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Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of stakeholders' satisfaction. This research focuses on an intelligence-driven solution to recommend the most effective approach to education policymakers by considering the unique characteristics of all components within the educational system (course type, student and teacher characteristics, and technological features) to achieve a sustainable E-learning system.

Through a systematic literature review and qualitative content analysis, a conceptual model of the critical components influencing E-learning quality and satisfaction has been developed. The proposed model comprises six main dimensions: usage, service quality, learning system quality, content quality, perceived usefulness, and individual characteristics. These dimensions are further divided into 15 components and 114 sub-components. A data mining process encompassing two scenarios has been designed to prioritize the components impacting E-learning success.

In the first scenario, data mining techniques identified the most influential components based on the features outlined in the conceptual model. According to the results, the components affecting E-learning quality enhancement in the studied case are “usage purpose, system loyalty, technical and supportive system quality, and student characteristics.” The second scenario examines the impact of individuals' personality types and learning styles on E-learning satisfaction across various aspects (Average System Satisfaction, Overall System Satisfaction, Efficiency and Effectiveness, Skill Enhancement, and Personal Enhancement). The findings reveal that, with an accuracy of over 70%, E-learning satisfaction for diplomat and guard learners is influenced by the alignment between “course learning style” and “student-suggested course learning style.” Conversely, for analyzer and researcher types, satisfaction levels are impacted by the “learning style compatible with their personality type.”

Implementing a dynamic model founded on data mining enables educational institutions to personalize the E-learning experience for each individual as much as possible. The study’s findings indicate that “achieving higher satisfaction levels in the E-learning process is not necessarily contingent upon providing a learning style congruent with learners' personality types.” Rather, perceived and suggested learning styles exert a more profound influence. Consequently, providing prescriptive principles for higher education institutions seeking to enhance E-learning quality is inadvisable. Instead, adopting a dynamic, knowledge-based process that furnishes recommendations to policymakers for each course—tailored to the specific course type, teaching records, current processes and technology, and student type—is highly recommended.

This study conducts a systematic literature review to examine the interrelationships between e-learning critical success factors, instructors' perceptions of these factors, and the corresponding institutional actions taken by higher education institutions to achieve success in e-learning implementation, by fostering instructors’ acceptance of e-learning as a viable mode of delivery in higher education.

The research design employed in this study involves a systematic literature review of 43 peer-reviewed articles from EBSCO host and Scopus databases. The selected methodology employed thematic analysis of the gathered data by utilizing a multistep qualitative coding method of analysis.

The systematic literature review delivers three key findings. First, there is a notable divergence between instructors' perceptions of critical success factors for e-learning in higher education and the perspectives of other stakeholders, such as students, e-learning experts, and institutional management. Second, it emphasizes the importance for higher education institutions to understand and address instructors' perceptions to facilitate effective e-learning implementation. Third, the literature suggests potential causal relationships between institutional actions addressing the success factors deemed important by instructors and instructors' sustained acceptance of e-learning as a viable delivery mode.

The present study enriches knowledge of instructor perceptions of critical success factors for effectiveness in higher education by extending research in institutional management actions to enable their achievement. This study has implications for research strands on how instructors’ motivation and propensity for e-learning acceptance can be influenced by institutional management and how to reduce the level of resistance to adopting e-learning courses by addressing e-learning’s critical success factors as perceived by instructors.

Based on the theoretical insights derived from the systematic literature review, a conceptual framework is constructed, integrating the three concepts under investigation: success factors, institutional actions, and instructors' acceptance of e-learning in higher education. This framework provides a basis for future research seeking to validate the potential causal relationships among these concepts. Moreover, the study contributes to existing literature by addressing and consolidating research strands related to critical success factors and instructors' perceptions of e-learning effectiveness in higher education.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

E-learning has become a polarizing issue. Some say that it enhances accessibility to education and some say that it hinders it. While the literature on the subject underscores the effectiveness of the pedagogical frameworks, strategies and distance learning technologies, the firsthand accounts of students, parents and practitioners challenge the validity of experts’ assessments. There is a gap between theory and practice and between the perceptions of providers and consumers of online learning. Following a period of lockdowns and a transition to online learning during the recent pandemic, the prevailing sentiment toward a distance mode of instruction became one of strong skepticism and negative bias. The aim of the study was to examine why e-learning has struggled to meet stakeholder expectations. Specifically, the study posed two research questions: 1. What are the reasons for dissatisfaction with online learning? 2. What are the implications for future research and practice?

The study used a mixed methods approach to examine the reasons behind negative perceptions of online learning by comparing the firsthand accounts posted on social media with the literature. To this end, n = 62,874 social media comments of secondary and postsecondary students, as well as parents, teachings staff and working professionals, covering the span of over 14 years (2008–2022), were collected and analyzed.

The study identified 28 themes that explain the stakeholder’s discontent with the online learning process and highlighted the importance of user-centric design. The analysis revealed that the perceived ineffectiveness of distance education stems from the failure to identify and address stakeholders’ needs and, more particularly, from the incongruence of instructional strategies, blindness to the cost of decisions related to instructional design, technology selection and insufficient levels of support. The findings also highlight the importance of user-centric design.

To address dissatisfaction with e-learning, it is imperative to remove barriers to learning and ensure alignment between technology and learners’ needs. In other words, the learning experience should be personalized to account for individual differences. Despite its cost-effectiveness, the one-size-fits-all approach hinders the learning process and experience and is likely to be met with resistance.

Drawing from the extensive literature, the study offers an explanation for stakeholders’ discontent with e-learning. Unlike survey research that is prone to social desirability bias, the sample provides a rare opportunity to observe and measure the visceral reactions that provide a more authentic sense of stakeholders’ perceptions toward online learning. The authors offer recommendations and identify areas for future research.

This systematic review aims to assess the studies collected by identifying factors influencing the acceptance of e-learning systems before and during the current propagation of the COVID-19 pandemic.

This study undertook a literature review on the in-depth revision of studies published before 2021. The reviewed research papers meet the inclusion and exclusion criteria. A total of 97 out of 214 articles met the inclusion criteria and were subsequently used in this review.

The findings revealed that the survey questionnaire is the most common data collection instrument used regardless of the research objectives. 2019 was a remarkable year because of the emergence of the COVID-19 pandemic.

This systematic review relied on specific databases (ScienceDirect, Emerald, IEEE and Google Scholar) to search for the articles included in this paper. However, these databases may not comprehensively represent all papers published on e-learning using the technology acceptance model (TAM).

This paper suggests a guide for managers and scholars in educational institutions and acts as a roadmap for practitioners and academics in the educational field and policymakers. This research spotlights the significant factors influencing the acceptance and adoption of e-learning.

This research assessed articles that examined the TAM in e-learning and classified them according to their methodology, country of dissemination, context and distribution within the year of publication. This paper contributes to the body of knowledge in a way that will benefit stakeholders in an educational setting.

The study aims to assess the impact of electronic learning (e-learning) on students' performance (SP), with an emphasis on the mediating role of sustainable education (SE) at the Sharjah Police Sciences Academy (SPSA). The urgency of this study was highlighted by the global COVID-19 pandemic that happened between 2020 and 2022, which emphasized the need for e-learning as a tangible and imperative solution.

The study applied a quantitative approach, targeting the 91 student population at SPSA in the winter semester of 2022/2023 who practiced the e-learning process. A comprehensive survey was implemented disseminating 91 questionnaires by Google Forms to all students. Of the total, 61 questionnaires were returned, resulting in a response rate of 67.03%.

The results revealed that e-learning predictors explained 85.4% of the variations in SP, and 46.4% of the variations in SE. The model demonstrated a strong fit and high predictive relevance. The indirect impact of e-learning on SP through SE was found to be positive and statistically significant at the 0.05 level. Consequently, the mediation effect was considered partial and statistically significant.

Policymakers and educators should consider findings of the study when designing educational programs and policies. Accordingly, the SPSA management could gradually focus on safeguarding a sustainable e-learning environment and improving high-tech platforms. This would involve creating a sustainable e-learning curriculum to enable students to remain informed on the best e-learning practices.

An empirical study is essential for exploring the optimal answers to inquiries related to e-learning, SE and their impact on SP. The finding of the current study may contribute to the existing knowledge on e-learning, SE and SP. Additionally, they may improve learning activities and provide more sustainable learning experiences, leading to enhanced learning outcomes for students

This study aims to reveal the impact of e-learning on accounting education amid COVID-19 in Jordanian universities from the viewpoint of faculty members.

The questionnaire is used as a study instrument distributed to faculty members at the Accounting Departments of the Jordanian public and private universities. Due to the COVID-19 pandemic, Google Forms has been used to distribute 117 questionnaires that have been analyzed via the partial least squares-smart program.

The results show a negative impact of learning difficulties on accounting education, a negative impact on the personal skills of faculty members on the digitization of accounting education, no impact on the personal skills of faculty members, a positive impact on training courses, the use of technology on accounting education and the digitization of accounting education, as well as a positive impact on the skills of faculty members on the digitization of accounting education.

These results are significant in determining the adequacy of online learning for accounting education at the Accounting Departments of Jordanian public and private universities from the viewpoint of faculty members amid COVID-19.

This study highlights the impact of the e-learning system imposed amid COVID-19 on accounting education, teaching efficiency and the future of accounting education.

The purpose of this paper is to investigate the factors that influence business students’ adoption of e-learning systems by merging innovation diffusion theory (IDT) and the teaching for professional competence model (TPCM).

Snowball sampling was used to conduct the survey. In addition, 217 responses were obtained from students at private educational institutions. Similarly, literature on the determinants of e-learning adoption, TPCM, and IDT were reviewed to contribute to the factors that are instrumental in determining e-learning systems adoption.

The findings of the study show that e-learning systems adoption is influenced by factors such as online collaborative learning (OCL) and technology self-efficacy. Above all, the OCL variable was found to be influential in determining students’ adoption of e-learning systems platforms. On the contrary, perceived attributes such as perceived compatibility and perceived relative advantage were found not to be significant determinants of e-learning systems adoption.

This study contributed not only to the theoretical extensions but also to practical implications, which would benefit the policymakers of higher education providers in terms of e-learning system adoption in the country.

IDT and TPCM models are evaluated alongside additional variables, namely, OCL and technology self-efficacy. As a result, this paper will serve as a useful reference guide for academicians, higher education administrators, and future researchers.

The intricate and unpredictable nature arising in higher education institutions (HEIs) implementing technology-driven change for e-learning environments demands a much closer examination of individuals’ interpretations and interactions as they undergo these changes. Through a micro-foundational lens, this study aims to examine the micro-level inhibitors and supporting factors of individual’s readiness for change by investigating technology-driven change in HEIs.

A two-phased research design using grounded theory methodology was used to collect and analyse data incorporated within a single-case study in an HEI. Data was collected using semi-structured interviews with 22 participants, followed by a focus group with eight participants centered on factors affecting their readiness for change during technology-driven change in e-learning environments. The data analysis followed an iterative constant comparative approach and its three-phased coding process: open, axial and selective coding.

This study revealed that staff with little awareness of the organisations expectations towards a technology-driven change or who are poorly communicated with can exhibit higher resistance and lower individual readiness for change. While macro-level factors of organisational structure can contribute to the success or failure of technology-driven change, the fundamental features related to individuals’ readiness for change are integral to understanding the micro-level causal behaviours underlying these macro-level phenomena.

The dominant model of change is often focused on drivers that are centered on examining macro-level constructs rather than individuals who are facing the change. This study presents theories on readiness for change and offers a micro-foundational view to bring new perspectives into the current literature on how individual-level micro-foundations enhance understanding of technological change in HEIs.