IT Governance Framework and Smart Services Integration for Future Development of Dubai Infrastructure Utilizing AI and Big Data, Its Reflection on the Citizens Standard of Living

Advances in intelligent systems and computing, Journal Year: 2021, Volume and Issue: unknown, P. 235 - 247

Published: Jan. 1, 2021

Language: Английский

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Examining the Factors Influencing the Mobile Learning Usage During COVID-19 Pandemic: An Integrated SEM-ANN Method

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 102567 - 102578

Published: Jan. 1, 2021

The way in which the emotion of fear affects technology adoption students and teachers amid COVID-19 pandemic is examined this study. Mobile Learning (ML) has been used study as an educational social platform at both public private higher-education institutes. key hypotheses are based on how influenced incorporation mobile learning brings about increase different kinds fear. major that teachers/instructors facing time include: because complete lockdown, experiencing education collapse having to give up relationships. proposed model was evaluated by developing a questionnaire survey distributed among 280 Zayed University, Abu Dhabi Campus, United Arab Emirates (UAE) with purpose collecting data from them. This uses new hybrid analysis approach combines SEM deep learning-based artificial neural networks (ANN). importance-performance map also determine significance performance every factor. Both ANN IPMA research showed Attitude (ATD) most important predictor intention use learning. According empirical findings, perceived ease use, usefulness, satisfaction, attitude, behavioral control, subjective norm played strongly significant role justified continuous usage. It found expectation confirmation were factors predicting Our field education, coronavirus pandemic, offered potential outcome for teaching learning; however, impact may be reduced losing friends, stressful family environment future results school. Therefore, during it examine appropriately so enable them handle situation emotionally. theoretically given enough details what influences ML viewpoint internet service variables individual basis. In practice, findings would allow higher decision formers experts decide should prioritized over others plan their policies appropriately. examines competence deciding non-linear relationships theoretical model, methodologically.

Language: Английский

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Factors That Affect E-Learning Platforms after the Spread of COVID-19: Post Acceptance Study

Data, Journal Year: 2021, Volume and Issue: 6(5), P. 49 - 49

Published: May 12, 2021

The fear of vaccines has led to population rejection due various reasons. Students have had their own inquiries towards the effectiveness vaccination, which leads vaccination hesitancy. Vaccination hesitancy can affect students’ perception, hence, acceptance e-learning platforms. Therefore, this research attempts explore post-acceptance platforms based on a conceptual model that variables. Each variable contributes differently platform. investigates moderating role among students. Thus, study aims at exploring perceptions about where functions as moderator. current depends an online questionnaire is composed 29 items. total number respondents 630. collected data was implemented test and proposed constructs hypotheses depending Smart PLS Software. Fear significant impact platforms, it strong mediator in model. findings indicate positive effect variables: perceived ease use usefulness, daily routine, critical mass self-efficiency. implication gives deep insight take effective steps reducing level supporting confidence educators, teachers students who will, turn, society whole.

Language: Английский

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Acceptance of Google Meet during the Spread of Coronavirus by Arab University Students

Informatics, Journal Year: 2021, Volume and Issue: 8(2), P. 24 - 24

Published: March 30, 2021

The COVID-19 pandemic not only affected our health and medical systems but also has created large disruption of education at school universities levels. According to the United Nation’s report, influenced more than 1.6 billion learners from all over world (190 countries or more). To tackle this problem, colleges have implemented various technologically based platforms replace physical classrooms during spread Coronavirus. effectiveness these technologies their educational impact on sector been concern researchers pandemic. Consequently, current study is an attempt explore effect Google Meet acceptance among Arab students in Oman, UAE, Jordan. perceived fear factor integrated into a hybrid model that combines crucial factors TAM (Technology Model) VAM (Value-based Adoption Model). integration embraces with other important ease use (PEOU) usefulness (PU) one hand technically influential VAM, which are technicality (PTE) enjoyment (PE) hand. data, collected 475 participants (49% males 51% females students), were analyzed using partial least squares-structural equation modelling (PLS-SEM). results shown hypotheses easy supported. Similarly, supported related being useful enjoying, helps reducing atmosphere due

Language: Английский

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A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps

Sustainability, Journal Year: 2022, Volume and Issue: 14(18), P. 11389 - 11389

Published: Sept. 10, 2022

Over the past three decades, Technology Acceptance model (TAM) has garnered considerable attention in higher education. COVID-19 boosted development of TAM as multiple studies were rapidly undertaken during pandemic. This, however, created a gap our current understanding directions and trends advancement. The purpose this study is to obtain insight into advancement throughout It would assist researchers comprehending direction education, such gaining an prevalent external variables for TAM, statistical analysis employed, research methodologies, technologies studied, geographic location conducted. Finally, gaps future are presented. A systematic review utilizing PRISMA was conducted on 104 sampled publications. found that self-efficacy, subjective norms, experience, enjoyment most frequently used while internal motivation received minimal attention. existing have focused mainly student samples, so further investigation needed lecturers, education personnel, mixed groups. Further also required qualitative methods, with partial least square structural equation currently dominating analysis. Future 5G, AI, cloud computing, augmented reality, virtual BYOD represent new TAM-related gaps. majority been Asian countries, China those southeast Asia. This literature provides trend sustainability pandemic, identified gaps, recommendations directions. These findings serve reference by enhancing foundation established previous reviews thereby facilitating model’s ongoing expansion.

Language: Английский

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A systematic review on machine learning models for online learning and examination systems

PeerJ Computer Science, Journal Year: 2022, Volume and Issue: 8, P. e986 - e986

Published: May 18, 2022

Examinations or assessments play a vital role in every student's life; they determine their future and career paths. The COVID pandemic has left adverse impacts all areas, including the academic field. regularized classroom learning face-to-face real-time examinations were not feasible to avoid widespread infection ensure safety. During these desperate times, technological advancements stepped aid students continuing education without any breaks. Machine is key this digital transformation of schools colleges from online mode. Online examination during lockdown made possible by methods. In article, systematic review Lockdown Exam Management Systems was conducted evaluating 135 studies over last five years. significance entire exam cycle pre-exam preparation, conduction examination, evaluation studied discussed. unsupervised supervised algorithms identified categorized each process. primary aspects examinations, such as authentication, scheduling, proctoring, cheat fraud detection, are investigated detail with perspectives. main attributes, prediction at-risk students, adaptive learning, monitoring integrated for more understanding machine followed its management post-examination Finally, concludes issues challenges that imposes on system, discussed solutions.

Language: Английский

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Personalized and Adaptive Context-Aware Mobile Learning: Review, challenges and future directions

Education and Information Technologies, Journal Year: 2022, Volume and Issue: 27(6), P. 7491 - 7517

Published: Feb. 12, 2022

Language: Английский

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Exploring the effects of personalized recommendations on student’s motivation and learning achievement in gamified mobile learning framework

Education and Information Technologies, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 29, 2024

Language: Английский

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The Impact of COVID-19 on E-learning: Advantages and Challenges

Advances in intelligent systems and computing, Journal Year: 2021, Volume and Issue: unknown, P. 75 - 89

Published: Jan. 1, 2021

Language: Английский

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Blockchain-Enabled Internet of Things (IoT) Platforms for Pharmaceutical and Biomedical Research

Advances in intelligent systems and computing, Journal Year: 2021, Volume and Issue: unknown, P. 589 - 600

Published: Jan. 1, 2021

Language: Английский

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