Cloud Computing Adoption Factors Affecting Academic Performance in UAE Public Universities

Cloud computing helps in reducing costs and providing accessibility, reliability, and flexibility especially in educational sector. This able to provide the best educational resources and facilities to all level of students effectively and efficiently. It also seen as a creative technological innovation that provides stable and on-demand access to the available network. Hence, this study aimed to measure the cloud computing adoption factors affecting the academic performance in UAE university. The factors are clustered into five groups namely, knowledge sharing; knowledge application; learnability; perceived self-efficacy; and perceived enjoyment. A questionnaire survey was conducted with the university students to gauge their opinions on the level of significant of each factor affecting the academic performance using 5-points Likert scale. Out of 400 questionnaire sets distributed using random sampling, 382 valid responses were extracted as the collected data. This data was analysed descriptively. The results of the analysis found that that cloud computing adoption factors in perceived self-efficacy group are ranked first in term of its significance in affecting academic performance. The second rank is factors in learnability group; the third is perceived enjoyment; the fourth rank is knowledge application and finally, the fifth rank is knowledge sharing. The impact of this research will be felt simultaneously in the IT and education sectors, particularly through assisting students in utilising cloud computing to store and exchange information for both their academic and personal lives

Issues and challenges: cloud computing e-Government in developing countries

Cloud computing has become essential for IT resources that can be delivered as a service over the Internet. Many e-government services that are used worldwide provide communities with relatively complex applications and services. Governments are still facing many challenges in their implementation of e-government services in general, including Saudi Arabia, such as poor IT infrastructure, lack of finance, and insufficient data security. This research paper investigates the challenges of e-government cloud service models in developing countries. This paper finds that governments in developing countries are influenced by how the top management deals with the attention to the adoption of cloud computing. Further, organisational readiness levels of technologies, such as IT infrastructure, internet availability and social trust of the adoption of new technology as cloud computing, still present limitations for e-government cloud services adoption. Based on the findings of the critical review, this paper identifies the issues and challenges affecting the adoption of cloud computing in e- government such as IT infrastructure, internet availability, and trust adopted new technologies thereby highlighting benefits of cloud computing-based e-government services. Furthermore, we propose recommendations for developing IT systems focused on trust when adopting cloud computing in e-government services (CCEGov)

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Acceptance model of SaaS cloud computing at northern Malaysian main campus public universities

Technology advancement has side effects, although it has moved in a fast pace that facilitated life and increased business revenue. To cope with negative aspects while looking for friendly technology, Software as a Service (SaaS) Cloud Computing emerged to preserve natural resources, effectively utilize computing and power consumption, while achieving performance, decreasing cost, and increasing revenue. Yet, there are paucity in empirical studies investigating salient factors affecting the usage, acceptance, or adoption of SaaS services from the individual perspectives specifically in higher education sector. The main objective of this study is to investigate the salient factors with proper model that includes technical, social and control characteristics, as well as user security predisposition. Besides, educational level has also proven to be influential in adopting innovations. Hence, probing its role is another objective. The last objective is to investigate differences between student and lecturer groups in the relationships postulated in the model. A survey with questionnaires was conducted on students and lecturers in four public universities in Northern Malaysia. The scope of the acceptance is to investigate the personal-level use of SaaS services. Decomposed Theory of Planned Behaviour (DTPB) and Diffusion of Innovation Theory (DOI) were applied. Results revealed appropriateness of the model although the role of Trialability and Subjective Norms were not significance. The findings contribute to the body of knowledge and literature in highlighting the role of these factors that SaaS providers could benefit in planning for new services and in promoting SaaS usage to universities

Uncovering the Critical Drivers of Blockchain sustainability in higher education using a deep learning-based hybrid SEM-ANN approach

The increasing popularity of Blockchain technology has led to its adoption in various sectors, including higher education. However, the sustainability of Blockchain in higher education is yet to be fully understood. Therefore, this research examines the determinants affecting Blockchain sustainability by developing a theoretical model that integrates the protection motivation theory (PMT) and expectation confirmation model (ECM). Based on 374 valid responses collected from university students, the proposed model is evaluated through a deep learning-based hybrid structural equation modeling (SEM) and artificial neural network (ANN) approach. The PLS-SEM results confirmed most of the hypotheses in the proposed model. The sensitivity analysis outcomes discovered that users’ satisfaction is the most important factor affecting Blockchain sustainability, with 100% normalized importance, followed by perceived usefulness (58.8%), perceived severity (12.1%), and response costs (9.2%). The findings o

Energy-Aware Mobile Learning:Opportunities and Challenges

As mobile devices are becoming more powerful and affordable they are increasingly used for mobile learning activities. By enabling learners' access to educational content anywhere and anytime, mobile learning has both the potential to provide online learners with new opportunities, and to reach less privileged categories of learners that lack access to traditional e-learning services. Among the many challenges with mobile learning, the battery-powered nature of mobile devices and in particular their limited battery life, stands out as one issue that can significantly limit learners' access to educational content while on the move. Adaptation and personalisation solutions have widely been considered for overcoming the differences between learners and between the characteristics of their mobile devices. However, while various energy saving solutions have been proposed in order to provide mobile users with extended device usage time, the areas of adaptive mobile learning and energy conservation in wireless communications failed to meet under the same umbrella. This paper bridges the two areas by presenting an overview of adaptive mobile learning systems as well as how these can be extended to make them energy-aware. Furthermore, the paper surveys various approaches for energy measurement, modelling and adaptation, three major aspects that have to be considered in order to deploy energy-aware mobile learning systems. Discussions on the applicability and limitations of these approaches for mobile learning are also provided

Future Trends and Directions for Secure Infrastructure Architecture in the Education Sector: A Systematic Review of Recent Evidence

The most efficient approach to giving large numbers of students’ access to computational resources is through a data center. A contemporary method for building the data center\u27s computer infrastructure is the software-defined model, which enables user tasks to be processed in a reasonable amount of time and at a reasonable cost. The researcher examines potential directions and trends for a secured infrastructure design in this article. Additionally, interoperable, highly reusable modules that can include the newest trends in the education industry are made possible by cloud-based educational software. The Reference Architecture for University Education System Using AWS Services is presented in the paper. In conclusion, automation boosts efficiency by 20% while decreasing researcher involvement in kinetics modeling using CHEMKIN by 10%. Future work will focus on integrating GPUs into open-source programs that will be automated and shared on CloudFlame as a service resource for cooperation in the educational sector

Understanding and predicting teachers’ intention to use cloud computing in smart education

Purpose Applying cloud computing (CC) in education is a great opportunity to globalize knowledge with the minimum costs and maximum accessibility. This study aims to understand and predict teacher intention to use cloud commuting as infrastructure in Smart education. Design/methodology/approach This was a cross-sectional study in which faculty members’ perception concerning CC services adoption in education were assessed based on the extended model of theory of planned behavior, by researcher-developed questionnaire (a = 0.9). Collected data were analyzed by regression analysis and the final model was tested by structural equation modeling. Findings Attitude towards the behavior, perceived behavior control and privacy; had direct and significant associations with faculty members’ intention to use CC. However, subjective norms (p = 0.311) and security (p = 0.505 ) were not significant predictors of intention to use CC. Originality/value The results of this study elucidate the critical factors associated with teacher’s behavioral intentions toward CC services and also serve as a valuable reference for education sector to plan for the better use of these services. The presented model can be considered as best practice framework for adapting cloud commuting as infrastructure in education. Applying CC services in education is great opportunity and should be subsequently the major concern of educational organizations. This study clearly identified significant and non-significant factors that should be considered when successful implementation on could computing services is in progress

A Literature Review on Intelligent Services Applied to Distance Learning

Distance learning has assumed a relevant role in the educational scenario. The use of Virtual Learning Environments contributes to obtaining a substantial amount of educational data. In this sense, the analyzed data generate knowledge used by institutions to assist managers and professors in strategic planning and teaching. The discovery of students’ behaviors enables a wide variety of intelligent services for assisting in the learning process. This article presents a literature review in order to identify the intelligent services applied in distance learning. The research covers the period from January 2010 to May 2021. The initial search found 1316 articles, among which 51 were selected for further studies. Considering the selected articles, 33% (17/51) focus on learning systems, 35% (18/51) propose recommendation systems, 26% (13/51) approach predictive systems or models, and 6% (3/51) use assessment tools. This review allowed for the observation that the principal services offered are recommendation systems and learning systems. In these services, the analysis of student profiles stands out to identify patterns of behavior, detect low performance, and identify probabilities of dropouts from courses.info:eu-repo/semantics/publishedVersio