Search Results (815)

This study aims to (1) examine the impact of AI-driven learning tools (AI-LTs) on educational sustainability (EDS) and (2) investigate the mediating role of students’ engagement (SE) and the moderating effect of digital resilience (DR) in this relationship. Based on sociotechnical systems theory (STS), self-determination theory (SDT), and resilience theory, and (3) developing a multidimensional framework to explore how technological, psychological, and contextual factors interact to shape sustainable learning outcomes. Data were gathered from 387 university students in Saudi universities using a standardized questionnaire and subsequently analyzed utilizing SPSS version 28 and PROCESS Macro Version 4.0. The study performed multiple regression and moderated mediation to evaluate the proposed relationships. The results confirmed that AI-LTs significantly enhance educational sustainability. Based on the findings, AI-LTs significantly improve the long-term viability of education, particularly when it is tailored to individual students, encourages active participation, and is logical from a pedagogical perspective. Student engagement was found to influence the relationship, suggesting that when AI tools are utilized effectively, they foster a sustained commitment to education and improved learning outcomes. Furthermore, digital resilience has a significant influence on the connection between AI-LT–EDS, indicating that students who exhibited improved adaptability to digital challenges reaped considerable benefits. The research enhances the existing literature by integrating three complementary frameworks—STS, SDT, and resilience theory—to provide a comprehensive understanding of AI’s role in sustainable education. Practically, the study underscored the importance of AI integration strategies that improve digital resilience, student engagement, and structural imbalance. The results demonstrated that AI usage necessitates significant institutional support and improved technology to establish educational environments that are adaptable, resilient, and easily accessible to students. Full article

The incorporation of Artificial Intelligence (AI) into medical services in Saudi Arabia offers a substantial opportunity. Despite the increasing integration of AI techniques such as machine learning, natural language processing, and predictive analytics, there persists an issue in the thorough comprehension of their applications, advantages, and issues within the Saudi healthcare framework. This study aims to perform a thorough systematic literature review (SLR) to assess the current status of AI in Saudi healthcare, determine its alignment with Vision 2030, and suggest practical recommendations for future research and policy. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 699 studies were initially obtained from electronic databases, with 24 studies selected after the application of established inclusion and exclusion criteria. The results indicated that AI has been effectively utilised in disease prediction, diagnosis, therapy optimisation, patient monitoring, and resource allocation, resulting in notable advancements in diagnostic accuracy, operational efficiency, and patient outcomes. Nonetheless, limitations to adoption, such as ethical issues, legislative complexities, data protection issues, and shortages in worker skills, were also recognised. This review emphasises the necessity for strong ethical frameworks, regulatory control, and capacity-building efforts to guarantee the responsible and fair implementation of AI in healthcare. Recommendations encompass the creation of national AI ethics and governance frameworks, investment in AI education and training initiatives, and the formulation of modular AI solutions to guarantee scalability and cost-effectiveness. This breakthrough enables Saudi Arabia to realise its Vision 2030 objectives, establishing the Kingdom as a global leader in AI-driven healthcare innovation. Full article

Employer-funded education and training (EFET) has gained increasing attention as a strategic human resource practice for developing human capital and enhancing organizational performance. However, empirical evidence on its effectiveness remains limited in emerging economies, particularly within the Kingdom of Saudi Arabia (KSA), where workforce localization and human capital development are central to Vision 2030. This study examines the associations between EFET participation and three key employee outcomes: motivation, retention intention, and productivity. Using a quantitative research design, data were collected from 200 employees and managers across multiple sectors in KSA through a structured questionnaire. Structural Equation Modeling (SEM) was employed to test the hypothesized relationships while controlling for gender, age, sector, and years of experience. The results indicate that EFET participation is positively and significantly associated with employee motivation, retention intention, and self-reported productivity, with the strongest association observed for retention intention. Model fit indices demonstrate an excellent overall fit, supporting the proposed model’s robustness. By integrating Human Capital Theory with empirical evidence from the Saudi context, this study contributes to the literature by extending understanding of how employer-funded education functions within a non-Western labor market. The findings offer practical implications for organizations and policymakers seeking to optimize education and training investments in support of sustainable workforce development and Vision 2030 objectives. Full article

This investigation provides a critical analysis of the digital forensics field within the Kingdom of Saudi Arabia (KSA), specifically focusing on its educational systems, and the effectiveness of prosecutorial efforts. Utilizing a mixed-methodology framework and extensive literature reviews, this study reveals pronounced deficiencies in digital forensics against increased cybercrime activities. Furthermore, it highlights a general lack of preparedness among digital forensics professionals in KSA and notes significant variations in forensic applications across different judicial and educational contexts. The research recommends creating a uniform national educational framework for digital forensics, improving professional training programs, and strategically enhancing forensic technologies. Through a thorough analysis of demographic trends, educational programs, and adherence to procedural standards, this study proposes targeted strategies to fortify the digital forensic infrastructure of KSA, aligning with the strategic imperatives of Vision 2030. Full article

Food waste undermines the four dimensions of food security, availability, accessibility, utilization, and stability, while imposing adverse economic, social, and environmental impacts on sustainable food systems. Understanding the behavioral determinants of food consumption rationalization is essential for addressing this challenge in the Kingdom of Saudi Arabia. This study examines household food waste behaviors within a knowledge-based framework that integrates three interconnected constructs: awareness of food waste consequences, behavioral knowledge of waste-reduction practices, and actual engagement in conservation strategies. Data were collected from 255 households (response rate: 66%) in Buraydah City through an electronic questionnaire administered in shopping malls. Using Baron and Kenny mediation analysis and multiple linear regression, awareness of waste consequences influences conservation practices both directly (β = 0.132, p < 0.001) and indirectly through behavioral knowledge (accounting for 68.6% of the total effect), explaining 74.9% of the variance in household conservation behaviors (R² = 0.749). The analysis reveals that awareness of waste consequences influences conservation practices both directly and indirectly through behavioral knowledge, establishing a mediation pathway. Together, these knowledge dimensions significantly explain variations in household conservation behaviors. The findings highlight the critical interplay between awareness and practical behavioral knowledge in driving sustainable food consumption practices. These insights provide empirical guidance for policymakers and agencies seeking to develop targeted interventions that integrate consequence messaging with practical behavioral training to effectively reduce household food waste and promote food security in Saudi Arabia. Full article

This study investigates the impact of AI augmentation level on employee productivity and innovation quality, while examining the mediating role of knowledge augmentation quality and the moderating roles of task complexity and employees’ trust in AI. The research aims to uncover how AI can act as a strategic cognitive enhancer rather than a mere automation tool in modern workplaces. A quantitative, cross-sectional design was employed, and data were collected from 275 employees working in AI-enabled organizations across the technology, banking, telecommunications, and digital services sectors in the Kingdom of Saudi Arabia. Validated measurement scales from prior studies were used, and SmartPLS was applied to test direct, mediating, and moderating effects. The results confirmed that AI augmentation positively influences both employee productivity and innovation quality. Knowledge augmentation quality significantly mediated these relationships, while task complexity and employee trust in AI positively strengthened the impact of knowledge augmentation on performance outcomes. This study extends the AI literature by demonstrating that AI’s true value lies in enhancing the quality of knowledge that employees receive, not just automating tasks. It offers theoretical insight into human–AI collaboration and provides practical guidance for designing AI systems that enhance cognitive support, trust, and performance in intelligence-driven work environments. Full article

This study aimed to determine the degree of diversification in exports of fresh/chilled salmon and the level of international competitiveness of Norway, Sweden, Chile, and the United Kingdom over 2020–2024, using the Herfindahl–Hirschman Index (HHI) and the normalized revealed comparative advantage (NRCA). A quantitative, descriptive approach was adopted, drawing on annual Trade Map data for HS subheading 030214. HHI series were constructed by country–destination and NRCA series by country–market, and both were examined through univariate analysis. The findings showed that Norway exhibited low concentration levels and strong, stable advantages in Saudi Arabia, Türkiye, and Russia, whereas Sweden displayed moderate but rising concentration, supported by high advantages in Belgium, the United Kingdom, Germany, and Italy. In contrast, Chile and the United Kingdom recorded persistently high HHI values, with pronounced advantages concentrated in a limited number of markets (Brazil in Chile’s case; France and Chinese Taipei in the UK’s) and intra-product positions or comparative disadvantages in China, the United States, and Mexico. The study concludes that the combination of geographic diversification and positive NRCA enhances export resilience, while extreme specialization increases vulnerability to demand and regulatory shocks. It is recommended that Chile and the United Kingdom further develop diversification strategies toward markets where NRCA is neutral or negative, and that Norway and Sweden consolidate their advantages through investments in sustainability, traceability, and logistics. Further multivariate research incorporating macroeconomic and firm-level variables is also suggested. Full article

Cyberbullying generally reveals two leading players: the attacker side (perpetrator) and the victim side; each side has its distinctive social and psychological dynamics. In most prior empirical studies, the victim side is pivotal, as it bears the direct psychological and emotional consequences of online aggression. Recently, cyberbullying victimisation has been elevated as a main psychological concern among university students. Nevertheless, the moderating role of family support remained untested, particularly in a collectivist cultural context such as the Kingdom of Saudi Arabia (KSA). This study tested the impacts of cyberbullying victimisation on mental health consequences (anxiety, stress, and depression) among KSA university students. The study further tested family support as a moderator in these relationships. Data was collected from 650 students employing a self-structured survey. The data obtained was analyzed using “Partial Least Squares Structural Equation Modelling” (PLS-SEM). The findings revealed that cyberbullying-victimization can significantly raise students’ anxiety, stress, and depressive signs, supporting its place as a critical psychological risk factor. Contrary to the “traditional stress-buffering theory”, family support failed to alleviate the influence of cyberbullying-victimization on anxiety and stress, and unexpectedly, higher levels of family support were related to higher depressive levels, suggesting a reverse-buffering impact. These results highlighted the complicated relationships between family support and emotional outcomes in the context of digital threats. The study stressed the urgent need for culturally delicate mediations, such as training sessions for digital resilience, and colleague-based supportive systems to successfully deal with the mental health consequences of cybervictimization. Full article

This review highlights Artemisia annua, a medicinal plant which grows in the Kingdom of Saudi Arabia, known for its abundant therapeutic properties. A. annua serves as a rich source of various bioactive compounds, including sesquiterpenoid lactones, flavonoids, phenolic acids, and coumarins. Among these, artemisinin and its derivatives are most extensively studied due to their potent antimalarial properties. Extracts and isolates of A. annua have demonstrated a range of therapeutic effects, such as antioxidant, anticancer, anti-inflammatory, antimicrobial, antimalarial, and antiviral properties. Given its significant antiviral activity, A. annua could be investigated for the development of new nutraceutical bioactive compounds to combat SARS-CoV-2. Artificial Intelligence (AI) can assist in drug discovery by optimizing the selection of more effective and safer natural bioactives, including artemisinin. It can also predict potential clinical outcomes through in silico modeling of protein–ligand interactions. In silico studies have reported that artemisinin and its derivatives possess a strong ability to bind with the Lys353 and Lys31 hotspots of the SARS-CoV-2 spike protein, demonstrating their effective antiviral effects against COVID-19. This integrated approach may accelerate the identification of effective and safer natural antiviral agents against COVID-19. Full article

NOOR is the Kingdom of Saudi Arabia’s national Educational Management Information System (EMIS), developed by the Ministry of Education to digitize and streamline academic and administrative processes across public schools. Through its unified digital infrastructure, the platform enables essential functions such as student enrolment, grade and attendance management, curriculum administration, and communication with families. Beyond its operational role, NOOR is regarded as a flexible digital foundation, with a predictive architecture, modular integration, and distributed infrastructure which position it as a potential model for broader public-service domains, including healthcare and digital governance. NOOR’s design supports equitable access, facilitates cooperation between educational organizations, and provides real-time data to inform evidence-based decision making. These capabilities contribute to improving learning processes, though their impact depends on wider institutional and pedagogical environments. The system has already demonstrated progress in areas such as data accuracy, academic monitoring, family engagement, and reporting efficiency. Aligned with Saudi Arabia’s Vision 2030 and the Tanweer educational reform program, NOOR reflects the national shift toward centralized, data-driven management of public education. With more than 12 million users, it is one of the largest EMIS platforms in the Middle East and contributes to global discussions on how integrated digital infrastructures can support impactful educational reform. Full article

Saudi Natural Pozzolan (SNP) can be processed and used in construction as a partial replacement for Ordinary Portland Cement (OPC). Its use as a supplementary cementitious material supports more sustainable and eco-friendly building practices. This study investigates various treatment methods for enhancing the reactivity of SNPs, including thermal, mechanical, thermo-mechanical, mechano-thermal, and chemical techniques. The activity of 18 different treated SNP mixtures was evaluated using the Strength Activity Index (SAI). Results identified the optimum conditions for each treatment: thermal treatment at 600 °C, mechanical treatment through 6 h of grinding, and chemical treatment with a 9% addition of hydrated lime. The SAI results demonstrated that a 6 h mechanical treatment was the most effective method for activating the raw pozzolan. X-ray diffraction (XRD) analysis revealed that phases such as quartz, anorthite, and aluminate are significant contributors to pozzolanic activity. The XRD analysis was further supported by scanning electron microscopy (SEM), which examined microstructural changes. This study highlights the potential of maximizing the utilization of extensive pozzolan resources in the Harrat region of the Kingdom of Saudi Arabia. Treated SNP can be applied in various industries, such as mining backfills, brick industry, and pozzolanic concrete, as a sustainable and environmentally friendly material. Full article

Over the last 40 years, the Kingdom of Saudi Arabia (KSA) has experienced economic growth that has driven urbanization and infrastructure improvements. However, this has also led to high resource use and poor planning, exacerbating climate challenges and underscoring the need for international cooperation. Given the substantial energy use associated with buildings, sustainable global building standards have been developed. Saudi Vision 2030 encourages sustainable practices in energy, housing, and water by adopting green building standards to guide environmentally friendly initiatives. This study provides an overview of the current status of green building rating systems in KSA and examines the principal obstacles faced during their implementation. Utilizing importance-performance analysis (IPA), the study identifies and evaluates strategies to advance green building ratings, drawing upon survey data from diverse stakeholders. Major barriers include low awareness across the public and private sectors and technical challenges such as a shortage of qualified professionals, limited information, and unreliable resources. The strategies proposed aim to establish clear standards for sustainable construction and promote targeted awareness campaigns with industry leaders and government, highlighting the long-term environmental and financial advantages of green buildings. Identifying these barriers and evaluating interventions will help to advance green building rating systems and sustainability in KSA and worldwide. Full article

Background: Chronic obstructive pulmonary disease (COPD) is a progressive respiratory condition with significant economic burden, morbidity, and mortality rates worldwide. In the Kingdom of Saudi Arabia (KSA), 4.2% of adults 40 years and older have COPD, with a higher prevalence in men and older populations. Key risk factors include smoking, air pollution, occupational exposures, and genetics. COPD coexists with cardiovascular disease (CVD) often, making diagnosis and management more difficult. This study proposes two referral algorithms to optimize care for COPD patients with coexisting CVD in the KSA. Methods: A nine-member cardiopulmonary task force reviewed pertinent literature, guidelines, and held virtual meetings from April to August 2025. Every algorithmic component was iteratively refined; consensus was reached when at least 80% of participants agreed, and items not reaching this threshold were revised until full agreement was reached. Results: According to the cardiology-to-pulmonology algorithm, patients who have unidentified respiratory symptoms or COPD risk factors undergo spirometry assessment and, if confirmed, are referred to pulmonology for diagnostic confirmation, phenotyping, and treatment, including triple fixed-dose combination therapy (TFDC) when necessary. On the other hand, the pulmonology-to-cardiology algorithm directs the evaluation of CVD risk factors and comorbidities using clinical evaluation, electrocardiogram, echocardiography, and biomarker testing, for cardiology referral. Conclusions: By establishing bidirectional referral pathways, morbidity and healthcare burden can be decreased, early detection can be improved, and multidisciplinary management can be strengthened. Future research should assess the feasibility, cost-effectiveness, and real-world impact within KSA’s healthcare system. Full article

Protected agriculture increasingly requires solutions that reduce energy consumption and environmental impacts while maintaining stable microclimatic conditions. The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) with solar technologies has emerged as a pathway toward autonomous and energy-efficient greenhouses and solar dryers. This study analyzes the scientific and technological evolution of this convergence using a mixed review approach bibliometric and systematic, following PRISMA 2020 guidelines. From Scopus records (2012–2025), 115 documents were screened and 79 met the inclusion criteria. Bibliometric results reveal accelerated growth since 2019, led by Engineering, Computer Science, and Energy, with China, India, Saudi Arabia, and the United Kingdom as dominant contributors. Thematic analysis identifies four major research fronts: (i) thermal modeling and energy efficiency, (ii) predictive control and microclimate automation, (iii) integration of photovoltaic–thermal (PV/T) systems and phase change materials (PCMs), and (iv) sustainability and agrivoltaics. Systematic evidence shows that AI, ML, and DL based models improve solar forecasting, microclimate regulation, and energy optimization; model predictive control (MPC), deep reinforcement learning (DRL), and energy management systems (EMS) enhance operational efficiency; and PV/T–PCM hybrids strengthen heat recovery and storage. Remaining gaps include long-term validation, metric standardization, and cross-context comparability. Overall, the field is advancing toward near-zero-energy greenhouses powered by Internet of Things (IoT), AI, and solar energy, enabling resilient, efficient, and decarbonized agro-energy systems. Full article

The rapid global shift toward transportation electrification has positioned e-mobility as a key part of low-carbon transition strategies. Saudi Arabia, as a major energy producer undergoing economic diversification under Vision 2030, has recently increased its policy efforts for electric mobility. This study performs a qualitative document analysis of 52 national policies, strategies, and institutional publications issued between 2010 and 2025, creating a longitudinal dataset of 1240 coded references. Using a PRISMA-aligned screening process and NVivo-based thematic coding, the analysis highlights main policy trends, institutional priorities, and implementation challenges influencing the Kingdom’s e-mobility transition. Results show a clear shift from early technology-neutral sustainability rhetoric to a more explicit policy framework focusing on industrial localization, charging infrastructure growth, renewable energy integration, and regulatory development after 2020. Despite these advances, gaps remain in governance coordination, market readiness, charging accessibility, and user adoption incentives. The paper provides a systematically mapped view of Saudi Arabia’s e-mobility policy landscape and places it within global transition trends. The findings offer practical insights for policymakers aiming to strengthen implementation, accelerate adoption, and align transport electrification with national decarbonization goals. Full article