Babawande Emmanuel Olawale
Bunmi Isaiah Omodan2- 1Faculty of Education, Walter Sisulu University, Queenstown, South Africa
- 2Faculty of Education, University of the Free State, Free State, South Africa
- 3Faculty of Education, University of Tasmania, Hobart, TAS, Australia
Introduction: In recent years, the landscape of higher education has undergone significant transformation, largely driven by technological advancements and the increasing demand for flexible learning options. E-learning, defined as the use of electronic technologies to access educational curricula outside of a traditional classroom, has emerged as a critical component of this evolution. This systematic review aims to identify and analyse the enablers and barriers associated with e-learning in the higher education sector, thereby contributing to the ongoing discourse surrounding its effectiveness and implementation.
Method: A comprehensive literature search was conducted across multiple academic databases, including JSTOR, Scopus, ERIC, and Science Direct, to gather relevant studies published between 2015 and 2025. The inclusion criteria focused on empirical research that examined e-learning in higher education. Data were extracted and analysed using thematic analysis to categorise the enablers and barriers identified in the literature.
Result: The review identified several key enablers of e-learning, including technological advancement, diverse learning resources, flexibility and accessibility, and cost-effectiveness. Conversely, barriers such as lack of motivation and self-discipline, technical issues, faculty resistance to change, and inadequate technological infrastructure were also prominent. The findings suggest that addressing these barriers while leveraging enablers is crucial for the successful adoption of e-learning in higher education institutions.
Conclusion: This systematic review contributes significantly to the existing body of knowledge surrounding e-learning in higher education. By elucidating the enablers and barriers that influence e-learning implementation, the study provides valuable insights for policymakers, educators, and administrators. As the landscape of higher education continues to evolve, the insights gained from this review can serve as a foundational resource for improving e-learning outcomes and ensuring that institutions are well-equipped to navigate the challenges and opportunities presented by this transformative approach to education. Ultimately, fostering an environment that embraces both the potential of e-learning and the necessary support structures will be crucial for the future success of higher education institutions in an increasingly digital world.
1 Introduction
In recent years, the landscape of higher education has undergone a significant transformation, driven largely by technological advancements and the increasing demand for flexible learning options. E-learning, characterised by the use of electronic technologies to access educational curricula outside of a traditional classroom, has emerged as a pivotal component of this evolution. As institutions strive to meet the diverse needs of students and adapt to the rapidly changing educational environment, understanding the factors that facilitate or impede the successful implementation of e-learning initiatives becomes paramount. Thus, studies indicate that the term e-learning encompasses various meanings or interpretations (Sangrà et al., 2012; Kumar Basak et al., 2018); however, its primary component is the utilisation of technology to provide online access to educational resources that enhance learning. E-learning is characterised as an educational approach that enhances learning through the utilisation of information technology and communication, hence granting learners access to necessary educational programmes (Khan, 2015; Kumar Basak et al., 2018; Alnemrat et al., 2023). The term e-learning is synonymous with web-based learning, online education, computer-assisted instruction, computer-based instruction, internet-based learning, multimedia learning, technology-enhanced learning, and virtual learning (Karnatak et al., 2015; Trelease, 2016; Wang and WANG, 2018). This terminology has caused ambiguity regarding whether e-learning pertains to the medium (e.g., computer-assisted instruction) or the delivery method (e.g., online learning). E-learning, often defined as the use of electronic technologies to access educational curricula outside of a traditional classroom setting, encompasses a wide range of modalities, including online courses, virtual classrooms, and blended learning environments (Abd-Elsayed et al., 2015; Anderson, 2017; Aladwan et al., 2018; Al Rawashdeh et al., 2021). Theoretical frameworks such as Community of Inquiry (CoI) and Connectivism have been instrumental in understanding the dynamics of e-learning. The CoI framework posits that meaningful learning occurs through the interplay of cognitive, social, and teaching presence, emphasising the importance of interaction and collaboration in online learning environments (Garrison and Akyol, 2015; Suppiah et al., 2019).
Conversely, Connectivism, proposed by Mukhlisa (2024) and Siemens (2005), argues that learning in the digital age occurs through networks and connections, highlighting the significance of technology in facilitating knowledge acquisition and dissemination. The shift to e-learning necessitates a re-evaluation of pedagogical approaches. Research indicates that e-learning fosters active learning through interactive content, collaborative projects, and immediate feedback mechanisms (Khan et al., 2017; Spring and Graham, 2017; Chen and Swan, 2020). For instance, studies have shown that incorporating multimedia elements, such as videos and simulations, enhances student engagement and comprehension (Shelton et al., 2016; Mayer, 2017; Hung and Chen, 2018; Alnemrat et al., 2023). Furthermore, e-learning can provide personalised learning experiences, allowing students to progress at their own pace and tailor their educational journeys according to individual needs (Alamri et al., 2021; Gligorea et al., 2023; Verma et al., 2024). Research has also demonstrated that well-structured e-learning environments can improve learning outcomes, increase student satisfaction, and lead to higher retention rates (Violante and Vezzetti, 2015; Yurdugül and Çetin, 2015; Daultani et al., 2021; Innab et al., 2022). Technological advancements have played a crucial role in the proliferation of e-learning in higher education. The emergence of Learning Management Systems (LMS) such as Moodle, Blackboard, and Canvas has facilitated the organisation and delivery of online courses (Mncube et al., 2021; Shurygin et al., 2021; Almarashdeh, 2016). These platforms provide educators with tools to create, manage, and assess learning activities while also enabling students to access resources and collaborate with peers. Additionally, the integration of emerging technologies, such as artificial intelligence (AI), virtual reality (VR), and augmented reality (AR), is reshaping the e-learning landscape (Trelease, 2016; Olawale, 2024). AI-driven personalised learning systems can analyse student performance and adapt content accordingly, while VR and AR offer immersive learning experiences that can enhance the understanding of complex concepts (Hwang et al., 2020; Olawale, 2024). Moreover, mobile learning, or m-learning, has gained traction as a complementary mode of e-learning, allowing students to access educational resources anytime and anywhere (Pereira and Rodrigues, 2013; Nyembe and Howard, 2019). The proliferation of smartphones and tablets has made it increasingly feasible for learners to engage with course materials on the go, thus promoting flexibility and accessibility in higher education (Wong and Looi, 2011).
Despite the numerous advantages of e-learning, several challenges persist in its implementation within higher education institutions. One of the primary concerns is the digital divide, which refers to the disparities in access to technology and the internet among different socio-economic groups (Cullen, 2001; Ghobadi and Ghobadi, 2015; Sims et al., 2008). Students from low-income backgrounds may face barriers to participating in e-learning due to inadequate access to devices or reliable internet connectivity. This inequity can exacerbate existing educational inequalities and hinder the potential benefits of e-learning for all students (Van Dijk, 2006; Deng and Sun, 2022). Additionally, the shift to e-learning requires significant changes in institutional culture and faculty training. Many educators lack the necessary skills and confidence to effectively design and deliver online courses (Bates and Sangra, 2011; Tugwell and Maduabuchukwu, 2020). Professional development programmes that focus on pedagogical strategies for e-learning and the use of technology are essential to equip educators with the competencies needed to thrive in a digital learning environment (Anderson, 2005; Ottenbreit-Leftwich et al., 2010). Another challenge is the potential for decreased student engagement and motivation in online learning environments. Research has indicated that the absence of face-to-face interaction can lead to feelings of isolation and disconnection among students (Palloff and Pratt, 2009; Mutongoza and Olawale, 2022). Nonetheless, while the swift advancement of technology has fundamentally altered several areas, including higher education, e-learning has become a prominent method of education delivery, propelled by the widespread availability of digital tools and materials (Almarashdeh, 2016; Mutongoza and Olawale, 2022). Despite the increasing acceptance of e-learning in higher education institutions (HEIs), the success and sustainability of these programs depend on a complex interaction of many facilitators and obstacles. Understanding these factors is essential for stakeholders, including educators, administrators, policymakers, and students, as they address the problems and possibilities inherent in e-learning settings. Regardless of the growing corpus of literature on the subject, a thorough review of more current research on the facilitators and obstacles to e-learning in higher education is conspicuously absent. This gap is significant as it impedes a thorough comprehension of the complex dynamics that affect the execution and efficacy of e-learning initiatives. Thus, the uniqueness of this review resides in its ability to integrate varied viewpoints and experiences from different empirical studies to provide significant resources for practitioners and decision-makers aiming to improve e-learning frameworks. By identifying key enablers and barriers to e-learning in HEIs, this review informs interventions and policy formulations that enhance its integration in higher education institutions, therefore fostering a more inclusive and flexible educational environment.
2 Methods
This study employed a systematic literature review (SLR) methodology. Systematic literature reviews are regarded as a significant research methodology that adheres closely to scientific principles, as they are “designed to locate, appraise, and synthesize the best available evidence” pertinent to the research objective, thereby facilitating “informative and evidence-based” findings (Dickson, 2017; Boland et al., 2023). A systematic search for articles published on e-learning in higher education institutions was conducted in JSTOR, Scopus, ERIC, and ScienceDirect from 2015 to 2025. The primary search terms were “e-learning” and “higher education,” using ‘Textword searching’ (i.e., searching for a word or phrase appearing anywhere in the citation—article title, journal name, author, etc.) rather than the full text of an article, and ‘Thesaurus (LCSH, AACE) searching’, employing Boolean operators and truncations. The search strategy included the following terms: (“e-learning” OR “online learn*” OR “distance learning” OR “computer-assisted instruction” OR “web-based learning” OR “internet-based learning” OR “multi-media learning” OR “technology-enhanced learning” OR “distributed learning” OR “virtual classroom” OR “virtual environment” OR “virtual learning”) AND (“higher education institution” OR “higher education” OR “tertiary education” OR “postsecondary education” OR “advanced education” OR “graduate education” OR “public further education” OR “university education”) AND (“challenges” OR “barriers” OR “enablers” OR “facilitator”) (see Table 1).
Table 1. Inclusion and exclusion criteria.
Based on the inclusion and exclusion criteria, the literature obtained from the databases underwent a two-stage screening process. In the first stage, abstracts and titles were reviewed to determine compliance with the minimum inclusion requirements. In the second stage, the complete texts of the included papers were examined using a critical assessment instrument (Kmet et al., 2004). Thus, Means et al. (2010) contend that “the objective of the two-stage approach was to enhance efficiency while avoiding the exclusion of potentially pertinent, high-quality studies on the effects of online learning.” The typical PRISMA flowchart has been used to illustrate the study selection procedure (Moher et al., 2010).
According to the final search results, 21 papers were identified for inclusion in the review, predominantly of a quantitative nature. Thus, Clarke (2007) contends that when methodological heterogeneity exists, “systematic review does not require the amalgamation of study results to yield an average estimate.” This study synthesised data through narrative synthesis employing thematic analysis (TA) (Regmi and Jones, 2020). Thematic Analysis is defined as “a method […] for identifying, analysing, and reporting patterns (themes)” or for seeking meaning within literature or data (Ritchie et al., 2003). In this study, we employed six steps to identify recurrent themes while synthesising data through thematic analysis: familiarising ourselves with the data, developing initial (sub) codes, searching for (sub) themes, reviewing (sub) themes, charting or compiling ideas or issues, and producing final data aligned with the study’s aims and objectives (Ritchie et al., 2003; Regmi and Jones, 2020). Thereafter, a table was created to delineate the characteristics of the studies, including designs, techniques, and populations (see Table 2). Two researchers engaged in the processes and independently assessed each article, yielding an inter-rater reliability of 78% as determined by Cohen’s kappa coefficient (Creswell and Poth, 2016; Salas-Pilco et al., 2022). Disputes were resolved by deliberation until a consensus was reached. Therefore, Petticrew and Roberts (2008) assert that this would enhance transparency by elucidating the types of data taken from various studies and acknowledging the contribution of each study to the overall synthesis.
Table 2. Demographic profile of studies included.
Following the PRISMA principles, 873 articles were identified from the four selected search engines, of which 212 were deemed suitable. An additional 38 duplicates were removed, leaving 174 papers available for abstract screening. Furthermore, a total of 103 articles were excluded for not meeting the highlighted inclusion criteria. After applying the inclusion and exclusion criteria, 71 articles were found to meet the requirements for further examination. However, upon closer inspection, it was determined that 50 articles were unrelated to the topic of this study. Ultimately, 21 publications were evaluated. A graphical representation is shown in Figure 1 below:
Figure 1. PRISMA flowchart showing results of the searches.
3 Results
Through thematic analysis of the collected studies, two overarching descriptive themes/categories were identified: enablers of e-learning and barriers to e-learning in higher education institutions, under which eight significant themes emerged (see Table 3).
Table 3. Study characteristics and summary of the factors associated with e-learning.
Enablers of e-learning in higher education institutions
• Technological advancement
• Diverse learning resources
• Flexibility and accessibility
• Cost-effectiveness
Barriers to e-learning in the Higher Education Institutions
• Lack of motivation and self-discipline
• Technical issues
• Faculty resistance to change
• Inadequate technological infrastructure
4 E-learning enablers or drivers
4.1 Theme 1: technological advancement
Studies such as Naveed et al. (2017), West and Malatji (2021), and Garrad and Nolan (2023) have revealed that technological advancement is a crucial enabler of e-learning in higher education institutions by providing the necessary tools and infrastructure to facilitate online learning. The emergence of Learning Management Systems (LMS) such as Moodle, Blackboard, and Canvas allows educators to create, manage, and deliver online courses effectively (Mncube et al., 2021; Shurygin et al., 2021; Olawale, 2024; Hwang et al., 2020). These platforms offer a range of features, including the ability to host multimedia content, conduct assessments, and foster communication between students and instructors (Almarashdeh, 2016; Aladwan et al., 2018). Additionally, advancements in internet connectivity and the proliferation of mobile devices, such as smartphones and tablets, enhance accessibility, enabling students to engage with course materials anytime and anywhere (Farounbi, 2024; Rafiq et al., 2020; Aguilos and Fuchs, 2022; Garrad and Nolan, 2023). This flexibility supports diverse learning styles and schedules, making education more inclusive. Furthermore, technological innovations such as interactive simulations and gamification can improve student engagement and learning outcomes, thereby reinforcing the effectiveness of e-learning initiatives (Tuševljak et al., 2016; Aguilos and Fuchs, 2022). Therefore, integrating advanced technology streamlines the learning process and promotes collaboration and interaction among students from different geographical backgrounds, enriching the educational experience.
4.2 Theme 2: diverse learning resources
Studies such as Naveed et al. (2017), Alghizzawi et al. (2019), Rafiq et al. (2020), West and Malatji (2021), Aguilos and Fuchs (2022), Tymoshchuk (2022), Garrad and Nolan (2023), Saleem et al. (2023), and Tyagi and Krishankumar (2023) have reported that e-learning is a successful approach and tool that fosters student engagement in higher education institutions. Consequently, diverse learning resources play a crucial role as enablers of e-learning. They cater to various learning styles and preferences, allowing students to engage with the material in ways that best suit their individual needs (Aguilos and Fuchs, 2022; Innab et al., 2022; Rafiq et al., 2020). The availability of a wide range of resources, such as videos, articles, interactive quizzes, and forums, enhances the learning experience by providing multiple avenues for understanding and retaining information (Nyembe and Howard, 2019; Garrad and Nolan, 2023). This variety not only keeps students interested and motivated but also promotes deeper engagement with the content (Aguilos and Fuchs, 2022; Olawale, 2024). Furthermore, diverse resources can facilitate collaborative learning opportunities, connecting students from different backgrounds and locations, which enriches their educational experience (Anderson, 2005; Naveed et al., 2017; Alamri et al., 2021; Farounbi, 2024). Thus, by incorporating diverse learning resources, institutions can create a more inclusive and effective e-learning environment that supports student success and satisfaction.
4.3 Theme 3: flexibility and accessibility
Flexibility and accessibility are crucial enablers of e-learning in higher education institutions. The ability to learn anytime and anywhere allows students to tailor their educational experiences to fit their individual lifestyles and commitments (Torkzadeh et al., 2022; Garrad and Nolan, 2023; Simanjuntak and Sukresna, 2023; Tyagi and Krishankumar, 2023). This flexibility caters to diverse learning preferences, enabling students to engage with course materials at their own pace, which can enhance their overall learning experience (Ali et al., 2018; Tymoshchuk, 2022; Shisakha et al., 2024). Moreover, the widespread availability of technology, such as smartphones and tablets, increases accessibility to educational resources, making it possible for a larger audience to participate in e-learning. This is particularly important for students who may face geographical or time constraints (Tugwell and Maduabuchukwu, 2020; Deng and Sun, 2022), as they can access learning materials and engage in coursework without the limitations of traditional classroom settings (Aguilos and Fuchs, 2022; Tymoshchuk, 2022; Simanjuntak and Sukresna, 2023). The combination of flexibility and accessibility promotes self-paced learning and empowers students to take control of their educational journeys (Gunasinghe et al., 2020; Feliz et al., 2022). Thus, by providing a more inclusive and adaptable learning environment, higher education institutions can better meet the needs of their diverse student populations, ultimately leading to improved educational outcomes.
4.4 Theme 4: cost effectiveness
Cost-effectiveness is a significant enabler of e-learning in higher education institutions. Studies such as Ali et al. (2018), Torkzadeh et al. (2022), Simanjuntak and Sukresna (2023), and Abich and Eriku (2023) have revealed that by reducing the costs associated with physical infrastructure and commuting, e-learning provides a more affordable alternative to traditional education. Consequently, institutions can allocate resources more efficiently, allowing for investment in technology and content development that enhances the learning experience (Ali et al., 2018; Abich and Eriku, 2023). Furthermore, e-learning can cater to a broader audience, making education accessible to individuals who may not have the means to attend in-person classes (Wong and Looi, 2011; Aguilos and Fuchs, 2022). This flexibility benefits students and helps institutions remain competitive in a rapidly changing educational landscape (Abich and Eriku, 2023). Therefore, the cost-effectiveness of e-learning supports continuous education and skill development, making it a compelling option for both learners and educational institutions.
5 E-learning barriers or challenges
5.1 Theme 1: lack of motivation and self-discipline
The lack of motivation and self-discipline is a significant barrier to e-learning in higher education institutions. Studies such as Alghizzawi et al. (2019), Rafiq et al. (2020), Matarirano et al. (2021), Aguilos and Fuchs (2022), Feliz et al. (2022), and Tyagi and Krishankumar (2023) have revealed that in an online learning environment, students often have more autonomy over their schedules and learning pace, which can lead to challenges in maintaining focus and commitment. Without the structured environment of traditional classrooms, some learners may struggle to engage with the material consistently, resulting in decreased participation and poor academic performance. Additionally, the absence of regular face-to-face interactions with peers and instructors can contribute to feelings of isolation, further diminishing motivation (Matarirano et al., 2021; Saleem et al., 2023). The study by Saleem et al. (2023) indicated that a notable percentage of students reported difficulties in sustaining their motivation throughout the course, highlighting the importance of self-regulation in online education. To address this barrier, institutions can implement strategies that foster self-motivation, such as setting clear goals, providing timely feedback, and encouraging collaborative learning opportunities among students (Saleem et al., 2023; Tyagi and Krishankumar, 2023).
5.2 Theme 2: technical issues
Studies such as Gunasinghe et al. (2020), Matarirano et al. (2021), Tymoshchuk (2022), Abich and Eriku (2023), Saleem et al. (2023), and Tyagi and Krishankumar (2023) have revealed that technical issues are significant barriers to the effective implementation of e-learning in higher education institutions. These issues can manifest in various forms, including inadequate access to technology, unreliable internet connectivity, and problems with system reliability. Many students may lack the necessary devices or face difficulties with network speed, which can hinder their ability to participate in online courses (Matarirano et al., 2021; Saleem et al., 2023). Additionally, technical barriers can arise from the complexity of e-learning platforms, leading to frustration among both students and faculty (Ali et al., 2018; Gunasinghe et al., 2020; Aguilos and Fuchs, 2022). Faculty members may also resist adopting new technologies due to unfamiliarity or discomfort with the digital tools required for e-learning (Abich and Eriku, 2023). These technical challenges can impede learner engagement, reduce the quality of the educational experience, and exacerbate existing inequalities in access to education. Therefore, addressing these technical barriers is crucial for enhancing the effectiveness and success of e-learning initiatives in higher education.
5.3 Theme 3: faculty resistance to change
Studies such as those by Alghizzawi et al. (2019), Abich and Eriku (2023), and Simanjuntak and Sukresna (2023), have revealed that faculty resistance to change is a significant barrier in higher education institutions, particularly when transitioning from traditional teaching methods to more adaptive e-learning approaches. This resistance can stem from various factors, including a lack of familiarity with new technologies, comfort with established teaching practices, and concerns about the effectiveness of e-learning compared to face-to-face instruction. Faculty members may also fear that adopting new methods could undermine their authority or expertise in the classroom. Such reluctance can hinder the integration of innovative teaching strategies and technologies, ultimately affecting the overall quality of education and student engagement (Abich and Eriku, 2023; Simanjuntak and Sukresna, 2023). To address this barrier, institutions must prioritise professional development and training programmes that enhance faculty technological proficiency and demonstrate the benefits of e-learning (Alghizzawi et al., 2019). Encouraging a culture of collaboration and innovation among faculty can also help mitigate resistance and foster a more supportive environment for the adoption of e-learning initiatives.
5.4 Theme 4: inadequate technological infrastructure
Inadequate technological infrastructure is a significant barrier to the effective implementation of e-learning in higher education. Studies such as Shahmoradi et al. (2018), Alghizzawi et al. (2019), Abich and Eriku (2023), and Okoye et al. (2023), reveal that many institutions struggle to provide the necessary resources, such as reliable internet access and modern devices, which are crucial for both students and educators to engage with online learning platforms. This lack of infrastructure can lead to difficulties in accessing course materials, participating in online discussions, and completing assignments, ultimately hindering students’ learning experiences (Alghizzawi et al., 2019; Okoye et al., 2023). Additionally, insufficient support for faculty in utilising digital technologies can further exacerbate the challenges faced in adopting e-learning approaches (Shahmoradi et al., 2018; Abich and Eriku, 2023). Thus, without adequate investment in technological infrastructure, the potential benefits of e-learning, such as flexibility, accessibility, and cost-effectiveness, may not be fully realised, leading to disparities in educational opportunities among students from different socio-economic backgrounds.
6 Discussion
Technological advancement plays a crucial role in enabling e-learning in higher education institutions. The rapid development of digital tools and platforms has allowed students and educators to engage in interactive and immersive learning experiences. Technologies such as learning management systems, virtual classrooms, and multimedia resources facilitate the delivery of content and enhance student engagement (Violante and Vezzetti, 2015; Yurdugül and Çetin, 2015; Almarashdeh, 2016; Rafiq et al., 2020). This advancement not only improves the quality of education but also makes it more appealing to a tech-savvy generation of learners (Alghizzawi et al., 2019; Saleem et al., 2023; Tyagi and Krishankumar, 2023). Moreover, the availability of a wide range of educational materials, including videos, articles, e-books, and interactive quizzes, caters to different learning styles and preferences which enriches the educational landscape (Tuševljak et al., 2016; Alghizzawi et al., 2019; West and Malatji, 2021; Garrad and Nolan, 2023). These resources empower students to take ownership of their learning journeys, encouraging exploration and critical thinking. Furthermore, this variety of materials allows students to select resources that best fit their individual needs, promoting a more personalised learning experience (Rafiq et al., 2020; Saleem et al., 2023). Thus, democratising information access reinforces the idea that education must be inclusive, enabling learners from diverse backgrounds to utilize high-quality resources that were once unattainable (Mncube et al., 2021; Shurygin et al., 2021; Olawale, 2024). The study findings also revealed that flexibility and accessibility are essential elements of e-learning, catering to the varied requirements of the contemporary student demographic for the effectiveness of higher education institutions (Ali et al., 2018; Tymoshchuk, 2022; Simanjuntak and Sukresna, 2023). The capacity to learn independently and according to a personal timetable accommodates diverse obligations, therefore diminishing obstacles to education (Tugwell and Maduabuchukwu, 2020; Shisakha et al., 2024). Also, the ability to access educational materials anytime and anywhere eradicates geographical barriers and allows for a more inclusive learning environment (Khan et al., 2017; Aladwan et al., 2018). This flexibility accommodates diverse lifestyles and empowers students to take control of their learning processes. Furthermore, the cost-effectiveness of e-learning models presents a compelling argument for their adoption. By reducing overhead costs associated with physical infrastructure and offering scalable solutions, institutions can allocate resources more efficiently (Tymoshchuk, 2022; Tugwell and Maduabuchukwu, 2020; Simanjuntak and Sukresna, 2023; Tyagi and Krishankumar, 2023). This financial viability not only supports institutional sustainability but also makes higher education more attainable for a wider audience. Thus, the interaction of these linkages between above above-discussed enablers highlights the transformational capacity of e-learning in higher education. By leveraging technology, diverse resources, flexibility, and cost-effectiveness, institutions can create a more inclusive and effective educational environment that meets the needs of today’s learners.
This study’s findings further highlight the intricate relationship among motivating variables, technical preparedness, and institutional culture in determining the efficacy of e-learning in higher education. The review indicates that insufficient motivation and self-discipline frequently arise from a disparity between conventional teaching methods and the requirements of a digital learning context. This lack of motivation and self-discipline significantly hinders students’ engagement in e-learning (Tuševljak et al., 2016; Rafiq et al., 2020; Feliz et al., 2022; Abich and Eriku, 2023). This disconnection may result in disengagement, thereby impeding the potential advantages of e-learning. As such, the lack of intrinsic motivation can be compounded by external issues, including insufficient support systems and unclear information about the benefits of e-learning. Furthermore, technical challenges, such as erratic internet connectivity and faulty learning management systems, exacerbate the e-learning environment, making it difficult for students to participate fully in online courses (Gunasinghe et al., 2020; Tymoshchuk, 2022). Faculty members, used to in-person interactions, may frequently exhibit mistrust regarding e-learning methodologies, apprehensive that these approaches may undermine educational quality (Abich and Eriku, 2023; Simanjuntak and Sukresna, 2023). This reluctance can establish a cyclical impediment; without teacher endorsement, students are less inclined to participate substantively with e-learning platforms, leading to subpar educational results. Also, findings revealed that inadequate support for faculty members in employing digital technology can intensify the difficulties encountered in implementing e-learning (Shahmoradi et al., 2018; Abich and Eriku, 2023; Okoye et al., 2023). Insufficient technology infrastructure within institutions acts as a fundamental catalyst for these difficulties (Shahmoradi et al., 2018; Matarirano et al., 2021). Institutions that neglect to invest in substantial technology resources may unintentionally convey to educators and students that e-learning is a subordinate concern. The absence of investment may foster a culture of indifference towards e-learning initiatives, hence sustaining disengagement and resistance. Therefore, tackling these interconnected difficulties necessitates a comprehensive strategy that emphasizes motivation, improved technical assistance, and the cultivation of a culture of creativity among academics. Only through comprehensive strategies can higher education institutions effectively leverage e-learning to enhance the educational experience.
7 Conclusion
This systematic review highlighted essential enablers and barriers of e-learning in the higher education institutions. Identified key enablers are technology innovation, diversified learning materials, cost-effectiveness, flexibility, and accessibility. These elements jointly improve the educational experience, creating an atmosphere favorable to learning and engagement. In contrast, the highlighted barriers—namely, faculty resistance to change, insufficient technological infrastructure, lack of desire and self-discipline among students, and technical difficulties—present considerable hurdles that may obstruct the successful integration of technology in education. The results obtained from this review have significant implications for interventions and policy development. By identifying the facilitators, educational institutions may strategically allocate resources towards technology innovations and varied learning materials that enhance engagement and accessibility. Moreover, overcoming obstacles, especially faculty opposition and insufficient infrastructure, is essential for cultivating a flexible educational environment. This review, therefore, emphasizes the need for customized professional development programs designed to educate educators with the skills and motivation required to adopt technology advancements. The findings enhance current research by offering a nuanced comprehension of the interaction between facilitators and obstacles in the incorporation of educational technology. These insights can assist educational leaders in formulating strategic initiatives that utilize technology breakthroughs while addressing resistance and infrastructure obstacles. The social ramifications are substantial; improving accessibility and flexibility via technology may democratize education, rendering it more accessible for many communities. It is crucial to recognize the limits of this research, including possible biases in the examined studies and the dynamic nature of educational technology. Future studies should, therefore, investigate the long-term effects and efficacy of certain remedies across varied institutional settings to enhance these findings. This review serves as a fundamental reference for those seeking to navigate the intricacies of technology integration in education.
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
BEO: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Writing – original draft, Writing – review & editing. BIO: Supervision, Validation, Writing – review & editing. KS: Investigation, Supervision, Validation, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Gen AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Abd-Elsayed, A., Botros, M., Huynh, P., and Lawrence, J. P. (2015). E-learning, distance learning. Online learning in the setting of medical education, a review of current literature. J. Clin. Anesth. Manag. 1, 1–16. doi: 10.16966/2470-9956.102
Abich, Y., and Eriku, G. A. Challenges and opportunities for the adoption of e-learning at the University of Gondar: a qualitative study. E-learning working paper series, (2023), 1, 1–21. doi: 10.14507/MCF-eLi.I6
Aguilos, V., and Fuchs, K. (2022). The perceived usefulness of gamified e-learning: a study of undergraduate students with implications for higher education. Front. Educ. 1, 1–11. doi: 10.3389/feduc.2022.945536
Al Rawashdeh, A. Z., Mohammed, E. Y., Al Arab, A. R., Alara, M., and Al-Rawashdeh, B. (2021). Advantages and disadvantages of using e-learning in university education: analyzing students' perspectives. Electron. J. E-Learn. 19, 107–117. doi: 10.34190/ejel.19.3.2168
Aladwan, F., Al-Shboul, M., and Al Awamrah, A. (2018). Distance education, blended learning, and e-learning predictions and possibilities. Mod. Appl. Sci. 13, 192–206. doi: 10.5539/mas.v13n2p192
Alamri, H. A., Watson, S., and Watson, W. (2021). Learning technology models that support personalization within blended learning environments in higher education. TechTrends 65, 62–78. doi: 10.1007/s11528-020-00530-3
Alghizzawi, M., Habes, M., Salloum, S. A., Ghani, M. A., Mhamdi, C., and Shaalan, K. (2019). The effect of social media usage on students' e-learning acceptance in higher education: a case study from the United Arab Emirates. Int. J. Inf. Technol. Lang. Stud. 3, 13–26.
Ali, M., Raza, S. A., Qazi, W., and Puah, C. H. (2018). Assessing e-learning system in higher education institutes: evidence from structural equation modelling. Interact. Technol. Smart Educ. 15, 59–78. doi: 10.1108/ITSE-02-2017-0012
Almarashdeh, I. (2016). Sharing instructors experience of learning management system: a technology perspective of user satisfaction in distance learning course. Comput. Hum. Behav. 63, 249–255. doi: 10.1016/j.chb.2016.05.013
Alnemrat, A., Aldamen, H., Al-Deaibes, M., and Alsharefeen, R. (2023). E-learning in a Jordanian higher education institution. Front. Psychol. 14:1136142. doi: 10.3389/fpsyg.2023.1136142
Anderson, T. (2017). How communities of inquiry drive teaching and learning in the digital age. North Contact 1, 1–6.
Bates, A. T., and Sangra, A. (2011). Managing technology in higher education: strategies for transforming teaching and learning. New Jersey: John Wiley and Sons.
Boland, A., Cherry, M. G., and Dickson, R. (2023). Doing a systematic review: a student's guide. Washington DC: SAGE.
Chen, C. C., and Swan, K. (2020). Using innovative and scientifically-based debate to build e-learning community. Online Learn. 24, 67–80. doi: 10.24059/olj.v24i3.2345
Clarke, M. (2007). Overview of methods. Reviewing research evidence for nursing practice: Systematic reviews. (Eds.) W. Christine and R. Brenda. Oxford: Blackwell Publishing. doi: 10.1002/9780470692127.ch1
Creswell, J. W., and Poth, C. N. (2016). Qualitative inquiry and research design: choosing among five approaches. New York: Sage Publications.
Cullen, R. (2001). Addressing the digital divide. Online Inf. Rev. 25, 311–320. doi: 10.1108/14684520110410517
Daultani, Y., Goswami, M., Kumar, A., and Pratap, S. (2021). Perceived outcomes of e-learning: identifying key attributes affecting user satisfaction in higher education institutes. Meas. Bus. Excell. 25, 216–229. doi: 10.1108/MBE-07-2020-0110
Deng, X., and Sun, R. (2022). Barriers to e-learning during crisis: a capital theory perspective on academic adversity. J. Inf. Syst. Educ. 33, 75–84.
Dickson, R. (2017). Doing a systematic review—a students guide. Washington DC: Sage Publications Limited.
Farounbi, T. T. (2024). Assessing the use of e-learning for higher education: a cross-sectional study of Nigerian students' perspectives. Int. J. Learn. Dev. 14, 88–104. doi: 10.5296/ijld.v14i1.21631
Feliz, S., Ricoy, M. C., Buedo, J. A., and Feliz-Murias, T. (2022). Students' e-learning domestic space in higher education in the new normal. Sustainability 14, 1–16. doi: 10.3390/su14137787
Garrad, T. A., and Nolan, H. (2023). Rethinking higher education unit design: embedding universal design for learning in online studies. Student Success 14, 1–8.
Garrison, D. R., and Akyol, Z. (2015). Toward the development of a metacognition construct for communities of inquiry. Internet High. Educ. 24, 66–71. doi: 10.1016/j.iheduc.2014.10.001
Ghobadi, S., and Ghobadi, Z. (2015). How access gaps interact and shape digital divide: a cognitive investigation. Behav. Inf. Technol. 34, 330–340. doi: 10.1080/0144929X.2013.833650
Gligorea, I., Cioca, M., Oancea, R., Gorski, A. T., Gorski, H., and Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: a literature review. Educ. Sci. 13, 1216–1223. doi: 10.3390/educsci13121216
Gunasinghe, A., Hamid, J. A., Khatibi, A., and Azam, S. F. (2020). The adequacy of UTAUT-3 in interpreting academician's adoption to e-learning in higher education environments. Interact. Technol. Smart Educ. 17, 86–106. doi: 10.1108/ITSE-05-2019-0020
Hung, I. C., and Chen, N. S. (2018). Embodied interactive video lectures for improving learning comprehension and retention. Comput. Educ. 117, 116–131. doi: 10.1016/j.compedu.2017.10.005
Hwang, G. J., Sung, H. Y., Chang, S. C., and Huang, X. C. (2020). A fuzzy expert system-based adaptive learning approach to improving students' learning performances by considering affective and cognitive factors. Comput. Educ. Artif. Intell. 1, 100003–100015. doi: 10.1016/j.caeai.2020.100003
Innab, A., Albloushi, M., Alruwaili, M., Alqahtani, N., Alenazi, L., and Alkathiri, A. (2022). The influence of sense of community and satisfaction with e-learning and their impact on nursing students' academic achievement. Int. Rev. Res. Open Distance Learn. 23, 19–34. doi: 10.19173/irrodl.v23i4.6436
Karnatak, H., Raju, P. L., Krishnamurthy, Y. V., and Senthil Kumar, A. (2015). E-learning based capacity building in geoinformatics. ISG 21, 4–13.
Khan, A., Egbue, O., Palkie, B., and Madden, J. (2017). Active learning: engaging students to maximize learning in an online course. Electron. J. e-Learn. 15, 107–115.
Kmet, L. M., Cook, L. S., and Lee, R. C. (2004). Standard quality assessment criteria for evaluating primary research papers from a variety of fields. Alberta: Alberta Heritage Foundation for Medical Research Edmonton.
Kumar Basak, S., Wotto, M., and Bélanger, P. (2018). E-learning, M-learning and D-learning: conceptual definition and comparative analysis. E-learn. Digit. Media 15, 191–216. doi: 10.1177/2042753018785180
Matarirano, O., Yeboah, A., and Gqokonqana, O. (2021). Readiness of students for multi-modal emergency remote teaching at a selected South African higher education institution. Int. J. High. Educ. 10, 135–152. doi: 10.5430/ijhe.v10n6p135
Mayer, R. E. (2017). Using multimedia for e-learning. J. Comput. Assist. Learn. 33, 403–423. doi: 10.1111/jcal.12197
Means, B., Toyama, Y., Murphy, R., Bakia, M., and Jones, K. (2010). Evaluation of evidence-based practices in online learning: a meta-analysis and review of online learning studies center for technology in learning. Jessup, MD, USA: US Department of Education.
Mncube, V., Olawale, B. E., and Bitso, C. (2021) Democratisation of knowledge through open educational resources: opportunities and challenges at a South African University. Global Education Network 2021. South Africa
Moher, D., Liberati, A., Tetzlaff, J., and Altman, D. G.Prisma Group (2010). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int. J. Surg. 8, 336–341. doi: 10.1016/j.ijsu.2010.02.007
Mukhlisa, H. H. (2024). Connectivism and digital age education: insights, challenges, and future directions. Kasetsart J. Soc. Sci. 45, 1–13. doi: 10.34044/j.kjss.2024.45.3.11
Mutongoza, B. H., and Olawale, B. E. (2022). Safeguarding academic integrity in the face of emergency remote teaching and learning in developing countries. Perspect. Educ. 40, 234–249. doi: 10.18820/2519593X/pie.v40.i1.14
Naveed, Q. N., Muhammad, A., Sanober, S., Qureshi, M. R., and Shah, A. (2017). A mixed method study for investigating critical success factors (CSFs) of e-learning in Saudi Arabian Universities. Methods 8, 171–178. doi: 10.14569/IJACSA.2017.080522
Nyembe, B. Z., and Howard, G. R. (2019). The utilities of prominent learning theories for mobile collaborative learning (MCL) with reference to WhatsApp and m-learning. International conference on advances in big data, computing and data communication systems (icABCD). KwaZulu Natal, South Africa.
Okoye, K., Hussein, H., Arrona-Palacios, A., Quintero, H. N., Ortega, L. O., Sanchez, A. L., et al. (2023). Impact of digital technologies upon teaching and learning in higher education in Latin America: an outlook on the reach, barriers, and bottlenecks. Educ. Inf. Technol. 28, 2291–2360. doi: 10.1007/s10639-022-11214-1
Olawale, B. (2024). Collaborative virtual environments (CVEs) in the preparation of pre-service mathematics teachers. J. Learn. Teach. Digit. Age 9, 55–63. doi: 10.53850/joltida.1359772
Ottenbreit-Leftwich, A. T., Glazewski, K. D., Newby, T. J., and Ertmer, P. A. (2010). Teacher value beliefs associated with using technology: addressing professional and student needs. Comput. Educ. 55, 1321–1335. doi: 10.1016/j.compedu.2010.06.002
Palloff, R. M., and Pratt, K. (2009). Assessment, academic integrity, and community online. Second Edn. Hershey, Pennsylvania: IGI Global.
Pereira, O. R., and Rodrigues, J. J. (2013). Survey and analysis of current mobile learning applications and technologies. ACM Comput. Surv. 46, 1–35. doi: 10.1145/2543581.2543594
Petticrew, M., and Roberts, H. (2008). Systematic reviews in the social sciences: a practical guide. Hoboken, New Jersey: John Wiley & Sons.
Rafiq, F., Hussain, S., and Abbas, Q. (2020). Analyzing students' attitude towards e-learning: a case study in higher education in Pakistan. Pak. Soc. Sci. Rev. 4, 367–380. doi: 10.35484/pssr.2020(4-I)29
Regmi, K., and Jones, L. (2020). A systematic review of the factors-enablers and barriers-affecting e-learning in health sciences education. BMC Med. Educ. 20, 1–18. doi: 10.1186/s12909-020-02007-6
Ritchie, J., Lewis, J., Nicholls, C. M., and Ormston, R. (2003). Qualitative research practice. London: Sage.
Salas-Pilco, S. Z., Xiao, K., and Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: a systematic review. Educ. Sci. 12, 1–18. doi: 10.3390/educsci12080569
Saleem, Q., Khan, M. A., Mahmud, S. A., Usman, M., Aslam, F., Saifullah, M., et al. (2023). Medical students expectations, experiences and use of E learning resources in higher education. Pak. J. Med. Health Sci. 17, 643–645. doi: 10.53350/pjmhs2023173643
Sangrà, A., Vlachopoulos, D., and Cabrera, N. (2012). Building an inclusive definition of e-learning: an approach to the conceptual framework. Int. Rev. Res. Open Distance Learn. 13, 145–159. doi: 10.19173/irrodl.v13i2.1161
Shahmoradi, L., Changizi, V., Mehraeen, E., Bashiri, A., Jannat, B., and Hosseini, M. (2018). The challenges of E-learning system: higher educational institutions perspective. J. Educ. Health Promot. 7, 116–121. doi: 10.4103/jehp.jehp_39_18
Shelton, C. C., Warren, A. E., and Archambault, L. M. (2016). Exploring the use of interactive digital storytelling video: promoting student engagement and learning in a university hybrid course. TechTrends 60, 465–474. doi: 10.1007/s11528-016-0082-z
Shisakha, M. B., Njuguna, F. W., and Ogeta, N. (2024). Institutional information communication technology capacity influence on E-learning utilization for instruction in Kenyan universities. Msingi J. 8, 27–45. doi: 10.33886/mj.v8i1.458
Shurygin, V., Saenko, N., Zekiy, A., Klochko, E., and Kulapov, M. (2021). Learning management systems in academic and corporate distance education. Int. J. Emerg. Technol. Learn. 16, 121–139. doi: 10.3991/ijet.v16i11.20701
Siemens, G. (2005). Connectivism: a learning theory for the digital age. Int. J. Interact. Technol. Distance Educ. 2, 3–10.
Simanjuntak, M., and Sukresna, I. M. (2023). The role of adaptive e-learning co-design as main solution to higher education's marketing performance. Int. J. Learn. Teach. Educ. Res. 22, 131–147. doi: 10.26803/ijlter.22.2.8
Sims, J., Vidgen, R., and Powell, P. (2008). E-learning and the digital divide: perpetuating cultural and socio-economic elitism in higher education. Commun. Assoc. Inf. Syst. 22, 1–16. doi: 10.17705/1CAIS.02223
Spring, K. J., and Graham, C. R. (2017). Blended learning citation patterns and publication networks across seven worldwide regions. Australas. J. Educ. Technol. 33, 1–13. doi: 10.14742/ajet.2632
Suppiah, S., Wah, L. K., Lajium, D. A., and Swanto, S. (2019). Exploring a collaborative and dialogue-based reflective approach in an e-learning environment via the community of inquiry (CoI) framework. Comput. Assist. Lang. Learn. Electron. J. 20, 117–139.
Torkzadeh, J., Ahangari, M., Mohammadi, M., Marzooghi, R., and Hashemi, S. (2022). Examining the external effectiveness components of e-learning to provide a framework for developing qualitative change in higher education. Technol. Educ. J. 16, 221–236.
Trelease, R. B. (2016). From chalkboard, slides, and paper to e-learning: how computing technologies have transformed anatomical sciences education. Anat. Sci. Educ. 9, 583–602. doi: 10.1002/ase.1620
Tugwell, O. O., and Maduabuchukwu, A. P. (2020). Impediments to effective utilization of e-learning platforms for quality teaching and learning in universities in Niger-Delta, Nigeria. Int. J. Innov. Res. Dev. 9, 18–22. doi: 10.24940/ijird/2020/v9/i7/JUL20021
Tuševljak, M., Majcen, L., Mervar, L., Stepankina, T., and Cater, B. (2016). E-learning in higher education: focus groups and survey among students in Central Europe. J. Educ. Technol. 13, 11–20. doi: 10.26634/jet.13.2.8160
Tyagi, S. K., and Krishankumar, R. (2023). Examining interactions of factors affecting e-learning adoption in higher education: insights from a fuzzy set qualitative and comparative analysis. J. Sci. Technol. Policy Manag. 1, 1–21. doi: 10.1108/JSTPM-02-2023-0022
Tymoshchuk, N. (2022). Implementing E-learning to support learning and teaching foreign language: a case study in Ukrainian higher education. Arab World English J. 1, 233–244. doi: 10.24093/awej/covid2.15
Van Dijk, J. A. (2006). Digital divide research, achievements, and shortcomings. Poetics 34, 221–235. doi: 10.1016/j.poetic.2006.05.004
Verma, R. K., Gupta, S., and Illinich, S. (2024). Technology-enhanced personalized learning in higher education. In Advances in Technological Innovations in Higher Education. (Eds.) A. Garg, B. V. Babau, and Valentina E. Balas. Boca Raton: CRC Press, Taylor & Francis. 1, 71–92. doi: 10.1201/9781003376699-7
Violante, M. G., and Vezzetti, E. (2015). Virtual interactive e-learning application: an evaluation of the student satisfaction. Comput. Appl. Eng. Educ. 23, 72–91. doi: 10.1002/cae.21580
West, J., and Malatji, M. J. (2021). Technology integration in higher education: the use of website design pedagogy to promote quality teaching and learning. Electron. J. E Learn. 19, pp629–pp641. doi: 10.34190/ejel.19.6.2557
Wong, L. H., and Looi, C. K. (2011). What seams do we remove in mobile-assisted seamless learning? A critical review of the literature. Comput. Educ. 57, 2364–2381. doi: 10.1016/j.compedu.2011.06.007
Keywords: barriers, enabler, E-learning, higher education institution, technology
Citation: Olawale BE, Omodan BI and Saddiq K (2025) X-raying the enablers and barriers of e-learning in higher education institutions: a systematic review. Front. Educ. 10:1526076. doi: 10.3389/feduc.2025.1526076
Edited by:
Rizwan Raheem Ahmed, Indus University, PakistanReviewed by:
Irene Pittman Aiken, University of North Carolina at Pembroke, United StatesMutasim Al-Deaibes, Yarmouk University, Jordan
Copyright © 2025 Olawale, Omodan and Saddiq. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Babawande Emmanuel Olawale, Ym9sYXdhbGVAd3N1LmFjLnph