IMPACT OF COVID-19 PANDEMIC ON ACCEPTANCE OF E-LEARNING SYSTEM IN JORDAN: A CASE OF TRANSFORMING THE TRADITIONAL EDUCATION SYSTEMS

Purpose of the study: This paper aimed at investigating factors influencing students’ intention to use e-learning within the context of Jordan. The proposed model integrated subjective norms with the extended Technology Acceptance Model (TAM). Methodology: The data collected 587 students from Jadara University. Data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Main Findings: The result has confirmed the direct effect of all variables. Next, the result has also shown that the mediation effect of perceived usefulness and perceived ease of use between subjective norm and the behavioral intention to use the E-learning system was partially supported. Applications of this study: The results of the current work may contribute to the improvement of the existing literature in the e-learning acceptance fields, and can be applied as an essential input for the development of the recent e-learning training programs. Novelty/Originality of this study: The present work is intended to conclude a series of concrete research data as well as to contribute a new angle to the existing literature on students’ perception of the e-learning system.


INTRODUCTION
Technological and internet development changed how learning services are provided and delivered. These changes and developments help in improving the quality of education (Al-Fraihat, Joy, Masa' deh & Sinclair, 2020). In light of the rapid technological development in the world, the e-learning system has also emerged and developed as a means to facilitate the educational process, especially for those with barriers from enrolling in abroad universities. Recently, due to Corona Virus Disease 2019 (COVID- 19) crisis, e-learning has become a very urgent need and an imperative of education necessities in most countries all over the world. Its great importance manifested in solving the problem of quarantined students, reduce the effects of the corona-virus epidemics, and supporting societies in their endeavor to fight the current COVID-19 pandemic. E-learning system has added new scopes in the educational process by improving new technologies and originating processes and methods to enhance the education process and distance learning activities. The e-learning system concept, as well as mobile learning, has become an essential channel in the education process, whether it is primary, secondary, and higher education, through facilitating the education process and develop its output. There are various definitions in previous studies of the e-learning system. Almarabeh et al. (2014) define it as the providing of education, including several activities relates to teaching, learning, and instructing via numerous automated media, whether it is the internet, extranet, and satellite. Hoppe and Breitner (2004) define the e-learning system as the learning that is supported by the use of modern information and communication technology.
The abundance of studies has examined the student's intention to use e-learning (Hoppe & Breitner, 2004 Mousa et al., 2020). One question that has arisen and still needs more evidence relates to what are the new main factors that could contribute to the Jordanian student's intention to use the e-learning system. In Jordan, most of the universities are supplying-learning system techniques for their students to provide safe and simple websites (portal), as well as, to help students and their lecturers in explains the courses' contents simply and effectively, also to facilitate the online discussion, collaborations, and exams. However, most of the Jordanian universities face some challenges in using e-learning. Of the most important is the lack of the number of students enrolled in the e-learning system classes. Moreover, the percentage of attendance is still generally modest and needs improvement. Thus, the question arises that how the university can face this challenge? what are the factors or techniques that can be used to handle this issue? that person's attitude is not only determined by perceived usefulness and perceived ease of use. Accordingly, the researcher has broadened the theoretical horizon of the TAM model by adding two external factors in the TAM model, namely social influence and peer influence, that are claimed to determine behavioral intention by the subjective norm. It's been argued that social and peer influence effect occurs only in compulsory environments and has less importance in a voluntary environment.
Consequently, under the current conditions as a COVID-19 pandemic, the e-learning system has become mandatory for all educational institutions all over the world. Therefore, the current situation is conducive to studying the effect of the aforementioned variables on the intention to use distance learning. However, this research proposes a holistic framework of the acceptance determinants. Those predictors are classified based on the constructs of the TAM model and other proposed factors, namely, social influence and peer influence.
The rest of this paper is structured as follows. Section 2 introduces a literature review of the e-learning system and the study framework. The data and methodology are provided in Section 3. Section 4 discusses the results of the study. Eventually, Section 5 presents the conclusion and policy implications.

LITERATURE REVIEW
The evaluation of e-learning system acceptance under the conditions of the corona-virus pandemic is vital to ensure effective use by instructors and positive influences on students. Thus, this study is aimed to examine the determinants of e-learning system acceptance in the Jordanian context by using the TAM. Based on a comprehensive review of the previous studies, the current research model has been developed, which provides a holistic picture of acceptance determinants. In this respect, this part focuses on the discussion of the most significant e-learning system acceptance predictors. Those predictors are classified based on the constructs of the TAM model, and other proposed factors as social influence and peer influence. Consequently, the researchers expect that current research will contribute to the TAM model as a theoretical contribution.
Given this, the TAM model was proposed by Davis (1989) in the context of Information Technology (IT) used to explain and predict user acceptance of IT. It was presented as one of the most important information technologies acceptance models (Alalwan, Baabdullah, Rana, Tamilmani & Dwivedi, 2018; Shankar & Datta, 2018). It should also be noted that TAM's, similar to the TRA and TPB, which aimed at predicting IT acceptance and adoption. Moreover, the TAM model has been adopted by researchers all over the world to test the acceptance of IT, which has been confirmed to be a strong predictor of technology use (Venkatesh & Davis, 2000). Accordingly, the success of any IT implementation depends on the integration of user acceptance (Raid, 2009). Other recent studies, as Alalwan et al. PU rises from the extent to which users believe that embracing a specific system/innovation could improve their performance, while PEU refers to the extent to which users believe that embracing a specific system could be free of physical and mental efforts (Venkatesh & Bala, 2008;Venkatesh & Davis, 2000).
The second stage is when the PU and PEU affect the user's Attitude Towards Using (ATU) a particular system (Wolk, 2007). In the third stage, the PU and ATU determine the usage intention (Wolk, 2007). The final stage is making decisions to accept or reject the use of technology. However, despite TAM popularity, several researchers have noted that one of the weaknesses of the TAM model is that a person's attitude is not only determined by perceived usefulness and perceived ease of use but also by other critical factors such as social influence that determine users' attitudes towards the use of IT (Miller, Malhotra & Galetta, 1999). Some researchers also indicated that the TAM model just focused only on extrinsic motivation, not intrinsic motivation (Davis, 1989). This means that this model focuses only on the outcomes of using IS or IT and does not consider the processes of the usage itself. For example, some people want to use IT because it is interesting or because they want to have rich experience (Alrawashdeh, 2011).
In short, as an extension to the TAM model as external factors in the same conceptual model as highly recommended by Davis (1989) to broaden the theoretical horizon of the TAM model. There are two external factors in the TAM model, namely social influence and peer influence, that are claimed to determine behavioral intention by the subjective norm, as illustrated in Figure 2. These two important factors have been used directly to determine the behavioral intention in other recent studies (e.g., Al-Okaily, Abd Rahman & Ali, 2019). In this regard, they are used in the proposed research model to predict the intention of students to use the e-learning system. . In this research, SN was conceptualized as a global variable derived from two dimensions, which were measured using eight items. The first dimension is the social influence, and the second dimension is peer influence. According to the UTAUT model, SI is a good predictor of the use of IT (Venkatesh et al., 2003). Moreover, Venkatesh and Davis (2000) claim that the social influence effect occurs only in compulsory environments and has less importance in a voluntary environment.
Consequently, under the current conditions as the COVID-19 pandemic, the e-learning system has become mandatory for students at Jadara University (i.e., students must use the e-learning system to access learning resources to complete their course, and know the date and venue of exams as well as accomplish and submit exams). Thus, this research will evaluate the experience of Jadara University students toward using Microsoft Teams as an e-learning tool. We will investigate the intention of Jadara University students toward the impact of interactive learning structures accepted in most of the courses in the university. In the e-learning systems context, student's decision to accept such systems is usually affected by other colleagues and lecturers' pressures (El-Masri & Tarhini

Perceived Ease of Use (PEU)
PEU is defined as ''the extent to which users believe that applying a specific system would be free of efforts'' (Davis 1989, p.320). PEU is similar to Effort Expectancy (EE) in the UTAUT model (Venkatesh et al., 2003;Venkatesh et al., 2012). According to the UTAUT model, EE has a significant influence on the behavioral intention of a user to use IT (Venkatesh et al., 2003). In the TAM model, perceived ease of use was theorized as a direct determinant of behavioral intention (Davis, 1989). Theoretically, perceived ease of use was found to be a significant factor predicting the intention to use the e-learning system ( . It is expected that if the students' perceptions of the e-learning system are free of effort, then they will play an important role in using the e-learning system. Consequently, this leads to the following hypotheses: H4: PEU is positively associated with perceived usefulness.
H5: PEU has a positive effect on e-learning intention.
H6: PEU mediates the relationship between subjective norms and intention to use the e-learning system.

Perceived Usefulness (PU)
PU is defined by Davis (1989, p.320) as "the degree to which a person believes that using a particular system would enhance his or her job performance". PU is similar to performance expectancy in the UTAUT model ( . In a related context, it is claimed that the greater level of the PU to the e-learning, will lead inevitably to the higher intention of the students to adopt/use e-learning system. Thus, we propose the following hypothesis: H7: PU has a positive effect on e-learning intention.
H8: PU mediates the relationship between subjective norms and intention to use the e-learning system.

METHODOLOGY
This research aimed at understanding the behavioral intention to utilize the e-learning system, in light of the COVID-19 pandemic circumstances. The period early 2020 has enforced most of the countries in the world to implementing Elearning in schools and universities, due to the lockdown and quarantine. In Jordan, all universities have utilized the elearning system to be capable of continuing the education system. Hence, this circumstance has encouraged researchers to take a view toward utilizing E-learning, to promote the learning and teaching system in Jordan. The sample has addressed the students of Jadara University as a sampling frame. This work concerns the student's perception of elearning system acceptance. Therefore, the student's become a unit of analysis and the targeted respondent of the study.
An instrument (questionnaire) was developed, and a survey was conducted for obtaining data. The items of studied variables were adapted from published research regarding the e-learning context, and some of them were rewritten according to the study context (see Appendix), using a five-Likert scale 1 to 5 =strongly disagree to strongly agree, respectively such prior studies (e.g. Considering their comments, we revised some of the items to enhance the clarity of our questionnaire survey. After that, we carried out a pilot test in a sample of 35 students. The finding revealed evidence of the reliability and validity of the instruments. For data collection purposes, a survey questionnaire was directed to 4500 students online using the university pages on Social Media. To maximize the response rate, two rounds of follow-up messages were undertaken after the initial distribution. The first follow-up messages were issued two weeks after the questionnaires were sent out. The second follow-up message took place three weeks later the first reminders. After five weeks, 587 valid responses were obtained (373 early respondents and 214 late respondents). The response rate was 13.5%. Then, comparing the groups of early and late respondents, the finding from the Kolmogorov-Smirnov test specified an absence of nonresponse bias. The majority of respondents were bachelor students (572 The discriminant validity test was also conducted to evaluate the range to which a provided study latent variable is distinct from others. Whereby, when the average variance extracted of an individual latent construct is higher than the multiple squared correlations of that construct with other constructs, the discriminant validity will be at an acceptable level (Fornell & Larcker, 1981). As illustrated in Table 2, all studied variables had good discriminant validity values. Regarding the structural model, the R square (R²), effect size (f²), t-value, and path coefficient of each relationship have been calculated. The R² value of behavioral intention shows that approximately 70 percent of the variance in the E-Learning Intention is considered by the proposed framework. Besides, Perceived Usefulness, with an R² of about 75 percent, proven to be well forecasted by its predictors. Also, the R² value for the Perceived Ease of Use was 46.6 percent, is moderately predicted by its predictors (see Figure 1). Concerning f², Cohen's (1988)

RESULTS/FINDINGS
This study is investigated the stated hypotheses by utilizing the procedure of 1000 bootstrapping to compute the T-value, P-value, and path coefficients. Table 3. shows that behavioral intention to use the e-learning system is significantly and positively affected by subjective norms (peer influence and social influence), perceived usefulness, and perceived ease of use, thus all respective hypotheses were supported. Besides, the results also confirmed that the perceived usefulness of the e-learning system is significantly and positively affected by perceived ease of use. Hence H4 was supported.
Concerning the mediating effect of perceived ease of use the e-learning system, the result has revealed that perceived ease of use is partially mediate the relationships between subjective norms (social influence and peer influence) and the behavioral intention to use the e-learning system. Also, the result has confirmed that perceived usefulness is partially mediate the relationships between subjective norms and the behavioral intention to utilize the e-learning system. Whereby, as shown in    . This result implied that learners will perceive the e-learning system as easy to use if influential persons make use of the system and consider it necessary. Another possible explanation for these findings is the fact that when learners' anticipations towards the e-learning benefits are confirmed, the e-learning system will enhance their satisfaction and acceptance which ultimately achieves the perceived objectives. H3 formulates that subjective norm has a significant direct impact on e-learning intention. This study results confirmed the significant effects of subjective norm on elearning acceptance and intention to use. Students seem to favor informal types of networking such as peers, other student's colleagues, and teachers instead of formal types while seeking advice and supports on e-learning related matters. It is widely argued that if individuals perceive that persons who are important to them think or advice that they should use and accept IS\IT, then the individual's will incorporate their beliefs into their own beliefs system, and accordingly perceives the system more beneficial in its purpose ( conclude, students learning under the conditions of corona-virus pandemic tend to rely on a greater amount of information via the e-learning system to sustain and achieve their objectives. The results also pointed out that each of the three hypotheses H4 (perceived ease of use → perceived usefulness), H5 (perceived ease of use → e-learning intention), and H7 (perceived usefulness → e-learning intention) are supported. Perceived ease of use is found to have a significant positive impact on e-learning intention (H5). This finding is consisting of earlier works (Mousa et al., 2020;Alghizzawi et al., 2019;Mohammadi, 2015). These findings could be explained by the reason that if students think or perceive that it is uncomplicated and simple to use new technologies such as e-learning, then they are willing and intent to spend more effort and time to learn how to do so, which would undoubtedly improve their performance. In contrast, if e-learning is complicated and difficult to operate and use, then students would be unwilling to try to use it. Likewise, perceived usefulness is found to have a significant impact on the intention to use e-learning (H7 In comparison with traditional teaching methods and e-learning, e-learning is not limited by place and time and can be carried out anytime, which seriously increases the efficiency of student learning. Accordingly, if students perceive the usefulness of e-learning, their intention and willingness to use e-learning would also undoubtedly be improved. Additionally, the ease of use of the elearning system also directly affects the usefulness of e-learning (H4). Jadara University students believe that if elearning is easy to use to them, its usage and acceptance will also be very useful. To be Rational, these two constructs are fairly reasonable, as the use of e-learning should be not complicated and useful so that students and learners tend to accept and use it.
Concerning the mediation test, H6 and H8 state that perceived usefulness and perceived ease of use mediate the relationship between subjective norm and e-learning intention. Results have revealed promising mediating between subjective norm and e-learning intention via both perceived usefulness and perceived ease of use. As discussed earlier, the perceived usefulness of learning from an online system is known as the perceived advantages and the overall perceived benefits of the e-learning system. Perceived ease of use, is about perceived needed technological features accepted and agreed by system users (learners). The influence of subjective norm on e-learning intention to use is highly meditated by the technological features (elements) and benefits (advantage) that an e-learning system provides to learners. Accordingly, e-learning providers and designers should give particular attention on the improvement and development of the advanced and latest technologies that enable e-learning users to get services and access learning resources such as (complete their course and know the date and venue of exams as well as accomplish and submit exams) easily and simply. Likewise, to increase the perceived benefits for learners, e-learning providers and designers need to offer easy access, convenient communication, students and instructors training/consulting, continuance repair, and maintenance, etc.
Overall, the current work demonstrates some important theoretical and practical insights and implications. It identifies the role of the subjective norm (social and peer influence) as an important external variable of the TAM model. Although the subjective norm is one of the most significant facilitators of e-learning technology, prior works have rarely integrated social and peer influence together as an external variable (subjective norm) into the TAM to successfully investigate the student's e-learning intention to use and acceptance. Besides, it also extends e-learning literature by extending the applicability of the TAM model in explaining the direct relationship between subjective norm and elearning intention to use as well as the mediation effect of both perceived ease of use and perceived usefulness on such relationship. Despite extensive studies on the use of the TAM model as a theoretical foundation, very rare has been specifically related to such relationships.
Concerning the practical implications of this work, the developed model facilitates policymakers to recognize subjective norm factors that promote more extensive acceptance and use of the e-learning system. Specifically, the validated model helps e-learning providers to give specific attention to possible impacts of both social and peers that they might have overlooked. This can benefit them to estimate the influence of social and peers to the students as well as to facilitate their intentions on e-learning particularly during emergency circumstances such as the corona-virus pandemic. Additionally, the findings of the current study proven that when e-learning system usage effortless and is more useful to users, it will be used more beneficially and promote higher levels of e-learning use and acceptance. Accordingly, e-learning system designers and developers should pay further attention to these two essential factors (perceived usefulness and perceived ease of use) that are important aspects of the learners' viewpoint. As a result, they should decrease the learner's efforts while using the e-learning system by designing friendly interfaces and the government should also provide suitable ICT infrastructure. Finally, advertising and marketing campaigns should also launch on the potential benefits of e-learning usage.

CONCLUSION
This work aimed to identify factors that influence a student's intention to accept the e-learning system. The TAM model was applied as a proper theoretical foundation for the proposed conceptual framework. To achieve the study aims; a quantitative survey was conducted with self-administered questionnaires, which were distributed to acquire data from a target sample. Data analysis and findings were discussed, including the details of the measurement model, and validity