Success Of E-learning Systems Research Articles

An empirical study of students' perceptive on e-learning systems success

PurposeThe effect of e-learning success relies on the learning management system and its effectiveness provided to the learners. As a result, higher education institutions (HEIs) are expanding using various e-learning platforms and focusing on system and information quality. This study adopts the ISS (information system success) model to assess students' perception of e-learning system success (e-LSS).Design/methodology/approachA quantitative research approach was used to analyse 151 students' perceptions collected from HEIs in Oman. The survey instrument was built on prior research related to DeLone and McLean’s ISS model, and expert opinion was involved for validation. The snowball sampling method was used to collect the data, and participants' anonymity and confidentiality were maintained as part of the ethical process. The reliability of data was tested using Cronbach's alpha analysis. A statistical tool like correlation was used to examine the relationship between the study variables (system quality, information quality, user satisfaction and e-LSS).FindingsThis study’s results revealed that students positively perceived system usage, and users' satisfaction with e-learning systems (e-LSs) was high. Moreover, the correlation results indicated that the system and information quality aspects of e-learning significantly influence e-LSS.Practical implicationsThe study results on students' perspective towards e-learning information systems can be advantageous to HEIs and various stakeholders like policymakers, and e-learning platforms. It may support and assist the HEIs and corporate firms in deciding on e-learning platforms for students and learners, respectively. Moreover, the consolidated findings will contribute to the existing literature on e-learning success factors from students’ perspectives.Originality/valueThis study examines the students' perception of e-LSS in Oman HEIs and advocates prospects for further in-depth study and analysis.

Developing The E-Learning System Success Model: A Developing Country Perspective

This study aimed to develop a comprehensive e-learning system success model from a developing country perspective. The integrated lens of DeLone & McLean-Information System Success Model, the Model for Measuring E-learning System Success, and the Social Cognitive Theory was used to develop a research model. Twelve hypotheses were developed and tested with 188 participants. The study employed the Structural Equation Modeling technique to analyze data. Out of 12 hypotheses, two were rejected. At the same time, ten were supported, implying that variables such as contentment and information quality, user self-efficacy, user satisfaction, intention to use/use, net benefits, and loyalty to the system were appropriate for measuring the e-learning system success in developing countries. Based on these results, we recommend that the technical system quality and educational system quality of e-learning systems should be improved.

Development, Feasibility, and Knowledge Impact of a Massive Open Online Course on Radiation Safety: A Multicentre Prospective Cohort Study

This study reports the development of an innovative, interactive Massive Open Online Course (MOOC) teaching radiation safety principles in the vascular workplace, using stepwise e-learning with multiple choice question tests (MCQs), educational videos, and a serious game. The aim was to study the MOOC impact on radiation safety knowledge and assess its feasibility and acceptability. An international multicentre prospective study included team members active in the hybrid operating room. The MOOC was offered voluntarily via a secure online learning platform. A standardised MCQ test (15 questions) assessed radiation safety knowledge pre- and post-course (range 0 - 100%). Acceptability and feasibility were tested via the previously validated, Evaluating e-learning system success (EESS) model, using five point Likert scales. In eight centres across four countries, 150 of 203 invited endovascular team members consented. Over a seven week study period, surgeons (28%, including vascular surgery trainees and consultants), nurses (27%, including scrub, circulating and anaesthetic nurses), anaesthetists (43%, including trainees and consultants), and radiographers (3%) participated. Of those, 67% completed the course. The average radiation knowledge improved by 22.8% (95% CI 19.5 - 26.0%; p < .001) after MOOC completion, from 48% to 71% (standard deviation [SD] 14 and 15% respectively), requiring a mean time investment of 169 minutes (SD 89 minutes). In centres with a radiographer, mean knowledge gain after MOOC completion was significantly smaller (14%, SD 19% vs. 24%, SD 16%, p= .036). The course was deemed feasible and acceptable according to the EESS model with a total mean score of 3.68/5. This newly developed, multimodal MOOC was deemed feasible and effective across multiple international centres. The MOOC significantly contributes to radiation safety education of the entire endovascular team, improving radiation safety knowledge. The course may optimise workplace radiation safety behaviour and therefore enhance team and patient safety.

Medical students’ knowledge and attitude towards tele-education and associated factors at University of Gondar, Ethiopia, 2022: mixed method

BackgroundTele-education is the use of ICTs to conduct remote learning. It has been utilized to deliver ongoing training for many years. The world’s modern culture is increasingly reliant on the use of information technology to enhance standards of education. However, in order to deploy successful e-learning systems in a developing nation, understanding of user characteristics is required in the creation and usage of e-learning systems. Thus, this study will enable us to understand the user’s level of knowledge and attitude towards tele-education.MethodsAn institution-based quantitative cross-sectional study supported by qualitative design was used 397 medical students at University of Gondar from May to June 2022. A pre-tested self-administered structured questionnaires and in-depth interview were used to collect quantitative and qualitative data respectively. Thematic-content analysis was conducted using open-code software for analyzing qualitative data. Quantitative data was entered to Epi-data version 4.6 and exported to SPSS version 25 software for further statistical analysis. Binary logistic regression was conducted. The adjusted odds ratio(AOR) was used to measure the association between the dependent and independent variables.ResultsA total of 397 medical students were participated in this study with a response rate of 93.63%. In this study nearly six out of ten 230(57.9%) of study participants had good knowledge towards tele-education. More than half. 211(53.1%) of medical students participated on the study also had a favorable attitude towards tele-education. Factors associated with knowledge about tele-education is training related to ICT (AOR = 2.27 95% CI; (1.13,4.55)), knowledge of medical education digitization (AOR = 3.80 95% CI; (2.12,6.84)), high computer literacy (AOR = 2.82 95% CI; (1.68,4.72)) and favorable attitude towards tele-education (AOR = 3.52 95% CI; (2.12,5.84)). Factors associated with attitude towards tele-education is age group > 21 (AOR = 3.89, 95% CI; (1.33,11.39)) and good knowledge towards tele-education (AOR = 3.42,95%CI;(2.06,5.66)).ConclusionThe study revealed that the knowledge of the medical students was good and nearly five out of ten of them had a favorable attitude towards tele-education. The study shows that training related to ICT, knowledge of medical education digitization, high computer literacy and favorable attitude towards tele-education were associated significantly with knowledge of tele-education. In this study age group > 21 and good knowledge towards tele-education of study participants were associated significantly with attitude towards tele-education.

Revisiting the E-Learning Systems Success Model in the Post-COVID-19 Age: The Role of Monitoring Quality

The COVID-19 pandemic brought about significant changes in educational delivery methods and student learning. E-learning systems, which previous research had found to be effective in voluntary contexts, suddenly became mandatory but proved to be less effective for students worldwide. Hence, there is a need for academics and practitioners to revisit the e-learning systems success model in the post-COVID-19 era. Building upon previous e-learning and information systems success models, this study aimed to re-specify and validate the e-learning systems success model by examining the role of monitoring quality. Data were collected from 191 college students and analyzed using the partial least squares approach. The results indicated that information quality, system quality, and service quality had a positive influence on both user satisfaction and communication quality, which, in turn, positively impacted loyalty intention and subsequently enhanced learning effectiveness. Notably, the newly added construct of monitoring quality had the strongest effect on communication quality compared to information quality, system quality, and service quality. However, it had no impact on user satisfaction. The findings of this study provide several important theoretical and practical implications for e-learning systems success models in the post-COVID-19 era.

Examining the Critical Success Factors of E-Learning Using Structural Equation Model: A Case Study on the Mandatory Use

Several researchers have studied e-learning success factors. However, there is rare research linking the success factors from the student perceptions to their data stored in the e-learning system, i.e., the student usage behavior and learning achievement. In addition, there is little research in the literature on mandatory use contexts. Thus, this study aimed to systematically examine and investigate the critical success factors (CSFs) of e-learning used for e-learning evaluation, using an e-learning system in mandatory use as a case study. The study is based on the D&amp;M IS success model, the user satisfaction model, and success factors of e-learning systems. A structural equation model was used to analyze the data collected from 221 undergraduate students who used the system. The results indicated that e-learning success factors were information quality, system quality, instructor characteristics, diversity of assessment, system use, user satisfaction, benefits, and learning performance. In addition, system use has a highly positive and significant effect on learning performance, whereas the perceived benefits are determined by system use, instructor characteristics, information quality, and user satisfaction. Besides, instructor characteristics, system quality, and diversity of assessment had positive impact on user satisfaction. The findings provide insights to practitioners, academics, and policymakers to help them focus on factors that can be used to improve and evaluate the e-learning system. Our study contributes to the body of knowledge on e-learning system success and evaluation in mandatory use contexts.

Analisis Kualitas Layanan Terhadap Penggunaan Aplikasi Blended Learning Menggunakan Model EESS

&#x0D; &#x0D; &#x0D; &#x0D; Research aim : This study aims to test the Quality of Moodle Borneo E-Learning (BEL) which includes Service Quality, Student Quality and Lecturer Quality on Perceived Satisfaction, Perceived Usefulness and Benefits based on the E-learning System Success Evaluating Model for active BEL users&#x0D; Design/Methode/Approach : This research uses a quantitative approach with non-probability sampling method and the technique used is Quota Sampling. To determine the number of samples, the hair formula was used which determined that the sample consisted of 280 University of Borneo students who had used BEL. The data analysis method used is SEM (Structural Equation Modeling) with the help of the SmartPLS program.&#x0D; Research Finding : The results showed that the variables of Service Quality, Student Quality and Lecturer Quality had a positive and significant effect on satisfaction and usability. And the Satisfaction and Usefulness Variables also have a positive and significant effect on benefits.&#x0D; Theoretical contribution/Originality : It is hoped that this research can provide insight and knowledge as well as provide information to researchers and academics regarding the analysis of the quality of BEL application service quality using the EESS model.&#x0D; Practitionel/Policy implication : The results of this study are used as input for the Borneo Tarakan University's LP3M, so that in the future it can improve the quality and quality of BEL so that in the future students will be more comfortable doing online learning with BEL.&#x0D; Research limitation : In this study it only focuses on evaluating the quality of using the BEL application but only looks at it from the perspective of students at the University of Borneo Tarakan. And also focuses on the EESS conceptual model which includes only social factors, namely Service Quality, Learner Quality, Instructor Quality.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; sitive and significant effect on benefits

Technologies for designing and programming big data in e-learning

Recently, e-education around the world is developing rapidly and the main problem is the timely provision of students with quality educational information. A significant impetus for this is the global epidemic of covid-19. The problem of implementing e-education cannot be solved without analysing the large flow of information coming into the information environment of e-education from participants in the educational process – students, teachers, administration, etc. In this environment, there are a large number of different types of data, both structured and unstructured, which are difficult to process by traditional statistical methods. The aim of the study is to show that the development and implementation of successful e-learning systems requires the use of new technologies that would allow the storage and processing of large data streams. Large amounts of disk space are required to store large data. It is shown that to solve this problem it is expedient to use cluster technology NAS (Network Area Storage), which allows to store information of educational institutions on NAS - servers and to have access to them from the Internet. To process and personalize Big Data in the e-learning environment, it is proposed to use technologies MapReduce, Hadoop, NoSQL and others. The article provides examples of the use of these technologies in the cloud environment. These technologies in e-learning make it possible to achieve flexibility, scalability, accessibility, security, confidentiality and ease of use of educational information. Another important problem of e-learning is the discovery of new, sometimes hidden, relationships in big data, new knowledge (data mining), which can be used to improve the educational process and increase the efficiency of its management. To classify electronic educational resources, identify patterns (patterns) of students with similar psychological, behavioural and intellectual characteristics, the development of individualized curricula in the article it is proposed to use methods of big data analysis. The article shows that to date, many software applications have been developed for big data mining. These software products can be used for classification, clustering, regression and network analysis of educational information. The application of these methods in e-education will allow teachers to receive timely information about students, to respond quickly to any changes in the learning process, to make timely changes to educational content. The obtained results of the research are offered to be used for development of recommendations at creation of electronic courses in higher and secondary educational institutions of Ukraine.

Undergraduates’ Satisfaction with Zoom e-learning Application: Empirical Evidence from Management Undergraduates

E-learning is developing as the new paradigm of modern education. The global e-learning business is growing at a 35.6 percent annual rate and still, there are failures. The success of e-learning systems is predicted mainly by user satisfaction. However, factors derived from users’ satisfaction with using zoom for e-learning are still underexplored. Therefore, the purpose of this study is to explore the factors that might impact undergraduate satisfaction regarding the use of zoom applications for e-learning. A theoretical foundation was laid for the study from empirical findings based on that conceptual framework was developed. Data was collected from 213 Management undergraduates of the University of Ruhuna by using a questionnaire survey. Results of the study indicated that perceived quality, perceived value, and technology self-efficacy positively impact undergraduates’ satisfaction with using the Zoom application for e-learning. Further, the study found that perceived utility has a significant negative impact on undergraduates’ e-learning satisfaction by using Zoom. The study was conducted from a student's point of view and implies their actual desires for e-learning specifically the Zoom application. Based on the findings stakeholders can pay attention to taking necessary actions to fulfil students’ needs and guiding them to gain higher satisfaction with e-learning and finally it will lead to the overall success of implemented e-learning system.

Evaluating E-learning system success in higher education during the Covid-19

Human lives globally have been affected by the COVID-19 pandemic. The quantitative research method was followed to assess e-learning system success from students' perspectives during the pandemic. ISS and USAT model was adopted to measure it, and a survey was used to collect 632 voluntary students. The regression analysis method presented variations between the quality of factors that anticipate user-perceived satisfaction, system use, and individual performance. While the quality factors suggested the impact of the dependent variable was (collaboration, information, service, System, IATE, DIA, LCAx, and LPIWO). In students' opinion, the study found quality factors significantly positively influence the adopted model, except for the QSer and IATE. The study outcome is expected to help academic staff and learners with further research. Keywords: E-learning, distance education, students' opinion, DeL&amp; McL model, USAT model

Students' perspectives on using e-learning applications and technology during the COVID-19 pandemic in Indonesian higher education

PurposeThe e-learning-based approach is critical in keeping the wheels of education turning in the face of the COVID-19 epidemic. In this scenario, analyzing the implementation of the e-learning system is required to properly grasp the needs. The purpose of this paper is to demonstrate the relationship between technical system quality, information quality, service quality, educational system quality, support system quality, learner quality, instructor quality, perceived satisfaction, perceived usefulness, e-learning system use and benefits.Design/methodology/approachThis study was carried out by giving online questionnaires to students attending private institutions in Indonesia. A total of 593 students participated in the study and provided responses. The structural equation model, which is supported by the program WarpPLS7.0, is used to analyze the data.FindingsMaintaining the quality of the technological system, the information system, the learners and the educational system can help achieve the goal of increasing perceived utility. In the meanwhile, factors such as inadequate service quality, educational system quality, support system quality and teacher quality can all pose challenges to perceived levels of satisfaction. To get the most out of e-learning apps, users' expectations about how fun, useful and easy to use they are need to be met.Research limitations/implicationsThis study was carried out in the midst of the COVID-19 epidemic with a restricted number of participants from Indonesian institutions of higher education. This research has the potential to be expanded into a variety of different types of higher education in the future.Practical implicationsThe main thing that will determine whether an e-learning system model works is the quality of the learners.Originality/valueThe institution should think about changing the material offered in the e-learning system to make it easier for students to grasp by describing the current material and providing digital handouts of lecturers' explanations. This study expanded the e-learning system success model and applied it to the evaluation of e-learning deployment in Indonesian higher education. This study will improve student comprehension of the e-learning model and contribute to the body of knowledge about e-learning applications and technology.

Exploring Factors Affecting Graduate Students' Satisfaction toward E-Learning in the Era of the COVID-19 Crisis.

Background: Shifting the educational system from a traditional to an online context during COVID-19 necessitated several considerations to assure students’ satisfaction with e-learning. Aim: This study aims to explore the factors influencing students’ satisfaction with e-learning during the COVID-19 crisis. In particular, it tests multiple mediations, student factors, and system quality between students’ satisfaction and each course evaluation and instructor’s performance. Methodology: In this cross-sectional study, 258 undergraduate and postgraduate students enrolled in online courses at multiple Malaysian universities were recruited using non-probabilistic purposive sampling. Data were collected using a questionnaire that assessed four factors that influenced students’ satisfaction with e-learning during the COVID-19 crisis (i.e., instructor performance, course evaluation, student factors, and system quality) and analyzed using the partial least squares route structural equation modelling (PLS-SEM). Results: The results indicated that the four factors were significantly associated with students’ satisfaction with e-learning during COVID-19. Student factors and system quality were the most factors predicting students’ satisfaction with e-learning. Findings indicate statistically significant relationships between the instructor’s performance, student factors, course evaluation, and system quality on students’ satisfaction. Furthermore, the results depict that both course evaluation and system quality serially mediate the relationship between instructors’ performance and students’ satisfaction. Conclusion: This study finds that improving and enhancing student factors and system quality is critical for students’ satisfaction with e-learning. Furthermore, e-learning platforms should contain new advances of computer-mediated technologies that enable collaboration, which is a critical factor in the success of e-learning systems.

Measuring Learner Satisfaction of an Adaptive Learning System.

Tertiary educational institutions have continually implemented various educational technologies to support student learning. An example is adaptive learning systems, within which learners take ownership of their learning experience and accelerate future learning. Despite the importance of considering learner satisfaction in the development of such systems given how it has been widely acknowledged as an indication of the success of e-learning systems, research in the area of adaptive learning technologies for education has concentrated more on tailoring instruction to implement personalised learning. A review of instruments measuring learner satisfaction of virtual learning environments found that the learner satisfaction questionnaire (LSQ) that was developed to measure learner satisfaction of e-learning systems, and preliminarily validated by means of exploratory factor analysis, was most suitable for adaptation. This study sought to adapt and validate the LSQ for the purpose of measuring learner satisfaction of an adaptive learning system developed in-house. A total of 121 tertiary students recruited via availability sampling took part in this study. Hierarchical confirmatory factor analysis was performed as part of the validation. Results presented the adapted LSQ as a 14-item instrument that can be readily deployed on a broad scale basis. The adapted LSQ also yielded valid and reliable satisfaction scores both at the subscale as well as the overall scale level. Practical implications are discussed, noting that such scores could inform the further development and refinement of AdLeS or similar systems, with the view of benefiting students.

Evaluating and Prioritizing Barriers for Sustainable E-Learning Using Analytic Hierarchy Process-Group Decision Making

E-Learning is a popular computer-based teaching–learning system that has been rapidly gaining global attention during and post COVID-19. The leaping changes in digital technology have enabled E-Learning to become more effective in recent years. It offers freedom from restrictions caused by geographical boundaries and provides time flexibility in the teaching–learning process. Apart from its numerous advantages, the success of E-Learning depends upon many critical success factors (CSFs) and barriers. If the barriers that lie in the way of successful E-Learning implementation are not addressed diligently, it will limit E-Learning success. It has been revealed through past research that these barriers are serious threats that need immediate attention in their redressal. This paper attempts to reveal sixteen barriers under four different dimensions by going through a comprehensive review of the literature and engaging decision makers. Furthermore, it uses the Analytic Hierarchy Process-Group Decision Making (AHP-GDM) methodology to evaluate and prioritize them. The results obtained show that barriers related to the Institutional Management Dimension (BIMD), Infrastructure and Technological Dimension (BITD), Student Dimension (BSD), and Instructor Dimension (BID) pose the greatest challenges in the successful implementation of E-Learning. The AHP-GDM methodologies reveal the comparative relationship among these barriers as BIMD &gt; BITD &gt; BSD &gt; BID and further quantify their negative effects as 46.35%, 29.88%, 12.30%, and 11.4%, respectively, on successful E-Learning systems (‘&gt;’ indicates comparative challenges).

DESIGN AND VALIDATION OF EDUCATIONAL THEORIES-BASED FRAMEWORK FOR E-LEARNING SYSTEMS

Educational theories play a key role in attaining e-learning success. This contribution of theories is even more important for primary education which requires special attention since children possess childish behaviors.However, research shows that most e-learning systems lack theoretical foundations. We argue that these systems can be more effectively utilized by integrating educational theories. Therefore, we offer an e-learning system design framework based on learning and e-learning theories for primary education. The paper first discusses educational theories from different domains. Next, we provide an overview of how each theory can contribute toa successful e-learning system. Ethnographic Content Analysis (ECA) was conductedof the most renowned theories to construct this framework. Shortlisted theories belonged to domains of constructivism, early education, and e-learning. Design principles from each theory were extracted with the help of grounded theory methodology. These principles were mapped to e-learning system components including tasks, tools, and interfaces by performing thematic analysis.A comprehensive framework based on theoretical design principles was constructed. Lastly, the framework was validated by developing an e-learning system based on design principles. We evaluated students academic performance after they used the developed system for three weeks. Findings revealed that an e-learning system has great potential in primary education and can assist practitioners in achieving desired learning outcomes by integrating educational theories. It was also found that the sequence in which learning activities are performed can overshadow a systems performance and hence needs to be addressed for e-learning success.

Author Correction: Analyzing student aspirations factors affecting e-learning system success using a structural equation model

Author Correction: Analyzing student aspirations factors affecting e-learning system success using a structural equation model

What roles do quality and cognitive absorption play in evaluating cloud-based e-learning system success? Evidence from medical professionals

Purpose The purpose of this study is to propose a hybrid model integrating the expectation-confirmation model with the views of cognitive absorption (CA) theory and updated DeLone and McLean information system success model to examine whether quality factors as antecedents to medical professionals’ beliefs can affect their continuance intention of the cloud-based e-learning system. Design/methodology/approach This study’s sampling frame was taken from among medical professionals working in hospitals with over 300 beds in Taiwan which had implemented the cloud-based learning management system (LMS) with a blend of asynchronous and synchronous technologies. Sample data for this study were collected from medical professionals at six hospitals in Taiwan. The data for this study were gathered by means of a paper-and-pencil survey, and each sample hospital that participated in this study was asked to identify a contact person who could distribute the survey questionnaires to medical professionals who had experience in using the cloud-based LMS in their learning. A total of 600 questionnaires were distributed, and 378 (63.0%) usable questionnaires were analyzed using structural equation modeling in this study. Findings This study proved that medical professionals’ perceived learner–content interaction quality, learner–system interaction quality, service quality, cloud storage service quality and learner–human interaction quality all positively caused their perceived usefulness, confirmation and CA elicited by the cloud-based e-learning system, which jointly explained their satisfaction with the system, and resulted in their continuance intention of the system. Research limitations/implications Several limitations and suggestions may open avenues for future research. First, the limitation of self-reported measures should be considered; future research may combine with qualitative data (e.g. semi-structured, narrative, in-depth interviews, focus group interviews and open-ended questions) to get more complete interpretations of medical professionals’ cloud-based e-learning continuance intention. Next, this study’s data were collected from hospitals in Taiwan only; given this study’s limited scope, future research may generalize this study’s sample to the respondents of other national cultural backgrounds and make cross-country comparisons to enhance the completeness of this study. Finally, this study’ results were based on cross-sectional data; future research may use a longitudinal analysis by taking into account the evolution of medical professionals’ cloud-based e-learning continuance intention over time. Originality/value This study fully evaluates interaction-related and cloud-related quality determinants through an understanding of medical professionals’ state of CA in explaining their cloud-based e-learning system continuance intention that is difficult to expound with only their utilitarian perception of the system. Hence, the results contribute to deep insights into an all-round quality evaluation in the field of medical professionals’ cloud-based e-learning continuance intention, and extrinsic and intrinsic motivators are both taken into consideration in this study’s theoretical development of medical professionals’ cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic.

The adoption of e-learning in response to COVID-19 is to ensure the continuous development of human capital through alternative means. Nevertheless, the success of e-learning systems depends much on the attitude of the users. This study developed and empirically tested a model to predict antecedents of students’ actual usage of e-learning during the COVID-19 period. A synthesis of UTAUT 2, Self Determination Theory and Core Self-Evaluation Theory were employed to examine the behaviour of students using a sample of 1024. PLS-SEM was used to analysed the hypothesised paths in the model. The results revealed that (1) Personality is positively related to behavioural intention (2) Actual usage is positively influenced by motivational factors (3) Behavioural Intention positively mediates the relationship between motivational factors and actual use (4) motivational factors positively mediate the relationship between UTAUT 2 constructs and behavioural intention. The results will guide stakeholders in education, especially e-learning system designers to incorporate personality and motivational factors in the designing of e-learning systems in order to increase the acceptability of the system by students. This study is among the first few attempts to incorporate personality, motivation and UTAUT2 to examine e-learning users’ behaviour, especially in Sub-Saharan Africa during the COVID-19 pandemic. This work presents a contemporary perspective of e-learning users’ behaviour during the COVID-19 pandemic.

Analyzing student aspirations factors affecting e-learning system success using a structural equation model.

E-learning system success factors identification is of major interest in higher education. Understanding the role of students’ aspirations factor affecting the success of the e-learning system is a challenge for most educational institutions. The present study aims to analyze the effects of students’ aspirations factors in ensuring the success of the e-learning system through a developed research model extended from the integrated updated Unified Theory of Acceptance and Use of Technology and the DeLone and McLean Information System Success Model. The study participants who made up the model data sample were collected from 379 students engaged in the e-learning system at universities across the Kingdom of Saudi Arabia. Students’ aspirations are resumed in Motivation, Expectation, and Enjoyment factors. The structural equation model was used to analyze the main causes and effects that would guide students towards the use and success of the e-learning system. The study results showed the strong relationship between the students’ aspirations factors (Motivation, Expectation, and Enjoyment) and the adoption factors (Intention to Use and Perceived Usefulness) that lead to increased students’ confidence that e-learning adds value to their educational experience. In addition, results revealed the determining role of the effect of the Enjoyment factor on the benefits expected from the e-learning system process. Therefore, higher education institutions that aspire to benefit the most from the e-learning system should pay close attention to the aspirations of their students and enhance their enjoyment, and then redefine the “e” in e-learning as enjoy rather than simply electronic.

Towards a Sustainable Adoption of E-Learning Systems: The Role of Self-Directed Learning

Aim/Purpose: This study seeks to investigate the factors that influence online students’ continued usage intention toward e-learning systems by presenting an extended model that is based on the Delone and McLean (2003) IS success model (D&amp;M ISS model). Background: The use of e-learning systems in this era has become a vital element of delivering higher education. Learning via e-learning systems has significant benefits that support conventional learning. Thus, it is crucial to measure the success of e-learning systems’ implementation. Methodology: This study was conducted with 590 undergraduate and postgraduate students from three private universities in Jordan, and data was gathered via an online self-report questionnaire. Contribution: Theoretically, this study advances the literature and empirically examines a modified version of the D&amp;M ISS model by including context-specific factors that are drivers of successful implementations of e-learning systems. Findings: The path analysis with structural equation modelling confirms that students’ satisfaction and their continued usage intention regarding the e-learning system are positively related to service quality, system quality, and information quality. Self-directed learning, however, has a negative effect on satisfaction and continued usage intention. Furthermore, the findings reveal that both satisfaction and continued usage intention positively influence students’ perceptions of perceived academic performance. Recommendations for Practitioners: The quality of learning content format and design are recognized as fundamental factors for e-learning success. Thus, both instructors and e-learning developers should provide reliable, accurate, and up-to-date learning materials. This directs e-learning developers toward designing systems with simple and useful functionalities that embrace the essential features that enable students to perform the required tasks effectively and to access and share learning materials flexibly. Furthermore, the current study reveals that self-directed learning (SDL) is a key barrier to successful e-learning system employment. It has a negative impact on satisfaction (SAT) and continued usage intention (CUI). Thus, developing students’ skills related to SDL is deemed a necessity. This could be attained by designing contemporary pedagogical curricula that are based on student-centered learning. This approach to learning encourages students to acquire self-regulatory skills and be accountable for their learning. This environment has to be supported by pedagogical tools (e.g., synchronous/asynchronous communication channels and multimedia tools) to enable effective interaction between instructors and students. Recommendation for Researchers: The current study does not investigate the role of potential moderators that might influence the research model’s relationships. Future studies might tackle such limitation by examining the moderating effect of computer self-efficacy and culture. Impact on Society: This study reveals that the success of e-learning systems depends not only on the quality of the information, system, and service but also on student self-directed learning. Future Research: The sample employed for this study was selected from three private universities in Jordan; consequently, the results cannot be generalized to the entire student population of Jordan. Further research, therefore, should focus on targeting a larger scope by including public universities, which in turn would enhance the generalizability of the findings. In addition, this cross-sectional study was conducted using a quantitative method based on the use of self-reported online survey to gather data. Thus, future research should consider longitudinal study that employs a mixed methods approach to reveal additional constructs and insights regarding e-learning system adoption by students.