Cloud-based E-learning System Research Articles

Achieving Excellence in Cloud-Based E-Learning Systems: Exploring Quality Factors and Benefits

Purpose: This study examines the effectiveness and advantages of cloud-based e-learning platforms in Kuwait, integrating concepts from Information System Success Model (ISSM) and Technology Acceptance Model (TAM). It investigates the impact of system quality (SQ), service quality (SRQ), and information quality (IQ) in cloud computing (CC) on user satisfaction (SAT), perceived ease of use (PEOU), and perceived usefulness (PU). Furthermore, it examines how PEOU and usefulness affect SAT and the role of SAT in mediating benefits. Study design/methodology/approach: Survey data were used to analyze relationships in 15 hypotheses using SmartPLS structural equation modelling. Sample and data: The empirical data were gathered from a sample of 221 college students. Results: The analysis revealed that several hypotheses were rejected, including SRQ on SAT, PU, and PEOU, which were found to be insignificant. Similarly, IQ did not exhibit a significant effect on SAT and PU, yet it did have an impact on PEOU. Consequently, it was found that the SAT only mediates the relationship between SQ and benefits. The study further explores potential explanations for these insignificant findings. Originality/value: Despite limited research on cloud computing learning platforms, this study sheds light on the intricate dynamics among these variables and the overall benefits of such platforms in Kuwait.Research limitations/implications: The unexpected insignificant relationships, such as SRQ, suggest practical implications, including the need to re-evaluate the providers’ approaches to customer service. Using services that are more tailored to specific contexts may be beneficial. The timing and context of the study could limit its generalizability.

Cloud-Based E-Learning Systems Implementation for Technical and Vocational Colleges in Kenya: A Case Study of Vihiga County

Cloud-Based E-Learning Systems Implementation for Technical and Vocational Colleges in Kenya: A Case Study of Vihiga County

Intention to adopt Cloud-based e-Learning in Nigerian Educational Institutions

Institutions of higher education must utilize innovative information and communication technologies for teaching in Nigeria. Thus, cloud-based e-Learning is essential to curtail educational challenges such as limited infrastructure, funds, and student-to-lecturer ratio. Recently, there has been widespread enthusiasm regarding Cloud computing for e-Learning; adopting and strategically utilizing these technologies remains a significant challenge for higher education institutions. Furthermore, there is a limited understanding of how cloud-based e-learning can transform Nigerian educational establishments. Cloud-based e-Learning systems' technological components have been the subject of numerous study studies, but little is known about how they operate from an organizational perspective. Accordingly, using the Technology-Organization-Environment theory, the goal of this study is to investigate the variables that influence the adoption of cloud-based e-learning. The findings of the research show that relative benefit and competing pressure have a big impact on whether cloud-based e-learning is adopted. However, compatibility, security, and top management commitment do not appear to be significant determinants. These findings will help Nigerian education institutions, the ministry of education, and practitioners to understand the critical factors for adopting this technology for improved education.

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.

Interpreting Usability Factors Predicting Sustainable Adoption of Cloud-Based E-Learning Environment during COVID-19 Pandemic

The COVID-19 pandemic affected educational institutions in an unrivaled way around the globe and forced them to switch from conventional classroom learning mode to e-learning mode within a short time period. Neither instructors nor students had ample time to prepare. The purpose of the current study is to accomplish two objectives: to explore the functional relationship between attitudinal readiness (ATR), subjective well-being (SWB), and cloud-based e-learning adoption intention in Taiwan and examine the constancy of recommended proposed relationships among different students’ groups. The model was then empirically tested using data of 256 university students by structural equation modeling. The current study demonstrates that ATR is completely explained through four dimensions: peer reference, perceived ease of use, perceived usefulness, and perceived ubiquity. SWB is positively interpreted through four dimensions: online course quality, system quality, perceived service quality, and perceived closeness. Self-efficacy has a significant relationship with both attitudinal readiness and adoption intention of a cloud-based e-learning system. Finally, the invariance test explores substantial variance among students who intend to use the system and students who reject it. Therefore, researchers and practitioners regarding educational, technological innovation must consider this empirical evidence to develop and validate a sustainable cloud-based e-learning program in higher education.

Assessing the impact of cultural characteristics, economic situations, skills and knowledge on the development and success of cloud-based e-learning systems in the COVID-19 era

PurposeOne of the most significant threats of COVID-19 in the world is the closure of universities, schools, training courses and even companies and organizations. In such a situation and with the free time that has arisen, this threat of education closure can become a golden opportunity for learning and progress in virtual education. E-learning uses information technology (IT) to distribute knowledge and information for training and education. Also, cloud computing is a technology utilized in the IT domain. It can be employed in performing e-learning. Therefore, the main goal of this study is to assess the impact of cultural characteristics, economic situations, skills and knowledge on the development and success of CELS in the COVID-19 era.Design/methodology/approachCloud-based e-learning system (CELS) provides all e-learning requirements like software and hardware resources to promote conventional e-learning technologies. The CELS stands on several factors of diverse aspects that have been of high significance in CELS success. So, these systems must be checked to analyze their significance rate and successfully carry out their effectiveness. On the other hand, these days, the 2019 coronavirus disease (COVID-19) changes our daily lifestyles. Therefore, the present investigation provides a new model investigating the development and success of CELS in the COVID-19 era. Also, an online questionnaire was used to gather the data. The content validity of the questionnaire was obtained by applying the opinions of ten experts from e-learning specialists. The collected data are analyzed using LISREL and Smart PLS software.FindingsThe results from the path coefficient and the sample t-test have implied that skills and knowledge positively influence CELS in the COVID-19 era. In addition, the relationship between cultural characteristics and CELS in the COVID-19 era has been positive and significant. The relationship between the economic situations and the CELS in the COVID-19 era is positive and significant.Practical implicationsThe proposed model helps managers get a big picture of CELS necessities and more effectively in the COVID-19 era. This research has a unique impact on universities to develop an e-learning platform to facilitate the education process in the COVID-19 era. It provides guidelines for educational institutions to effectively implement the learning management system to facilitate students' education.Originality/valueCELS are getting increasingly essential to offer training courses more efficiently in educational institutions. Although the intersection between cloud computing and e-learning has increasingly grown in both practical and academic contexts, few studies on the impact of cultural characteristics, economic situations, skills and knowledge on the development and success of CELS in the COVID-19 era. This paper explores the ignored but critically important subject of CELS. This paper's main contribution is to present a new and integrated model containing the essential aspects of the development and success of CELS in the COVID-19 era. The proposed framework comprises cultural characteristics, economic situations, skills and knowledge aspects simultaneously, as well as sub-criteria denoting each element.

Students' satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors

PurposeThe purpose of this study is to propose a research model based on expectation-confirmation model (ECM) to examine whether interactivity and course quality factors (i.e. course content quality, course design quality) as antecedents to student beliefs can influence students' satisfaction and continuance intention of the cloud-based electronic learning (e-learning) system within the educational institution.Design/methodology/approachSample data were collected from students enrolled in a comprehensive university in Taiwan. A total of 600 questionnaires were distributed in the campus, and 515 (85.8%) useable questionnaires were analyzed using structural equation modeling.FindingsFindings showed that students' perceptions of interactivity, course content quality and course design quality positively significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, which in turn directly or indirectly led to their continuance intention of the system. Thus, the results strongly supported the research model based on ECM via positioning key constructs as the drivers with all hypothesized links being significant.Originality/valueThis study identifies three factors (i.e. interactivity, course content quality, course design quality) as drivers from the learner perspective within the cloud-based e-learning environment, and links these factors to students' satisfaction and continuance intention of the cloud-based e-learning system based on ECM. It is particularly worth mentioning that the three drivers can serve as precursors for recognizing the determinants that are crucial to understand students' satisfaction and continuance intention of the cloud-based e-learning system. Hence, this study may provide new insights in nourishing the cloud-based e-learning continuance literature in the future.

Investigating medical professionals' continuance intention of the cloud-based e-learning system: an extension of expectation–confirmation model with flow theory

PurposeThe purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.Design/methodology/approachSample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsSynthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.Originality/valueParticularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, 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.

An agent-based framework for providing security in a cloud-based E-learning system

An agent-based framework for providing security in a cloud-based E-learning system

Cloud Computing Based E-Learning in Malaysian Universities

Cloud computing is considered as a new innovation which essentially influences teaching and learning forms in educational sector. Utilizing this innovation not as it were upgrades the quality of teaching and learning, but too diminishes overhead consumption of instructive educate. In spite of the beneficial points of interest of cloud computing, in any case, its adoption is still distant from full potential, especially in university settings. However, there are not many studies on the adoption of cloud-based E-learning systems. Thus, this research is aimed to develop a theoretical research model for the adoption of cloud computing in universities of Malaysia. For this purpose, TAM model is used to represent the research framework. A survey was conducted among 265 cloud-based E-learning participants and analyzed by structural equation modeling (SEM). The findings indicate that the adoption of cloud-based E-learning is influenced by need, perceived usefulness, although inattentiveness is not significant to use intention to adopt cloud based e-learning.

ARTIFICIAL INTELLIGENCE INFLUENCE IN EDUCATION 4.0 TO ARCHITECTURE CLOUD BASED E-LEARNING SYSTEM

Business Application Layer in the Architecture of E-learning cloud is an important part, because it is the part that differentiates it from the application of cloud in other fields. The development of education today recognizes the term Education 4.0 which is an adaptation of the Industrial era 4.0 where in this era the role of Artificial Intelligent is important. In this paper the author will review a part of the cloud-based architecture of E-Learning which will correspond with Education 4.0. The aim will be to produce a Cloud-Based E-learning system Architecture design that can be used as a guideline in the direction of Education 4.0.

A comprehensive framework to rank cloud-based e-learning providers using best-worst method (BWM)

Purpose Today, the high cost of e-learning systems’ implementation and the difficulty of managing the infrastructures motivate educational institutions toward application of cloud-based e-learning systems. This new system should be aligned with the academics’ aims and pedagogical principles to be beneficial for learners and instructors. Therefore, the vendor selection of learning systems is one of the most important processes to migrate toward cloud-based e-learning. The purpose of this paper is to develop a new framework to facilitate the vendor selection of cloud-based e-learning systems in the cloud market. Design/methodology/approach To identify the initial criteria as to the vendor selection of cloud-based e-learning services, a literature review is done. To enrich the initial criteria, a focus group of experts is investigated, and the framework developed; then, a survey analysis is conducted to validate the proposed framework. The extracted criteria and sub-criteria are weighted and prioritized using best-worst method (BWM). Findings The results indicate that the main dimensions of vendor selection framework as regards cloud-based e-learning systems are managerial, technological and pedagogical factors. The rank orders and weights of the mentioned aspects and their sub-criteria are calculated using the BWM. Practical implications The proposed framework helps managers to get a big picture of requirements as to cloud-based e-learning and more effectively to select appropriate vendors in this initiative. In the vendor selection process, managers must pay attention to technological issues as well as managerial and pedagogical considerations. Originality/value Cloud-based e-learning systems are getting increasingly essential to offer training courses more efficiently in educational institutions. Although the intersection between cloud computing and e-learning has increasingly grown in both practical and academic contexts, there are little studies on how educational institutions and organizations could be able to select appropriate cloud-based e-learning systems. This paper explores the ignored but critically important subject of cloud-based e-learning. The main contribution of this paper is to propose a novel and integrated framework containing the important aspects of vendor selection in cloud-based e-learning services. The proposed framework comprises managerial, technological and pedagogical aspects simultaneously as well as sub-criteria denoting each aspect.

How does task-technology fit influence cloud-based e-learning continuance and impact?

PurposeAccording to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution.Design/methodology/approachSample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study.FindingsThis study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant.Originality/valueThis study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

Harnessing Cloud Computing Services for E-Learning Systems in Higher Education

The use of e-learning suggests the use of ICT to enhance the quality of learning and teaching. However, many higher education institutions, does not have e-learning platforms, resources and infrastructure necessary to implement this type of training. This is due to the need for high cost of basic infrastructure and applications challenges related projects it has to face. This article puts forward an overview on what is the current state of the use of cloud computing in e-learning in higher education context, where the use of computers is increasingly intensive. The article analyzes e-learning systems challenges and trends, the convenience of cloud computing for e-learning and the key benefits of e-learning on the cloud. The article exposes also some application solutions using cloud computing in e-learning for higher education, by presenting the most common architecture that has been adopted. Finally, this article discusses issues related to the implementation of cloud-based e-learning systems and presents some potential ways to overcome them.

Cloud Computing-Based E-Learning System Architecture in Education 4.0

E-learning architecture based on Cloud Computing is an implementation of the E-learning System by utilizing the benefits of Cloud Computing. Furthermore, the E-learning system will experience a change with the emergence of the Education 4.0 era which is an adaptation of the development of Industry 4.0. Therefore the writer try to review the architecture of the e-learning system based on cloud computing in relation to Education 4.0 era. In this paper, the authors propose a concept of cloud computing-based e-learning system architecture at Education 4.0. The aim is to produce architecture that can be used as a guideline in developing cloud computing-based e-learning systems that answer the needs of Education 4.0. For this reason, in this paper, the author reviews the papers that review the architecture of cloud-based e-learning systems and also papers on Education 4.0.

Using cloud computing services in e-learning process: Benefits and challenges

During the recent years, Information and Communication Technologies (ICT) play a significant role in the field of education and e-learning has become a very popular trend of the education technology. However, with the huge growth of the number of users, data and educational resources generated, e-learning systems have become more and more expansive in terms of hardware and software resources, and many educational institutions cannot afford such ICT investments. Due to its tremendous advantages, cloud computing technology rises swiftly as a natural platform to provide support to e-learning systems. This paper focuses on the research on the application of cloud computing in e-learning. The aim of this paper is to give an overview of the current state and the impact of the use of cloud computing for e-learning. Thus, at first the paper introduces concepts of e-learning and cloud computing infrastructure with their key characteristics. The paper analyzes also challenges facing e-learning systems deployment. In follow the paper considers cloud-based e-learning solutions by focusing on the raisons of the convenience of cloud computing for e-learning. Therefore cloud computing benefits are introduced as a solution for these challenges. Finally, the paper presents some solutions of cloud computing in e-learning and describes the most common architecture adopted. Issues in implementing cloud-based e-learning systems and some potential ways to overcome them are also discussed.