Factors That Influence English Teachers’ Acceptance and Use of E-Learning Technologies

The world has witnessed a major pandemic that has threatened the status of education across the globe. Such a crisis highlights the importance of education technology, which has not been an influential part of Kuwait’s education until the onset of COVID-19. Delays and interruptions of the academic year disrupted the lives of many students around the world, including Kuwait. Since e-learning technologies are not traditionally used in Kuwaiti higher education, this study aims to investigate the acceptance of technology and whether that has changed with the pandemic. It seeks to find useful strategies that could assist teachers in effectively using electronic distance-learning digital resources. The Unified Theory of Acceptance and Use of Technology (UTAUT) has been developed to investigate the degrees of usage and acceptance of technology. This paper adopts an improved model that also includes the educational experience of teachers, in an attempt to understand the context of Kuwaiti higher education. Therefore, this quantitative study examines the use and acceptance of educational technologies of English language instructors in higher education. The study uses an online survey among 33 English language instructors at the Public Authority for Applied Education and Training (PAAET) to also account for the perceptions and experiences of the teachers. The results revealed an overall high acceptance level of educational technology, with varying degrees of implementation.

adopt textbooks developed by international organizations that provide access to e-learning tools. Many English language courses at PAAET use textbooks that provide companion digital packages for teaching and practice purposes, in addition to a considerable amount of free-access online material. This places English language courses at a better level than other courses in terms of course material and practice. Research has also shown that technology improves the language-learning process, with numerous programs and online services that make learning more accessible and enjoyable, such as learning vocabulary (Horst, Cobb, & Nicolae, 2005). Furthermore, information technology increases collaboration and interaction among students, which are beneficial for the language-learning process (Kukulska-Hulme & Viberg, 2018).
However, acceptance and utilization of new technologies by users is considered to be a primary indication of the success of the implementation and development of any educational technology approach. The attitudes of the user towards adopting new technologies are an essential indication of the success or failure of any information technology project (Succi and Walter, 1999;Pinto and Mantel, 1990). Venkatesh, Morris, G. Davis, and F. Davis (2003) see users' acceptance of technology as being the user's initial decision to interact with the technology.

Literature Review
Teachers' usage of technology is affected by numerous factors, and it is important to understand whether there is a relationship between their usage and their attitudes. Research (e.g. Nuttall, Edwards, Mantilla, Grieshaber, & Wood, 2015;Sime & Priestley, 2005) has shown disparity between teachers' attitudes and actual use of ICT. While the majority of teachers express favourable attitudes, their actual implementation of ICT is relatively limited. Shroff et al. (2011) state that manipulating these two factors helps system developers take better control over users' attitudes towards the technology. This in turn allows the system developers to predict the behavioural intention of the user and their actual application of the system. In addition, users' perceptions of technology can be a major factor in predicting their attitudes (Liu, 2010). Overall, research has repeatedly shown that attitudes towards using a new system could play a major role in influencing future behaviour, or at least give insight into the users' actual intentions, which could eventually lead to certain behaviours (Afshari et al., 2013;Elias et al., 2012).
There are also other factors that can influence the usage of ICT. For instance, the subject matter could affect users' attitudes, as Jimoyiannis and Komis (2007) state that, while foreign language, technology, and science teachers have apparent positive attitudes regarding ICT, other fields, such as social sciences teachers, conveyed negative attitudes. Additionally, the study found that male teachers show more positive attitudes to ICT than female teachers (Jimoyiannis & Komis, 2007). Kalogiannakis (2010) reported similar findings, noting that age also could affect teachers' attitudes towards ICT, as younger teachers appear to be more in favor of adopting ICT in education than older teachers (Blackwell et al., 2014;Camilleri & Camilleri, 2017;Kalogiannakis, 2010). On the other hand, Jimoyiannis and Komis (2007) suggested that older teachers with long teaching experiences show more positive attitudes towards e-learning technologies in education than less experienced teachers.
The likelihood that an educational institution will adopt ICT also depends on that institution's infrastructure and financial status. In some cases, teachers state that they are afforded neither the time nor the funds to adopt new technologies (Levy & Stockwell, 2008). Numerous studies note that teachers' intentions to implement ICT are often hindered by the lack of proper equipment (access to computer labs, the internet, or relevant applications) (Bingimlas, 2009;Fageeh, 2011;Hismanoglu, 2012;Mumtaz, 2000). Teachers' attitudes are therefore affected by the lack of accessibility to proper ICT resources.
While some numerous approaches and theories help researchers examine users' acceptance and adoption of information technologies, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are two useful ones. TAM and UTAUT have been the most commonly used models to explain the adoption of new technology-oriented projects in several fields (Carter, 2008;Gefen & Warkentin, 2002).
TAM, which was first founded by Davis (1989), is based on the Theory of Reasoned Action (TRA). It posits that two constructs essentially define the individual's behavioural intention for the use and acceptance of technologies: Perceived Ease of Use (PEU), and Perceived Usefulness (PU) (Davis et al., 1989). PU is "the degree to which a person believes that using a particular system would enhance his or her job performance" (Davis, 1989: p.320), whereas PEU is defined as "the degree which a person believes that using a particular system would be free of effort" (ibid.). TAM is a well-researched, simplified model that aims to explore and identify the factors that affect computer users' acceptance across various contexts. In addition, it provides predictions and explanations for whether a system will succeed (Davis et al., 1989). According to Davis et al. (1989), the TAM model suggests that the intention to use e-learning technologies increases in accordance with the usefulness and ease of use.
However, other researchers, including Bagozzi et al. (2003), suggest that, in practice, other obstacles restrict the technology acceptance constructs on perceptions on the convenience of use, such as the TAM's perceived ease of use (Pynoo et al., 2011), and complexity (Ghalandari, 2012). EE is considered the second independent variable in the UTAUT, which could be problematic if users find a certain e-learning technology difficult to use (Khechine et al., 2014).
Social Influence (SI) is "the degree to which an individual perceives that important others believe he or she should use the new system" (Venkatesh et al., 2003). Important others may include family members or colleagues. SI can be considered as, a subjective norm, as in C-TAM-TPB, TPB/DTPB, TAM2, part of the individual's image as in IDT, or a social factor, as in MPCU. However, they all share the position that the individual's behaviour is believed to be influenced by the attitudes of others (Bere, 2014). The value of SI stems from the fact that social influence affects the user's commitment to adopt a certain technology, as well as their usage behaviour and acceptance (Riad et al., 2013). Venkatesh et al. (2012) state that SI is moderated by other variants such as age, gender, experience, and willingness to volunteer time and effort. In educational contexts, SI is an indicator of teachers' behavioural intention to adopt e-learning, which can predict the usage of e-learning technologies (Adegbite & Downe, 2005).
Facilitating Conditions (FC), as a UTAUT factor, refers to how the user perceives the technical readiness and infrastructure of the organization and its support (Venkatesh et al., 2003). FC is also combined from earlier models, such as compatibility, facilitating conditions, and perceived behavioural control (Bhatiasevi, 2015). In education, facilitating conditions may include school organizational policies, environment, and infrastructure, as well as e-learning content. The quality of the facilities and equipment provided by management is also one of the most important factors for the institution's environment (Blum, 2005;Dutta & Bilbao-Osorio, 2012;Phau & Teah, 2009).
Behavioural Intention (BI) predicts whether the individual will undertake a certain behaviour, which can be affected by several factors, such as attitudes, the perceived ease of use, and convenience. BI is considered a significant factor for using technology (AlAwadhi & Morris, 2008;Riad et al., 2013). It is worth mentioning that perceived ease of use overrides other factors, as teachers may not use complicated systems, regardless of their attitudes towards their usefulness or convenience (Teo, 2011).
Teacher Educational Experience (TEE) is another important factor for the acceptance and planning for e-learning technologies since teachers learn from their experiences as e-learners (Donnelly & McSweeney, 2008). The e-learning experiences of teachers are an important factor in understanding technology, as well as in improving their students' experiences. For teachers with no e-learning experiences, targeted training and support for e-learning systems are vital (Giannakos & Vlamos, 2013). TEE can also influence the acceptance of technology, as well as the users' confidence while operating it (Alexander, 2001;Pullen, Swabey, Abadooz, Ranjit Sing, & Kaur, 2015).

Method
The questionnaire adopted in this study is based on research on the UTAUT model by Venkatesh et al. (2003), who studied the acceptance of technology, and researchers' experiences (i.e. teachers' experiences). It was developed after reviewing relevant research, then sent to five professors for refereeing purposes, and their feedback and suggestions have been taken into consideration. The questionnaire consisted of eight sections. The first section contained an information sheet, the second section included participants' information details, and the third section consisted of performance expectancy statements. The fourth section was devoted to effort expectancy statements, followed by the fifth section statements. The sixth section was for social influence statements, with facilitating conditions statements being the seventh part, and the eighth was instructors' experiences statements 4. The questionnaire was also piloted for reliability purposes and the result was 0.85 Cronbach's Alpha.

Sampling Procedures
The target population for this study is English language instructors at the language center in PAAET; participants are drawn from a total of 103 full-time English language instructors. According to PAAET, there were 103 full-time English teachers in 2019/20 teaching at English language units across PAAET's five colleges, where the Language Center provides English as a Foreign Language (EFL) courses and English for Specific Purposes (ESP) courses. Therefore, a purposive sampling protocol was applied (Cohen, Manion, & Morrison, 2007), since the population is limited to this particular group. The questionnaire was sent to all of the English language instructors, i.e. 103. A total of 33 instructors completed the survey, representing 32.04% of the population. The participants were from all five colleges across PAAET, with varying degrees of qualifications and teaching experiences.
A survey, which was translated into Arabic and distributed online (using Google Forms), was sent to all of the instructors at the Language Center in PAAET, inviting them to take part. In reaction to the spread of COVID-19, ies.ccsenet.org International Education Studies Vol. 14, No. 9; PAAET has offered all of its faculty members online courses on using e-learning technologies for teaching purposes, thus encouraging them to be prepared to adopt these technologies upon their return to schools. It has also invited all students to attend online courses to learn how to use e-learning systems provided by PAAET. Similar to many educational institutions around the world, PAAET has resorted to online courses since August 2020.

Results
The researchers first used Statistical Package for the Social Sciences (SPSS) to analyze the data. In order to achieve the objectives of the study, several statistical techniques were utilized in the data analysis. The tool reliability was verified using Cronbach's alpha coefficient, as shown in Table 1 below:

The Survey
The first part of the questionnaire includes personal information that aims to collect personal and professional data about the participants, such as age, gender, educational background, and qualifications. This helps in understanding how representative the sample was from the targeted population, in addition to getting an insight into the participants' professional experiences. The following sections will discuss each part of the survey in detail.

Performance Expectancy (PE)
A majority of participants expressed positive views regarding PE, though in varying degrees. Most of the participants (90.9%) held positive attitudes towards e-learning for both teaching and learning, in comparison to fewer participants who were either unclear or neutral (3%), while 6.1% disagreed. Similarly, more than 66% of the participants view e-learning technologies as a facilitating tool to achieve work more rapidly, while 54.5% thought that e-learning technologies enhanced teacher-student communication. Finally, 66.7% of the teachers found that using e-learning facilitated the teaching process. The response indicates that the majority of teachers consider e-learning technologies a valuable aid for teaching education contents, and an improvement to their performance. The results also show that English language instructors have positive attitudes towards the efficiency of e-learning technologies.
The Mean (M) of teachers' responses about how e-learning technologies help them in the teaching process (Performance Expectancy) is 3.67, while the Standard Deviation (SD) is 0.951, which implies that e-learning technology is believed to be an efficient tool for teachers of the English Language Centre. expressed less positive, if not negative beliefs, which makes the higher positive response rate not entirely conclusive. The positive response (72.7%) also thought that learning to operate and use new e-learning technologies was easy, which indicates that the teachers are already familiar with using e-learning technologies, and/or find them easy to learn.
The M of teachers' effort experience, i.e., how convenient it is to learn and use e-learning technology, is 3.84, and the SD is 0.596. This implies that the majority of the teachers in the English Language Center find it is easy to use e-learning for their educational content.

Social Influence (SI)
The survey findings indicate that SI regarding e-learning technologies has an impact on their users. Firstly, more than half of the participants (54.5%) believed that their dean and supervisor think that they should use e-learning technologies. Only one participant did not think this was the case, while the rest (42.2%) were neutral. Although 51.5% believed that colleagues assist one another when facing difficulty in using e-learning technologies, a sizable minority (48.4%) thought otherwise. However, the majority of instructors were neutral (54.5%) or did not agree (18.2%) that students prefer adopting e-learning technologies in their courses.
Similarly, despite the fact more than half the participants (51.5%) believed their colleagues acknowledge the importance of e-learning, there were noticeable responses with either neutral (36.4%) or negative (12.1%) position towards staff perception of e-learning technologies. Finally, teachers' responses about their superiors' beliefs, colleagues' collaboration, and students' expectations show that SI positively impacts teachers' perceptions towards using e-learning technologies. My students think that I should use e-Learning technologies.

Facilitating Conditions (FC)
The survey established that the majority of participants (63.6%) believe that classes in their college are inadequately equipped with computers. However, the majority (57.5%) believed they had the resources necessary to use e-learning. Also, more than half of the participants (51.6%) stated that technical assistance was available by personnel or department dedicated to e-learning technology issues.
Overall, it seems that there are no satisfactory e-learning technologies facilitating conditions, which limits English language instructors' potential of maximizing the potential of e-learning technologies.
The M of sample responses about instructors' perception of the current technological facilities for e-learning technologies (FC) is 2.95, with an SD of 0.854. This shows prevailing negative attitudes from the teachers towards the provided technological facilities at work that could help them adopt e-learning.

Behavioural Intention (BI)
Statements on BI reported positive attitudes from most of the participants towards using e-learning technologies in the future. Most of the participants responded positively to (81.9%) attending training courses for e-learning technologies, with a few (21.1%) uncertain, and even fewer (6.1%) not showing interest in attending e-learning technologies training. This shows an overall positive attitude and behavioural intention towards using and learning how to use e-learning technologies by English language instructors, which is an important indicator of their belief that e-learning technologies would improve the learning and teaching experience.
The M of the responses on teachers' BI about using e-learning technologies is 4.17, with an SD of 0.693, indicating very high behavioural intentions from the teachers to use e-learning technologies.

Behavioural Use (BU)
The survey showed that all participants use computers as part of their preparation, either daily (69.7%), or weekly (30.3%). However, when it comes to using computers as part of the teaching process, most use them daily or weekly (75.8%), while 15.2% use them scarcely, and 12.1% never use computers for teaching. The most used presentational tools used were data Show (51.5%), and PowerPoint (45.4%). However, a significant minority said they never use Data Show (33.3%) or PowerPoint (39.4%) as part of their teaching. It can be argued that using these e-learning tools provides teachers with more efficient and diverse tools for teaching and presenting information to students.
The M of instructors' use of e-learning technologies is 3.50, with an SD of 1.053. This confirms a high usage of e-learning technologies by teachers.

Educational Experience (EE)
The survey aimed to understand the English language instructors' experience with e-learning technologies when they were students. However, more than half the participants (54.5%) stated that they had never used e-learning technologies in high school, while the rest either used it rarely, weekly, or daily. On the other hand, most of the participants reported regular e-learning technology use at the college level, either by them or their lecturers, with a notable minority indicating that have never, or scarcely, used e-learning technologies at the tertiary level. Similar views were also expressed regarding pre-service teacher training, with 45.5% of participants using e-learning technology regularly, and 36.4% rarely using them, while 18.2% stated that they never used them.
The M of instructors' educational experience in using e-learning technologies is 3.99, with an SD of 0.937, meaning there is an overall high level of experience among teachers in using e-learning technologies as students on varying levels.

Correlations
Correlations are used to examine the acceptance and use of e-learning technology in relation to other variants in the study. Also, Significance Testing is used to test the patterns and differences, and whether they occur by chance (Berman, Brown, & Saunders, 2008). To sum up, the questionnaire revealed notable features regarding the acceptance and use of e-learning technologies among the PAAET English language instructors. Overall, survey respondents showed positive attitudes towards using technology for teaching purposes, as they find it easy to use and agree it improves their teaching experience. However, they expressed varying responses about the attitudes of people in the workplace towards their use of e-learning technologies, although more than half the participants reported positive responses. Even though facilitating conditions in PAAET are below the participants' expectations, most of them expressed their desire to adopt e-learning technologies for their classes, if it isn't already part of their teaching experience. When investigating correlations among the variables that could influence adopting and using e-learning technologies, significant correlations were found between Behavioural Intention and other factors to use these technologies.

Discussion
In general, the majority of instructors from the Language Center at PAAET showed positive attitudes towards using and accepting technologies.

Performance Expectancy (PE)
Prior research has established a relationship between PE and Behavioural Intention to use e-learning technologies (Pullen et al., 2015;Lowenthal, 2010;San Martin & Herrero, 2012;Venkatesh et al., 2003). In this current study, four questions were devised to test key aspects of PE, notably how teachers perceived the usefulness of e-learning technologies for teaching and learning, to accomplish tasks faster, to communicate with students, and to facilitate teaching course content. The survey findings revealed that teachers were almost unanimous in their agreement that e-learning technologies were useful in their replies to all four questions. The overall M of the PE scale was (3.67), while the SD was (0.951), which underscores a high level of influence from PE on the use of e-learning technologies.
It can be concluded that PE can help explain variances in English language instructors' Behavioural Intention to engage with e-learning. Although teachers find it difficult to adopt e-learning technologies in their teaching practices, they still expect e-learning tools to improve the educational experience for teachers and students alike. This indicates that English language instructors would engage with e-learning when they deem it beneficial for their educational experience.

Effort Expectancy (EE)
In this study, EE is defined as the ease of use of e-learning technologies at PAAET colleges. The majority of English language instructors had positive attitudes towards the ease of use of e-learning technologies. The results show that EE positively influences teachers' intention to use e-learning technologies. These findings are in linee with prior studies (Venkatesh et al., 2003, Venkatesh & Zhang, 2010Wang & Shih, 2009).
The survey aimed to find out how the instructors perceive the ease and convenience of using e-learning technologies. In their responses, English language instructors have overwhelmingly shown that they find learning new technologies is an easy task, with the majority of them describing these technologies as clear and easy to use. The relevance of EE in this study is also reflected in earlier research (Im, Kim, & Han, 2008;Schaik, 2009), which finds that an increase in EE leads to an improvement in Behavioural Intention to accept and use e-learning technologies.

Social Influence (SI)
The SI variable is defined as the degree to which an individual perceives others' opinions as being important in respect to whether they should use new technologies such as e-learning technologies (Venkatesh, Davis, & Morris, 2007).
The survey investigated how teachers believe whether their colleagues, superiors, and students expected them to use e-learning and if they provided assistance in that respect. It also aimed to understand how the respondents view the perception of other people in their organization towards e-learning technologies. In contrast to previous studies, (Chan et al., 2010;Cheng, Yang, King, & Lyu, 2011;Loo, Yeow, & Chong, 2009), SI did not appear to have a substantial influence on English language instructors' intention to use e-learning technologies. According to findings in this study, SI does not seem to be an important factor for instructors' intentions to adopt e-learning technologies. This might be because there was not a clear policy or guidebook to help the instructors use e-learning technologies at the time of conducting this research. Indeed, PAAET only announced its intention to universally adopt e-learning technologies after the spread of the coronavirus impacted schools. (KUNA, 2020).

Facilitating Conditions (FC)
The FC construct in this study refers to the available technological and organizational resources to support the use of e-learning technologies (Venkatesh et al., 2003). FC was measured as the extent to which the necessary resources and technical support were provided, as well as the readiness of the classrooms and infrastructural foundations for e-learning technologies within the institution. Numerous studies have established that FC has a clear influence on the actual use of technology (Al Awadhi & Morris, 2008;Tibenderana, Ogao, Ikoja-Odongo, & Wokadala, 2010).
The results indicate that the English language instructors' attitudes towards the facilities that currently support their use of e-learning technologies are generally negative. However, the majority of instructors have expressed that they have the required resources to use e-learning technologies in college. This might be because they buy their resources. Williams, Rana, and Dwivedi (2015) argued that research has shown that BI was the only consistent factor in the UTAUT that could significantly predict the acceptance and use of e-learning technologies. The current study is consistent with the literature, as the English language instructors' BI to adopt e-learning methods, learn new technologies, or takes the required training, is positive. This factor was shown to be significant in explaining the variant degrees in English language instructors' use of e-learning technologies. A notable number of instructors reported their intention to attend training sessions, which means that they want to enhance their technological abilities for e-learning purposes.

Behavioural Use (BU)
It could be argued that, with the increase in online learning due to the COVID-19 restrictions, teachers would essentially increase their dependency on technology for teaching purposes.

Instructor Experience (IE)
A number of authors have suggested that IE influences teachers' attitudes about e-learning and that the degree of experience (e.g. high or low) can be related to the degree of certainty or hesitation in accepting and using e-learning technologies (Donnelly & McSweeney, 2008;Jimoyiannis & Komis, 2008;Wong & Shih, 2012).
The responses to IE questions in the survey show that a minority of the respondents reported using or experiencing the use of e-learning technologies as students. This can be related to the fact that education in Kuwait has been largely dependent on traditional learning methods at all levels since its inception. It can also be a result of the lack of proper technical infrastructure and technical training at educational institutes.
In conclusion, it can be argued that English academic staff accepts and uses technology to a large extent during the COVID-19 pandemic, although they asserted that technology facilities at their colleges are inadequate. At the same time, they have access to technologies that allow them to present their lessons; this might be due to the subjects they teach, with a large number of free online content for English language lessons. The study found a high level of acceptance and use of technology for educational purposes.

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