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Universities have focused on learning outcomes as a metric for evaluating the quality assurance of educational systems. However, due to the absence of a clear guide on measuring outcomes and analysing them accordingly to improve the educational cycle, educators struggled to efficiently and effectively address shortcomings. By proposing a new framework, this study fills this gap and provides a guided approach to measuring learning outcomes in the context of university e-learning systems. Facilitated by a comprehensive research literature review of 102 articles, filtered from 271 articles using the PRISMA method, the opinions of five experts regarding e-learning systems and their outcomes were analysed using the analytical hierarchy process (AHP) to provide priority rankings. Teaching methods, teaching quality, learning environment, and students emerged as the main factors, along with their sub-factors. Moreover, our experts from diverse educational and geographical backgrounds provide added value, enabling the framework to be implemented across various environments and fields. Ultimately, this framework accurately measures sub-factors to identify the strengths and weaknesses of educational variables. The proposed framework is a step in the right direction, enabling the design of a suitable system that takes into account users' needs when assessing e-learning outcomes. [ABSTRACT FROM AUTHOR]

This study aims to explore the difference between on-line and off-line teaching and comprehensively evaluate the of elearning system operation effect as both technology-mediated learning and an open information system. This study develops "process-situation-result" (PSR) network, a comprehensive learning system evaluation model. It empirically analyzes the PSR models under off-line and on-line teaching, as well as the intermediary role of e-learning situation in the impact of e-learning process on elearning results. The results show: (1) Learners' perception of e-learning situation is obviously different between off-line and on-line teaching. (2) The eight dimensions of e-learning process have no significant direct impact on e-learning outcome Except in on-line teaching groups, SF (getting self-feedback) has a significantly positive influence. In off-line teaching, GA (gaining attention), IO (informing learner of the objectives), and PG (providing learning guidance) have indirect effects on e-learning. (3) GA, IO and PG have a direct impact on e-learning situation in both on-line and off-line teaching, and only RK (Stimulating recall of prior knowledge) has an impact only in on-line teaching. The other four dimensions have no direct impact on e-learning We provide a theoretical framework for the integration of technology and teaching, on-line teaching and off-line teaching. [ABSTRACT FROM AUTHOR]

This study highlighted the role played by digitalization elements, such as information and communication technology (ICT) adoption, the social internet of things (IoT), and artificial intelligence (AI), in e-learning systems. It also examined the mediating role of digital literacy (DL) and pedagogical digital competence (PDC) and the potential moderating role of technostress (TS). A total of 262 responses to survey questionnaires were received from the IT administrators who worked under the directorate of information technology in top QS ranking Malaysian universities; the survey data was then analyzed through PLS-SEM. The study findings revealed that ICT adoption and the social IoT considerably impact e-learning systems and highlighted that artificial intelligence also has a partial impact. Digital literacy and pedagogical digital competence also significantly mediated the relationships between ICT adoption, artificial intelligence, and e-learning systems. Social IoT and technostress did not show a significant impact. The study developed a new theoretical concept for adopting innovative technology in e-learning systems through 'Four Tier Technology Gears', such as start-up, boost-up, smooth-up, and speed-up technology gears. From a theoretical perspective, the study has built-up a theoretical affiliation with the TAM and UTAUT models, which are especially proposed for technology adoption in real-life. The study provides remarkable and valuable recommendations to researchers, designers, policymakers, IT instructors, and structural developers in the context of awareness of key facts for e-learning systems in practical life – especially in an emergency condition, such as the Covid-19 pandemic in Malaysia. [ABSTRACT FROM AUTHOR]

In smart education, adaptive e-learning systems personalize the educational process by tailoring it to individual learning styles. Traditionally, identifying these styles relies on learners completing surveys and questionnaires, which can be tedious and may not reflect their true preferences. Additionally, this approach assumes that learning styles are fixed, leading to a cold-start problem when automatically identifying styles based on e-learning platform behaviors. To address these challenges, we propose a novel approach that annotates unlabeled student feedback using multi-layer topic modeling and implements the Felder–Silverman Learning Style Model (FSLSM) to identify learning styles automatically. Our method involves learners answering four FSLSM-based questions upon logging into the e-learning platform and providing personal information like age, gender, and cognitive characteristics, which are weighted using fuzzy logic. We then analyze learners' behaviors and activities using web usage mining techniques, classifying their learning sequences into specific styles with an advanced deep learning model. Additionally, we analyze textual feedback using latent Dirichlet allocation (LDA) for sentiment analysis to enhance the learning experience further. The experimental results demonstrate that our approach outperforms existing models in accurately detecting learning styles and improves the overall quality of personalized content delivery. [ABSTRACT FROM AUTHOR]

This study examines the relationship between the Total Quality Management Strategy (STQM) variable and the E-Learning System (ELS) variable in the context of climate change. The aim is to develop a sustainable educational system and effectively incorporate technological improvements at the University of Kufa. This will be achieved by surveying the perspectives of various individuals. The teaching staff at the university and its colleges used the random sample approach and utilized statistical tables to investigate the population of 2262 teaching staff members. The study determined that the ideal sample size comprises 327 teaching staff members. Of the sent surveys, 20 were not received, and 12 were incomplete. Therefore, 295 questionnaires that met the criteria were used for statistical analysis. The findings demonstrated a considerable and favorable impact of the entire quality management approach on the e-learning system. We found that implementing comprehensive quality control in the e-learning system is efficacious and should be used. The effectiveness of the elearning system in higher education depends on implementing comprehensive quality management. Several suggestions have been put forth to enhance the standard of higher education in Iraq and establish a sustainable educational system amidst the challenges posed by climate change. When formulating comprehensive strategic plans for quality management, all faculty members must exert maximum effort in attaining total quality management. This can be achieved by contributing beneficial ideas and implementing advanced educational programs while adapting academic curricula to anticipate the effects of climate change. [ABSTRACT FROM AUTHOR]

The Internet and cloud computing technology have enabled learners to choose courses based on their interests through e-learning systems. E-learning systems such as Massive Open Online Courses (MOOC) offer a comprehensive curriculum and teaching resources, including courseware, teaching videos, exercises, and homework. These systems provide free courses, rich content, and flexible selection. However, the abundance of teaching resources in e-learning systems can lead to information overload, making it challenging for learners to select suitable courses and resources. Personalized learning recommendation is a research field within intelligent learning. Its goal is to automatically and efficiently identify learners’ characteristics and recommend matching learning resources to specific learners on e-learning systems to enhance learning motivation and effectiveness. This study examines the research articles on personalized learning recommendation technology and methodology published between 2013 and 2023, and only English articles and conference papers were selected. This study collects articles from five scientific databases: ACM Digital Library, IEEE Xplore, ScienceDirect, SpringerLink, and Worldwide Science. Out of 3413 identified articles, 64 relevant studies were selected for further systematic literature research. Only those with specific recommendation methods or implementation codes are chosen to ensure the quality of the articles. It summarizes the modeling of learners and learning objects and the algorithms used for personalized learning recommendations. Finally, the problems of current personalized learning recommendation methods are outlined, and views on future research opportunities are proposed.

With the emergence of the digital era, the e-learning platform has become an effective tool for obtaining quality e-learning content. However, despite its potential, the true extent of its capabilities has yet to be fully explored. In order to attract users and maximize revenue, e-learning platforms are now expected to provide content tailored to their users' needs and preferences. These recommendations are generated by considering factors such as prior purchases, browsing history, demographic information, and more. By leveraging these advanced technologies, e-learning platforms can enhance the learning experience by providing users with content that is both engaging and relevant to their individual needs and interests. This paper explores the popular Machine Learning (ML) techniques employed in e-learning content recommender platforms. Two machine learning techniques, k-Nearest Neighbour Baseline (KNNBaseline) and Singular Value Decomposition (SVD), are selected and used to accurately forecast customer interests and preferences. By examining the data patterns and user behaviors, these ML techniques provide insights into the most relevant and personalized educational content for individual users, enhancing their learning experience. The item ratings predicted are generated based on the underlying pattern in past ratings of users. The performance of applied approaches was assessed using several evaluation metrics, which include root mean square error and mean absolute error. [ABSTRACT FROM AUTHOR]

Blackboard is the most recognized integrated e-learning management system. It has been proven especially during the COVID-19 pandemic when all businesses shifted online. It manages the educational process synchronously and asynchronously and provides a safe learning environment for students and faculty. This survey-based study aims to understand the use of learning management systems (Blackboard) among higher education students and faculty at King Abdulaziz University (KAU) by exploring different aspects of the system features and determining whether mobile devices and social media influence the use of Blackboard. The findings confirm the importance of improving the quality of LMS already in use by providing more knowledge about effective utilities of LMS tools and technical support for LMS use with mobile devices. Furthermore, this study validates the importance of making the most of LMS, especially in situations like the COVID-19 pandemic. The study's implications indicate a positive correlation between mobile blackboard use and social media if solely used for the learning process rather than for distractions. [ABSTRACT FROM AUTHOR]

Introduction: The outbreak of Coronavirus Disease-19 (COVID19) was a global disaster that greatly impacted the education system. The Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis can be used to identify favourable and unfavourable factors and conditions in offline and e-learning systems, and to address problems in a targeted manner. Aim: To evaluate the understanding and perception of students regarding the online learning system through SWOT analysis. Materials and Methods: This cross-sectional study was conducted at a tertiary care teaching hospital in the Department of Pharmacology at a tertiary care teaching hospital in Tamil Nadu, India for a duration of one month in October 2021. The study included 589 undergraduate students from medical, dental, and allied health sciences. A preformed questionnaire using Google Forms was used to assess the students’ perception of the online teaching methodology during the COVID-19 pandemic. Data was assessed using a five-point Likert scale, and results were expressed as numbers and percentages. Results: The present study reported that 52.46% of the study participants had a strong positive opinion about the convenience and flexibility of online learning methods, as they can be accessed from anywhere and at any time. However, 214 (36.33%) participants agreed that monitoring students during online teaching was more difficult compared to classroom teaching. During the pandemic, when all educational institutions were closed, 412 (69.95%) students felt that completing a course within a stipulated period was made possible by the online method. On the other hand, 401 (68.08%) students believed that some countries do not recognise certificates from online learning systems, as they may not provide sufficient practical experiences compared to classroom teaching. Conclusion: The current study showed that more than half of the study participants had a very favourable assessment of the portability and adaptability of online learning techniques. However, they also strongly felt that it was more challenging to keep track of students during online learning compared to traditional classroom methods. Online learning has both benefits and drawbacks, and it is important for individuals to decide how best to utilise it for their own gain while avoiding any negative side effects. Based on the experiences of the pandemic, it is crucial to find innovative solutions that are appropriate for different learning contexts.

In smart education, adaptive e-learning systems personalize the educational process by tailoring it to individual learning styles. Traditionally, identifying these styles relies on learners completing surveys and questionnaires, which can be tedious and may not reflect their true preferences. Additionally, this approach assumes that learning styles are fixed, leading to a cold-start problem when automatically identifying styles based on e-learning platform behaviors. To address these challenges, we propose a novel approach that annotates unlabeled student feedback using multi-layer topic modeling and implements the Felder–Silverman Learning Style Model (FSLSM) to identify learning styles automatically. Our method involves learners answering four FSLSM-based questions upon logging into the e-learning platform and providing personal information like age, gender, and cognitive characteristics, which are weighted using fuzzy logic. We then analyze learners’ behaviors and activities using web usage mining techniques, classifying their learning sequences into specific styles with an advanced deep learning model. Additionally, we analyze textual feedback using latent Dirichlet allocation (LDA) for sentiment analysis to enhance the learning experience further. The experimental results demonstrate that our approach outperforms existing models in accurately detecting learning styles and improves the overall quality of personalized content delivery.

Introduction: The outbreak of Coronavirus Disease-19 (COVID-19) was a global disaster that greatly impacted the education system. The Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis can be used to identify favourable and unfavourable factors and conditions in offline and e-learning systems, and to address problems in a targeted manner. Aim: To evaluate the understanding and perception of students regarding the online learning system through SWOT analysis. Materials and Methods: This cross-sectional study was conducted at a tertiary care teaching hospital in the Department of Pharmacology at a tertiary care teaching hospital in Tamil Nadu, India for a duration of one month in October 2021. The study included 589 undergraduate students from medical, dental, and allied health sciences. A preformed questionnaire using Google Forms was used to assess the students' perception of the online teaching methodology during the COVID-19 pandemic. Data was assessed using a five-point Likert scale, and results were expressed as numbers and percentages. Results: The present study reported that 52.46% of the study participants had a strong positive opinion about the convenience and flexibility of online learning methods, as they can be accessed from anywhere and at any time. However, 214 (36.33%) participants agreed that monitoring students during online teaching was more difficult compared to classroom teaching. During the pandemic, when all educational institutions were closed, 412 (69.95%) students felt that completing a course within a stipulated period was made possible by the online method. On the other hand, 401 (68.08%) students believed that some countries do not recognise certificates from online learning systems, as they may not provide sufficient practical experiences compared to classroom teaching. Conclusion: The current study showed that more than half of the study participants had a very favourable assessment of the portability and adaptability of online learning techniques. However, they also strongly felt that it was more challenging to keep track of students during online learning compared to traditional classroom methods. Online learning has both benefits and drawbacks, and it is important for individuals to decide how best to utilise it for their own gain while avoiding any negative side effects. Based on the experiences of the pandemic, it is crucial to find innovative solutions that are appropriate for different learning contexts. [ABSTRACT FROM AUTHOR]

E-learning implementation is growing alongside the e-learning market's growth. As a result, competing models and approaches were proposed to improve e-learning and learner performance; one of these models is the e-learning systems success model. In order to expand this model, an analysis of the published e-learning models and frameworks in the period 2017-2022 was conducted using the aggregative review method. 37 studies that match the current study interests have been selected and analyzed. The main results support the e-learning system success model. In addition to further constructs other than those used in the model that have been used to enhance it, an adaptive e-learning success model has been proposed, which integrates the e-learning success model with the other models and frameworks proposed in the literature. This study recommends that achieving e-learning success requires an analysis of the internal and external environment and crafting an adaptation plan to determine the e-learning methods depending on the pedagogical approaches and tutors' and learners' abilities and characteristics, which in turn determine the instructional material required and assessment methods, besides the required ICT. Besides the required enhancements, such as tutor and learner training, as well as the institution's policy and e-learning management, in addition to the required adaptations to cope with environmental factors in order to embrace learners in education policies and future strategies. [ABSTRACT FROM AUTHOR]

The purpose of the study was to investigate the application of open-distance e-learning systems in the institutions of higher learning to encounter pandemic and student population increase in South Africa. The in-class contact teaching and learning system can have very serious negative effects on students when it comes to a limitation of intake to universities and lockdowns in relation to outbreaks like Covid-19. This study applies the literature to develop a framework for using the open-distance electronic learning system (Open Distance e-learning – ODeL). The study discovered that institutions of higher learning, especially contact institutions, could face risks and disruptions that may result in the suspension of academic programmes. The study provides a framework for the possible adoption of the Open Distance e-learning (ODeL) system by institutions of higher learning. The results of this study will provide alert and guidance to institutions of higher learning about the adoption of open-distance e-learning to accommodate all interested students and ensure continuity of learning during a pandemic like COVID-19. The framework provided will assist institutions of higher learning with the how-to in terms of implementation of Open Distance e-learning in case they decide to adopt it. Learners will be able to get admitted and enjoy learning in any institution of their choice without any limitation due to space shortage and institutions may ensure continuity in teaching and learning for their educational business even during the pandemic. [ABSTRACT FROM AUTHOR]

The prevalence of e-learning systems has made educational resources more accessible, interactive and effective to learners without the geographic and temporal boundaries. However, as the number of users increases and the volume of data grows, current e-learning systems face some technical and pedagogical challenges. This paper provides a comprehensive review on the efforts of applying new information and communication technologies to improve e-learning services. We first systematically investigate current e-learning systems in terms of their classification, architecture, functions, challenges, and current trends. We then present a general architecture for big data based e-learning systems to meet the ever-growing demand for e-learning. We also describe how to use data generated in big data based e-learning systems to support more flexible and customized course delivery and personalized learning. [ABSTRACT FROM AUTHOR]

In order to effectively implement adaptive learning within E-learning systems, it is crucial to accurately define the learner's profile that reflects the characteristics necessary for optimal learning. Traditional methods of identifying profiles often rely on questionnaires to collect data from learners, which can be time-consuming and result in irrelevant data due to arbitrary responses. As a solution, we propose an intelligent and dynamic model for adaptive learning that takes into account the entire learning process, from diagnostic assessment to knowledge assimilation. Our approach utilizes the k-means classification algorithm to group learners based on similar characteristics, as defined by the KOLB model. To enhance the accuracy of our model, we also incorporate neural networks to automatically predict learning styles and using decision tree to propose a adaptative pedagogical content to learner. By doing so, we aim to improve the overall performance of our proposed model. [ABSTRACT FROM AUTHOR]

Kid-Dose is a mobile solution designed to increase knowledge in the English language and Mathematics for kids. The app is designed to be engaging and interactive, with a range of learning activities that reinforce the learning objectives. [1] The methodology for Kid-Dose involves a structured approach that includes a needs assessment, content development, user interface design, learning activities, assessment and evaluation, and continuous improvement. The app has the potential to be an effective tool for improving knowledge in the English language and Mathematics for kids, and further research can be conducted to assess its effectiveness. [ABSTRACT FROM AUTHOR]

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Over the last decades, using e-learning systems as an alternative format of education for traditional classroom has been growing in higher education and due to COVID-19 pandemic, this transition has been unprecedently accelerated. Although there is a large body of research on e-learning, little is known about the extent to which innovative and continuous use of e-learning systems can be influenced by students' social and motivational factors especially their relational identity and autotelic experience. This study collected data from 400 higher education students through a survey to explore the role of students' relational identity and autotelic experiences regarding their innovative and continuous use of e-learning systems while considering the mediating role of students' perception of relatedness. Collected data were analyzed using the structural equation modeling method. The results showed that students' relational identity and autotelic experience significantly influence the innovative and continuous use of e-learning. The results showed that relational identity and autotelic experience positivly associatewith innovative (β = 0.190, t = 3.544; β = 0.405, t = 7.973) and continuous use of e-learning (β = 0.188, t = 3.115; β = 0.344, t = 7.459) and relatedness plays a moderating role between relational identity and continuous use (β = 0.194, t = 4.500, p = 0.000). Relatedness weakens the relationship between relational identity and innovative use of e-learning. However, it reinforces the relationship between relational identity and the continuous use of e-learning. It was found that relatedness strengthens the relationship between autotelic experience with innovative and continuous use of e-learning. The results of this study provide evidence of how students' social and motivational factors can influence their approaches to the innovative and continuous use of e-learning systems. We discuss these results and provide agenda for future practical and professional work. [ABSTRACT FROM AUTHOR]

Cloud computing has lately been deployed in educational institutions for a range of services and applications by way of virtualization of computing resources such as processors, memory, storage and networking. This paper discusses the use of cloud computing in tutorial group discussions as a teaching pedagogy and its influence in learning. It explores the essentials in tutorial group discussions in class including the preparations, activities, processes, benefits and opportunities. The research utilized a mixed method approach including qualitative and quantitative for data collection, then both action research and agile software development to develop and test the cloud computing based tutorial management system (Tutmas). Results indicated that both students and lecturers appreciated the benefits and usefulness of regular tutorials. Further, both students and lecturers appreciated the role of the cloud based Tutmas platform in improving efficiency in the management of tutorials and enhancement of students’ learning experiences and academic skills.

Based on constructivism theory and the Information System Success Model, this study suggests a research model that examines the factors that influence students' collaborative engagement and satisfaction in an e-learning system setting. This study intends to validate the theoretical concepts and the Information System Success Model (ISSM) on e-learning platforms for user satisfaction and collaborative activity in order to expand the adoption of e-learning systems in higher education. This research used a questionnaire as the primary data collection method to obtain information for the study from 300 responses from different students at the University of Bisha, who all use e-learning platforms. The results were achieved using structural equation modeling, a quantitative research technique (SEM-AMOS). All of the study's hypotheses were supported, according to the findings of the structural model and hypothesis testing. The outcomes of peer interaction (IP) and instructor interaction (IL) have a favorable impact on satisfaction and teamwork, which have a beneficial impact on the usage of e-learning in higher education. This is advantageous for sustainability as well as the adoption of e-learning systems. Finally, the study demonstrates that user happiness and collaborative involvement have a favorable impact on the utilization of e-learning systems. As a result, universities should promote e-learning as a long-term educational strategy.

The purpose of this study is to conduct empirical testing of the influence of the use of the Moodle E-learning System in the Muhammadiyah Samarinda Junior High School environment in supporting the process of ICT-based activities in the teaching and learning process in order to develop ICT-based learning that is considered innovative under the standards of the 2013 Education Curriculum. This study's subjects were Muhammadiyah Junior High School students in Samarinda. The UTAUT model is used to determine the factors influencing E-Learning Behavior's purpose. The data collection survey was conducted by distributing questionnaires directly to 56 students, using Multiple Linear Regression Analysis by conducting a statistical T-test. The results of this study show the influence of expected variables in the performance of E-Learning (PE) technology, expectations on the business of using E-Learning (EE) technology, the influence of teachers and students (SI), the condition of school facilities (FC) and the suitability of learning (JF) with the behavioral intention of Muhammadiyah Junior High School students to use E-Learning learning technology by 83.4%. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors affecting the acceptance of e-learning among university students, especially during the COVID-19 pandemic, and to reveal the factors affecting the reasons for students to use e-learning systems. We adopted the Technology Acceptance Model (TAM) to understand better the adoption of e-learning systems by university students. We gathered data from 716 university students who received distance education during the pandemic and used SPSS 22.0, AMOS 22.0 and SmartPLS 3.3 software to perform statistical analyses. The findings indicate that compatibility is related to perceived ease of use and perceived usefulness. Moreover, attitude is influenced by perceived ease of use and perceived usefulness. The results reveal the importance of perceived ease of use, perceived usefulness, self-learning necessity, and compatibility on intention to use. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has rekindled interest in online learning as a desirable substitute. In Saudi Arabia's educational system, technology and online learning are becoming more and more significant. In order to prepare students for the digital age and Saudi Vision 2030, there is an increasing desire for educational institutions to use e-learning. Students and faculty at Saudi institutions now have more opportunities to better grasp the globalized digital age thanks to the integration and acceptance of digital technology into learning and teaching. Therefore, this study aims to analyze and investigate the educational quality, social influence, and TAM Model factors that increase the students' attitude toward using e-learning; thus, it affects students' satisfaction and academic performance. The study was conducted at two universities in Saudi Arabia. Structural equation modeling (SEM) and route analysis were used to evaluate the research model and analyze data from e-learning users through a questionnaire. The findings revealed that perceived ease of use (PEU) and perceived usefulness (PU) mediate the effects of educational quality (EDQ), social influence (SOI), and perceived enjoyment (PE), which in turn affect students' attitude toward use (ATU), and students' satisfaction with using e-learning systems (SSE). Additionally, the results demonstrated that the mediator factors had favorable "R square (R2)" values for adopting e-learning systems in higher education, with PEU = 0.562, PU = 0.712, ATU = 0.608, and SSE = 0.636. The hypotheses' findings led to the development of a validated instrument to measure students' online learning in Saudi Arabia's higher education. [ABSTRACT FROM AUTHOR]

Summary: A novel model of data similarity estimation and clustering method is proposed in this article to retrieve the relevant data with the best matching in big data processing. An advanced model of graph distance pattern (GDP) method with lexical subgroup (LS) system is used to estimate the similarity between the query data and the entire database. With the help of neural network, the relevancy of feature attributes in the database are predicted and matching index is sorted to provide the recommended data for given query data. This was achieved by using the correlated sim‐neural network (CSNN). This is an enhanced model of neural network technology to find the relevancy based on the correlation factor of feature set. The training process of CSNN classifier is carried by estimating the correlation factor of the attributes of dataset. These are forms as the clusters and paged with proper indexing based on the LS parameter of similarity metric. The results obtained by the proposed system for recall, precision, accuracy, error rate, F‐measure, kappa coefficient, specificity, and MCC are 0.98, 0.98, 0.97, 0.03, 0.99, 0.991, 0.986, and 0.984, respectively. [ABSTRACT FROM AUTHOR]

The successful application of the e-learning system is of great significance to the implementation, management and continuous improvement of blended learning in higher education. Hence, we focused on identifying key factors affecting college students' adoption of the e-learning system in mandatory blended learning environments. In this study, the Unified Technology Acceptance and System Success (UTASS) model was proposed, a method integrating self-reported and system log data was implemented, while the moderator variables of gender and major were considered. Self-reported questionnaires were distributed in the e-learning system-starC and a total of 287 valid questionnaires were collected, meanwhile system log was collected to record students' actual behavior online. Structural equation modeling analysis revealed that system quality (SQ), social influence (SI) and facilitating conditions (FC) have significant positive effects on behavioral intention (BI) whereas information quality (IQ) has none on BI. There is no significant positive relationship among FC, BI and use behavior (UB), and only moderator effect of gender exists. The results suggested that male college students are more susceptible to the impact of system quality and social influence. [ABSTRACT FROM AUTHOR]

Adopting technology in this new normal education improved students' engagement and motivation to learn. This paper aimed to investigate the impact of technical support on Technology Acceptance Model to examine Project PAIR (Portable and Accessible Instructional Resources) in the distance learning modality employing Partial Least Squares-Structural Equation Modeling. Applying a convenience sampling technique, the investigation involved 305 senior high school learners from a secondary school in Cagayan, Philippines. Sample sizes were calculated using the inverse square root and gamma-exponential methods. Results showed that technical support directly impacts the perceived ease of use, usefulness, and attitude toward using. The findings also revealed that the perceived ease of use of PAIR has a direct impact on its perceived usefulness and attitude toward use. In contrast, perceived usefulness directly influences the attitude toward using and behavioral intention to use. Likewise, attitude towards using directly impacts the behavioral intention and actual use, while behavioral intention directly influences actual use. This paper concluded that technical support is a reliable external variable of the technology acceptance model. Hence, the application of PAIR for remote learning is strongly recommended for the school and the public. It is also recommended that the schools must ensure that they have provided technical support to ensure the PAIR functioning runs appropriately. Further implications for institutions and future studies are also discussed in this paper. [ABSTRACT FROM AUTHOR]

Abstract E-learning was mandated for all the higher education institutions (HEI) in the United Arab Emirates (UAE) to encounter the pandemic and practice social distancing in year 2020. This led education institutions to shift from face-to-face traditional classroom settings to online education channels for delivering education to their students despite being less familiar with the real-time remote learning. The current study attempts to measure the success of e-learning systems adopted by the HEIs in UAE. An e-learning system success measuring the framework based on DeLone and McLean (J Manage Inf Syst 19(4):9–30, 2003) was developed including the measures of quality, system use, perceptual benefits and future outcomes from students’ perspective. A survey was conducted from more than 1200 students studying at different higher education institutions of the UAE region. The findings have implications for educators and policy-makers recommending the success factors of e-learning delivery channels in this region.

The Covid-19 pandemic in Indonesia has an impact on changes in policies and the learning process at Budi Luhur University (UBL). The complete online learning policy has been implemented since the 2nd semester of 2019/2020, which began in March 2020. Students and lecturers carry out teaching and learning activities through an e-learning system developed in 2005. Although it has been implemented for a long time, the level of acceptance has never been measured comprehensively. This research has a contribution in measuring the level of acceptance of the e-learning. In addition, before the Covid-19 pandemic, the use of the e-learning system was still partially implemented and only for a few courses. In this study, an analysis of the student acceptance of the UBL e-learning system was carried out by involving respondents and a more comprehensive acceptance model. The modeling used in this study refers to the Comprehensive Technology Acceptance Model (CTAM) with seven exogenous variables and five endogenous variables. Testing and analysis are based on variant-based structural equation models, namely Partial Least Square (PLS) using the SmartPLS application. The results show that nine main factors influence student acceptance of the e-learning system: system quality, content quality, information quality, accessibility, enjoyment, perceived ease of use, perceived usefulness, and student attitudes towards applications and behavioral intention to use. This research is helpful for UBL and other educational institutions as material for developing a quality e-learning system accepted by its users.

The COVID-19 pandemic has rekindled interest in online learning as a desirable substitute. In Saudi Arabia’s educational system, technology and online learning are becoming more and more significant. In order to prepare students for the digital age and Saudi Vision 2030, there is an increasing desire for educational institutions to use e-learning. Students and faculty at Saudi institutions now have more opportunities to better grasp the globalized digital age thanks to the integration and acceptance of digital technology into learning and teaching. Therefore, this study aims to analyze and investigate the educational quality, social influence, and TAM Model factors that increase the students’ attitude toward using e-learning; thus, it affects students’ satisfaction and academic performance. The study was conducted at two universities in Saudi Arabia. Structural equation modeling (SEM) and route analysis were used to evaluate the research model and analyze data from e-learning users through a questionnaire. The findings revealed that perceived ease of use (PEU) and perceived usefulness (PU) mediate the effects of educational quality (EDQ), social influence (SOI), and perceived enjoyment (PE), which in turn affect students’ attitude toward use (ATU), and students’ satisfaction with using e-learning systems (SSE). Additionally, the results demonstrated that the mediator factors had favorable “R square (R2)” values for adopting e-learning systems in higher education, with PEU = 0.562, PU = 0.712, ATU = 0.608, and SSE = 0.636. The hypotheses’ findings led to the development of a validated instrument to measure students’ online learning in Saudi Arabia’s higher education.

Background and Objectives: E-learning as a direct consequence of the integration of technology and training has emerged as a powerful learning media, especially using the Internet technologies. Electronic learning is the use of remote communication technology to provide information for training and learning, which has become a new paradigm for modern education with the development of information and communication technology. The quality of e-learning is dependent on the size or the extent to which technology, interactions, content and services allows the learner and the teacher to work in accordance with their expectations in the learning environment and get satisfaction. Increasing the capabilities of e-learning and the possibility of realizing educational goals in this way depend on considering its various dimensions and aspects and paying attention to the factors influencing the e-learning system. By using the electronic content, a wider spectrum of the students' senses is involved in the teaching-learning process and learning process is deeper and the motivation of the students is higher. The purpose of this study was to investigate the relationship between the quality of school education services and the success of the e-learning systems with the perceived mediating role of satisfaction among the primary school male students in the first region. Methods: The research method of this study is applied in terms of purpose and in terms of the method and nature of the research is a descriptive study of correlation type. The statistical population of the study consisted of approximately 9,000 male students of the fifth and sixth grade of primary school in the first region of Mashhad among whom 369 students were selected as statistical sample size, using Cochran sampling formula. The random sampling method is available. The most important research tool was a questionnaire. The research questionnaire was derived from the research of Al-Ferries and colleagues. The formal and content validity of the questionnaire was examined and its compatibility was confirmed in the research of Al-Ferries and their colleagues. In the research of Al-Ferries and colleagues, the reliability of the questionnaire was obtained, using Cronbach's alpha coefficient of 85%. AMOS and SPSS software were used to analyze descriptive and inferential data. Findings: According to the findings of the research, it can be said that the perceived satisfaction has an indirect and mediating effect on the dimensions of the quality of educational services and the perceived usefulness of the electronic learning system of the students. Moreover, the indirect effect of the perceived satisfaction in the relationship between the quality of the educational services and the application of the students' electronic learning system was approved. Conclusion: The results of the study show that if the quality of school training has a desirable quality from different dimensions and the students can adapt themselves to the e-learning system, they will have a feeling of more perceived usefulness and effectiveness . The more satisfied are the students in various training services that they receive (that is, high-quality technical system, teacher quality being up-to-date and knowledgeable, the quality of comprehensive and accurate information and educational system support), the more they are most likely to use the e-learning system as the user. user more. [ABSTRACT FROM AUTHOR]

The objective of the current study is to examine the role of the event log and elearning system in analysis of learning behavior of learners in Phatthalung Thailand. Data is collected from Phatthalung Thailand by using a survey questionnaire. Respondents of the study are based on the e-learners in Phatthalung Thailand. Area cluster sampling is used in this study for data collection. Finally, the current study used 265 valid responses for data analysis. Data analysis is carried out by using Partial Least Square (PLS) in which measurement model and structural model is used to examine the relationship. Findings of the study show that; the event log has an influential role to promote the e-learning system which further causes to increase learning behavior of e-learners. E-learning systems transfer the positive effect of event log on learning behavior. Thus, the current study has theoretical and practical implications to promote learning behavior through event log and elearning system in Thailand. [ABSTRACT FROM AUTHOR]

One of the most significant changes the information and communication ecology is the internet. It not only allows for real-time contact and engagement across time zones, but it also allows for successful social growth and crisis management, including the promotion of distance learning, particularly during the COVID-19 epidemic and its associated lockdown on educational systems. This disruption of education poses a threat to learning in Nigeria, and the consequences of continuing to close schools and academic programmes might have detrimental consequences for students, parents, and the country. Students can be encouraged to explore their own interests and become active learners during the lockdown by using internet-enabled ICT as a resource. However, this was noticeably absent in Nigeria 's educational system. This paper aims to provide a simple, cost-effective, and alternative pedagogical system for use during and after the epidemic, particularly for open schools and institutions. This study offers an e-learning system based on the use of a computer and Android smartphone apps to help mitigate the detrimental effects of the continued lockdown on the Nigerian pedagogical system, or what this paper refers to as the 'edulockdemic.' The proposed system was developed as a framework based on a comprehensive examination of existing literature, and it is projected to allow institutional managers to monitor school and academic teaching and learning activities in a virtual learning area known as a "CT-learning area." In the conclusion, policy recommendations are made. [ABSTRACT FROM AUTHOR]

Cloud computing has lately been deployed in educational institutions for a range of services and applications by way of virtualization of computing resources such as processors, memory, storage and networking. This paper discusses the use of cloud computing in tutorial group discussions as a teaching pedagogy and its influence in learning. It explores the essentials in tutorial group discussions in class including the preparations, activities, processes, benefits and opportunities. The research utilized a mixed method approach including qualitative and quantitative for data collection, then both action research and agile software development to develop and test the cloud computing based tutorial management system (Tutmas). Results indicated that both students and lecturers appreciated the benefits and usefulness of regular tutorials. Further, both students and lecturers appreciated the role of the cloud based Tutmas platform in improving efficiency in the management of tutorials and enhancement of students' learning experiences and academic skills. [ABSTRACT FROM AUTHOR]

Previous research on e-learning in underdeveloped countries has seldom taken a comprehensive approach. A literature review of recent published research in the field of e-learning use during the COVID-19 epidemic is also included in this study. Therefore, the aim of this study is to look at the technology acceptance model (TAM) and information systems (IS) performance models to see how system quality (SYQ), service quality (SEQ), and quality of life (QoL) are related, as well as the mediating impact of perceived ease of use (PEU) and perceived usefulness (PU), affect students' behavioral intention to use (BIU), and actual use of an e-learning system (AUE) as sustainability for education during the COVID-19 pandemic. Path analysis and structural equation modeling (SEM) were used to evaluate the research model, using the data from e-learning users obtained through a survey. Participants were e-learning users from two Saudi Arabian public universities. The findings revealed that PU and ease of use were positively correlated and influenced by SYQ, SEQ, and QoL in education, and that PEU and PU were positively influenced by students' BIU and AUE system. In the sense of e-learning in developing countries, previous studies rarely looked at an integrated model. This paper also attempts to provide a recently published study in the area of the use of an e-learning system as sustainability for education during the COVID-19 pandemic. There is a lot of ongoing research.

Background and Objectives: E-learning is the necessity of the information society and the main condition for achieving the goal of the Fourth National Development Plan (Knowledge-Based Development) which has paid special attention to the university activities while benefitting from the electronic learning in higher education in order to provide equal education opportunities and increasing the coverage of the student population. Along with the development of e-learning at the level of universities and institutions of higher education, the issue of evaluating the e-learning system and justifying the implementation of programs and the need to meet the proper requirements and standards for designing, developing and implementing e-learning in higher education is important. Given that the structure of e- learning is complex and consists of various components, it is necessary to examine all these components to evaluate the e-learning system. Therefore, it is necessary to conduct a comprehensive study to identify and introduce the main and practical indicators of evaluating the e-learning system so that they can be used for designing and developing appropriate frameworks and tools for evaluation of this system. Evaluation of the e-learning system provides the relevant staff and managers in higher education with the opportunity to identify the strengths and weaknesses of this system and enhance the strengths or eliminate possible deficiencies and shortcomings. Methods: This research was an inquiry into the lived experiences of the faculty members of the University of Tehran in 2019 of evaluating the e-learning system. In this study, an attempt was made to identify the components of e-learning system evaluation in the University of Tehran by using qualitative methodology. The data of this research have been extracted through a qualitative approach with a descriptive phenomenological method and with semi-structured interview tools and the data have been analyzed through coding and categorization methods. Sampling in this study has been purposeful and standard and a total of 17 experts in the field of e-learning from Tehran University have participated in thestudy. The validity of qualitative data using four judgment criteria of Lincoln and Goba)1985( including validity or reliability, transferability verifiability or neutrality, and reliability or compatibility and reliability of qualitative data through recoding by the second encoder and the encoder himself has been confirmed. Findings: Based on the research findings, the factors related to the evaluation of e-learning system are classified into three dimensions of pedagogy, organization and technology which, on the whole has 17 components and 95 concepts. These components have been identified in the form of teacher, student, teaching assistant, teaching-learning process, content, evaluation, support services, interaction, education and empowerment system, motivation system, university goals and strategies, knowledge management system, culture, physical resources, software, hardware and infrastructure. Conclusion: In general, the results of this study indicate important points that can provide valuable information for administrators and authorities the University of Tehran in the field of e-learning system to adopt principled policies regarding the evaluation of this system to improve and enhance the quality and effectiveness of e-learning. It is recommended that the university uses the model presented in the present study in order to evaluate the e-learning system of the University of Tehran. ===================================================================================== COPYRIGHTS ©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. =====================================================================================