INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL
Online ISSN 1841-9844, ISSN-L 1841-9836, Volume: 17, Issue: 5, Month: October, Year: 2022
Article Number: 4854, https://doi.org/10.15837/ijccc.2022.5.4854

CCC Publications 

The role of E-Learning generated by the COVID-19 epidemic in
higher education

T.O. Breaz, M.T. Fülöp, L.I. Cioca

Teodora Odett Breaz
1. Lucian Blaga University Sibiu, Romania
2. „1 Decembrie 1918” University of Alba Iulia
Alba Iulia, Romania
teodora.breaz@uab.ro, teodora.breaz@uab.ro

Melinda Timea Fülöp*
Babeş-Bolyai University of Cluj-Napoca
Cluj-Napoca, Romania
*Corresponding author: melinda.fulop@econ.ubbcluj.ro

Lucian Ionel Cioca
Lucian Blaga University
Sibiu, Romania
lucian.cioca@ulbsibiu.ro

Abstract

As key players in our society, universities have a special responsibility for sustainable devel-
opment. As institutions of education, research, and services, universities are key players in the
sustainable development of society and the economy. With the health crisis caused by Covid-19, it
was necessary to introduce digitalized teaching. We could even say that Covid-19 is an accelerator
for students’ and teachers’ acceptance of digital technologies in teaching. In many universities,
there is still some impotence on how distance or short-term university teaching can take place. In
the European higher education area, there has long been a commitment to greater digitalization
of teaching under the keyword e-learning, so we set out to analyze these issues in the Romanian
university environment. The results show that substantial efforts have been made, but these efforts
must be continued to be successful and to reach a sustainable university.

Keywords: e-Learning, TAM, university sustainability.

1 Introduction
As institutions of education, research, and services, universities are key players in the sustainable

development of society and the economy. University sustainability must be the dynamic contribution
of all advanced teaching organizations in the development of environmental protection policies. A
sustainable academia is the university that, in addition to the governmental participation, donates



https://doi.org/10.15837/ijccc.2022.5.4854 2

to the fortification of the environment by adjusting the learning curricula to the environmental re-
quirements, respectively, by the improvement of the methodical knowledge, because of the educational
and investigate, respectively, research activities. The way in which the present humanity mechanism,
by increasing the manufacture and consumption of goods and facilities, is not feasible and will have
a damaging consequence in the extended run. This characteristic has presently produced powerful
apprehension in university, but also at the flat of decision makers concerning sustainability. The UN
has established and issued the 2030 Agenda for Sustainable Development Goals, which includes 17 key
goals, including the goal of developing education so that universities become more sustainable. The
17 Sustainable Development Goals have been designed to increase awareness of the various facets of
sustainability, drawing explicit goals that contain an accomplishment strategy for a extensive series of
social, environmental, and technological subjects, from reducing deficiency, health for all, infrastruc-
ture progress, education, gender equality, maintainable use of oceans, energy, water, and sanitation.
All 17 goals can be connected to engineering and individually request engineering to accomplish their
goal [32]. With the digitalization of higher education, the fourth goal of the UN Sustainable Devel-
opment Agenda, computer scientists and engineers have a special role to play in the efficient use of
(recorded) data for process optimization, IT, resource saving programming, renewable energy, energy
transition, energy, efficient production, electronic waste disposal, recycling, the role of decision based
on IT, etc. Thus, new study programs need to be developed in an agile, flexible, and targeted manner.
Furthermore, courses should promote personal, ethical, social, and methodological skills more than
ever before. Practical, technical, and interdisciplinary teaching content or partnerships with compa-
nies are more important than ever in training, especially in the field of engineering. Ready in this way,
tomorrow’s engineers can better meet the challenges of the digital world of work for decision markets
[13], [14], [15], [19]. The future as a location for technology and innovation depends in particular
on the successful and timely digitalization of business, research, and teaching. The digital revolution
in the education involves the engrossment of sustainable management, in demand to adjust to the
fluctuation’s compulsory by new technologies, will play an important role in supporting decision [13],
[14], [15], [19]. In current periods, universities have been informed of a set of significant changes,
encouraged by technological and social tendencies concerning digitalization. Like all revolutions, dig-
italization involves a powerful change in all segments. Presently, the implementation of technologies
by academes is connected to a paradigm change, in which technology is considered as a multifaceted
and interrelated environment that allows digital learning through transformation and plays the role
of decision-maker [13], [15], [19]. In this way, the attention is further absorbed on the student and
the necessity for technology. In this framework, digitalization is a stipulation in higher education
organizations, able to attract more and better students, to improve the teaching materials used in
courses, and the teaching procedure in over-all. New technologies such as artificial intelligence, big
data, Moodle platforms [13], [15], [19] also allow better monitoring and help to identify barriers and
decrease the hazard of dropping out of university. However, the hesitancy to appreciate and take
benefit of prospects to change to this digital environment persists. The digital revolution in the world-
wide higher education business is the forthcoming approach to sustainable teaching management [22],
[24]. The world we live in is shifting at a fast pace, and anything we explain and in what way we
teach is also growing quickly. In current years, universities around the world take knowledgeable fast
variations with influence, which have remained influenced by technological development and the social
tendencies of digitalization. Like all other innovative variations, the digital revolution includes power-
ful change/rearrangement. Robust variations in the socioeconomic-educational system follow-on from
the globalized economy have led to fluctuations in impulsion, particularly in universities, such as the
normal of instruction, value, regionalization, and computer-generated and self-governing education.
These factors in the field of instruction communally encourage transcontinental teaching. The wide
spread of global teaching has fundamentally inclined academies to form their education and growth
instruments, transfer, and constant perfection. Universities may no longer be dependent on traditional
systems of education to face the challenges posed by the phenomenon of globalization. Virtual learn-
ing is becoming increasingly significant for schools among the 2019 pandemic [7]. It is imperative to
cover the serious situation of computer-generated learning beyond the IT tool and instrumentalization
[5], [9]. Consequently, academies need to discover how they might balance people with e-learning



https://doi.org/10.15837/ijccc.2022.5.4854 3

to safeguard teamwork and participation. Virtual learning technology has grown at an astonishing
rate and its use, especially in transcontinental academies, has converted additional common. This
phenomenon has particularly affected training approaches and their transfer. Therefore, this article
highlights the impact of digitalization on institutional management and performance, respectively,
investigating factors that influence the digital transformation during the Covid-19 pandemic, which
led to the transition to e-learning [6], [7], [12], [18], [27]. The novelty and the main contribution are
the examination of the situation for Romanian universities because we identify this goal in the existing
literature and we consider it to be very important to analyze the acceptance of new theology because it
can be decisive for the future. Moreover, automation and digitalization can have a significant positive
effect on the well-being [13]. To achieve our objectives, we make a short examination of the literature
on the digitalization in the university environment, the acceptance of technology, and the relationship
with the sustainability and the university to identify al main goals and et and we present the result
of our study.

2 Digitalization in the university environment
Technological progress, the increasing national and international interdependence of companies

and the liberalization of the markets lead to problems in almost all areas of the economy, which are
characterized, among other things, by increasing dynamics, interconnectedness, and increasing opac-
ity. The handling and management of such complex economic situations with ever-shorter decision
cycles is one of the essential requirements for the management of the future [20], [21], [25], [27]. At the
same time, the importance of the "information" factor as one of the main determinants of problem-
solving and decision making has steadily increased in recent years. The worldwide and constantly
growing spread of information and communication technologies in many areas of human life and the
emergence of a new employment sector "information" industrial information age. This also and es-
pecially applies to the microeconomic, business administration area. "Information" is more and more
frequently referred to here as an independent production factor, and information technology can serve
as a "strategic weapon" for more efficient and effective use of existing and for the development of future
universities potentials and thus for the attainment of operative and strategic competitive advantages.
Digitalization has now reached all areas of work in universities and penetrates the fields of research
and teaching, as well as their administrative processes, and helps to make decisions [13], [15], [19].
Digitalization in universities is associated with various potentials and expectations, but at the same
time with uncertainties and fears. Learning in Internet-supported teaching-learning scenarios is not
isolated, it is not lonely learning. Rather, the shared use of the learning platform, the collaboration
with the learning group, the virtual exchange with the tutor or the lecturer represent an important
social component. Digitalization determines the public discourse in and for educational institutions,
as well as internal discussions in the universities about their further development. However, there
are many myths about what is addressed or meant by digitalization, such as that the media per se
would improve the learning of students [26]. The universities themselves have created realities, for
example through their e-learning activities. Since then, perspectives relating to digitalization have
also opened, which, on the one hand, are rooted in their technical, organizational and didactic possi-
bilities, but on the other hand, also ask about forms of their study and research in universities. All
discussions are flanked by developments in education and science policy, with research and funding
programs or university policy or strategic objectives using terms such as e-learning, media, or digi-
talization in their various forms. However, their novelty is not necessarily reflected in new concepts,
reorganized processes, or in a completely changed practice of academic teaching and research. Rather,
digitalization appears as a postulate. Therefore, it is essential to also disclose narratives in connection
with the concept of digitalization for science and practice. All these aspects are discussed with the
necessary productive-critical distance. In short, digitalization should allow universities to conduct
research, teaching, and administration at a higher quality and more professional level [20], [31]. In
fact, a variety of visions, strategies, and implementation concepts for the “digital university” have
been and are being developed and lived in universities. Innovations are perceived innovations with
benefits, so it is initially unclear who the beneficiaries are. In this respect, the concern is legitimate



https://doi.org/10.15837/ijccc.2022.5.4854 4

to shed light on e-learning, what is new about it, and what daily teaching-learning problems can be
solved with it. However, when it comes to educational innovations such as this, it takes a surprisingly
long time to find one player in this research. At best, it becomes active when it comes to checking
an innovation in school, university, or further education, as a kind of "research afterwards". Everyone
wants to be innovative these days: companies, political parties, the cultural program, university man-
agement, etc. Ultimately, those affected decide whether something new is also suitable for everyday
use. When it comes to research into learning and teaching, whether with or without new media, things
look rather bleak in terms of both suitability for everyday use and innovative strength. The special
structural needs, challenges, and implementation potential are very different for different areas of the
university [30]. As a cross-cutting issue, digitalization is becoming more widespread in all areas of the
university, offering new opportunities in teaching, research, and communication, but at the same time
presenting new challenges to teachers and students. E-learning has come through a decade of growth,
decline, experimentation, transfer, excitement, and disillusionment. Irrespective of public perception,
the political and economic trends and their reflection in the media, over the course of this decade
universities have been increasingly dependent on reacting inventively to new challenges in teaching
and learning. Many institutions used the possibilities of information and communication technologies.
In this way, efforts were made to face up to the changing teaching framework conditions and the
changed demands of various stakeholders inside and outside the universities [4], [5], [6], [9]. According
to Ehlers (2018) [10], a key factor of the future university are greater participation in education, in-
creased diversity in life situations, digitalization, and student needs. Although Ehlers (2018) [10] sees
the strongest factors, on the one hand, in the growing importance of education in society and, on the
other hand, in digitalization, another equally important factor is the needs of students as part of the
digitalization project. The reason for this is the assumption that students’ needs will be a significant
part of shaping their profile [27]. Classically, the term Decision Support System (DSS) is defined
as a computer-aided planning and information system that prepares or supports the preparation of
decisions at management levels but does not make the decision itself. Against the background of rapid
development in IT and the widespread spread of the Internet, this definition seems to be outdated in
many cases, since a large number of decision support systems nowadays make not only strategic but
also operative decisions. The development of the digital university is a demanding and complex task.
It is too narrow a view if digitalization is seen only in standardized mass-produced mechanization
of teaching and learning processes and also does not include aspects of permeability, personalization,
effectiveness, lifelong learning, labor market requirements, educational partnerships, and innovation
[2], [3], [4]. Finally, the “student-centric” factor is the application of the well-known client-centered
strategy [11]. This benefits from greater transparency and improved communication and interaction
options on digital platforms [16], [21], [27].

3 Accepting technology in the university environment
The term e-learning has its origins in the 1980s, and subsequent, the outline of the primary

computer-assisted jobs, which led to the replacement of handheld computers and typewriters with
computers, so to speak. Employees have been trained in new software applications (e.g., operating
systems, text programs, and databases) through traditional employee training courses and - and this
remained new - through small education programs that have been installed on a computer unit by
software workers. These tools remained initially modest didactic manuscripts, which were processed
in the following years using illustrations and animations. The outline of such e-courses firstly shaped
a persevering misperception around the potentials of this new category of skill. For many educational
specialists, legislators, and software producers, this technology has been considered a miracle tool. It
should help to reduce (staffing) prices in the teaching segment and open novel delivery networks for
education contributions. For example, traditional academies were anticipated to expand into numer-
ous categories of academies, most of which remained virtual organizations, such as worldwide groups,
systems, and virtual academies. From a didactic point of view, nothing less than better learning
has spread. Consequently, specific procedures of likeness, response, creation, communication, and
relationship should be stimulated only through the use of the media, which in particular promotes



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the acquisition of knowledge. E-learning could do this, e.g. it has only partially met the euphoric
expectations so far, or expectations should have been revised because they are excessive. This shows
that providers of virtual higher education offerings or online courses face subjects such as employer
acceptance and dropout tolls fairly additional intensely than providers of traditional educational of-
ferings.

Figure 1: The relationship about TAM and the sustainability of universities

It is difficult to discover an explanation of the term e-learning in the literature. On the one hand,
this can be traced back to the circumstance that the concept of e-learning has become recognized to
define e-learning approaches, but it still requests to be avowed alongside numerous other designations
and attempts at arrangement [12], [21], [27]. It doesn’t matter if it is computer-based learning,
computer-assisted teaching, computer-mediated learning, or computer-assisted learning: most of these
are comparable concepts that cannot be straight distinguished from each other. The first systematic
debates around e-learning occurred in the late 1990s; at the equivalent period, they encouraged the
primary methodical efforts at providing a characterization. Originally, the effort was concerned with
concerning the practical potentials of dispensing the learning content, e.g., satellite learning, CD-ROM
learning, interactive television, or videotape learning. The essential element of the description of the
setting of concept is the education as a intermediary of the education provided for the student. An
explanation of the education condition does not take place in the primary efforts of characterization,
nor ensures the debate about the importance of the student in the education situation: that of an
asset and the learning scenario with creative recipients or that of the passive observer [17]. It is
now understood that e-learning should be understood as a common term for all categories of media-
supported learning. What they have in common is that the learning process is considered a key factor
in achieving individual learning goals. However, the term does not specify the content of what is to
be learned but refers to the technological means used. This leaves an overly rigid technological focus.
According to this agreement, e-learning includes accepted forms of learning both online and offline (for
example, learning without internet support). Thus, we can emphasize that e-learning always means
dealing with electronic media. However, this method of learning can only be successful if you can
work and learn with technology as a tool without much cognitive effort. Technology should not be
at the heart of the learning situation but the learning offer. Therefore, it should be irrelevant to the
learner if they access the network-based or locally stored information systems. To make this possible,
software developers have now made available learning systems, many of which are difficult to monitor.

4 Research framework and results
The technology acceptance model was developed by Davis (1986) [8] as part of his dissertation and

is an adaptation of action theory. The model was developed to predict the acceptance of technical
systems. According to the Fishbein-Ajzen theories (1977) [1], the technology acceptance model is
intended as a direct predictor of behavior (acceptance). The purpose articulates a person’s intention
to usage the technical system in question in the future. The aim is, in turn, determined by two



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perceptive issues: perceived benefit and the perceived ability to use the system under consideration.
Davis defines the impact of third outside variables in the model as project structures that take an
impact only on cognitive variables. Figure 2 shows the model.

Figure 2: Davis’ technology acceptance model

In acceptance research, it is the best operationalized and the empirical model most generally
verified to elucidate the acceptance of technical structures [17], [23], [28], [29]. A September 2021 Web
of Science Index query returned 1,302 citations for the two introductory articles. A questionnaire was
designed based on the literature and subsequently sent to students to obtain an x-ray of the status and
challenges they face in the full adoption of e-learning. Specifically, the questions are about perceived
usefulness and perceived ease of use. The first section deals with the personal information of faculty
members that reflects their field and experience. The second section focuses on the level of use of e-
learning. Pilot-tested surveys were selectively distributed to students for a first opinion. The purpose
of the pilot testing of these surveys was double: to observe the reliability of the survey items and to
confirm that the respondents could easily comprehend the substances in the survey. Care has been
taken to safeguard that construction, linguistic and clearness are at a satisfactory level. These surveys
were disseminated directly to students at ten universities using a non-likely sampling approach. Data
were collected from these students, who remained all scholars, who came from diverse universities,
different academic years, men and women. The answers to the questions in the technology acceptance
model and the items in the subjective norm were recorded using a five-point Likert scale, analogous
to the original questions: 1 = ‘total disagreement’ to 5 = “total agreement”. The 36 items include
the perceptions and barriers to the availability of learning resources, material comprehension, learning
attitudes, ease of access, delivery methods, and interaction patterns. In this study, the perceptions
were obtained from the learning/experience they experienced, both in terms of models of interaction
with lecturers, interactions with other students, the availability of support facilities, including Internet
networks, and the availability of teaching materials in the e-learning system. In a structured way, this
perception implies indicators of perceived use and ease of use. This study used quantitative data
collection methods to empirically examine and highlight factors that had a greater influence on user
behavior. A nonprobable sample was adopted, which is commonly used in higher education [33]. The
study was used to target respondents who were teachers or students in universities and also used the
resources of e-learning systems offered by their universities. Data were collected using a survey, which
was conducted using the CAWI (computer-assisted web interview) technique. A link to the electronic
surveys was distributed to individual students from Romanian universities through the university’s
email system. These were distributed between January and February 2022. In total, 1875 completed
questionnaires were received. Structural Equation Modeling (SEM) was used to process the data from
the developed model. The use of SEM will deliver more precise estimations as it delivers a simultaneous
level of examination for both the structural model and the provided measurements. Moreover, SEM
offers a supplementary comprehensive method to test hypotheses around observed and latent variables.
SEM is the most common approach to measuring the level of acceptance of information technology by
users. E-learning learning in this study refers to the entire distance learning that uses the Internet and
hardware to provide subjects or materials from teachers to students. All interactions, both synchronous
and asynchronous, are performed through the media. More and more research is enjoying the TAM
model, which is widely used to predict the acceptance of any new technology. We used TAM for the
similar predictive validity that it showed in previous studies in a similar context. Our investigation
model is grounded on the study of variables that affect the acceptance of the e-learning system using



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the extended TAM model. The starting point of the research is the observation that e-learning has
become an essential part of education. We are primarily talking about companies that offer a wide
range of e-learning programs for their employees, for example, through newly established corporate
universities as well as universities that integrate new technologies into their teaching institutions.
At the same time, it should be noted that e-learning offers face acceptance problems much more
frequently than traditional face-to-face offers. The growing number of students who use e-learning
willingly face a large number of people who are critical and negative about multimedia courses. This
means that e-learning is facing the problem of being the fastest growing sector of technology-based
education, on the one hand, on the other hand, it can only partially reach its target group. This raises
the question of the factors that influence the acceptance of e-learning and what the consequences for
the successful implementation of e-learning. The characteristics of the sample show that 67.04% of
those sampled were from the category of undergraduate students, 32.64% master’s students, and a
percentage of 0.32% doctoral students. We also note that 58.99% of respondents fall into the age
category of 18-25 years and a percentage of 6.77% are over 45 years. All 1885 were students at a
public or private university. Exploratory investigations were carried out to inspect the validity of the
proposed variables and to contrast the preliminary reliability of the scales. Factor analysis to confirm
the magnitudes obtained in the investigative study and to permit the abolition of the established
scales. It also facilitates the confirmation of the psychometric properties of the factors that are part of
the model. Correspondingly, the causal investigation contrasts the planned structural relationships. A
first step before examining and testing the hypotheses was an investigative examination of the validity
and reliability of the variables. The validity of a element is the grade to which one element varies
from the other established elements. Validity can be measured by examining the main elements with
Kaiser Varimax rotation; see Table 1.

Table 1: Test KMO & Bartlett
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .946
Bartlett’s Test of Sphericity Approx. Chi-Square 15296.343

df 66
Sig. .000

As can be seen from the results obtained based on the Kaiser-Meyer-Olkin & Bartlett test, our
elements fall within the recommended range of 0.8 to 1, which indicates that the sampling is adequate.
Also, to test the reliability of the elements, we performed the reliability test, and the results confirm
this time that the sample is adequate.

Table 2: The reliability test
Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items

.923 .929 12

The factor load is practically the correlation coefficient for the variable and the factor. The factor
load illustrates the variance elucidated by the elements for that specific factor. In the structural
equations (SEM) method, as a general regulation, the factor load of 0.7 or higher value indicates that
the issue extracts a satisfactory variation from those elements. The outcomes we found are beyond 0.7
so we can consider them adequate. Composite reliability (sometimes called construction reliability)
is a measure of the interior constancy of measure elements, just like Cronbach’s alpha. It can be
considered equal to the total value of the variation of the real score in relation to the total variation
of the scale score, and the recommendation is that its value be greater than or equal to 0.7, and this
condition is met by the elements of our model. And last but not least for the variation test we chose
the average extracted variance (AVE), which is a value of the quantity of variance that is taken by
a hypothesis in link to the amount of variance due to dimension mistake and the optional values are
superior to or equivalent to 0.5 and this indicator being met. Thus, we can consider our elements
to be able to continue our analysis. Correlations superior to 0.3 remained statistically significant at
0.01. In our correlation matrix, most correlations among elements were significant at 0.01, with values
greater than or equivalent to 0.3. Completely, we complete an initial examination of the reliability of



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the dimension scale of our model using Cronbach’s alpha, the most widely used indicator for this type
of analysis. This coefficient covers values between 0 and 1. In our study, the Cronbach’s alpha for
each of the 12 variables is greater than or equal to the threshold of 0.7, above which the reliability is
considered acceptable. The Cronbach’s alpha coefficient with values above 0.900, which indicates that
the instrument can be considered reliable and consistent internal. Following the determination of the
reliability, correlations, and validation tests that showed that the elements are adequate, we proceeded
to the next step in which we analyzed the degree of fit and the adequacy of the model. The indices that
we used were: Chi square, for which a value less than 3 is considered a good match; GFI (good match)
ranges from 0 (bad match) to 1 (perfect match) recommend a value 0.8; AGFI (adjusted goodness-
matching), with an acceptable value greater than or equal to 0.8; NFI (standard match index) with
values between 0 and 1 but a value above 0.8 is recommended; The IFC (Comparative match index)
fluctuates between 0 and 1, and the RMSEA (root-average pattern error) matches well between 0.05
and 0.08 (. To determine the fit and suitability of the model, the analysis was performed using IBM
SPSS AMOS 26 Graphics. Following the analysis of the model fit indices, it is observed that it is
suitable, as shown in the table below:

Table 3: Model matching indices
Indicator Recommended Values Obtained Values
Chi square < 3.00 2.943

GFI > 0.90 0.911
AGFI > 0.80 0.848
NFI > 0.80 0.901
CFI > 0.90 0.934

RMSEA < 0.10 0.061

As noted in all preliminary tests or within an appropriate and acceptable range, we moved on to
the last stage in which we analyzed the estimates based on path analysis (path coefficient) to validate
or reject the assumptions made earlier. The results of the analysis are presented in the table below.
As can be seen from the 21 hypotheses, 5 were rejected due to a higher value of P of 0.001 which
indicates that there is no influence between variables or that the influence is insignificant.

Table 4: Hypothesis Validation
Path coefficient P Validation

Ability to use → Perceived ease of use .391 *** Accepted
Course content and design → Perceived ease of use .262 *** Accepted

Instructor contribution → Perceived ease of use .051 *** Accepted
Previous experience in E-learning → Perceived ease of use .022 .025 Rejected

The quality of the E-learning system → The perceived ease of use .089 *** Accepted
Ability to use → Perceived utility .075 *** Accepted

Course content and design → Perceived utility .499 *** Accepted
Instructor contribution → Perceived utility .003 .851 Rejected

Previous experience in E-learning → Perceived utility .029 .003 Rejected
E-learning system quality → Perceived utility .011 .487 Rejected

Perceived ease of use → Perceived utility .377 *** Accepted
Perceived utility → Satisfaction and personal development .679 *** Accepted

Perceived utility → Attitude towards the use .493 *** Accepted
Perceived ease of use → Satisfaction and personal development .199 *** Accepted

Perceived ease of use → Attitude towards the use .304 *** Accepted
Perceived utility → Behavioral intent to use .248 *** Accepted

Perceived ease of use → Behavioral intent to use .022 .305 Rejected
Satisfaction and personal development � Behavioral intention to use .498 *** Accepted

Attitude towards use → Behavioral intention to use .264 *** Accepted
Behavioral intent to use → Actual use .268 *** Accepted

Behavioral intent to use → Academic performance .497 *** Accepted

However, the results of this investigation show that the less central elements that determine the use
of e-learning resources by students in academies are the ability of students, course content, satisfaction
and personal development and attitude toward the use. While elements such as the contributions of
the instructors, the content of the course, and the design are shown to most influence the behavior of



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students in the use of e-learning resources in Romanian universities. More research is needed on the
use of e-learning resources. This can be attributed to the continuous and fast growth of technology
requirement and the unremitting expansions in the domain of education. In the present situation, the
supplementary issues included in the model are supported using TAM. Furthermore, this investigation
can be measured as added value to the present literature in the field by examining the elements that
additional have an impact the use of e-learning resources by instructors-students, who are offered by
their academies to expand their education developments at anytime and anywhere. Based on the
outcomes of the study, a deeper understanding of outside elements between instructors and students
was enabled, in addition to offering evidence for academic managers, designers, system developers,
and related professionals. Although technology is used to an effective grade in Romania and its higher
education institutions, more devotion needs to be rewarded to the issues that production a pertinent
role in helping the use of e-learning systems by students to supplementary improve their performance
and effectiveness among students and instructors correspondingly to accomplish sustainability pur-
poses. It can be noted that the results of the examination provide a deeper understanding of the
field and important elements that encourage the use of learning resources by instructors-students in
Romanian academies.

5 Conclusion
As technology advances at a rapid pace, further progress will be made in the field of e-learning, but

it is important to remember that e-learning also has limitations. On the one hand, one has to judge
an e-learning environment according to its didactic concept and certainly not only according to its
technical feasibility, which depends on the creators of the respective programs. In addition, the learner
is still usually the same person as in classical learning methods. When there is a lack of motivation,
interest, or desire to make an effort, e-learning will not be able to work wonders. Furthermore, the
constant flexibility and availability of learning programs tempt people to put in additional learning
effort and possibly overwhelm them. The study succeeded in showing that the acceptance of e-
learning can be explained as a function of personal determinants (e-learning). This finding now allows
the development of promising intervention measures for e-learning. If it is possible to influence one
or more predictors, then acceptance will change as well. What implications can be derived from this
research for future research? First of all, this paper is the first careful examination of the subject of
accepting e-learning in Romanian universities. By approaching the technology acceptance model, new
perspectives can be derived for the field of research acceptance of e-learning. Therefore, the article
should be understood as a starting point for future research. The acceptance investigation of e-learning
was conducted in the context of this research using two systems. On the one hand, technology that
supports e-learning has been analyzed from the perspective of students. A conscious decision has
been made not to further differentiate the type of use of e-learning, for example, on different types of
platforms or software used. Therefore, the way in which the respondents use the system in detail and
to what extent the different types of use influence the acceptance of e-learning remain unanswered.
As a result, the purpose of further investigation is to conduct a more detailed analysis of the different
types of e-learning used.

Author contributions

The authors contributed equally to this work.

Conflict of interest

The authors declare no conflict of interest.

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Cite this paper as:

T.O. Breaz, M.T. Fülöp, L.I. Cioca (2022). The role of E-Learning generated by the COVID-19
epidemic in higher education, International Journal of Computers Communications & Control, 17(5),
4854, 2022.

https://doi.org/10.15837/ijccc.2022.5.4854


	Introduction
	Digitalization in the university environment
	Accepting technology in the university environment
	Research framework and results 
	Conclusion