E-learning, quality management, and higher education in the UAE: evolution and current landscape

Introduction: This systematic review provides an overview of e-learning quality management in higher education institutions in the United Arab Emirates (UAE).

Methods: A systematic bibliographic search of relevant academic databases was conducted, identifying 11 articles published between January 2019 and July 2024. The literature review integrates information on the following areas: institutional readiness and implementation, student readiness, satisfaction, and intention; factors influencing the adoption and quality of e-learning; management and assessment; the impact of COVID-19 on e-learning and professional development; and faculty perspectives. Additionally, a general summary of the methodological quality of the analyzed studies is provided.

Results: The major issues discussed include the increased use of e-learning solutions due to governmental support, the necessity of culture-sensitive strategies, problems concerning academic and credit recognition, and possibilities for individualized learning and international cooperation. The review emphasizes the integration of the technological, pedagogical, and organizational aspects of the quality management approach. Solutions are proposed to enhance staff training and development processes, student services, and quality assurance systems in education that utilize information technologies. The study also outlines areas for future research, including a longitudinal study of all quality management practices and innovations in assessment methods for online learning.

Discussion: The findings of this research are beneficial for the UAE and enhance the understanding of e-learning quality management in the context of higher education in the region. It also informs policymakers and practitioners about various issues they may face.

1 Introduction

Over the past few decades, the advancement of information technology has become a significant factor affecting higher learning institutions. E-learning, or electronic learning, is a concept that refers to the administration of education, particularly the provision of educational information via technology, specifically through the Internet (Chitra and Raj, 2018; Goyal, 2012; Sangrà et al., 2012). Leading this process is e-learning, which has now emerged as a key component of modern education systems. This encompasses various modalities, including online courses, virtual classes, multimedia content, and those that can be accessed through mobile phones. E-learning refers to the use of networked information and communication systems and technologies in education and learning processes. The letter “e” in e-learning stands for “electronic,” and therefore, e-learning is a method of educational learning that takes place using electronic methods, which can be online or offline. However, it is more commonly used online due to its advantages (Chitra and Raj, 2018).

1.1 Background to the study

Studies such as those by Abernathy and Thornburg (2021) define e-learning as the use of information and communication technologies to facilitate access to online teaching and learning resources. Along these lines, Goyal (2012) states that it refers to a science of learning, where the learning process is achieved without requiring or involving the use of printed instructions or paper-based study materials. In addition to these, there are other definitions based on technology, delivery systems, communication, or educational paradigms. Technology-oriented definitions reflect the way in which electronic media are used to transmit knowledge. Delivery system-oriented definitions reflect how electronic media are used to provide real-time delivery of knowledge through web-based technological means of information exchange. Communication-oriented definitions focus on the communicative aspect of the process, in the sense that interactions between teachers and learners in e-learning occur through information and communication technologies, enabling interactivity for learning purposes. Definitions oriented to the educational paradigm highlight how the use of technologies and electronic media enhances students’ learning and education, as information exchange in e-learning occurs through a broader combination of sources—infrastructure, content, processes, computer systems, and networks, enabling the mediation of both synchronous and asynchronous learning for students (Sangrà et al., 2012).

In summary, when describing the concept of e-learning, three characteristics are essentially associated: distance learning, information and communication technology as a basis, and the support of Internet tools and network systems. However, e-learning is not only an integration of technologies in the educational learning process, but it also adopts a pedagogical model of learning, in which the role of the learner is considered essential, as they are responsible for their own improvement in the overall learning process and have an active role (Fernández-Rodríguez et al., 2014). A pedagogical model in learning implies a cognitive learning process based on specific learning and instructional methods. Such learning can be instruction-specific, problem-based, or situated learning, mental methods, and/or supported by computer systems (Chou, 2010).

Among the advantages of e-learning over other traditional teaching methodologies, studies such as those by Abed (2019) report improvements in the levels of communication and interaction between teachers and students, as dialog between both parties is facilitated, thereby enhancing the overall learning process for students. E-learning also offers equal opportunities to all learners, regardless of their differences in background or personality. With e-learning, everyone has the same degree of access to facilities and possibilities, as well as flexibility in their learning, allowing different points of view and opinions to be shared, thus enhancing the learning experience.

In addition, e-learning allows learners to choose their preferred learning method, as they can access a variety of learning materials, including visual aids, audio content, and reading materials. Moreover, e-learning means that learning can take place at any time, allowing learners to have continuous access to lessons and study materials. Learning methods are varied and easily accessible, enabling learners to make the most of their time. Considering the factors of time and place of learning, e-learning provides learners with a high level of flexibility, which is also applicable to students in higher education. In addition, compared to face-to-face classes, e-learning offers learners a large amount of information, which contributes to more effective learning. Moreover, since e-learning methods take into account individual needs and preferences as well as the pace of learning, this method is advantageous because it offers learners an opportunity for active learning (Abed, 2019).

Therefore, reduced costs, improved quality of learning, increased access to a greater amount of information, and flexibility in the learning process, as obtained with e-learning, enable learners to prepare themselves effectively, responding to the needs of a knowledge-based society.

However, e-learning also has certain disadvantages. Since online learning allows students to learn at their own pace, it often leads to reduced interactions with teachers or other students, which can potentially affect their overall communication and socialization skills. In addition, when not conducted under the supervision or control of face-to-face teachers, it can be ineffective if students do not regulate or discipline themselves. In addition, disadvantages include the lack of explanation or clarification processes (which are more effective in face-to-face sessions) for learners due to the remoteness of the learning method. In the case of e-learning, if exams are also conducted online, learners may not be able to regulate or control fraudulent activities or unethical methods used during exams (Zhao et al., 2015).

When it comes to access to higher educational resources, e-learning has become extremely popular due to its flexibility, convenience, and individualized approach. Higher learning institutions across the globe are integrating e-learning solutions as a way of expanding learning and training options, increasing learners’ participation, and accommodating diverse learners. The evolution of e-learning has been marked by several significant milestones, from the very beginning of using computers in instruction, in the form of CAI in the 1960s and 1970s, through the use of personal computers and CD-ROM-based instructional materials in the 1980s, and the use of the internet in the 1990s. Students of the 2000s have been offered online degree programs and massive open online courses. The students of the 2010s have been introduced to mobile learning and adaptive learning technologies. Currently, approaches to personalized learning supported by AI and virtual/augmented reality are being implemented in education (Wren, 2021).

Thus, the role of e-learning could not be explained any better than through the use of the United Arab Emirates (UAE) as a case study. The current UAE government has focused its economic strategy on the creation of a knowledge-based economy through the promotion of education and learning, as knowledge has been identified as one of the critical tools for economic growth and diversification, as spelled out in the UAE Vision 2021 (Wren, 2021). As a national priority, this is seen in the efforts of the country to become an educational hub for the region as well as the entire world through the admission of international students and institutions. The UAE carries a modern technology setting that is well suited for e-learning solutions which gives it an advantage in the quick uptake and versatility of the kinds of methods used (Wren, 2021).

1.2 The UAE context: unique characteristics and challenges

The UAE situation has some specific features that make it different from other e-learning settings and require a dedicated systematic study. To begin with, technological uptake in UAE higher education has been extremely fast, which is supported by high governmental investment and national digital transformation projects. Nevertheless, this quick implementation has been exceeding the creation of contextually relevant quality management models; thus, it has established a disconnect between the technological potential and the pedagogic implementation.

Second, institutions of higher learning in the UAE have extremely diverse students, with Emirati, Arab expatriates, and international students representing more than 200 countries. This diversity poses special challenges to e-learning design, where culturally sensitive pedagogy and multilingual support are necessary and cannot be met by the usual quality frameworks.

Third, the educational environment in the UAE is a combination of institutional forms such as traditional government universities, private institutions, and international branch campuses that have various quality assurance needs and practices. This diversity makes it difficult to have a consistent quality standard.

Fourth, the cultural context integrates traditional Arab and cosmopolitan internationalism to establish distinct demands with regards to student–faculty interactions, communication patterns, and learning preferences that shape the effectiveness of e-learning.

Lastly, the COVID-19 pandemic further increased the pace of e-learning implementation in the UAE, even on top of the already fast rates, generating the additional need to manage quality in times of crisis. Developing insights into the ways UAE institutions have overcome such a transition would be helpful in constructing robust educational systems.

All these elements form a distinct e-learning ecosystem that can no longer be conceptualized using generalized international literature; thus, a systematic review, especially in the case of the UAE, is warranted.

This systematic literature review will serve the above purpose by evaluating the current literature on the management of quality in the e-learning context in UAE higher learning institutions. This review aims to contribute to the recognition of trends in the field and the identification of areas that need further study by laying out the current state of knowledge. The information derived from this study will be useful for policymakers, practitioners, and scholars as a reference point in shaping and executing appropriate e-learning models in the UAE higher education context.

1.3 Problem statement

Although the application of e-learning technologies in UAE higher learning institutions is being adopted quite rapidly, minimal systematic knowledge exists regarding the implementation of quality management practices, factors affecting their effectiveness, and the comparison of quality management practices to international standards. This is a critical gap considering that the UAE has its own unique educational environment, where technological change is rapid, students are heterogeneous, institutions are varied, and the government is highly supportive of adopting digital change. Although there have been individual studies that have captured certain issues of e-learning in the UAE, a synthesis of quality management practices and challenges, including outcomes, has not been conducted comprehensively. This gap is addressed in this systematic review through the identification, evaluation, and synthesis of the available empirical research in the quality management of e-learning in UAE higher education.

1.4 Research objectives and questions

This systematic review is guided by the following research questions and objectives:

Research questions:

RQ1: What are the current trends and practices in e-learning implementation within UAE higher education institutions (HEIs)?

RQ2: What factors drive quality improvements in e-learning delivery in the UAE context?

RQ3: What quality management challenges and best practices emerge from UAE e-learning experiences?

RQ4: How do UAE institutions approach quality assurance in e-learning environments?

Main objectives:

1. To identify the current trends in e-learning implementation in UAE higher education institutions.

2. To determine the potential drivers of improvement in the quality of e-learning in the UAE context.

3. To examine the issues and trends in quality management in e-learning in UAE higher education.

4. To evaluate quality assurance methods for e-learning adopted by UAE institutions.

5. To provide specific recommendations on quality management for e-learning within UAE higher learning institutions.

1.5 Literature review

While our systematic review focuses on contemporary literature (2019–2024), it is important to acknowledge the foundational work in e-learning that shaped current practices. Early research from 2000 to 2015 established key quality dimensions, including among others, technological infrastructure, pedagogical design, learner support, and faculty development (Ehlers, 2009; Fernández-Rodríguez et al. 2014; Frydenberg, 2007). These foundational principles continue to inform current quality management frameworks, though adapted for modern technologies and contexts.

Modern e-learning quality management has moved past the initial technical issues to include pedagogical effectiveness, learner experience, and organizational capacity (Ehlers, 2009). Studies have shown that quality is multidimensional, encompassing system quality (technical functionality and reliability), information quality (content accuracy and relevance), service quality (institutional support and responsiveness), and outcome quality (learning achievement and satisfaction) (DeLone and McLean, 2003). The technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) have emerged as some of the most useful models to consider when analyzing factors that determine the adoption and effectiveness of e-learning, with a special focus on the entire spectrum of perceived usefulness, ease of use, social influence, and facilitating conditions (Venkatesh et al., 2003).

E-learning in the Gulf region has been typified by significant investment in technological infrastructure, high implementation schedules by the government, and pedagogical adaptation problems (Alkharang and Ghinea, 2013). Research in the (Gulf Cooperation Council) GCC states shows some general trends: a high level of technological preparedness and the need to develop faculty is accompanied by the demand among students to restrain their eagerness due to the fear of deteriorating the quality of interaction, and the desire to establish commitment to changes in the institution is complicated by the complexity of managing change (Alshehri et al., 2019). Nevertheless, the educational policies and institutional structures of each country, along with the cultural context, result in unique quality management issues that require contextualized inquiry. The systematic investigation of quality management practices in e-learning is not well conducted in UAE higher education, even though the importance of e-learning in the sector is increasingly being acknowledged. Although each study has examined one area of the topic, including technology acceptance, student satisfaction, and faculty views, there has not been a synthesis of all the areas to identify patterns, gaps, and best practices. This lack of synthesis is of special concern, considering the particular circumstances of the UAE and its desire to become an international center of education. To achieve the desired improvements and develop policies, it is important to understand the current conceptualization of quality, its implementation, and measurement in UAE e-learning.

The COVID-19 outbreak around the world has also intensified the use of e-learning solutions in the UAE and across the globe, as they are considered key options for continuing education during acute crises (Wren, 2021). Furthermore, e-learning can be effectively integrated with the UAE’s vision of emphasizing a culture of lifelong learning and building updated qualifications for employees to successfully respond to the new tendencies of the labor market (Wren, 2021).

However, in many cases, it is observed that individuals are not well prepared for the demands of higher educational needs placed on them, as in the case of using e-learning, which may result in poor academic performance and significantly impact their future and career (Chamorro-Premuzic and Frankiewicz, 2019). Additionally, the lack of a high-quality higher education system would result in significant waste and loss of educational resources (Kyllonen, 2012). Therefore, higher education systems should adapt their services, quality, and management to the needs and capabilities of students, especially their cognitive abilities and willingness to adapt to the demands of higher education courses, bearing in mind that higher education is a right for all (Kyllonen, 2012).

In this regard, it is important for higher education institutions (HEIs) to adequately understand the needs of students and meet them to benefit the economy and society as a whole (Chan, 2016). Therefore, it is worth noting that when talking about quality in relation to higher education, the support of technological advances and the Internet is equally important, considering their applications and implications in improving the overall quality of educational services, such as through e-learning (Chan, 2016).

In addition, high-quality standards are extremely crucial to ensure that higher education institutions realize positive benefits for all service stakeholders. High quality is important for higher education institutions to meet societal expectations and ensure that students are prepared to effectively serve their societies and economies. Developed countries consider quality codes for this purpose, which should be established and implemented in the services offered by organizations (Saiz-Alvarez, 2019).

Therefore, it is important for higher education institutions to be evaluated for their courses, programs, and quality of services. Such evaluations are essential to reflect on both their strengths and challenges in order to improve the overall quality of education that can be offered to students. Student participation in the decision-making processes of institutions is also an important factor in evaluation (Rivza et al., 2015).

If students perceive that the quality of the higher education they are receiving is poor, they will most likely participate less in educational activities, and therefore, their academic performance will also suffer. This implies that universities must meet students’ expectations regarding the quality of higher education they offer to ensure that students are satisfied (Dicker et al., 2018).

The quality of teaching and learning has become an crucial aspect of higher education, and in many countries, it is considered essential. To manage high quality in higher education, assessment methods are utilized through the improvement of academic programs or student performance assessments, from which quality can be managed through improvement measures. The quality of academic staff performance is equally important for managing quality in higher education (Martin and Parikh, 2017).

Looking at the UAE case, although higher education is a priority for the government, there are challenges facing the higher education sector that also challenge the quality of services. Some of the key challenges prevailing in higher education in the UAE include high levels of speed in technological and scientific excellence, which are essentially driven by developed countries; the challenge of aligning students completing course programs with the labor market and employment opportunities; the challenge of keeping up with the strategic requirements of the institutions; the mismatch between the needs and expectations of the labor market and the course programs and academic offerings of the institutions; and the challenge of maintaining government databases and quality in higher education based on the expectations and satisfaction levels of students (Sebihi, 2014). Addressing these challenges associated with higher education institutions often affects the focus on quality, which in turn adds to the quality challenges for institutions (Sebihi, 2014).

With increasing globalization and heightened competition in the market, students are also increasingly demanding higher levels of quality in education, and their choice of higher education institutions depends on the performance quality of these institutions. This is therefore a major challenge for institutions to overcome, as it has a direct impact on their competitive advantage in the marketplace, as well as on student satisfaction levels.

In this context, the university’s role in the UAE in terms of information technology has grown exponentially and synergistically, promoting innovations in several fields, among them education. The tertiary education institutions use information technologies not only to deliver classes through web conferences and keep students connected to the class but also to assist in managing and minimizing paperwork and providing students with links to much wider information and research bases. Such changes have been well witnessed in the UAE since the government has long focused on promoting a knowledge-based economy as well as branding the country as an education city (Salloum et al., 2019).

2 Method

2.1 Eligibility criteria

The inclusion criteria were carefully designed to ensure the review captured studies directly relevant to e-learning quality management in UAE higher education. The timeframe of 2019–2024 was selected to focus on contemporary practices, particularly capturing the significant shift during and after the COVID-19 pandemic. The English language was chosen as it is the medium of instruction in most UAE higher education institutions and the primary language of academic publication in this field. Peer-reviewed journal articles were prioritized to ensure methodological rigor and quality, though we acknowledge this may exclude some practitioner insights. The geographical focus on the UAE was essential given the country’s unique educational context, characterized by rapid technological adoption, diverse student populations, and government initiatives toward a knowledge-based economy. To determine the eligibility of studies for inclusion in this review, the following elements were considered as inclusion/exclusion criteria: (1) topic relevance, (2) language, (3) type of publication, (4) geographical focus, (5) study design, and (6) publication period. Table 1 shows the description of the inclusion and exclusion criteria used.

Table 1

Table 1. Inclusion and exclusion criteria.

2.2 Resources and search strategy

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol (Page et al., 2021) to achieve these objectives, ensuring a transparent and comprehensive review process. The search for scientific literature was carried out using the following databases: Web of Science, Scopus, Musader (Arabic scholarly database), Education Resources Information Center (ERIC), and IEEE Xplore. The inclusion of Musader was particularly important given the Arabic-speaking context of the UAE and the potential for region-specific publications. ERIC was included for its comprehensive coverage of education research, and IEEE Xplore for technical and engineering education perspectives.

The following terms were searched for in titles, abstracts, and keywords: (e-learning OR online learning OR distance education OR virtual learning OR educational technology) AND (higher education OR university OR college OR tertiary education) AND (United Arab Emirates OR UAE OR Emirates) AND (quality OR quality management OR quality assurance OR effectiveness OR excellence). The Boolean search strategy was adapted for each database according to its specific search syntax. We conducted preliminary searches to test the sensitivity and specificity of our search terms, ensuring we captured relevant studies while minimizing irrelevant results. All searches were documented in detail, including specific search strings used for each database, to ensure reproducibility.

2.3 Selection of studies

Initially, a blinded peer review procedure was carried out to perform the study identification and selection process, in which two independent reviewers used the above search strategies, thus ensuring the results’ reliability. At the end of the identification and selection process of studies by both reviewers, the selected articles were compared, and unclear cases were resolved by consensus or by a third reviewer.

After conducting systematic searches across five databases, a total of 34 records were identified (Web of Science: n = 9; Scopus: n = 11; Musader: n = 6; ERIC: n = 5; IEEE Xplore: n = 3). Prior to screening, 10 duplicate records were removed, resulting in 24 unique records. These 24 records were screened based on titles and abstracts, and 3 records were excluded for not meeting the general inclusion criteria. Full-text retrieval was sought for the remaining 21 reports; however, 2 reports could not be retrieved and were therefore excluded. Subsequently, 19 full-text articles were assessed for eligibility. Of these, 8 studies were excluded due to reasons such as an insufficient focus on the UAE context, limited relevance to e-learning quality management, or non-empirical study designs. Following this systematic selection process, a total of 11 studies met all inclusion criteria and were included in the final systematic review. The study selection process is summarized in the PRISMA flow diagram (Figure 1).

Figure 1

Figure 1. PRISMA flow diagram.

2.4 Data mining

The data extraction was a crucial step in our systematic review, designed to ensure a comprehensive and consistent collection of relevant information from each included study. We developed a standardized data extraction form to capture key elements that would allow for thorough analysis and synthesis of the literature. To this end, the following data were extracted from each study, if available: (1) main theme; (2) objectives of the study; (3) design (intervention type/design of the evaluation); (4) sample and characteristics; (5) instruments and/or variables; (6) data analysis; (7) results; (8) conclusions; and (9) limitations.

2.5 Quality of studies

Assessing the methodological quality of the primary empirical studies included in a systematic review is a critical step, as it ensures that the synthesized results are based on methodologically sound research. For this review, we used the Mixed Methods Appraisal Tool (MMAT) Version 2018 (Hong et al., 2018) to evaluate the quality of the included primary studies (not the systematic review itself). The MMAT is a critical appraisal tool designed explicitly for assessing original empirical research studies rather than review articles. It enables the methodological quality of five categories of studies to be evaluated: qualitative research, randomized controlled trials, non-randomized studies, quantitative descriptive studies, and mixed-methods studies.

This instrument is composed of two initial questions for all study types: “Are there clear research questions?” and “Do the collected data allow addressing the research questions?” These two screening questions should be answered with “Yes,” “No,” or “Cannot tell.” Answering one or both of these questions negatively may indicate that the article is not an empirical study and therefore cannot be evaluated with the MMAT. Once the initial questions have been answered, the instrument allows evaluation of the methodological quality of the studies classified into five categories (1. Qualitative, 2. Quantitative randomized controlled trials, 3. Quantitative non-randomized, 4. Quantitative descriptive, and 5. Mixed methods), each with five items.

In the present study, categories (4) quantitative descriptive and (5) mixed methods have been used since the studies included in the review are of this type. The five items evaluated for each study should be answered with “Yes,” “No,” or “Cannot tell” (when the study does not clearly report the related criterion). Following the MMAT guidelines, we did not compute a single overall quality score from these ratings. Instead, we present a detailed distribution of scores for each criterion to inform the appraisal of the included studies, which also allows for sensitivity analyses based on study quality.

3 Results

The studies’ results provided valuable insights into various aspects of e-learning in higher education, particularly in the context of the United Arab Emirates (UAE), as shown in Table 2. These findings encompassed a range of topics, including institutional readiness, student perceptions and acceptance, factors influencing e-learning quality, and the impact of e-learning during the COVID-19 pandemic. The following provides a detailed description of the topics covered, characteristics, results, and conclusions of the analyzed studies.

Table 2

Table 2. Table of results (n = 11 studies).

3.1 Institutional readiness and implementation

Institutional readiness represents a foundational prerequisite for effective e-learning quality management, encompassing technological infrastructure, organizational capacity, and strategic planning. Shawar et al. (2024) conducted a survey research study to assess the readiness of higher education institutions in the UAE to adopt e-learning and online learning. Using the e-Learning Readiness Criteria Form (e-LRCF), they collected data from 54 participants, including faculty, students, higher management, and external reviewers. Their analysis revealed that learner engagement and assessment were significant predictors of institutional readiness. Interestingly, program design and delivery did not significantly predict readiness. These findings suggest that UAE institutions should focus on enhancing learner engagement and assessment strategies to improve their e-learning readiness while also paying attention to program design and delivery aspects.

These findings align with international research, which emphasizes that institutional readiness extends beyond technological adequacy to include organizational culture, leadership commitment, and change management capabilities (Mercado, 2008). The UAE context appears to demonstrate strong technological readiness, but it also faces emerging challenges in pedagogical adaptation and faculty development.

3.2 Student readiness, satisfaction, and intention

Student readiness, satisfaction, and behavioral intentions constitute critical quality indicators, reflecting the learner-centric dimension of e-learning effectiveness. Moussa (2023) examined students’ preparedness, satisfaction, and perception of e-learning, as well as their future usage within UAE higher education institutions. The study, which included a sample of 476 undergraduate students aged 18–23 years, found a high level of student readiness for e-learning at 82%. At the same time, the satisfaction rates were moderate at 77%, and the behavioral intention to continue with e-learning also stood at 77%. The study identified the predictors of behavioral intention as concern satisfaction, e-learning system outcomes, perceived usefulness, and interaction. The findings of this study provide evidence that UAE students are ready for and receptive to e-learning; nevertheless, there is potential for increasing both the satisfaction rate and the quality of the system regarding this type of learning module.

These findings suggest that while UAE students possess high technological readiness, sustained engagement and continued use depend on system quality, pedagogical effectiveness, and meaningful interaction—factors that extend beyond infrastructure provision to encompass instructional design and faculty capability.

3.3 Factors influencing the adoption and quality of e-learning, management, and assessment

Understanding the factors that influence e-learning adoption and quality is essential for developing effective quality management strategies, as these factors shape both initial acceptance and sustained effectiveness.

Some previous work focused on the following issues related to e-learning adoption and quality among higher education institutions in the UAE. Cao et al. (2022) identified the following relative factors that determine the use of e-learning instead of information technologies in a traditional classroom. Namely, by analyzing 569 UAE higher education students through partial least squares structural equation modeling (PLS-SEM), the authors indicate that relative computer self-efficacy, cognitive absorption, system interactivity, and system functionality affect relative performance and effort expectancy. Furthermore, a positive relative attitude positively impacted the relative intention to use e-learning systems, while relative facilitating conditions also positively influenced it. Thus, these findings suggest that the tangibility of the system and users’ perceptions are critical factors in the acceptance of e-learning.

Similarly, Chaudhry et al. (2021) analyzed the effectiveness of the adopted e-learning system in UAE HEIs using the DeLone and McLean (2003) information systems success model. Their sample consisted of 1,266 students from 38 public and private universities in the UAE. Using structural equation modeling (SEM), they found positive relationships between future e-learning use and four key factors: system quality, information quality, perceived usefulness, and user satisfaction. While these findings indicate successful implementation in several aspects, program design and delivery require further enhancement.

Salloum et al. (2019) sought to understand the students’ acceptance of e-learning using a rich technology acceptance model (TAM). Their quantitative study, which involved 435 students from five UAE universities and employed PLS-SEM, provided 70% support for the 23 hypotheses that had been developed. In this study, system quality was considered to positively influence perceived ease of use, as did computer self-efficacy and playfulness. While perceived ease of use and usefulness were negatively affected, information quality, enjoyment, and accessibility were positively impacted. As a result of these studies, there is a general understanding of the possible variables that may explain the acceptance of e-learning in higher education institutions in the UAE.

Likewise, in another study by Salloum and Shaalan (2019), the authors employed the unified theory of acceptance and use of technology (UTAUT) model to identify the key factors influencing students’ acceptance of e-learning systems in higher education institutions in the UAE. Their quantitative investigation was conducted to determine the level of behavioral intention among 280 university students to use e-learning, based on their performance expectancy, social influence, and facilitating conditions, as assessed by a self-developed questionnaire subjected to PLS-SEM analysis. Most of the present research results confirm the UTAUT model for e-learning acceptance and identify social influence and facilitating conditions as essential for acceptance in the UAE context.

El-Sakran et al. (2022) aim to identify the potential drivers of e-learning quality improvement in the UAE context. This study was conducted on a sample of 588 undergraduate students and a focus group of 10 students at the American University of Sharjah, UAE, using an online survey with questions on course quality, academic performance, preparation for future work/studies, and psychological distress (K10 scale). Results of structural equation modeling (SEM) and confirmatory factor analysis (CFA) indicated that course quality has a significant impact on both academic performance and readiness for work/future studies. These factors mediated the effect of course quality on psychological distress. The quality of Emergency Remote Teaching (RTE) significantly influences students’ academic outcomes and mental health; therefore, strategies are needed to improve resilient RTE environments. However, the data should be taken with caution as they are limited to a single university, self-reported measures, and the cross-sectional design limits causal inferences.

The convergence of findings across these studies reveals that successful e-learning quality management in the UAE requires attention to multiple interconnected factors: technological (system functionality and interactivity), individual (self-efficacy and attitude), pedagogical (course design and instructor effectiveness), and institutional (facilitating conditions and support structures). This multidimensional framework aligns with established models such as UTAUT and TAM while highlighting UAE-specific considerations.

3.4 Impact of COVID-19 on E-learning

The COVID-19 pandemic served as a natural experiment in the rapid adoption of e-learning, revealing both the capabilities and constraints in UAE higher education quality management under crisis conditions. The COVID-19 outbreak influenced the adoption and attitudes toward e-learning in UAE higher education institutions. In another study conducted by Anderson et al. (2022), the authors focused on preservice teachers’ perceptions of online learning during the COVID-19 lockdown, using a mixed-methods case study involving 35 preservice teachers pursuing their bachelor of arts in education and early childhood studies. Their study concluded that most students employed deep or strategic approaches to learning and favored didactic instruction. Although online learning was viewed as effective, students discussed that they felt disconnected from campus.

Alhasan and Al-Horani (2021) evaluated imaging students’ perspectives on COVID-19 awareness and the online delivery of radiography programs. Their cross-sectional survey of 212 female radiography students from two UAE campuses revealed an acceptable overall COVID-19 awareness (70%). However, online teaching satisfaction was less than 50% for most factors, and stress levels were reported as high. The study highlighted challenges in delivering lab and clinical courses online and emphasized the need for engagement and improved critical thinking development.

In the study by Al Mansoori et al. (2022), how Blackboard Learn (BBL) was used and faculty perceptions were investigated during the COVID-19 pandemic in a UAE institute of higher education. This study was conducted through a quantitative survey-based approach with some open-ended qualitative questions, sampling 329 faculty members at a multi-campus higher education institute in the UAE. It was found that, in general, perceptions of BBL were positive. Problems tended to relate to the online learning modality and not specifically to BBL. Blackboard Learn supported faculty in meeting teaching objectives and enhancing interaction with students. Some obstacles related to functionality, appropriateness as a substitute for face-to-face learning, the faculty learning curve, and practical issues.

The pandemic findings reveal a paradox: while emergency remote teaching demonstrated the feasibility of large-scale online education, it also exposed significant quality gaps in pedagogical design, faculty preparation, and student support. This suggests that crisis-driven adoption differs substantially from planned, quality-focused implementation, emphasizing the need for systematic quality management frameworks rather than reactive technology deployment.

3.5 Professional development and faculty perspectives

Faculty perspectives and professional development represent critical dimensions of quality management, as instructional quality ultimately depends on the capabilities of educators and the support of institutions. Several studies have examined professional development activities and faculty perspectives on e-learning. Albaz and Agha (2023) assessed healthcare professionals’ perspectives toward professional development activities using a synchronous learning approach. In Albaz and Agha's (2023) cross-sectional study, which was based on surveys of 136 healthcare professionals at KSAU-HS and UAEU, participants appreciated content diversity, presentation quality, and facilitator expertise. Most participants reported that the webinar content met objectives and was effective. The themes that emerged included overall effectiveness, educational advantage, quality of topics, the role of speakers, and challenges faced. These studies demonstrate the potential of synchronous online learning for professional development in the healthcare sector.

Al Mansoori et al. (2022) focused on the acceptance of Blackboard Learn (BBL) and the perception of faculty during the COVID-19 pandemic in UAE higher education institutes. This study was conducted with 329 participants, who were faculty members, and they had relatively positive attitudes toward BBL, which enabled the faculty to conduct numerous teaching activities. It is apparent from the challenges identified by the participants that they often referred to the online learning mode rather than BBL. More specifically, the study’s outcome revealed that BBL helped the faculty attain teaching goals and foster student engagement. Nonetheless, some challenges were associated with functionality, course relevancy as a replacement for in-person learning, faculty familiarity with the software, and other logistics.

These findings underscore the importance of continuous professional development and institutional support systems for maintaining e-learning quality. Faculty acceptance and competence emerge as mediating factors between technological infrastructure and educational outcomes, underscoring the need for quality management to address both human and technical dimensions.

3.6 General summary of main findings

After an in-depth analysis of the studies included in this review, a general description of the most relevant elements found is provided.

The main themes were the current state of e-learning implementation, factors influencing e-learning quality, student and faculty perspectives, and the effectiveness of existing quality management strategies in the UAE higher education sector. The objectives of the various studies conducted in relation to e-learning and higher education were diverse. These ranged from assessing institutional readiness for e-learning adoption to investigating factors affecting student acceptance and exploring the impact of COVID-19 on online learning delivery.

Regarding the interventions carried out by the different studies, these were primarily survey-based research designs, with some studies employing quantitative methods or mixed-methods approaches. The design of the evaluations varied, including cross-sectional surveys, focus groups, and quantitative analyses using structural equation modeling (SEM) or partial least squares SEM (PLS-SEM). Some studies also incorporated qualitative elements through the use of open-ended questions or focus groups.

The sample characteristics varied depending on the study objectives. Students in higher education were the focus of most studies, with sample sizes ranging from 35 to 1,266 participants. Some studies also included faculty members, with one study surveying 329 faculty members. Data analysis methods aligned with the research designs, ranging from descriptive statistics and correlation analyses to more complex approaches such as structural equation modeling, confirmatory factor analysis, and thematic analysis for qualitative data.

The results of the studies provided insights into various aspects of e-learning in UAE higher education, including levels of institutional readiness, factors influencing student acceptance and satisfaction, the impact of course quality on academic performance and psychological wellbeing, and the effectiveness of online professional development activities. The main conclusions drawn were that e-learning implementation in UAE higher education is generally well received but faces challenges in areas such as engagement, assessment, and the delivery of practical courses. Many studies emphasized the need for continued improvement in e-learning quality management and the importance of considering both technological and pedagogical factors.

A notable limitation across the included studies is the potential for sampling bias. Many studies relied on convenience sampling from single institutions or specific student populations, which may not accurately represent the diverse landscape of higher education in the UAE. The UAE context includes multiple institution types (public vs. private, international branch campuses, local institutions), diverse student populations (Emirati nationals, Arab expatriates, international students), and varying levels of technological infrastructure. Future research should employ stratified sampling strategies to capture this diversity and enhance the generalizability of findings.

3.7 Synthesis of findings: convergence and divergence

The reviewed studies reveal both consensus and contradictions that merit explicit acknowledgment and interpretation.

Areas of consensus:

Across the 11 included studies, several findings demonstrate strong consistency:

1. High technological readiness: All studies confirm that UAE higher education institutions possess robust technological infrastructure for e-learning delivery, supported by substantial governmental investment and institutional commitment.

2. Student digital readiness: Multiple studies report that UAE students generally demonstrate high levels of technological literacy and readiness for e-learning, with readiness scores consistently exceeding 75% (Shawar et al., 2024; Moussa, 2023).

3. Faculty development needs: There is universal agreement that faculty members require enhanced training in online pedagogy, instructional design, and the effective use of learning management systems, regardless of their technological proficiency.

4. Quality-outcome relationships: Studies consistently demonstrate that course quality has a significant impact on academic performance, student satisfaction, and behavioral intentions (Chaudhry et al., 2021; El-Sakran et al., 2022; Moussa, 2023).

Areas of divergence:

Several significant contradictions emerge across the reviewed literature:

1. Student satisfaction variations: Reported satisfaction levels vary dramatically, from less than 50% in radiography programs (Alhasan and Al-Horani, 2021) to 77% in general undergraduate populations (Moussa, 2023). This divergence likely reflects differences in program types, institutional contexts, student expectations, measurement instruments, and the specific aspects of e-learning being evaluated.

2. Relative importance of factors: While some studies emphasize system quality and technological functionality as primary determinants of success (Cao et al., 2022; Chaudhry et al., 2021), others prioritize pedagogical factors such as instructional design and faculty–student interaction (El-Sakran et al., 2022). This disagreement may reflect different theoretical frameworks (technology acceptance vs. learning effectiveness models) or disciplinary perspectives.

3. Emergency remote teaching effectiveness: Studies offer conflicting assessments of COVID-19 emergency remote teaching, with some highlighting successful adaptation (Anderson et al., 2022), while others document substantial dissatisfaction and stress (Alhasan and Al-Horani, 2021). These contradictions likely stem from variations in institutional preparedness, program characteristics, and student populations.

4. Blackboard Learn acceptance: While Al Mansoori et al. (2022) report generally positive faculty perceptions of Blackboard Learn, qualitative comments reveal significant concerns about functionality and appropriateness for certain teaching contexts. This mixed evidence suggests that aggregate satisfaction scores may mask important nuances.

Unexplored tensions:

Several important areas remain underexamined in the existing literature:

1. Institutional type comparisons: Limited research explicitly compares quality management practices across public, private, and international branch campus institutions in the UAE, despite their structural differences.

2. Long-term sustainability: Most studies employ cross-sectional designs, leaving questions about the long-term sustainability of pandemic-era adaptations and quality improvements unanswered.

3. Cultural dimensions: While the UAE’s cultural diversity is frequently mentioned, few studies systematically examine how cultural factors shape quality perceptions and effectiveness.

4. Discipline-specific considerations: With the exception of Alhasan and Al-Horani’s (2021) focus on radiography, most studies aggregate across disciplines, potentially obscuring important variations in quality requirements and challenges.

These patterns of convergence and divergence suggest that e-learning quality in UAE higher education is influenced by complex interactions among technological, pedagogical, institutional, and contextual factors. Future research should explicitly address these contradictions through comparative designs, longitudinal approaches, and theoretically informed investigations of moderating factors.

Regarding the assessment of study quality, based on the criteria established by the Mixed Methods Appraisal Tool (MMAT) (Hong et al., 2018), most of the analyzed studies obtained positive responses for the five evaluated items. However, in the studies by Shawar et al. (2024), Alhasan and Al-Horani (2021), El-Sakran et al. (2022), and Moussa (2023), the sampling strategy used to address the research question could not be determined as it is not reported. Similarly, in the studies by Albaz and Agha (2023) and El-Sakran et al. (2022), it has not been possible to determine whether the sample is representative of the target population as they do not report this. In the studies by Al Mansoori et al. (2022), and Anderson et al. (2022), they report that the samples may not be representative. On the other hand, in the studies by Alhasan and Al-Horani (2021), El-Sakran et al. (2022), and Moussa (2023), they do not report the risk of nonresponse bias. This suggests that while the overall quality of research in this area is good, there is still room for improvement in methodological rigor and reporting standards. Table 3 below shows the criteria analyzed and achieved for each study.

Table 3

Table 3. Results of the methodological quality assessment (n = 11 studies).

4 Discussion

This systematic review synthesizes several important insights into e-learning quality management in UAE higher education that both align with international literature and reveal additional context-specific patterns. Rather than merely summarizing individual study findings, this discussion interprets emerging themes, examines contradictions, explores theoretical implications, and considers practical applications for policy and practice.

E-learning has effectively expanded educational opportunities and improved flexibility in UAE higher education institutions. The convergence of evidence from multiple studies reveals a paradox: while Shawar et al. (2024) and Moussa (2023) report a high level of institutional preparedness and students’ receptiveness toward e-learning, other studies (Alhasan and Al-Horani, 2021; El-Sakran et al., 2022) reveal significant gaps in pedagogical quality and student satisfaction. This suggests that readiness encompasses multiple dimensions—technological infrastructure, pedagogical capability, organizational culture, and stakeholder attitudes—that do not continually develop in parallel. UAE institutions appear to have achieved technological readiness more readily than pedagogical transformation, reflecting patterns observed in rapid technology adoption contexts globally (Hew et al., 2020).

Despite all these possible advantages, the review has also highlighted essential difficulties that hinder the development of high-quality e-learning in the UAE’s higher education. Such difficulties entail technological structure limitations, instructor opposition, and the cultural appropriateness of the content (Al Mansoori et al., 2022). The present results align with the trends observed in the literature regarding e-learning implementation while also addressing concerns specific to the UAE.

The studies by Alhasan and Al-Horani (2021) and El-Sakran et al. (2022) are especially relevant, as they cover the COVID-19 period, dissatisfaction with online teaching for practice-oriented courses, and the moderating effect of course quality on students’ psychological issues, respectively. These results have signaled the need to establish enhanced e-learning implementation strategies that reflect broader benchmarks and local conditions.

The review highlights the need for holistic QM frameworks that comprise technological, pedagogical, and organizational factors. This is in concordance with the studies conducted by Cao et al. (2022) and Salloum and Shaalan (2019), where different factors were revealed to define e-learning adoption and its quality, such as the characteristics of the system, the perception of the users, and the institutional support offered to the consumers of e-learning solutions.

The COVID-19 pandemic has significantly increased the utilization of e-learning among learners and faculty members in UAE higher education. Therefore, quality management practices require enhancement with improved quality assurance methods. For instance, Anderson et al. (2022) and Al Mansoori et al. (2022) investigated the shift to online learning during the COVID-19 pandemic. In these studies, it is possible to identify the potential of e-learning to continue education during crises, the problems that arise in this context, and the fluctuation of learning outcomes and students’ interest.

Based on the discussion of the identified aims of this review, this study can assert that it provides a relevant and valuable contribution to the current state of knowledge and understanding of e-learning quality management in UAE higher education. It also presents the evolving state of this specific field of study and practice, which may be instrumental in shaping relevant future research agendas and policymaking initiatives.

4.1 Synthesis of key findings

The results of this systematic literature review have several significant implications for managing the quality of e-learning experiences in higher education institutions in the UAE. The impact of the findings of this systematic literature review on the quality management of e-learning in UAE higher education is as follows. Institutions should adopt a comprehensive approach to e-learning quality management that addresses technological, pedagogical, and organizational dimensions, aligned with broader higher education goals and UAE-specific needs. There is a clear need for ongoing professional development programs to enhance faculty competencies in e-learning design, delivery, and assessment, with a focus on technical skills and pedagogical approaches that are suitable for online environments.

Institutions should invest in robust student support systems that address the unique challenges of e-learning, including time management, self-motivation, and digital literacy skills. E-learning content and pedagogies should be tailored to reflect the cultural context of the UAE, ensuring relevance and engagement for local students while catering to the diverse international student population. There is a need to develop and implement e-learning-specific quality assurance frameworks beyond traditional accreditation models and to address the unique aspects of online and blended learning environments.

Institutions should explore innovative technologies, such as artificial intelligence and learning analytics, to enhance the quality and personalization of e-learning experiences. Finally, encouraging collaboration between institutions within the UAE and internationally can facilitate the exchange of best practices and drive continuous improvement in e-learning quality management.

4.2 Limitations and proposals for future research

This section outlines the main methodological and conceptual limitations identified in the present research and provides corresponding directions for future inquiry and policy development. Each limitation is presented together with its contextual meaning, practical and theoretical implications, and specific proposals for subsequent research. In addition, policy-oriented recommendations are included to bridge the identified gaps between academic knowledge, institutional practice, and policymaking. This structured approach aims to promote a cumulative scientific understanding of e-learning quality management in UAE higher education by clarifying the boundaries of the current study and delineating feasible paths for future investigations and applications.

4.2.1 Limitation 1: limited timeframe (2019–2024)

What it means: The review, which focused on recent publications, may have excluded relevant earlier research that established foundational principles or identified persistent challenges.

Implications:

• We may lack a historical perspective on whether current challenges are new or longstanding.

• The evolution of quality practices over time cannot be fully traced.

• Foundational theoretical work may be underrepresented.

Future research:

• Conduct historical analysis of e-learning quality evolution in the UAE from early adoption (2000s) to present.

• Examine whether quality challenges have changed or remained constant over time.

• Trace policy developments and their quality impacts longitudinally.

Policy recommendations:

• Institutional quality management should include historical assessment identifying persistent vs. emerging challenges.

• Quality frameworks should be evaluated against long-term outcome data, not just immediate satisfaction.

• Institutions should maintain quality archives documenting practices, challenges, and outcomes for future learning.

4.2.2 Limitation 2: language restrictions (English only)

What it means: Excluding Arabic-language publications may have missed locally published research, institutional reports, or practitioner perspectives not available in English.

Implications:

• Potentially incomplete representation of UAE-specific insights and innovations.

• Possible bias toward internationally oriented research over locally focused work.

• May miss cultural perspectives more fully expressed in Arabic scholarship.

Future research:

• Conduct parallel systematic review of Arabic-language literature on UAE e-learning quality.

• Investigate whether Arabic and English publications emphasize different quality dimensions.

• Examine practitioner knowledge documented in institutional reports and gray literature.

Policy recommendations:

• Institutions should document quality initiatives in both Arabic and English ensuring knowledge accessibility.

• Encourage bilingual publication of significant quality research and innovations.

• Establish Arabic-language quality resources and frameworks alongside English versions.

4.2.3 Limitation 3: peer-reviewed focus excluding practitioner knowledge

What it means: Requiring peer-reviewed publications excluded institutional reports, case studies, and practitioner knowledge that may not reach academic journals but contain valuable quality insights.

Implications:

• Gap between published research and actual institutional practices.

• Innovative quality approaches used but not formally studied may be missed.

• Implementation challenges faced by practitioners may be underrepresented.

Future research:

• Conduct surveys and interviews with quality managers, e-learning directors, and institutional leaders to capture practitioner knowledge.

• Develop case study series documenting institutional quality initiatives and their outcomes.

• Create knowledge exchange platforms where practitioners share experiences and innovations.

Policy recommendations:

• Establish UAE-wide e-learning quality knowledge repository including both research and practice documentation.

• Encourage practitioner–researcher partnerships bridging academic knowledge and practical implementation.

• Develop mechanisms for rapid dissemination of quality innovations across institutions.

4.2.4 Limitation 4: small number of included studies (n = 11)

What it means: The relatively small number of studies meeting inclusion criteria reflects limited systematic research on e-learning quality management specifically in UAE higher education.

Implications:

• Findings may not be fully representative of the diverse UAE higher education landscape.

• Statistical generalization is limited; findings should be considered exploratory.

• Important quality dimensions may be unstudied rather than unimportant.

• The scarcity itself is a significant finding indicating research need.

Future research:

• Conduct large-scale multi-institutional quality assessments across diverse UAE institutions.

• Develop research consortia pooling resources for comprehensive quality investigations.

• Establish research funding priorities for e-learning quality studies.

• Encourage doctoral dissertations and master’s theses on UAE-specific quality topics.

Policy recommendations:

• The Ministry of Education should fund systematic quality research as the basis for evidence-based policy.

• Institutions should allocate resources for quality assessment and research, not just implementation.

• Establish data-sharing agreements allowing researchers access to institutional quality data.

• Create incentives for publishing quality research to build the evidence base.

4.3 Theoretical implications

The findings of this review suggest that traditional e-learning quality frameworks need to be contextualized for the UAE environment. While established models, such as DeLone & McLean’s Information Systems Success Model (2003) and the Unified Theory of Acceptance and Use of Technology (UTAUT), provide valuable starting points, they do not fully account for the unique characteristics of UAE higher education that emerged across the reviewed studies.

Standard quality frameworks typically emphasize dimensions such as system quality, information quality, service quality, and user satisfaction (DeLone and McLean, 2003). The UAE studies confirm these dimensions’ relevance but reveal additional considerations:

1. Cultural sensitivity: The UAE’s diverse student body (Emirati nationals, Arab expatriates, international students from 200 + countries) creates unique quality requirements around multilingual support, culturally appropriate communication styles, and pedagogical approaches that respect different learning traditions. None of the reviewed studies systematically addressed this dimension, representing a significant gap in both theoretical and practical terms.

2. Institutional heterogeneity: Unlike many national higher education systems, the UAE context combines public universities, private institutions, and international branch campuses, each with different quality assurance frameworks, accreditation requirements, and organizational cultures. Quality management models must account for this structural diversity rather than assuming institutional homogeneity.

3. Rapid technological change: The UAE government’s strong support for digital transformation creates an environment of continuous technological evolution that outpaces pedagogical adaptation. Quality frameworks must therefore address not just static quality achievement but dynamic quality maintenance amid ongoing change.

4. Crisis resilience: The COVID-19 pandemic revealed that quality management must encompass not only optimization of normal operations but also rapid adaptation capability. This suggests that quality frameworks should include resilience dimensions—such as flexibility, adaptability, and continuity planning—alongside traditional effectiveness and efficiency criteria.

4.3.1 Proposed integrated framework

Building on these insights, we propose an adapted quality management framework for UAE e-learning that integrates:

1. Technical infrastructure quality: System functionality, reliability, accessibility (traditional dimension).

2. Pedagogical quality: Instructional design, faculty competence, student engagement (traditional dimension).

3. Service quality: Support services, responsiveness, user experience (traditional dimension).

4. Cultural responsiveness: Multilingual capability, culturally appropriate pedagogy, diverse learning style accommodation (UAE-specific dimension).

5. Institutional agility: Change management capacity, professional development systems, continuous improvement processes (UAE-specific dimension).

6. Stakeholder diversity management: Addressing the varied needs of multiple student populations, faculty backgrounds, and institutional models (UAE-specific dimension).

7. Resilience capacity: Crisis adaptation capability, continuity planning, flexible delivery modalities (emerging global dimension highlighted by UAE experience).

This framework suggests that quality in UAE e-learning is not merely high performance on universal dimensions but also effective management of context-specific challenges. Future research should operationalize and validate these additional dimensions through the development of instruments and empirical testing.

4.3.2 Theoretical tensions

The reviewed studies reveal several unresolved theoretical tensions:

1. Technology-centered vs. pedagogy-centered quality: Some studies prioritize technological functionality while others emphasize instructional effectiveness. This tension likely reflects disciplinary perspectives (information systems vs. education) but raises fundamental questions about whether technology or pedagogy should drive quality conceptualization.

2. Universal vs. culturally specific standards: International accreditation frameworks promote universal quality standards; however, the UAE context suggests that quality may be partially culturally constructed. How can institutions strike a balance between global standardization and local relevance?

3. Top–down vs. bottom–up quality management: Some studies emphasize institutional policies and systems (top–down), while others focus on faculty practices and student experiences (bottom–up). Effective quality management likely requires both, but the optimal integration of these remains unclear.

These tensions warrant explicit theoretical attention and empirical investigation in future research, as they shape both the quality of conceptualization and management practice.

4.4 Areas of divergence and debate

The reviewed literature reveals several areas of debate and contradictory evidence regarding the quality of e-learning in the UAE.

4.4.1 Student satisfaction: measurement or reality?

Student satisfaction rates vary dramatically across studies, from less than 50% (Alhasan and Al-Horani, 2021) to 77% (Moussa, 2023). This divergence reflects methodological differences—varied instruments, response scales, and sampling approaches—as well as genuine contextual variation across program types, pandemic versus non-pandemic conditions, and student expectations. This highlights the need for standardized satisfaction instruments, multidimensional conceptualization, and contextual interpretation rather than aggregate comparison.

4.4.2 Relative importance of quality factors: technology or pedagogy?

Studies disagree on whether technological or pedagogical factors have a more substantial influence on e-learning success. This disagreement may reflect disciplinary perspectives, threshold effects (where technology is necessary but not sufficient), or contextual variation. In the UAE, with a strong technological infrastructure, pedagogical excellence may be increasingly differentiated.

4.4.3 Emergency remote teaching: success or failure?

Studies offer starkly different assessments of emergency remote teaching during the COVID-19 pandemic, reflecting program differences, institutional preparedness, student populations, and faculty readiness. Emergency measures should not be conflated with planned, quality-focused e-learning.

4.4.4 LMS effectiveness: platform or practice?

Mixed evidence on Blackboard Learn suggests that effectiveness depends primarily on how faculty utilize the features rather than on platform selection. Quality management should emphasize capability development and pedagogical innovation over platform procurement.

4.4.5 Methodological debates

Most studies rely on self-reported data from cross-sectional, single-institution designs focusing on student perspectives. Comprehensive quality assessment requires triangulation across multiple data sources, methods, time points, and contexts.

4.4.6 Embracing complexity

These divergences suggest that e-learning quality is context-dependent, multidimensional, dynamically constructed, and influenced by multiple factors that operate simultaneously. Future research should explicitly investigate these complexities rather than seek a single answer.

5 Conclusion

This systematic review synthesizes valuable insights into e-learning quality management in UAE higher education based on rigorous analysis of 11 empirical studies published between 2019 and 2024. The findings reveal both significant progress in e-learning implementation and persistent critical challenges in quality management.

The review identifies multiple interconnected dimensions critical to e-learning quality in the UAE context: (1) robust technological infrastructure, which UAE institutions essentially possess; (2) pedagogical excellence in instructional design and delivery, where significant development needs remain; (3) faculty competence requiring ongoing professional development; (4) student engagement strategies appropriate for diverse learning preferences; (5) culturally responsive design addressing the UAE’s multicultural environment; and (6) institutional support systems enabling sustainable quality management. These dimensions must be addressed holistically rather than in isolation, as technology alone cannot compensate for pedagogical weaknesses, nor can excellent teaching overcome inadequate infrastructure or support systems.

Theoretically, this review contributes to the understanding that established e-learning quality frameworks require contextualization for the UAE environment. While international models provide valuable starting points, they do not fully account for UAE-specific factors, including the rapid technological adoption that outpaces pedagogical adaptation, extreme institutional diversity within a small geographic area, highly multicultural student populations, and strong governmental support combined with evolving regulatory requirements. The proposed integrated framework, which incorporates both universal quality dimensions and UAE-specific considerations, provides a foundation for future theory development and empirical testing.

Looking forward, the UAE higher education sector has a significant opportunity to leverage new technologies and develop innovative quality management approaches that could serve as models for other rapidly developing educational systems. The UAE’s advantages—substantial technological investment, governmental support for innovation, a diverse institutional landscape that facilitates experimentation, and a multicultural environment that requires adaptive solutions—position it to become not merely a consumer of international quality frameworks but a generator of new approaches addressing 21st-century challenges.

Key priorities include developing culturally responsive quality standards applicable in diverse contexts, creating scalable faculty development models that balance technological and pedagogical competence, establishing agile quality management systems that adapt rapidly to technological change, and building research capacity to generate evidence for continuous improvement. Achieving these priorities requires sustained commitment to research, collaboration, and constant improvement. UAE institutions must invest not only in technology and infrastructure but also in building knowledge through systematic research, fostering collaboration through consortia and networks, and developing human capacity through comprehensive faculty and staff development. By doing so, UAE higher education can fulfill its potential to deliver high-quality, accessible, and culturally sensitive e-learning that serves diverse stakeholders and contributes to the nation’s knowledge-based economy vision.

Regarding the future perspective, the UAE’s higher education sector may utilize new technologies to develop practical approaches and models of e-learning within the higher education system, thereby further enhancing its quality. The primary focus in the e-learning field among UAE institutions must be to eliminate all factors of difficulty in the best possible way and develop the advantages mentioned above. Thus, UAE institutions can be pioneers in offering high-quality, accessible, and culturally sensitive e-learning opportunities. Since the changes in higher education are evident, further research and partnerships will be essential to enhancing e-learning quality management. If higher education institutions in the UAE attempt to foster and sustain an organizational culture that promotes learning, development, and innovation, e-learning should address the existing and future demands of students, faculty, and other stakeholders to create a knowledge-based economy.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

HS: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Writing – original draft, Writing – review & editing. LS: Conceptualization, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – review & editing. MAM: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. MM: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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