing CPU and memory managing procedure

in the Windows operating system (simulating of

the operating system scheduling with use of the

special designed model WinMOS);

• Analysing the Windows virtual memory (getting

the information and optimising RAM memory

with use of built-in and third-party software);

• Analysing the structure of the Windows exe-

cutable ﬁles (getting the information about ﬁles

and its structure with use of the ﬁelds map and

third-party software);

• Analysing the Registry in the Windows operating

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148

system (using and changing the registry informa-

tion for managing the operating system);

• Analysing system services and drivers in the Win-

dows operating system;

• Analysing data security in the Windows operating

system (working with accounts, encryption algo-

rithms, digital signature);

• Analysing and optimising the Windows operating

system booting.

As the result of this work, students prepared and

submitted reports using Assignment activity in the

university Personal Learning System based on Moo-

dle. So, we have possibility to monitor the time of

completing the task by the student. The grades for

reports with late submission were less. The reports

that were prepared later than 2 weeks after deadline

were not accepted by personal learning system, and

students presented such reports to teacher in printed

form personally with oral discussion. These reports

with very late submissions have not analysed in this

paper. In total, 54 students took part in experiment.

274 reports were analysed. The ﬁnal test in written

form has been suggested to students for evaluating

their educational achievements. The results of this

test were the base for study the connection between

systematicity of student’s learning activity and his/her

educational achievements.

3.2 Results and Discussion

Speciﬁc values of ﬁnal test results were used for

analysing correlation between systematicity of stu-

dents’ learning activity and their educational achieve-

ments (ﬁgure 1). This values were calculated as ratio

of test result of each student to maximal test result.

The indicator of systematicity was evaluated as a part

of reports, submitted in time by a student, that is as a

ratio of the number of reports, submitted by a student

in time, to the number of reports according to plan

(11 reports for 11 tasks). We believe that both these

variables are measured on an interval scale, so Pear-

son correlation was used for analysis. The correlation

between these two variables is 0.28 and is statistically

signiﬁcant at the signiﬁcance level 5 % for samples

size of 54 that is enough in pedagogical researches.

So, we can conclude that the part of reports, sub-

mitted by student in time, positively connected with

educational achievements. What is the kind of this

correlation? Three variants are possible: 1) system-

atic work according to the plan, given by the teacher,

contributes for increasing educational achievements;

2) students with high initial educational achieve-

ments easily execute the tasks and submit their re-

ports in time; 3) students with high competence in

self-management of their independent work have high

educational achievements at all and, in particular, use

their skills to complete the tasks in time for higher

grading. Both the ﬁrst and the third variants corre-

spond the positive inﬂuence of systematicity on edu-

cational achievements.

Analysing the diagram at ﬁgure 1, we can see that

the second variant was not realised: students with

high test results (above 60 %) had systematicity in-

dicator from 0 to 100 % and there was not any trend.

Moreover, there was not any student with very high

(above 80 %) systematicity indicator and test results

simultaneously. So, we can see that the student with

highest educational results did not work according to

common plan even losing some grades. They, may

be, worked systematically, but according to their own

plans, so methodology of our experiment did not give

us possibility to measure peculiarities of this work.

Otherwise, they may be characterised by low level of

importance of the learning activity results and high

interest in the process of learning, and high cognitive

interest. It should be appropriate to use for such stu-

dents not the direct management of their independent

work, but co-management or self-management.

Analysing the lowest boundary of points alloca-

tion at ﬁgure 1, we can see that high value of the

systematicity indicator (above 60 %) guaranteed suf-

ﬁcient educational results (above 40 %). But students

with highest systematicity indicator did not show ex-

cellent results in testing. This analysis gives grounds

for hypothesis that the kind of management of stu-

dent’s independent work should be timely turned from

direct management through co-management and sub-

sidiary management to self-management according to

the level of student’s educational achievements and

skills in self-managing for increasing the efﬁciency

of educational process.

Choosing the day for completing the report, stu-

dents taken into account many tasks in various sides

of their life and study. But the fact that the number of

reports, submitted in the last day, exceeds in near four

times the number of reports, submitted in any other

day (see ﬁgure 2), show us the lack of students’ com-

petence in time planning and managing own work.

The deadline was set on Sunday at 11:55 PM.

There was Saturday, free of classes. In some cases,

students had more than a week to prepare their re-

ports. But only 40 % reports were submitted in this

period. Only 2 students used this period for stably

work with every of their tasks. Our conclusion is

to provide students with detailed direct management

of their independent work at the initial stages of the

course as well as to provide special training for in-

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Figure 1: Correlation between systematicity of students’ learning activity and their ﬁnal assessment results at traditional

blended learning process.

Figure 2: Frequency distribution of students’ report submissions by days relatively from the ofﬁcial deadline.

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150

creasing student’s competence in time planning and

self-management.

Did students work enough hardly in the educa-

tional process? Let us analyse diagram at ﬁgure 3. We

can see that students work at any time of day and night

accept of period from 4 AM to 7 AM. In our opin-

ion, such time scheme does not promote the learn-

ing of deeper questions of educational material, does

not support productive and creative learning activity.

This is not a problem of one course or one university,

but a complex goal of development the methodology

of education in direction to turning from reproduc-

tive methods of learning to more efﬁcient students’

activity with active use the information and commu-

nication technologies in education. We should take

into account dual educational process, which is coor-

dinated with professional-oriented practice work.

4 SYSTEMATICITY OF

STUDENTS LEARNING

ACTIVITY IN DISTANCE

LEARNING

4.1 Methodology of Empirical Research

COVID 2019 pandemic changed the educational pro-

cess to mostly distance form of learning. So we could

possibility to compare students behaviour in blended

and full distance educational process. We continued

to use the course “Operating Systems” and the Per-

sonal Learning System in Moodle as the base for our

investigations. Participants of this work were future

bachelors of software engineering both Ukrainian and

foreign citizens. The language of study was English.

The educational program was modiﬁed a little to shift

accent on the student independent work. Theoreti-

cal and practical issues of operating systems concepts

were studied in two content modules devoted to op-

erating system concepts and administrating processes

(table 2). There were suggested 8 laboratory work

tasks to students (table 2), which assume solving prac-

tical problems on analysing structure, functionality

and principles of design of some operating systems.

The key attention was paid to Microsoft Windows op-

erating system, because Linux solutions are the mat-

ter of additional course according to our educational

program. These tasks were devoted to deep under-

standing fundamentals of operating systems and mas-

tering skills of operating system administrating. Each

of these task contained both reproductive and creative

steps with problem solving. The tasks were suggested

for students assumed all work to be done at home, but

with online help of a teacher. The teacher was present

online with using Zoom Cloud Meeting environment

according to schedule. Each laboratory work was as-

sisted by 2 academic hours of such online consulta-

tion and there were additional individual consultation

in Zoom Cloud Meeting.

As the result of this work, students prepared and

submitted reports using Assignment activity in the

university Personal Learning System based on Moo-

dle. The grades for reports with late submission were

less. There were not hard deadline for submissions.

Students had to presented all their reports to teacher

online using Zoom Cloud Meeting environment with

oral discussion. In total, 25 students took part in the

course during 2020 and 2021 years under COVID-19

conditions. 147 reports were analysed. The ﬁnal test

has been suggested to students for evaluating their ed-

ucational achievements using Moodle Assessment el-

ement. The results of this test were the base for study

the correspondence between measured indicators and

student educational achievements.

4.2 Results and Discussion

Values of ﬁnal test results were used for analysing

correlation between the part of reports submitted in-

time by students and their educational achievements

(ﬁgure 4). This values were calculated as ratio of test

result of each student to maximal test result. The in-

dicator of systematicity was evaluated as a part of re-

ports, submitted in-time by a student, that is as a ratio

of the number of reports, submitted by a student in-

time, to the number of reports according to plan (8 re-

ports for 8 tasks). Pearson correlation between these

two variables is 0.67. This correlation is statistically

signiﬁcant at the signiﬁcance level 0.1 % for samples

size of 25.

We can conclude that the part of reports, submit-

ted by student in time, positively connected with edu-

cational achievements.

Analysing the diagram in ﬁgure 4, we can see that

despite the main tendency some students with high

test results had systematicity indicator from 10 %.

This results proves our previous hypothesis that some

student with highest educational results did not work

according to common plan even losing some grades.

According to our pedagogical observations some of

such students tried to complete the tasks earlier as

soon as possible if they wanted to have highest grades.

And distance learning process gave them such possi-

bility, because all tasks were uploaded on Personal

Learning System in Moodle environment. This situ-

ation ones more proves our conception that we need

adaptively transform the mode of student independent

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Figure 3: Frequency distribution of students’ report submissions by time, summarising all days (Deadline was 11:55 PM).

work management from direct management through

co-management and subsidiary management to self-

management. We still can see that all students, who

completed more than 50 % of the practical tasks in-

time, had more than 50 % in test. So systematicity

is the base obligatory requirement in educational pro-

cess.

We see that the day before deadline is the most

popular to complete the educational tasks, similar to

traditional blended learning process (ﬁgure 5). Such

behaviour require from student mobilizing energy,

persistence and will. From the other side such be-

haviour can be the result of the lack of students’ com-

petence in time planning and managing own work.

The deadline was set at 11:55 PM in different days

of a week. All students had more than a week to

prepare their reports. But only 44 % reports were

submitted in-time. We could not prove the statistical

identity of student groups in 2019 and 2021 – 2022

years. There were different proportions of foreign

and Ukrainian citizens in these samples, for example.

So we can not make statistical comparison of relative

time frequency distributions in blended and distance

learning process. But analysing the diagram (ﬁgure 5)

we can see more free students’ time planning. There

are some local maximums with a week (7 days) period

before and after the deadline. The right tail (tasks that

was not completed in-time) decreases slow. We be-

lieved that obtained new data conﬁrm the conclusion

to provide students with detailed direct management

of their independent work at the initial stages of the

course as well as to provide special training for in-

creasing student’s competence in time planning and

self-management.

The distribution of students’ working time has be-

come more natural in distance learning process (ﬁg-

ure 5). The most of reports were submitted in busi-

ness time unlike the traditional blended learning.

The relative (on deadline) time of student’s report

submission can be used to build once more indicator –

standard deviation of the submission relative time.

We calculate the set of differences between the real

time of each submission and deadline. After that we

calculated the standard deviation for this set of val-

ues. Such an indicator take into account not the fact

of in time submission, but evaluate stability of earlier

and late submissions in comparison with our previous

indicator (“Part of tasks that have been completed in

time”). May be, some students have the own work

schedule. They can submit the report 1 day later each

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Table 2: Structure of the “Operating System” course in distance learning format.

Content Module Theme Laboratory Work Task

Operating

System Concepts

Basic concepts, evolution, types of op-

erating systems

Virtual Machine and Virtual Disks

(creating virtual machine, installing

and customising the operating system

Kolibrios, doing some work in it)

Architecture and resources of operating

systems

Operating System Ubuntu: Basics of

Administrating

(installing and customising the oper-

ating system, doing some work in it,

analysing resourses of the operating

system using internal tools)

Multitasking. Scheduling and interac-

tion of processes and threads

Operating System Windows: Basics of

Administrating. Task Manager

(operating with processes and threads,

obtaining the information about the ac-

tive processes and threads using built-in

and third-party software)

RAM management RAM and Virtual Memory

(getting the information and optimising

RAM memory with use of built-in and

third-party software)

Operating

System

Administrating

Operating system booting. File systems Operating System Booting. File Sys-

tems

(getting the information about ﬁles and

ﬁle system of different devices using

internal Microsoft Windows tools and

third party software, analysing and op-

timising the Windows operating system

booting)

System Registry in OS Windows System Registry in OS Windows

(using and changing the registry infor-

mation for managing the operating sys-

tem)

Executable ﬁles. System services and

drivers

Executable Files. System Services and

Drivers

(getting the information about exe-

cutable ﬁles and its structure with use

of the ﬁelds map and third-party soft-

ware, analysing internal structure of

driver initialisation ﬁles, managing sys-

tem services using internal tools of Mi-

crosoft Windows operating system)

Information security in operating sys-

tems

Information Security in Operating Sys-

tems

(working with accounts, encryption al-

gorithms, digital signature)

time, the stability of learning activity will be high and

the value of “Standard deviation of the submission

relative time” will be low. May be, some other stu-

dent always submits the work in time, but does it 1

hour or 1 week randomly earlier. The stability of his

learning work will be low, and the “Standard devia-

tion of the submission relative time” indicator will be

of high value. The suggested indicator can be use-

ful in cases when the deadline is not hard but is only

recommended by a teacher.

We apply this indicator only to students, who

complete at least a half of the educational tasks, so the

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Figure 4: Correlation between systematicity of students’ learning activity and their ﬁnal assessment results at distance learning

process under COVID-19 conditions.

Figure 5: Frequency distribution of students’ report submissions by days relatively from the ofﬁcial deadline (distance learning

under the COVID-19 conditions).

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Figure 6: Frequency distribution of students’ report submissions by time, summarising all days at distance learning under

COVID-19 pandemic conditions (Deadline was 11:55 PM).

Figure 7: Correlation between standard deviation of the submission relative time and ﬁnal assessment results of students at

distance learning process under COVID-19 conditions.

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sample size was 19. We assume that this indicator cor-

responds to such criteria of the student psychological

and pedagogical model: stability of pace of learning

activity, student’s reﬂection on the process of activity.

We can see negative correlation between this indicator

and student’s learning achievements (ﬁgure 7). The

value of Pearson correlation is −0.51 and this corre-

lation is signiﬁcant at signiﬁcance level 0.05 for the

samples size 19. This result correlates with behaviour

of our previous indicator – “Part of tasks that have

been completed in time” ﬁgure 4. The standard devi-

ation of relative (on deadline) time of student’s report

submission can be used as a prognosis parameter for

student success in education.

5 CONCLUSIONS

Analysis of obtained experimental data in context of

our theoretical framework has given the base for such

conclusions:

• the ratio of educational tasks number completed

in-time to its total number is an indicator that pro-

vide combined information about such criteria in

student psychological and pedagogical model as

1) stability of pace of learning activity; 2) stu-

dent’s reﬂection on the process of activity; 3) con-

scious adherence to the educational discipline;

4) signiﬁcance of the result of learning activity for

the student. This indicator has good prognostic

ability on the educational achievements;

• the analysis of relative to deadline time of stu-

dents’ learning product submissions give us infor-

mation about 1) student’s reﬂection on the pro-

cess of activity; 2) ability to mobilize energy, per-

sistence and will; 3) stability of learning activity

pace;

• new data conform our previous conclusion that

students’ competency in self-management and

time planning should be improved by providing

students with detailed direct management of their

independent work at the initial stages of the course

as well as to provide special training for increas-

ing student’s competence in time planning and

self-management;

• the mode of student’s independent work manage-

ment should be timely turned from direct man-

agement through co-management and subsidiary

management to self-management according to the

level of student’s educational achievements and

skills in self-managing for providing the efﬁ-

ciency of educational process at highest level of

educational achievements.

This study does not exhaust all the aspects in the

ﬁeld of creating of comprehensive student model for

the systems of pedagogical diagnostics and progno-

sis. The main task in this direction is in obtaining a

lot of experimental data about corresponding of some

educational process indicators and efﬁciency of one

or another methods of learning. We also need to de-

velop algorithms for estimating given criteria using

available indicators.

Concerning further development of the course

“Operating Systems” we plan to introduce the man-

agement of student’s independent work with more or

less elements of self-management according to the

features and educational achievements of a student.

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