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ORIGINAL RESEARCH article

Front. Public Health, 27 July 2022
Sec. Public Mental Health
This article is part of the Research Topic Consumer Mental Health and Wellbeing: Socially Responsible Consumption Patterns View all 10 articles

The role of universities' sustainability, teachers' wellbeing, and attitudes toward e-learning during COVID-19

\nMelinda Timea Fülp
Melinda Timea Fülöp1*Teodora Odett Breaz,Teodora Odett Breaz2,3Xiaofei HeXiaofei He4Constantin Aurelian Ionescu,Constantin Aurelian Ionescu5,6George Silviu CordoGeorge Silviu Cordoş7Sorina Geanina StanescuSorina Geanina Stanescu5
  • 1Faculty of Economics and Business Administration, Babeş-Bolyai University, Cluj Napoca, Romania
  • 2Faculty of Economic Sciences, 1 Decembrie 1918 University, Alba Iulia, Romania
  • 3Lucian Blaga University, Sibiu, Romania
  • 4Hangzhou College of Commerce, Zhejiang Gongshang University, Hangzhou, China
  • 5Institute of Multidisciplinary Research for Science and Technology, Valahia University of Targoviste, Targoviste, Romania
  • 6Faculty of Economics, Hyperion University Bucharest, Bucharest, Romania
  • 7Transylvania Business School, Babeş-Bolyai University, Cluj Napoca, Romania

In recent years, universities worldwide have experienced rapid changes with an immense impact, which have been influenced by technological progress and the social trends of digitalization. Like all other revolutionary changes, digital transformation involves intense adjustment/readjustment. University sustainability must be the active concern of all higher education institutions. Thus, the present research aims to analyse teachers' acceptance of new technologies and the impact on their wellbeing and university sustainability. The main objective was to analyse the acceptance of technology in special the e-learning opportunities and the wellbeing of teacher in an emergent country like Romania. To achieve our goal, we created a questionnaire based on the literature, and with the help of the technology acceptance model, we tested our hypotheses. The results indicate several discontents on the part of teachers concerning adapting to new technologies and even a personal discomfort in adapting to these new technologies. Thus, we can note that wellbeing significantly influences job satisfaction and teachers' involvement in sustainable development.

Introduction

Today's working world has become very complex in many areas: processes are becoming more concentrated and often make it difficult for us to “switch off” in the truest sense of the word, with consequences for our wellbeing. Changing the world may be difficult, but individuals can do something for themselves and their mental health.

The concept of sustainability is more present than ever in our society and not just because of the growing presence of the Fridays for Future movement. Originally initiated by schoolchildren, the almost weekly demonstrations have also gained popularity among the general public. Due to the recent heated debate on climate change, many other sustainability issues have arisen in society and politics, which are also widely discussed. Society increasingly demands that companies take responsibility in this area (1).

However, not only do consumer goods manufacturers need to answer their customers' questions about sustainability, but service providers are also being monitored more and more closely. Sustainable corporate management is becoming increasingly important, and the relevance of corporate social responsibility is growing. This shift does not stop at educational institutions. Within universities, the theme of sustainability can be divided into two main aspects, namely, the educational mission of the university, and the institution itself, through its actions. As a knowledge broker, the company also expects a specific commitment to sustainability and, in general, environmentally conscious behavior from an educational institution. Universities fulfill a particular function as a model in the content it delivers. Nevertheless, in addition to social assessment, it is beneficial to consider and include sustainable issues in the management of a university. On the one hand, the economical use of resources can lead to cost advantages; on the other hand, a sustainably managed university operation can improve the university's reputation.

Sustainability can be exanimated with a macro method connected to the general economic structure, and a micro method, placing the examination on precise personnel. With regards to a commercial level, corporate sustainability can be definite as consulting the requests of a company's direct and indirect investors, not containing its aptitude to reply to the requirements of forthcoming investors (26). Corporate sustainability can be articulated in diverse ways, as businesses must produce and preserve the interrelated economic, social, and environmental resources, particularly if sustainability is anticipated in the long run (7, 8). In addition, Corporate Social Responsibility (CSR) has established important consideration in academic and professional discussions: scientists consider that businesses should recover the social and environmental effects of their activities, but their efforts would be directly related to the commercial approach of a business (9, 10).

We believe this paper contributes to the literature in being a good guide in accepting new technologies in academia, at least for the following reasons. First, this paper analyses the literature on sustainability and digitalisation in the university field. The novelty brought by the research aims at the impact of this process in the Romanian academic environment. So far, various studies have been carried out on the model of accepting technology in the university environment in different countries. However, we have not found such a study for Romania, so we deemed it worthwhile to analyse the situation in an emerging country like Romania. To achieve the objectives, we started with the literature analysis, followed by the presentation of the fundamental theories on education in the context of e-learning and the acceptance of technology. The theoretical component is followed by a practical part in which we present our study's results based on the technology acceptance model. We end the paper with a series of conclusions and research perspectives.

Analysis of literature on the role of sustainability in the university environment

Research on education for sustainable development in current research is grounded on the tradition of broader investigation with regards to curriculum modification. In the last decade, there have been an increasing number of papers on curriculum modification procedures in universities for sustainable change (1113).

“Keyword analysis on e-learning” (see Figure 1) showed a more detailed and interconnected model between the impact of the pandemic, digitisation, and e-learning. Therefore, it is clear that the pandemic significantly impacted the digitisation and transition to an e-learning type of learning.

FIGURE 1
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Figure 1. Academic e-learning cluster.

The green cluster aims at the effect of the pandemic on higher education, directly connected to the part of e-learning represented by the purple cluster. The red cluster represents digitisation and the digitisation process in the university environment.

E-learning and blended learning are essential elements of contemporary university teaching. The study models offered are as diverse as the students. With the help of innovative teaching concepts, students' learning styles can be more easily approached on the one hand, and on the other hand, we can discuss the different learning materials. Universities worldwide support students and faculty in creating and using digital courses, especially during this pandemic (14, 15).

The digitisation of higher education has recently gained widespread momentum. Although e-learning elements have been introduced since early 1990 s, there is a discussion regarding virtual universities and online studies. In addition, workshops were organized to address new media challenges (16).

In this situation, existing university e-learning strategies are checked for compatibility with current strategic guidelines. At the same time, the development of a comprehensive digitisation strategy that complements or replaces an e-learning strategy is often discussed. After a series of failures at the beginning of the millennium, awareness prevailed that e-learning in universities should not only be used as product innovation in teaching, but as a process innovation in the organization of the university. Therefore, for a long-term anchoring of e-learning, it seemed necessary not only conceiving educational media concepts, but also viable strategic guidelines for university management, developed as much as possible in a participatory process (16, 17).

Particular attention is paid in the literature to e-learning strategies and a digitisation strategy that goes beyond teaching and study. We elaborated on the advantages and disadvantages of focusing on digitalisation and sustainability of higher education with the help of the following dimensions: organization, economy, culture, and the process of change/leadership.

In a nutshell, the following conclusions can be drawn for keyword analysis. First, it was noticed that there were differences depending on terminology, referred to the aggregation level and the focal points in the content. On the other hand, the topics and considerations at the university level were found in all terms. Especially at the individual level, the ability to transfer, get involved and the competence in sustainability related to the topic of education. The different terms have all been viewed in the context of sustainable development and digitisation. They have shown intersections in R&D, technology, and information management, especially during the pandemic. On closer inspection of the implications of the pandemic, we can see a close link between digitisation and the sustainability of universities.

From fundamental theories of learning to didactics in the e-learning context

Behaviorism, cognitivism, and (socio-) constructivism have developed before the digital age (18, 19). Can these “pre-digital” learning theories describe or shape learning in the digital age? (20). If one asks the Canadian media education specialist Siemens, the answer is clearly “No!” George Siemens does not leave “no,” but with “connectivism,” he offers a model that claims to be a theory of learning for the digital age. Siemens' initial view is that the learning opportunities resulting from the Internet cannot be processed by the “classical theories of learning,” such as behaviorism, cognitivism, and (socio-) constructivism. Therefore, it is essential to express a theory of learning for the digital age: Behaviorism, cognitivism and constructivism are the three general theories of learning, most often used in creating learning environments (2123).

Reversed classroom approaches also provide virtual knowledge transfer, for example, video lectures to prepare or Blogs, wikis and social networks allow for social and collaborative learning. Blended learning, on the other hand, is based on integrating digital content into face-to-face formats, i.e., a link between the online and offline phases (24, 25). This accomplishes a variety of classroom methods—and electronic tools complement the social aspect of personal communication. Optional, selective enrichment of classroom teaching, for example, through a PowerPoint presentation, must be distinguished from this. Electronic assessments and exams are available for preparing digital exams with fast feedback and actual exams and assessments. Pioneering projects promise the use of artificial intelligence (AI), augmented reality (AR) and the integration of playful elements (gamification) or 360-degree videos.

Vocabulary learning, conversation exercises, exam preparation, technical discussions, or direct access to materials: Digital learning opportunities, also known as “Using Information and Communication Technology (ICT) to Learn,” are used as a variety of learning tools. They contrast with the “learning to use ICT” approach, in which digital media manipulation is learned as an end in itself, for example, using an Office program. Stationary computers or mobile devices, which can be used in many different ways, are indispensable for digital learning (26, 27).

A look at teaching practice shows that many formats and forms of application of digital higher education that can be found in universities. Online courses largely complement the classic face-to-face teaching. For example, students prepare for video seminars, complete self-learning programs during the event, or create group presentations using digital media. In addition, the university promotes a full range of blended learning formats, meaning that teaching and learning videos, virtual labs and interactive learning platforms are part of students' daily lives.

The didactic problem is also closely related to the reflections on the learning theory. In other words, reflections on the theory of learning make it possible to lay the foundations of didactics. In principle, teaching can be defined as a method. As a method, didactics can be understood as a regulated procedure for developing teaching/learning scenarios and as a moderation strategy in teaching/learning contexts (28). Didactics as a method is preceded by “methodology” or reflection: what is teaching and learning and how and why teaching and learning should take place.

Learning theories can be understood as teaching methodology. By linking didactics to learning theory, it is possible to provide a scientific basis for teaching models.

Integrating new media into teaching takes advantage of the almost explosive increase in internet users among students. The flexibility of studies with the help of new media has a possible added value for these groups more than their conventional counterparts. However, this can only work if target groups also have adequate access to e-learning opportunities.

As a rule, first-year students already have several previous experiences with new media. The individual acquisition of new media in adolescence is more leisure-oriented and hedonistic. Computers and the Internet are used primarily to provide entertainment (music, movies, games), get information about leisure activities, and communicate with other young people. They are primarily more straightforward instrumental skills in dealing with standard applications that are acquired in the context of media socialization.

However, the ability to reflect on the media and it usage, and creative-active usage is less pronounced. Thanks to previous experience, most students quickly find their way into campus information systems and learning platforms. When it comes to downloading course materials or e-mail communication, most students have no problems—especially if the browser or the e-mail is familiar.

In addition to this knowledge and skills, motivational requirements are also necessary. As has been repeatedly shown in various studies, the increased use of new media is accompanied by expectations. Students expect their teachers to be available by e-mail or instant messaging chat and support courses with electronic materials.

Integrating new media into teaching is already based on the individual requirements of students. However, it also creates new situations where one can practice dealing with new environments and learn new applications. Therefore, the use of new media in the context of teaching is in no way reduced to the role of mediator. On the contrary, the fact that the use of new media in teaching and learning contexts interacts with the aims, content and methods is always emphasized by media didactics (2931).

The main frame of reference for integrative media teaching is all the communication contexts. Communication using new media—inside and outside the courses—is part of this practice (32). Using the media is not an end, but its use is very context-dependent. Before students can access e-learning offerings, they must first learn how to operate the learning management system. What is this benefit, mainly if two or three learning platforms are used in a course? However, if students of educational sciences already use a learning management system during their studies, e.g., Moodle, which they will use later on, it can be an advantage for them. For the innovation process to be put into practice in the long term, obstacles to applying new teaching and learning scenarios must be removed.

Therefore, at this time, in the field of teachers' training, there is a plea for media priority and media scenarios that can be used in pedagogical areas of action. The consequences of integrative media teaching on a university's media development plan are obvious. Different areas of competence are already relevant throughout the study. Based on students' future action areas, other computer-supported communication and interaction processes are given prominence in educational studies (33, 34).

The role and impact of accepting technology on wellbeing

“Acceptance” explains a behavior or attitude depending on an acceptance object. As an object of acceptance, it means technical, organizational, institutional, and social changes or innovation. In this sense, acceptance is the appropriation of something offered, available, or suggested. The different types of use require the definition of the concept of acceptance for the specific used field, so we intend to define and present an empirical study on the acceptance of technology, more precisely, the acceptance of the e-learning system (35).

The first debates on the concept of acceptance took place in the mid-1970 s. They followed the social discussion about the innovative communication technologies used to permanently change the organizational processes in companies. At the time, acceptance research was less interested in the social consequences of these new technologies. Instead, it was primarily concerned with business issues, including sales market screening, economic risk assessment, or potential analysis to prevent poor investment (36). It was not until the late 1970 s and early 1980 s that research focused on economic and social acceptance issues due to the accelerated development of technical devices and their rapid penetration into almost every area of life. This period can be described as an era characterized by an increase in technology that also affected private households (37, 38).

A significant incentive for the genesis of acceptance research based on social sciences came from the assumption of a model of the hostile attitude of the population toward new technologies. This debate has been stimulated by public opinion polls with partially unconfirmed findings, either because of a supposedly declining number of students interested in technical fields of study or because of the critical opinion of the population on the expansion of nuclear technology. However, the differentiated climate of opinion in the context of public controversies about old and new technologies has been misinterpreted as a measure of a negative attitude of the population toward new technical innovations. As a result, the description of the situation by the various stakeholders turned into a new statement in which different approaches found traction simultaneously, which is understood by difficulties of acceptance and what possibilities exist to solve them (39, 40).

However, the concept of acceptance should not be equated exclusively with the acceptance of technology. Although most publications are technology-related, the construct is discussed in almost all research areas. This broad, multidisciplinary interest in issues related to acceptance, even if not related to technology, is mainly due to the discussion on the general phenomena of social acceptance.

Acceptance is not a term derived from science but a term of everyday language. The word is used primarily in social discourse by politicians, economists, and advertisers in the form of acceptance predictions and has made an actual career use in this form. Since the 1980 s, the term has become a buzzword for advertising and the linguistic repertoire of various stakeholders.

A presentation of the definitive use of acceptance in the context of scientific questions leads to the realization that there is no uniform definition of the term here either. At the beginning of the research effort, acceptance was primarily understood as an attitude that applied to certain forms of opinion and behavior and was mixed with terms such as attitude, acceptability, or adoption. For example, Alexandre et al. understand acceptance as “an attitude of larger social groups toward individual technologies that can be determined at a certain point in time and is expressed in certain forms of opinion and behavior” (41). Similarly, but in more detail, Hilbig defines acceptance as “a more or less affirmative attitude of an individual or group toward an object, subject, or other matter” (42).

Consequently, Anstadt et al. define acceptance as an expression of a user's positive attitude toward technology, expressed in the desire to implement and use it in a specific situation (43). According to Gunasinghe et al. acceptance “contradicts the rejection term and describes the positive acceptance of an innovation by the user” (44). The use of innovation can take place on several levels of acceptance (levels of use). For example, a purely passive use would indicate a relatively low level of acceptance. In contrast, a high level of use can be depicted if a user uses innovation in various ways, i.e., beyond the expected use.

For this study, a specific definition of acceptance reflects current research findings on acceptance.

Moreover, to be happy, we must feel good about our everyday work. Above all, due to the restrictions of the pandemic and changed conditions in the home office, wellbeing is becoming increasingly important (45). When we are overly stressed, alarm bells go off in the body, and we feel unfocused and exhausted. To get out of this hamster wheel, we must care for ourselves and our bodies (46). We are aware that we perform better and feel better when we are balanced, but are companies mindful of their duty to support employees to feel good?

Today's working world is changing swiftly, and the demands on employees and managers are increasing—directly affecting wellbeing and health. Stress, the ever-increasing flood of information and work intensification quickly leads to a lack of productivity, loss of concentration and health-related days off, if there is no prevention (47, 48).

Digital technologies are increasingly penetrating our daily routines, transforming how we work, spend our free time, and interact with each other. However, while supporters of spreading these technologies expect positive effects for individuals and society, opponents fear risks such as information overload, dependencies, and loss of privacy. Given these controversies, our goal is to explore the long-term individual and societal consequences of using digital technologies (49).

In the literature, there is debate on whether digitisation's effects on individuals' lives should be assessed as predominantly positive or negative. However, with a view to future business areas, it is essential to remember that it will continue to be about fulfilling people's basic psychological needs, both online and offline. Digital tools can help meet needs in new ways, but they must be designed to do that. A fully digital approach cannot make something successful or suitable for people (50).

While e-learning has many benefits, it also comes with some challenges. Some of these challenges can even affect our wellbeing. The e-learning environment offers many advantages, such as ease of use, flexibility, and accessibility. However, while online learning offers many benefits, it also comes with challenges. These challenges can affect our wellbeing (51). The WHO defines wellbeing as a “state of complete physical, mental and social wellbeing and not merely the absence of disease or infirmity.” The top three challenges affecting learning progress and wellbeing during the e-learning process are: isolation, computer skills and setting priorities (5256).

Isolation: While self-paced learning has significant benefits, the online environment can often feel lonely. The feeling of community, in an online context, is a complicated subject, especially when completing tasks and working through modules alone. While the traditional classroom offers face-to-face encounters, conversation, and socializing opportunities, we know these types of connections are rare or impossible online (52, 55).

Computer skills: With rapidly changing technologies, it can be challenging to keep up with the latest computer functions and features, especially for online platforms, as new software and other media are constantly coming onto the market. The flood of new technologies and the steep learning curves can affect our wellbeing. One may feel overwhelmed by the sheer volume of new information and skills needed to process the provided information (53, 54).

Setting priorities: Online learners are usually not just learners. It can be challenging to prioritize deadlines, assignments, and examinations, especially when everything is necessary and simultaneous. Effective time management is the best way to solve this problem (56).

It is essential to realize that we must take care of our wellbeing amid chaos. Even if it takes longer to reach our goals, it is not worth sacrificing our wellbeing.

Research methodology

A questionnaire was designed based on the literature and subsequently sent to teachers to obtain an x-ray of the status and challenges they face in adopting e-learning (Table 1).

TABLE 1
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Table 1. Items selection based on the literature.

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 e-learning levels of use.

The 36 items include respondents' perceptions and barriers to learning resource availability, material comprehension, learning attitudes, ease of access, delivery methods, and interaction patterns. In this study, respondents' perceptions were obtained from the learning they experienced 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. The answers to the questions on the technology acceptance model and the items of the subjective norm were recorded using a five-point Likert scale, corresponding to the original questions: 1 = “total disagreement” to 5 = “total agreement”.

Based on the technology acceptance model by Davis (101), we propose the following model and hypothesis to be tested (Figure 2).

FIGURE 2
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Figure 2. Hypothesis development.

The data was collected using a survey conducted using the CAWI (Computer Assisted Web Interview) technique. A link to the electronic questionnaires was distributed to teachers and individual students at Romanian universities through the university's e-mail system. These were distributed between January and February 2022. A total of 243 completed questionnaires were received from teachers.

Results and discussion

Below we present the results obtained on the 12 elements and the 36 related items to have an x-ray on teachers' perceptions regarding the acceptance and use of the e-learning system.

Skills development is increasingly recognized as an essential condition for the sustainable anchoring of new forms of learning and media in the university. It initially refers to teachers' knowledge, skills and attitudes toward the development, introduction, and use of innovative forms of e-learning in teaching. In addition, skills development also includes an institutional level; it also affects the ability of an organization to provide specific quality services. For this reason, many universities can increase efforts to motivate teachers to innovate in e-learning and reorganize or set up processes and structures of support facilities to build this competence at the individual and organizational levels. Computer skills are only a tiny part of “e-learning skills.” The demographical characteristics of the sample are presented in Table 2.

TABLE 2
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Table 2. Demographic results regarding the teachers involved in the study.

As in the case of the first and second models, we started with verifying and validating the data. Therefore, the first test applied was the validity test which indicates a value of 0.915 with a sig. 0.000, indicating that the sample is adequate (Table 3).

TABLE 3
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Table 3. KMO & bartlett test.

For better assurance of the suitability of the sample, we have resorted to an additional reliability test which also indicates that the sample is adequate with a Cronbach's value larger than 0.9, which indicates that the sample is, again, adequate (Table 4).

TABLE 4
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Table 4. Reliability test.

In order to highlight detail on factors related to each element, an analysis of the factor load was performed; respectively, we analyzed the elements' reliability, as see Table 5. All the values fall within the recommended range.

TABLE 5
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Table 5. Factor load and item reliability.

The correlation matrix of the data set is shown in Table 6. Correlations larger than 0.3 were statistically significant at 0.01.

TABLE 6
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Table 6. The correlation matrix.

Finally, we present the reliability results based on the Cronbach's index, for which a value larger than 0.7 is recommended to be considered adequate. In our case, all values are above 0.9 (Table 7).

TABLE 7
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Table 7. Reliability of elements based on Cronbach's alpha.

In order 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 Table 8.

TABLE 8
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Table 8. Fit indices.

It was necessary to perform preliminary tests to ensure that the elements used in the model are validated and reliable and meet the matching criteria to validate the formulated hypotheses. Thus, in Table 9, we present the results of the estimates based on the path analysis (Path coefficient) to validate or reject the previously formulated hypotheses. Ten of 21 hypotheses were rejected due to a higher value for P of 0.001, indicating no or insignificant influence between variables (Table 9).

TABLE 9
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Table 9. Results of the study.

As it results from validating the assumptions from the external factors, the content and design of the elective course and the use skills are validated. The use of skills by teachers is a vital percentage when it comes to e-learning. It is also imperative to think about personal wellbeing when it comes to personal skills, as it can significantly contribute to how knowledge is transferred. A vital issue during the pandemic also affected self-control; if we thought we were isolated, we would face developed IT knowledge. Acquiring technical skills and teaching skills at the same time has been a challenge for many teachers. However, it is a necessary process, due to the complexity and multifaceted nature of e-learning. The study results show that teachers do not consider having acquired practical teaching skills and methodology during the pandemic. On the other hand, this knowledge gained in the approach to e-learning has been exchanged and deepened, especially between specialist colleagues and teachers. Our results align with other field results (6567, 79).

It becomes clear that the lecturer who teaches is the most crucial factor in learning success. We note that the teachers consider that they are ready for the e-learning system, respectively, and the organization they belong to provides them with the necessary resources to access the e-learning system. Teachers who have had little previous experience with new electronic technologies have reported more often than they have had initial difficulties, and that they are overwhelmed and stressed. As a consequence, they are particularly reluctant to get involved in new media. Teachers face the challenge of rethinking these processes and critically evaluating their practical implementation.

The perceived usefulness of the information system depends on the results produced by the information system. The introduction of digitized teaching is greatly facilitated by students convinced of the benefits. Ease of use also plays a vital role in accepting the e-learning offer. It becomes clear that competencies can only be defined if there is a target framework in the university that names the scenarios intended to be implemented.

The specific benefits of using e-learning could not consistently be implemented to the satisfaction of teachers. As a result, it is often pointed out that using the platform is not always appropriate and, in some cases, it is rejected.

This study investigated the e-learning acceptance and wellbeing of teachers, especially during COVID-19, as a substitute for the traditional form of teaching in classrooms in Romania. Although there are any studies investigating students' perceptions regarding technology acceptance in the literature (5761, 6373), rarely any research scrutinized the teachers' perception regarding eLearning, particularly for Romania we don't find any research that study the acceptance theology model, so we consider it interesting to investigate the reactions and wellbeing of teachers in this difficulty period in that teacher don't have the possibility to teach in classroom, the only solution was to adopt e-learning. However, the weak e-learning system in Romania is a significant obstacle to keep pace with the growing educational challenges. So it was a challenge to manage a good strategy and infrastructure to continue education activities even during the crisis and in the future to establish a good and sustainable teaching and to archive the wellbeing of the teachers and students.

When discussing higher education, e-learning is regularly seen as an engine of potential change. Teachers are a vital factor when it comes to university performance and sustainability. They can be seen as guardians; however, it depends on whether e-learning is used successfully. It is difficult to accept that the classroom is being somewhat replaced with a virtual environment, but to remain competitive, it is necessary to adapt to a hybrid version.

Conclusions

Universities' teaching and learning processes are constantly changing due to evaluation and continuous further development. This change can be triggered by strategic decisions within a university or due to external disruption. The sudden switch to distance learning caused by COVID-19 presented teachers and learners with new challenges.

In the discussion of higher education, e-learning is regularly seen as an instrument for changes in higher education. Competence development is increasingly recognized as an essential condition for the sustainable anchoring of new learning forms and media in the university, initially referring to the teachers' knowledge, skills, and attitudes on introducing, developing, and applying innovative forms of e-learning.

In addition, competence development also includes an institutional level; it also affects the ability of an organization to provide certain services.

There is pressure on institutions to use digital media with the aim of being able to keep up nationally and internationally. As already discussed, there is a lack of strategy for sensibly designing the digitisation of teaching and integrating it into the curriculum accordingly. The university management and the departments should consider and implement these aspects. The focus is often on the necessary technology to be acquired and used.

Today, thanks to the never-ending stream of data on the Internet, more and more people can acquire knowledge, not only in western industrial nations but also in the Third World. Moreover, educational platforms such as Wikipedia bring concise summaries of information prepared so everyone can understand. As a result, even people who do not have the opportunity for an academic education can expand their general knowledge through established information sites on the Internet. In recent years, universities and educational institutions have also increasingly put scientific study results, academic publications, and library databases online access to the public.

Wellbeing can be defined as an individual or collective state or procedure of experiencing oneself and others and conforming to the life conditions as favorable. However, wellbeing is understood and respected differently depending on the scientific context in which it is used.

Wellbeing is sometimes also equated with positive and negative affective components, with happiness, life satisfaction, quality of life, wellness, and the negation of illness, anomie, or health.

Subjective wellbeing is the result of comparisons. These relate to judgments of the extent to which needs, standards of value, and attitudes have been adequately met. Objective wellbeing describes the living conditions necessary for the personal form. As a rule, a society's economic, ecological, and human capital is surveyed, i.e., its structural and security-providing possibilities to individually and collectively create the prerequisites for subjective wellbeing.

Digital forms of learning can also have an economic side, especially when online courses become fee-based. Nevertheless, industrial companies and representatives from universities and politics are promoting the digitisation of teaching, which often refers to further education and less to the undergraduate bachelor's degree.

The main limitation of our paper is that used data obtained by the sampling, maybe we can extend our research to greater number of respondents to have a better understanding of what is happening in the universities and how the teacher find the challenge about the e-learning and how they fell in this period of sanitary crises. Thus, we recommend more studies concerning technology acceptance for education purposes in Romania to cope with existing challenges regarding e-learning adoption.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

GC and MF: conceptualization. TB: methodology and funding acquisition. MF: software and data curation. XH: validation and visualization. SS: investigation. GC: resources. GC and TB: writing—original draft preparation. CI and MF: writing—review and editing and supervision. CI: project administration. All authors critically revised the manuscript and gave their final approval of the manuscript submitted for publication.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

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References

1. Reyes-Carrasco PM, Barrón Á, Heras Hernández F. Education for sustainable development and climate change: pedagogical study of the social movement fridays for future salamanca. In: Eighth International Conference on Technological Ecosystems for Enhancing Multiculturality, (Salamanca), (2020). p. 1031–6.

Google Scholar

2. Dyllick T, Hockerts K. Beyond the business case for corporate sustainability. Busin Strat Environ. (2002) 11:130–41. doi: 10.1002/bse.323

CrossRef Full Text | Google Scholar

3. Porter ME, Kramer MR. The link between competitive advantage and corporate social responsibility. Harv Busin Rev. (2006) 84:78–92. doi: 10.3389/fpsyg.2021.709678

PubMed Abstract | CrossRef Full Text | Google Scholar

4. Alshehhi A, Nobanee H, Khare N. The impact of sustainability practices on corporate financial performance: literature trends and future research potential. Sustainability. (2018) 10:494. doi: 10.3390/su10020494

CrossRef Full Text | Google Scholar

5. Drempetic S, Klein C, Zwergel B. The influence of firm size on the ESG score: corporate sustainability ratings under review. J Busin Ethics. (2020) 167:333–60. doi: 10.1007/s10551-019-04164-1

CrossRef Full Text | Google Scholar

6. Hermundsdottir F, Aspelund A. Sustainability innovations and firm competitiveness: a review. J Clean Prod. (2021) 280:124715. doi: 10.1016/j.jclepro.2020.124715

CrossRef Full Text | Google Scholar

7. Elkington J. Partnerships from cannibals with forks: the triple bottom line of 21st-century business. Environ Qual Manag. (1998) 8:37–51. doi: 10.1002/tqem.3310080106

CrossRef Full Text | Google Scholar

8. Landrum NE, Ohsowski B. Identifying worldviews on corporate sustainability: a content analysis of corporate sustainability reports. Busin Strat Environ. (2018) 27:128–51. doi: 10.1002/bse.1989

CrossRef Full Text | Google Scholar

9. Almagtome A, Khaghaany M, Önce S. Corporate governance quality, stakeholders' pressure, and sustainable development: an integrated approach. Int J Mathem Eng Manag Sci. (2020) 5:1077–90. doi: 10.33889/IJMEMS.2020.5.6.082

CrossRef Full Text | Google Scholar

10. Mubeen R, Han D, Abbas J, Álvarez-Otero S, Sial MS. The relationship between CEO duality and business firms' performance: the moderating role of firm size and corporate social responsibility. Front Psychol. (2021) 12:669715. doi: 10.3389/fpsyg.2021.669715

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Dmochowski JE, Garofalo D, Fisher S, Greene A, Gambogi D. Integrating sustainability across the university curriculum. Int J Sust Higher Educ. (2016) 17:652–70. doi: 10.1108/IJSHE-10-2014-0154

CrossRef Full Text | Google Scholar

12. Smigic N, Lazarov T, Djekic I. Does the university curriculum impact the level of students' food safety knowledge? Brit Food J. (2021) 123:563–76. doi: 10.1108/BFJ-06-2020-0485

PubMed Abstract | CrossRef Full Text | Google Scholar

13. Tasdemir C, Gazo R. Integrating sustainability into higher education curriculum through a transdisciplinary perspective. J Clean Prod. (2020) 265:121759. doi: 10.1016/j.jclepro.2020.121759

CrossRef Full Text | Google Scholar

14. Nortvig AM, Petersen AK, Balle SH. A literature review of the factors influencing e-learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electr J E-learn. (2018) 16:46–55. https://academic-publishing.org/index.php/ejel/article/view/1855

Google Scholar

15. Zhang Y, Ghandour A, Shestak V. Using learning analytics to predict students performance in moodle LMS. Int J Emerg Technol Learn. (2020) 15:102–15. doi: 10.3991/ijet.v15i20.15915

CrossRef Full Text | Google Scholar

16. Emily NG. Successful implementation of e-learning in self-financed higher education: experience from Hong Kong. J Educ Technol Online Learn. (2020) 3:91–107. doi: 10.31681/jetol.655496

CrossRef Full Text | Google Scholar

17. Meskhi B, Ponomareva S, Ugnich E. e-learning in higher inclusive education: needs, opportunities and limitations. Int J Educ Manag. (2019) 33:424–37. doi: 10.1108/IJEM-09-2018-0282

CrossRef Full Text | Google Scholar

18. Howell AJ. Flourishing: achievement-related correlates of students' well-being. J Posit Psychol. (2009) 4:1–13. doi: 10.1080/17439760802043459

CrossRef Full Text | Google Scholar

19. Ryan RM, Deci EL, Vansteenkiste M. Autonomy and autonomy disturbances in self-development and psychopathology: research on motivation, attachment, and clinical process. Dev Psychopathol. (2016) 1:385–438. doi: 10.1002/9781119125556.devpsy109

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Talja S, Lloyd A. Integrating theories of learning, literacies information practices. In: Lloyd A, Talja S, editors. Practising Information Literacy: Bringing Theories of Learning, Practice and Information Literacy Together. 1 ed. New South Wales: Centre for Information Studies. (2010). p. 9–18.

Google Scholar

21. Siemens G. Conectivismo: Una teoría de aprendizaje para la era digital. Recuperado el, 15. Colombia (2004). Available online at: https://skat.ihmc.us/rid=1J134XMRS-1ZNMYT4-13CN/George%20Siemens%20-%20Conectivismo-una%20teor%C3%ADa%20de%20aprendizaje%20para%20la%20era%20digital.pdf

Google Scholar

22. Gorospe JMC, Olaskoaga LF, Barragán AGC, Iglesias DL, Agirre BOA. Formación del profesorado, tecnología educativa e identidad docente digital. Rev Latinoam Tecnol Educ. (2015) 14:45–56. https://dialnet.unirioja.es/descarga/articulo/5118305.pdf

Google Scholar

23. Blanco AV, Amigo JC. El rol del docente en la era digital. Rev Int Form Profes. (2016) 30:103–14. http://hdl.handle.net/10201/120644

Google Scholar

24. Tayebinik M, Puteh M. Blended learning or e-learning? Int Mag Adv Comp Sci Telecommun. (2012) 3:103–10.

Google Scholar

25. Rasheed RA, Kamsin A, Abdullah NA. Challenges in the online component of blended learning: a systematic review. Comp Educ. (2020) 144:103701. doi: 10.1016/j.compedu.2019.103701

CrossRef Full Text | Google Scholar

26. Tvenge N, Martinsen K. Integration of digital learning in industry 4.0. Proc Manufact. (2018) 23:261–6. doi: 10.1016/j.promfg.2018.04.027

PubMed Abstract | CrossRef Full Text | Google Scholar

27. Malik S, Rohendi D, Widiaty I. Technological pedagogical content knowledge (TPACK) with information and communication technology (ICT) integration: A literature review. in 5th UPI International Conference on Technical and Vocational Education and Training (ICTVET 2018) (Bandung), (2019). p. 498–503.

PubMed Abstract | Google Scholar

28. Kergel D, Trifonas PP, Letamendia A, Paulsen M, Nowakowski S, Tadeusz PK, et al. David Kergel & birte heidkamp-kergel—learning in and beyond civil society. In: learning in the digital age. Wiesbaden: Diversität und Bildung im digitalen Zeitalter. Springer VS (2022).

Google Scholar

29. Witt M. Bad connections; how labor fails to communicate. New Labor Forum. (2005) 14:113. doi: 10.1080/1095760590901054

CrossRef Full Text | Google Scholar

30. Seaman J, Tinti-Kane H. Social Media for Teaching and Learning. London: Pearson Learning Systems (2013).

Google Scholar

31. Wang W. Analysis on the integration of media literacy into ideological and political education based on computer new media. J Phys. (2020) 1648:032076. doi: 10.1088/1742-6596/1648/3/032076

CrossRef Full Text | Google Scholar

32. Scott N, Goode D. The use of social media (some) as a learning tool in healthcare education: an integrative review of the literature. Nurse Educ Today. (2020) 87:104357. doi: 10.1016/j.nedt.2020.104357

PubMed Abstract | CrossRef Full Text | Google Scholar

33. van Rensburg ESJ. Effective online teaching and learning practices for undergraduate health sciences students: an integrative review. Int J Africa Nurs Sci. (2018) 9:73–80. doi: 10.1016/j.ijans.2018.08.004

CrossRef Full Text | Google Scholar

34. Yousufi U. An integrative review of flipped classroom model. Am J Educ Res. (2020) 8:90–7. doi: 10.12691/education-8-2-4

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Gómez-Ramirez I, Valencia-Arias A, Duque L. Approach to M-learning acceptance among university students: an integrated model of TPB and TAM. Int Rev Res Open Distrib Learn. (2019) 20:142–63. doi: 10.19173/irrodl.v20i4.4061

CrossRef Full Text | Google Scholar

36. Degenhardt MAB. The ‘ethics of belief and education in science and morals. J Moral Educ. (1986) 15:109–18. doi: 10.1080/0305724860150202

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Glatzer W, Hübinger W. Haushaltstechnisierung und gesellschaftliche Arbeitsteilung. In: Biervert B, Monse K,. editors. Wandel durch Technik?. Sozialverträgliche Technikgestaltung, Materialien und Berichte, vol 10. Opladen: VS Verlag für Sozialwissenschaften (1990). p. 81–99.

Google Scholar

38. Tully CJ. Lernen in der Informationsgesellschaft: Informelle Bildung Durch Computer und Medien. Opladen: Springer-Verlag (2013).

Google Scholar

39. Thakkar SR, Joshi HD. Impact of technology availability and self-efficacy on e-learning usage. Int J Res Appl Sci Eng Technol. (2018) 6:2956–60. doi: 10.22214/ijraset.2018.4492

CrossRef Full Text | Google Scholar

40. Sasere OB, Makhasane SD. Global perceptions of faculties on virtual programme delivery and assessment in higher education institutions during the 2020 COVID-19 pandemic. Int J Higher Educ. (2020) 9:181–92. doi: 10.5430/ijhe.v9n5p181

CrossRef Full Text | Google Scholar

41. Alexandre B, Reynaud E, Osiurak F, Navarro J. Acceptance and acceptability criteria: a literature review. Cognit Technol Work. (2018) 20:165–77. doi: 10.1007/s10111-018-0459-1

CrossRef Full Text | Google Scholar

42. Hilbig W. Die Mongoleisammlung im Herbarium der Martin-Luther-Universität Halle-Wittenberg (Lincoln), (1984).

Google Scholar

43. Anstadt SP, Burnette A, Bradley S. Towards a research agenda for social work practice in virtual worlds. Adv Soc Work. (2011) 12:289–300. doi: 10.18060/1894

PubMed Abstract | CrossRef Full Text | Google Scholar

44. Gunasinghe A, Abd Hamid J, Khatibi A, Azam SF. Academicians' acceptance of online learning environments: a review of information system theories and models. Global J Comp Sci Technol. (2019) 19:31–9. doi: 10.34257/GJCSTHVOL19IS1PG31

CrossRef Full Text | Google Scholar

45. García-Álvarez D, Hernández-Lalinde J, Cobo-Rendón R. Emotional intelligence and academic self-efficacy in relation to the psychological wellbeing of university students during COVID-19 in venezuela. Front Psychol. (2021) 12:1–10. doi: 10.3389/fpsyg.2021.759701

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Xiao Y, Becerik-Gerber B, Lucas G, Roll SC. Impacts of working from home during COVID-19 pandemic on physical and mental well-being of office workstation users. J Occup Environ Med. (2021) 63:181–90. doi: 10.1097/JOM.0000000000002097

PubMed Abstract | CrossRef Full Text | Google Scholar

47. Yu J, Park J, Hyun SS. Impacts of the COVID-19 pandemic on employees' work stress, well-being, mental health, organizational citizenship behavior, and employee-customer identification. J Hosp Market Manag. (2021) 30:529–48. doi: 10.1080/19368623.2021.1867283

CrossRef Full Text | Google Scholar

48. Bochiş LN, Barth KM, Florescu MC. Psychological variables explaining the students' self-perceived wellbeing in university, during the pandemic. Front Psychol. (2022) 13:812539. doi: 10.3389/fpsyg.2022.812539

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Wang X, Zhang R, Wang Z, Li T. How does digital competence preserve university students' psychological well-being during the pandemic? An investigation from self-determined theory. Front Psychol. (2021) 12:1252. doi: 10.3389/fpsyg.2021.652594

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Masterson M. An exploration of the potential role of digital technologies for promoting learning in foreign language classrooms: lessons for a pandemic. Int J Emerg Technol Learn. (2020) 15:83–96. doi: 10.3991/ijet.v15i14.13297

CrossRef Full Text | Google Scholar

51. Yang J, Peng MYP, Wong S, Chong W. How e-learning environmental stimuli influence determinates of learning engagement in the context of COVID-19? SOR model perspective. Front Psychol. (2021) 12:1–12. doi: 10.3389/fpsyg.2021.584976

PubMed Abstract | CrossRef Full Text | Google Scholar

52. Botner E. Impact of a virtual learning program on social isolation for older adults. Therap Recreat J. (2018) 52:126–39. doi: 10.18666/TRJ-2018-V52-I2-8664

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Jacobs B, McGovern J, Heinmiller J, Drenkard K. Engaging employees in well-being: moving from the triple aim to the quadruple aim. Nurs Admin Quart. (2018) 42:231–45. doi: 10.1097/NAQ.0000000000000303

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Duraku ZH, Hoxha L. The Impact of COVID-19 on Education on the Wellbeing of Teachers, Parents, Students: Challenges Related to Remote (online) Learning Opportunities for Advancing the Quality of Education. (2020). Available online at: https://www.researchgate.net/publication/341297812 (accessed May 15, 2022).

Google Scholar

55. Boamah SA, Dal Bello-Haas V, Weldrick R. The cost of isolation. Soc Sci Prot. (2021) 4:1–9. doi: 10.7565/ssp.v4.6190

CrossRef Full Text | Google Scholar

56. Al-Salman S, Haider AS, Saed H. The psychological impact of COVID-19's e-learning digital tools on Jordanian university students' well-being. J Mental Health Train Educ Pract. (2022) 17:342–54. doi: 10.1108/JMHTEP-09-2021-0106

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Ejdys J, Gulc A. Akceptacja e-learningu na poziomie szkoły wyzszej. Perspektywa studentów. Przeglad Organizacji. (2021) 7:27–37. doi: 10.33141/po.2021.07.04

CrossRef Full Text | Google Scholar

58. Salloum SA, Alhamad AQM, Al-Emran M, Monem AA, Shaalan K. Exploring students' acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access. (2019) 7:128445–62. doi: 10.1109/ACCESS.2019.2939467

CrossRef Full Text | Google Scholar

59. Fathema N, Shannon D, Ross M. Expanding the technology acceptance model (TAM) to examine faculty use of learning management systems (LMSs) in higher education institutions. J Online Learn Teach. (2015) 11:210–32. https://jolt.merlot.org/Vol11no2/Fathema_0615.pdf

Google Scholar

60. Ong CS, Lai JY. Gender differences in perceptions and relationships among dominants of e-learning acceptance. Comp Human Behav. (2006) 22:816–29. doi: 10.1016/j.chb.2004.03.006

CrossRef Full Text | Google Scholar

61. Tarhini A, Hassouna M, Abbasi MS, Orozco J. Towards the acceptance of RSS to support learning: an empirical study to validate the technology acceptance model in Lebanon. Elect J E-Learn. (2015) 13:30–41. http://gala.gre.ac.uk/id/eprint/13144

Google Scholar

62. Park SY. An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. J Educ Technol Soc. (2009) 12:150–62. https://www.jstor.org/stable/jeductechsoci.12.3.150

Google Scholar

63. Al-Maroof RAS, Al-Emran M. Students acceptance of Google classroom: an exploratory study using PLS-SEM approach. Int J Emerg Technol Learn. (2018) 13:112–23. doi: 10.3991/ijet.v13i06.8275

CrossRef Full Text | Google Scholar

64. Ifinedo P. Students' perceptions of the positive impact of learning with bogs: an investigation of influencing, moderating, and mediating factors. In: CONF-IRM 2019 Proceedings (Hatfield), (2019). p. 10.

Google Scholar

65. Shishakly R. A further understanding of the dominant factors affecting e-learning usage resources by students in universities in the UAE. EURASIA J Math Sci Technol Educ. (2021) 17:1–15. doi: 10.29333/ejmste/11234

CrossRef Full Text | Google Scholar

66. Eraslan Yalcin M, Kutlu B. Examination of students' acceptance of and intention to use learning management systems using extended TAM. Brit J Educ Technol. (2019) 50:2414–32. doi: 10.1111/bjet.12798

CrossRef Full Text | Google Scholar

67. Mailizar M, Burg D, Maulina S. Examining university students' behavioural intention to use e-learning during the COVID-19 pandemic: an extended TAM model. Educ Inform Technol. (2021) 26:7057–77. doi: 10.1007/s10639-021-10557-5

PubMed Abstract | CrossRef Full Text | Google Scholar

68. Tawafak RM, Romli AB, Arshah RBA, Malik SI. Framework design of university communication model (UCOM) to enhance continuous intentions in teaching and e-learning process. Educ Inform Technol. (2020) 25:817–43. doi: 10.1007/s10639-019-09984-2

CrossRef Full Text | Google Scholar

69. Chang CT, Hajiyev J, Su CR. Examining the students' behavioral intention to use e-learning in Azerbaijan? The general extended technology acceptance model for e-learning approach. Comp Educ. (2017) 111:128–43. doi: 10.1016/j.compedu.2017.04.010

CrossRef Full Text | Google Scholar

70. Roca JC, Chiu CM, Martínez FJ. Understanding e-learning continuance intention: an extension of the technology acceptance model. Int J Human Comp Stud. (2006) 64:683–96. doi: 10.1016/j.ijhcs.2006.01.003

CrossRef Full Text | Google Scholar

71. Pastor R, Hernández R, Ros S, Read T, Castro M, Hernández R, et al. An enterprise e-learning solution: the practical case of the UNED in the EHEA. In: IEEE Educon 2010 Conference (Madrid: IEEE EDUCON 2010 Conference) (2010). p. 611–9.

Google Scholar

72. Wu CH, Chen YS, Chen TG. An adaptive E-learning system for enhancing learning performance: based on dynamic scaffolding theory. EURASIA J Math Sci Technol Educ. (2017) 14:903–13. doi: 10.12973/ejmste/81061

CrossRef Full Text | Google Scholar

73. Joo-Nagata J, Abad FM, Giner JGB, García-Peñalvo FJ. Augmented reality and pedestrian navigation through its implementation in m-learning and e-learning: evaluation of an educational program in Chile. Comp Educ. (2017) 111:1–17. doi: 10.1016/j.compedu.2017.04.003

CrossRef Full Text | Google Scholar

74. Sánchez RA, Hueros AD, Ordaz MG. e-learning and the University of Huelva: a study of WebCT and the technological acceptance model. Camp Wide Inform Syst. (2013) 30:135–60. doi: 10.1108/10650741311306318

CrossRef Full Text | Google Scholar

75. Thatcher JB, Perrewe PL. An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quart. (2002) 26:381–96. doi: 10.2307/4132314

CrossRef Full Text | Google Scholar

76. Lin YC, Chen YC, Yeh RC. Understanding college students' continuing intentions to use multimedia e-learning systems. World Trans Eng Technol Educ. (2010) 8:488–93. http://www.wiete.com.au/journals/WTE&TE/Pages/Vol.8,%20No.4%20(2010)/14-20-Lin-Y-C.pdf

Google Scholar

77. Spreng RA, Mackoy RD. An empirical examination of a model of perceived service quality and satisfaction. J Retail. (1996) 72:201–14. doi: 10.1016/S0022-4359(96)90014-7

CrossRef Full Text | Google Scholar

78. Cheung R, Vogel D. Predicting user acceptance of collaborative technologies: an extension of the technology acceptance model for e-learning. Comp Educ. (2013) 63:160–75. doi: 10.1016/j.compedu.2012.12.003

CrossRef Full Text | Google Scholar

79. Mohammadi H. Investigating users' perspectives on e-learning: an integration of TAM and IS success model. Comp Human Behav. (2015) 45:359–74. doi: 10.1016/j.chb.2014.07.044

CrossRef Full Text | Google Scholar

80. Teo T, Zhou M. Explaining the intention to use technology among university students: a structural equation modeling approach. J Comp Higher Educ. (2014) 26:124–42. doi: 10.1007/s12528-014-9080-3

CrossRef Full Text | Google Scholar

81. Taylor S, Todd PA. Understanding information technology usage: a test of competing models. Inform Syst Res. (1995) 6:144–76. doi: 10.1287/isre.6.2.144

CrossRef Full Text | Google Scholar

82. Al-Harbi KAS. E-Learning in the Saudi tertiary education: potential and challenges. Appl Comp Inform. (2011) 9:31–46. doi: 10.1016/j.aci.2010.03.002

CrossRef Full Text | Google Scholar

83. Al-Gahtani SS, Hubona GS, Wang J. Information technology (IT) in Saudi Arabia: culture and the acceptance and use of IT. Inform Manag. (2007) 44:681–91. doi: 10.1016/j.im.2007.09.002

CrossRef Full Text | Google Scholar

84. Al-Gahtani SS. Testing for the applicability of the TAM model in the Arabic context: exploring an extended TAM with three moderating factors. Inform Res Manag J. (2008) 21:1–26. doi: 10.4018/irmj.2008100101

CrossRef Full Text | Google Scholar

85. Hwang HS, Cho J. Why instagram? Intention to continue using Instagram among Korean college students. Soc Behav Person Int J. (2018) 46:1305–15. doi: 10.2224/sbp.6961

CrossRef Full Text | Google Scholar

86. Junus IS, Santoso HB, Isal RYK, Utomo AY. Usability evaluation of the student centered e-learning environment. Int Rev Res Open Dis Learn. (2015) 16:62–82. doi: 10.19173/irrodl.v16i4.2175

CrossRef Full Text | Google Scholar

87. Govender I, Rootman-le Grange I. Evaluating the early adoption of moodle at a higher education institution. in European Conference on e-Learning (Sloan), (2015). p. 230.

Google Scholar

88. Hone KS, El Said GR. Exploring the factors affecting MOOC retention: a survey study. Comp Educ. (2016) 98:157–68. doi: 10.1016/j.compedu.2016.03.016

CrossRef Full Text | Google Scholar

89. El-Sofany HF, El-Seoud SA, Alwadani HM, Alwadani AE. Development of mobile educational services application to improve educational outcomes using Android technology. Int J Int Mob Technol. (2014) 8:4–9. doi: 10.3991/ijim.v8i2.3509

CrossRef Full Text | Google Scholar

90. Qteishat M, Alshibly H, Al-Ma'aitah M. Factors influencing the adoption of e-learning in Jordan: an extended TAM model. Eur J Busin Manag. (2013) 5:84–100.

Google Scholar

91. Cheng YM. Exploring the roles of interaction and flow in explaining nurses'e-learning acceptance. Nurse EducToday. (2013) 33:73–80. doi: 10.1016/j.nedt.2012.02.005

PubMed Abstract | CrossRef Full Text | Google Scholar

92. Lay JG, Chen YW. GIS Adoption and Diffusion Among Senior High School Geography Teachers in Taiwan. ISPRS Workshop Commissions VI/1–VI/2 E-Learning (Taipei), (2011).

Google Scholar

93. Shen D, Laffey J, Lin Y, Huang X. Social influence for perceived usefulness and ease-of-use of course delivery systems. J Int Online Learn. (2006) 5:270–82. www.ncolr.org/jiol

Google Scholar

94. Timbi-Sisalima C, Sánchez-Gordón M, Hilera-Gonzalez JR, Otón-Tortosa S. Quality assurance in e-learning: a proposal from accessibility to sustainability. Sustainability. (2022) 14:3052. doi: 10.3390/su14053052

CrossRef Full Text | Google Scholar

95. Malanga AC, Bernardes RC, Borini FM, Pereira RM, Rossetto DE. Towards integrating quality in theoretical models of acceptance: an extended proposed model applied to e-learning services. Brit J Educ Technol. (2022) 53:8–22. doi: 10.1111/bjet.13091

CrossRef Full Text | Google Scholar

96. Khan MA, Khojah M. Artificial Intelligence and Big data: the advent of new pedagogy in the adaptive e-learning system in the higher educational institutions of Saudi Arabia. Educ Res Int. (2022) 2022:1–10. doi: 10.1155/2022/1263555

CrossRef Full Text | Google Scholar

97. Shahabadi MM, Uplane M. Synchronous and asynchronous e-learning styles and academic performance of e-learners. Proc Soc Behav Sci. (2015) 176:129–38. doi: 10.1016/j.sbspro.2015.01.453

CrossRef Full Text | Google Scholar

98. Rasheed HMW, He Y, Khalid J, Khizar HMU, Sharif S. The relationship between e-learning and academic performance of students. J Public Affairs. (2020) e2492. doi: 10.1002/pa.2492

CrossRef Full Text | Google Scholar

99. Nácher MJ, Badenes-Ribera L, Torrijos C, Ballesteros MA, Cebadera E. The effectiveness of the GoKoan e-learning platform in improving university students' academic performance. Stud Educ Eval. (2021) 70:101026. doi: 10.1016/j.stueduc.2021.101026

CrossRef Full Text | Google Scholar

100. Alam MM, Ahmad N, Naveed QN, Patel A, Abohashrh M, Khaleel MA. E-learning services to achieve sustainable learning and academic performance: an empirical study. Sustainability. (2021) 13:2653. doi: 10.3390/su13052653

CrossRef Full Text | Google Scholar

101. Davis FD. A Technology Acceptance Model for Empirically Testing New End-User Information Systems. [doctoral thesis]. [Massachusetts]. Massachusetts Institute of Technology (1986).

Google Scholar

Keywords: sustainability, e-learning, wellbeing, TAM, attitudes

Citation: Fülöp MT, Breaz TO, He X, Ionescu CA, Cordoş GS and Stanescu SG (2022) The role of universities' sustainability, teachers' wellbeing, and attitudes toward e-learning during COVID-19. Front. Public Health 10:981593. doi: 10.3389/fpubh.2022.981593

Received: 29 June 2022; Accepted: 07 July 2022;
Published: 27 July 2022.

Edited by:

Umair Akram, RMIT University, Vietnam

Reviewed by:

Lili Rakos, Universitatea Din Petrosani, Romania
Alina Solomon, Dimitrie Cantemir Christian University, Romania

Copyright © 2022 Fülöp, Breaz, He, Ionescu, Cordoş and Stanescu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Melinda Timea Fülöp, melinda.fulop@econ.ubbcluj.ro

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.