2828 research outputs found
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Teachers' Perspectives on the Implementation of Individualised Education Plans (IEPs) for Students with Special Educational Needs and Disabilities (SEND): A Case Study in a Private School in Abu Dhabi
No full textThe study examines how teachers in a private school in Abu Dhabi view and experience using Individualised Education Plans (IEPs) for students with Special Educational Needs and Disabilities (SEND). As inclusive education is growing in the UAE, IEPs play a crucial role in helping SEND students succeed academically and socially. However, challenges in IEP implementation frequently arise because teachers lack sufficient training, resources are scarce, time is limited, and support from the school is inconsistent. Six primary school instructors from various subject areas and class levels were interviewed, and this study explores the realities of developing and using IEPs in a private school. Several significant trends emerged, including insufficient opportunities for staff development, varying levels of administrative support, and a need for enhanced collaboration among relevant parties. The findings highlight the importance of teachers’ attitudes, school structure, and ongoing development for student success under IEPs. Additionally, the study addresses issues with current policies and practices and provides practical tips to support inclusive education in other contexts. The information presented here aims to assist educators, policymakers, and school leaders in adopting effective strategies to support IEP implementation in private schools throughout the region, ultimately benefiting students with SEND
Drivers of AI Adoption for Project Risk Management in the UAE’s Oil and Gas Industry
No full textThis study examines the use of Artificial Intelligence (AI) technologies in the United Arab
Emirates oil and gas sector. AI has the potential to improve predictive analytics, decision making, and operational resilience. However, its integration into high-risk industries is still
limited. This study examines the influence of technological, organization, and environmental
factors, along with the moderating effect of perceived risk on AI adoption. Grounded in the
Technology-Organization-Environment (TOE) framework, Diffusion of Innovations (DOI)
theory, and Institutional Theory, a conceptual model was developed and tested using data from
268 professionals in the UAE oil and gas sector. Smart-PLS 4 was employed to conduct
Structural Equation Modelling (SEM) and assess hypothesized relationships. The findings
revealed that compatibility significantly influenced AI adoption intentions, while other factors,
such as innovation culture, leadership support, and complexity, were not supported.
Regulatory support and competitive pressure showed marginal effects. Perceived risk
moderated the relationship between relative advantage and adoption intention but had no
effect elsewhere. The study contributes theoretically by extending established adoption models
to a high-risk industrial context, highlighting the selective influence of perceived risk.
Practically, it offers industry-specific guidelines to support effective AI integration into project
risk management processes. The results underscore the early stage of AI adoption in the sector
and point to the need for enhanced technological readiness, regulatory clarity, and strategic
alignment
Investigating the Causes of Food Waste in the Hospitality Sector in Dubai-UAE. Toward Implementing Food Waste Prevention Strategies
No full textOne of the major environmental problems worldwide is food waste and loss. In Dubai, an Emirate in the United Arab Emirates, this problem is most significant in the hospitality sector including restaurants, hotels and food services, at the consumption level. The efforts to create campaigns and initiatives are notable, however, the theoretical part of finding the actual causes of this problem is still unobtrusive. This research focuses to fill this gap and find the main causes of food waste (FW) especially in the hospitality sector of Dubai and suggests prevention strategies for food services to follow. It used a mixed-mode methodology by spreading two surveys for food services guests and employees, then interviewing expert-positioned people in the emirate to verify the data. It found that customers’ main causes of FW were taking big portions and lack of awareness. The causes of FW from food services were mainly their over-production and wrong forecasting for numbers. Interviewees suggested strategies to prevent FW. Thus, the research combined all results to come up with a FW reduction fundamental plan for food services to follow
The Impact of Teachers’ Differentiated Instructions on Gifted Students at a Private School in Abu Dhabi
No full textThis study examines the effectiveness of differentiated instruction for gifted students within a private school in Abu Dhabi. The research investigates the impact of educators’ behaviours and instructional strategies on the learning experiences of gifted students, placing particular emphasis on advanced questioning, inquiry-based learning, flexible grouping and the implementation of appropriate educational resources technology. Grounded in a philosophical foundation based on the social constructivist worldview, classroom observations and interviews were conducted to gather empirical data from teachers and educational leaders. Results revealed that while some differentiation strategies are effectively implemented and positively impacted gifted and talented students’ learning experiences, inconsistencies and challenges such as time constraints, classroom management and a lack of targeted professional development impede their consistent application. The study highlights the significance of supportive school leadership and access to resources and technology in fostering effective differentiation. The results underscore the imperative for continual professional development and collaborative planning to augment educators’ ability to address the varied requirements of gifted students, with the ultimate objective of fostering their academic advancement and engagement
Evaluating Passive and Active Retrofit Strategies to Improve Energy Performance in Existing Federal Buildings in the UAE – Northern Emirates
No full textThis study evaluates passive and active retrofit strategies to enhance the energy performance of existing federal buildings in the Northern Emirates of the UAE. Using IES-VE simulation, the research quantified the technical, environmental, and financial outcomes of multiple retrofit scenarios. The results showed that glazing and insulation reduced energy consumption by 14.42% and 14.71%, respectively, while VAV-HVAC with heat recovery achieved 15.35% savings. BMS integration and lighting retrofits (LEDs, controls, and sunlight tubes) reduced energy use by up to 25%, and PV/BIPV systems generated 123.63–149.87 MWh annually. The combined retrofit package achieved a 44.79% reduction in total energy use (≈270.51 MWh/year) with a six-year payback and a 16.9% ROI. The findings align directly with the UAE Energy Strategy 2050, supporting targets of 40% demand reduction, 40% efficiency improvement, and 50% clean-energy contribution. The study confirms that these retrofit measures are technically feasible and economically viable, bridging regional disparities and advancing the national sustainability goals. Although limited to one case study, the results provide a replicable model for federal buildings across the UAE, transforming them from energy-intensive assets into exemplary sustainable facilities.
Keywords: energy efficiency, federal buildings, UAE, Northern Emirates, retrofit, passive & active technologies, IES-VE simulation, BMS, PV, BIPV, sunlight tube, HVAC-VA
The Impact of Internship and On-site Feedback on Enhancing Employable Skills: Accounting Stakeholders' Perspectives in UAE Hospitality and Tourism Programmes
No full textThis PhD thesis investigates the impact of internships and on-site feedback on employable skills in hospitality and tourism programs at selected higher education institutions in the UAE. It addresses the growing need for skilled graduates by exploring how experiential learning, particularly internships and feedback, enhances employability competencies. The study focuses on three objectives: (1) assessing the role of internships in skill development, (2) examining the impact of on-site feedback, and (3) analyzing stakeholder perspectives, including faculty, employers, and students. Using a mixed-methods approach incorporating a literature review, statistical analysis, and qualitative interviews with faculty, coordinators, and industry professionals the findings emphasize that internships significantly foster skill development, career readiness, and alignment with workforce demands. The study highlights the growing integration of internships into curricula, supported by industry partnerships and feedback systems. However, challenges like inconsistent feedback, variable placement quality, and unmet expectations persist. On-site feedback is vital for improving technical and soft skills, including adaptability and communication. Stakeholders emphasize structured roles, effective mentorship, and alignment with trends such as sustainability, Emiratization, and digital transformation. Key recommendations include standardizing internship frameworks, enhancing industry-academic collaboration, and improving feedback systems. Educational institutions should ensure quality placements, while employers provide structured training and mentorship. Policymakers must align programs with industry needs and emerging trends. These strategies aim to optimize internships, bridge academic learning with industry practice, and prepare students for success in the dynamic hospitality and tourism sectors.
Keywords: Stakeholders, UAE, Stakeholder Perspectives, Mixed Method
Cyber-risk Mitigation Strategies and the Role of Artificial Intelligence in Mitigating Cyber-Risks: The Case of the United Arab Emirates Transport Sector
No full textThe scale, volume, and sophistication levels of cyber-risks and threats to critical services and infrastructures of nations are surpassing defensive procedures and measures put in place. Destructive and disruptive cyber activities require the UAE government to address and invest in making the country move from a state of cyber insecurity to a state of cyber readiness. Losses are accumulating, the damage is growing and the danger to critical infrastructure assets is imminent. Critical infrastructures are physical structures and systems whose unavailability compromises the maintenance of services or resources of a locality, region or country. Critical infrastructures related to airport, sea power, traffic management and navigation systems, networks, vehicles and others can be the target of different cyber-attacks for different reasons. This research aimed to highlight the importance of building agile and resilient cybersecurity systems that can address emerging cyber-risks. The research employed a quantitative method, a survey questionnaire, which was completed by 286 participants. The key research findings based on the theoretical and practical data showed that there is a significant relationship between cybersecurity considerations and cyber-risk mitigation and also there is a significant relationship between employing artificial intelligence (AI) adoption and cyber-risk mitigation. The research findings emphasised the key role of leadership in steering the cybersecurity posture in terms of spreading a healthy cybersecurity culture within transport organisations, as it has a significant impact on preventing vulnerabilities and adopting smart technologies such as artificial intelligence and machine learning. Raising staff awareness about different cyber-risks, hygiene practices, and behavioural and attitude change play a key role in preventing and managing cyber-risks
Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls
No full textThe city of Dubai enjoys a plethora of shopping malls and retail centres. Due to harsh weather in the outdoor areas, visitors and residents prefer indoor spaces, especially areas such as central atriums in the shopping malls where people can socialise, dine and engage in daily activities. Such an atrium features skylights as these are considered the main source of natural light due to the absence of side windows in this type of building. This research investigates the impact of atrium and skylight configurations on daylight performance and visual comfort in shopping malls. The study begins with a comprehensive literature review to build a theoretical foundation and identify research gaps. Key variables and target metrics are identified, followed by a selection of representative case studies. Field measurements and computer simulations are conducted to model and validate daylight performance. Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. Comparative analysis quantifies such improvements, and generic guidelines are developed for broader application, along with a discussion of future steps and possible research opportunities
Drivers of AI Adoption for Project Risk Management in the UAE’s Oil and Gas Industry
No full textThis study examines the use of Artificial Intelligence (AI) technologies in the United Arab Emirates oil and gas sector. AI has the potential to improve predictive analytics, decision-making, and operational resilience. However, its integration into high-risk industries is still limited. This study examines the influence of technological, organization, and environmental factors, along with the moderating effect of perceived risk on AI adoption. Grounded in the Technology-Organization-Environment (TOE) framework, Diffusion of Innovations (DOI) theory, and Institutional Theory, a conceptual model was developed and tested using data from 268 professionals in the UAE oil and gas sector. Smart-PLS 4 was employed to conduct Structural Equation Modelling (SEM) and assess hypothesized relationships. The findings revealed that compatibility significantly influenced AI adoption intentions, while other factors, such as innovation culture, leadership support, and complexity, were not supported. Regulatory support and competitive pressure showed marginal effects. Perceived risk moderated the relationship between relative advantage and adoption intention but had no effect elsewhere. The study contributes theoretically by extending established adoption models to a high-risk industrial context, highlighting the selective influence of perceived risk. Practically, it offers industry-specific guidelines to support effective AI integration into project risk management processes. The results underscore the early stage of AI adoption in the sector and point to the need for enhanced technological readiness, regulatory clarity, and strategic alignment.
Keywords: Artificial Intelligence (AI), AI adoption, UAE, perceived ris
