SACM - United States of America
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668
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Item Restricted EXAMINING READING-RELATED TEACHER EDUCATION AMONG GENERAL EDUCATION TEACHERS OF PRIMARY SCHOOL STUDENTS WITH LEARNING DISABILITIES IN TAIF, SAUDI ARABIA(Saudi Digital Library, 2026) Alqrashi, Ahmad; Hosp, JohnThe education system of Saudi Arabia has made significant advances in expanding access to its general education through policies of inclusion, particularly through initiatives aligned with Vision 2030. In spite of these advances, the system still lacks an effective support structure for students with learning disabilities (LD) in general education classrooms, especially at the primary school level. Research on inclusive education indicates that teachers’ preparedness, encompassing their knowledge of evidence-based reading strategies, awareness of students’ needs, and capacity to implement appropriate strategies, directly enhances the academic outcomes of students with LD. In this study, the researcher investigated three central questions: 1. What professional development in reading do Saudi general education teachers of students with LD in primary schools report having undertaken? 2.) To what extent do Saudi general education teachers' university training and professional development in reading instruction relate to their implementation of evidence-based practices for students with LD in inclusive primary classrooms? and 3.) What are the perceptions of Saudi general education teachers toward evidence-based reading instruction for students with LD? To address these questions, a mixed-methods approach was employed, including a survey of 98 general education teachers in Taif and semi-structured interviews with six teachers from the same region. Quantitative analysis indicated that teachers received significantly more training in general reading than in LD-specific instruction, and that formal training did not predict the use of evidence-based strategies. Qualitative findings revealed that while teachers held positive perceptions of evidence-based reading strategies, structural barriers such as large class sizes, limited instructional time, and insufficient collaboration with special education professionals severely constrained implementation. The study concludes that there are both knowledge and application gaps between the Saudi inclusive education policy and classroom practice. To realise the goals of Vision 2030, urgent reforms are needed in teacher preparation, mandatory professional development, and classroom resource allocation.20 0Item Embargo Optimizing Aerosol Therapy During Noninvasive Ventilation in Pediatric Patients: A Narrative Review(Saudi Digital Library, 2025) AlKhiry, Ali; Goodfellow, Lynda TTitle: Optimizing Aerosol Therapy During Noninvasive Ventilation in Pediatric Patients: A Narrative Review Background: Noninvasive ventilation (NIV) is widely used in pediatric respiratory care, often in conjunction with aerosolized medications. However, the effectiveness of aerosol delivery in children remains uncertain due to anatomical, physiological, and behavioral complexities unique to this population. Objective: To systematically evaluate the influence of interface type, circuit configuration, and nebulizer placement on the effectiveness of aerosol therapy in pediatric patients receiving NIV. Methods: A comprehensive literature search was conducted in PubMed, Embase, and CINAHL using standardized indexing terms. A total of 328 records were screened, with 11 studies meeting inclusion criteria for qualitative synthesis. Studies were selected based on relevance to pediatric populations using NIV and reporting measurable clinical outcomes such as lung deposition, symptom improvement, adverse events, and hospital length of stay. Results: Oronasal masks were found to yield significantly higher pulmonary drug deposition (up to 30%) compared to nasal cannulas (1–6%). Dual-limb ventilator circuits outperformed single-limb setups in minimizing aerosol loss. Optimal nebulizer placement between the exhalation valve and patient was critical for maximizing drug delivery. Clinical outcomes associated with optimized aerosol therapy included reduced respiratory distress, shortened duration of respiratory support, lower intubation rates, and decreased hospital stays. Adverse events were rare but included skin and eye irritation when masks were poorly fitted. Conclusion: The effectiveness of aerosol therapy during pediatric NIV is closely linked to the selection of interface, ventilator circuit design, and nebulizer positioning. Evidence consistently supports the use of oronasal masks and dual-limb circuits, when tolerated by the patient, as these configurations maximize pulmonary drug deposition and clinical efficacy. Proper placement of the nebulizer, ideally between the exhalation valve and the patient, further enhances drug delivery. These adjustments not only improve therapeutic outcomes such as reduced respiratory distress and shorter hospital stays but also minimize the need for invasive ventilation and associated complications. Importantly, optimizing aerosol therapy in this context demands a patient-centered approach that balances drug delivery efficiency with comfort and tolerance. These findings offer a practical and evidence-based framework for clinicians seeking to refine aerosol administration strategies in pediatric NIV, ultimately contributing to safer, more effective, and personalized respiratory care. Keywords: Pediatric, NIV, aerosol delivery, nebulizer interface, lung deposition, respiratory therapy, noninvasive ventilation27 0Item Restricted USING MACHINE LEARNING TO PREDICT OPTICAL PROPERTIES OF MOLECULES(Saudi Digital Library, 2026) Alotaibi, Maha; Clayborne, AndreUnderstanding and predicting optical properties at the molecular scale is essential for the development of functional materials in fields such as photovoltaics, sensing, and molecular electronics. Several approaches have been developed to model these properties, ranging from traditional quantum mechanical simulations to emerging datadriven techniques. Traditional quantum chemical methods, such as time-dependent density functional theory (TD-DFT), are known for their high computational demands. This dissertation focuses on using machine learning (ML) to predict optical spectra for molecular systems and potentially reduce the computational cost for calculations. Two sets of molecules were used as testbeds for the machine learning workflow: 1) Organic Molecules from the QM8 database and 2) Metalloporphyrins. Initially, a dataset of small organic molecules was used to train and evaluate machine learning models for the prediction of UV-Vis profile. Two regression algorithms, Kernel Ridge Regression (KRR) and Random Forest (RF), were applied using molecular descriptors generated xv with RDKit. These models were trained and validated on optical property data obtained from quantum chemical calculations using TD-DFT. To further validate the ML models, additional DFT-data was collected for metalloporphyrins. This included information about the geometry, electronic properties, and optical spectra of metalloporphyrins that included first and second row transition metals with varying anchoring groups. The relatively small dataset for the optical properties of metalloporphyrins introduced challenges to the ML model. This research highlights importance of structure and composition on optical properties and how machine learning can provide insight into the optical properties and ultimately molecular design principles for specific applications.5 0Item Restricted Essays on Audit Committee Chair Characteristics, Cybersecurity Risk Disclosure, and ESG Disclosure Scores(Saudi Digital Library, 2025) Alanazi, Musharraf; Thiruvadi, SheelaIn recent years, environmental, social, and governance (ESG) considerations have shifted from peripheral concerns to central pillars of corporate governance and reporting. Growing attention to climate risks, sustainability practices, and corporate responsibility has led regulators, investors, and civil society to demand high-quality and comparable ESG information. Audit committees are emerging as key players in this process because their oversight of financial reporting, risk management, and internal controls increasingly intersects with ESG responsibilities. This role has been reinforced by evolving regulatory frameworks such as the EU Corporate Sustainability Reporting Directive and the SEC's climate and cybersecurity disclosure rules. However, despite the rising importance of disclosure, limited evidence exists on how the personal and professional traits of audit committee chairs influence transparency in ESG and cybersecurity reporting. The first essay examines the relationship between audit committee chair characteristics, namely, gender, age, CPA qualification, and prior auditor experience, and ESG disclosure scores, utilizing panel data from S&P 500 firms between 2015 and 2023. Results from ordinary least squares (OLS) regressions show that female chairs are strongly associated with higher ESG disclosure scores, particularly in environmental and social dimensions, while chair age is negatively related to ESG outcomes. CPA credentials have no consistent effect, and prior auditor experience is modestly associated with the level of governance disclosure. Interaction results reveal that younger female chairs drive the strongest ESG disclosure score and that combining gender diversity with prior audit experience further enhances transparency. The second essay examines cybersecurity risk disclosure, employing logistic regression on the same dataset. Findings indicate that demographic traits such as gender, age, and CPA credentials are not significant predictors, while prior auditor experience improves disclosure quality, highlighting the value of technical expertise in addressing IT risks. Firm-level factors also matter: profitability (ROA) is negatively associated with disclosure, while larger firms are more likely to report, reflecting heightened regulatory and investor pressures. This study makes significant contributions to the accounting, auditing, and sustainability literature in several ways. First, it fills an important gap, as no prior research has jointly examined how audit committee chair characteristics influence both ESG disclosure score and cybersecurity risk disclosure. Second, the findings provide new evidence that demographic and professional traits, such as gender, age, and prior audit experience, affect disclosure outcomes, with notable effects on ESG transparency. Third, the study applies Upper Echelons Theory to explain how leadership diversity and experience shape ESG reporting, while highlighting the role of evolving regulatory frameworks in driving cybersecurity disclosure. Together, these insights offer practical implications for boards, regulators, policymakers, and investors seeking to strengthen corporate transparency and accountability. Keywords: Corporate Governance; Audit Committee Chair; ESG disclosure score; Cybersecurity Risk Disclosure; Gender Diversity; CPA Qualification; Prior Auditor Experience25 0Item Restricted THE INFLUENCE OF ENTREPRENEURIAL ORIENTATION ON SMEs' DEGREE OF INTERNATIONALIZATION: THE MODERATING ROLE OF GOVERNMENT SUPPORT AND DIGITAL TRANSFORMATION(Saudi Digital Library, 2025) Aljadani, Rayan; Omar, J. KhanThe internationalization of small and medium enterprises has become an urgent direction of development today. Internationalization is an entrepreneurial act of identifying and exploiting international opportunities. As markets have increasingly globalized, entrepreneurial orientation has gained momentum in international entrepreneurship. While entrepreneurial orientation is extensively studied for its role in cross-border entry for large multinational corporations, little research has examined its use in international performance for small and medium enterprises. This dissertation investigates the influence of entrepreneurial orientation on small and medium enterprises' degree of internationalization, the mediating effect of networking capability, and the moderating role of government support and digital transformation. This dissertation draws on the dynamic capabilities theory to examine the influence of these factors on degree of internationalization. A company's capabilities are the configurations of routines and resources that allow it to have competitive advantage. A questionnaire survey was used to collect the data for this dissertation from 296 Saudi small and medium enterprises. The results shown a significant relationship between entrepreneurial orientation and small and medium enterprises' degree of internationalization. The results also found that networking capability mediates entrepreneurial orientation and small and medium enterprises' degree of internationalization. Finally, the results also show that government support and digital transformation moderate the relationship between entrepreneurial orientation and degree of internationalization. This dissertation contributes to the literature on international entrepreneurship by identifying new empirical indication. Moreover, it contributes to executive practices by showing the significance of translating entrepreneurial orientation practices into internationalization outcomes through networking capability.11 0Item Restricted Strategies for Enhancing Creativity in the Classroom(Saudi Digital Library, 2020) AlKhamis, Arwa Mohammed; Kathy, HooverThe purpose of this study was to investigate the strategies of enhancing creativity in the classroom and teaching strategies. The study involved 9 participants in total; all participants were teachers. The research relied on random sampling to select the study participants. The researcher used the observation sheets to gather data from the study participants. The study employed qualitative data analysis methods to synthesize the data collected from the study respondents. The collected data from respondents during the study were analyzed in tabular form, while tables were also be used to draw patterns on responses provided. Data was coded and specific themes were identified, which include classroom participation, active strategies, inhibitors of creativity, internet creativity and creativity tools. The researcher found that this study highlights that collaboration can be a very useful strategy to enhance creativity in the classroom. The researcher noted that asking open-ended and random questions keep the learners engaged in the class activities. The researcher also observed that the Internet proved to be a great avenue for the young children, because a range of learning opportunities available on the internet can increase children’s problem solving abilities, and critical thinking skills, which enhances creativity. The strategies discussed in this research are all proven to be effective in making early childhood education a better and improved experience. the researcher is planning to continue with further research and explore more about the field of enhancing creativity in the classroom.13 0Item Restricted DYNAMIC GRAPH NEURAL NETWORK FRAMEWORK FOR REAL-TIME MULTI-MODAL DATA ANALYSIS AND PREDICTIVE MODELING(Saudi Digital Library, 2025) Almousa, Ghadah; Lee, YugyungIn recent years, Graph Neural Networks (GNNs) have become increasingly prominent for analyzing complex, interconnected data across fields such as transportation, social networks, and cybersecurity. Despite their advancements, many existing GNN models struggle to capture the intricate interactions among temporal, spatial, and domain-specific knowledge, particularly as these factors evolve dynamically, while also accounting for the complexities of multi-modal data in real-time, with current GNN architectures often falling short in leveraging cross-modal correlations. We present a novel Dynamic Graph Neural Networks (DGNNs) Framework that integrates Partial Differential Equations (PDEs), temporal-spatial modeling, and domain-specific knowledge to address these gaps. By enabling real-time processing of multi-modal data, this framework bridges real-world dynamic systems with the evolving landscape of AI and machine learning applications. This interdisciplinary approach uniquely advances AI, machine learning, and big data analytics by harmonizing spatial-temporal dynamics, domain customization, and multi-modality integration in a cohesive framework. GNNs have become essential tools for analyzing complex, interconnected data in domains such as transportation, social networks, and cybersecurity. However, current GNN models often struggle to effectively capture the dynamic interactions of temporal, spatial, and domain-specific knowledge, especially when processing multi-modal data in real time. This dissertation presents the development of a DGNNs Framework designed to overcome these challenges, illustrated through extensive use cases. For instance, in traffic prediction, experiments using datasets such as Performance Measurement System Bay Area (PEMS-BAY), Metropolitan Traffic Los Angeles (METR-LA), and other PeMS Performance Measurement System datasets demonstrate the framework’s superior performance in prediction accuracy and robustness, effectively managing real-world data variability and spatial-temporal dependencies. Additionally, the framework efficiently models inter-variable dependencies in Multivariate Time Series (MTS) forecasting in domains such as energy, weather, and environmental monitoring, achieving stable long-horizon predictions through its PDE-enhanced graph structure. Ultimately, the framework’s capabilities extend to social media analysis for misinformation detection and rumor spread pattern discovery, with superior classification results on datasets like Pheme, Twitter15, Twitter16, and WEIBO. These examples showcase how the framework uncovers evolving patterns across platforms by processing multi-modal data inputs such as17 0Item Restricted EXAMINING THE EFFECTS OF VIDEO MODELING TO ENHANCE CULTURALLY SPECIFIC SOCIAL GREETING SKILLS IN PRESCHOOLERS WITH ASD IN SAUDI ARABIA(Saudi Digital Library, 2025) Alzahrani, Sarah; Green, BridgetA lack of social communication skills, including initiation and responding, has been a prominent characteristic of children diagnosed with ASD (Kanner, 1943; Kroeger et al., 2007). Enhancing these skills in children with ASD during early childhood is crucial to their future relationships, friendships, participation in communal activities, and overall lowering the likelihood of adverse long-term effects, giving significance to this age as a pivotal period for enhancing various skills (Hart Barnett, 2018). Failure to provide interventions to address social communication in children with ASD, specifically in cultures that value this skill, can impede their integration into that society. Thus, this study aimed to develop social initiation, particularly culturally specific greetings, and responding skills in preschool children with ASD in Saudi Arabia by using a video modeling intervention with least-to-most prompting and reinforcement. Three preschool children with ASD participated in the study. A multiple baseline design across participants was used to evaluate the effectiveness of the video modeling intervention on the two targeted social behaviors: initiating a cultural religious greeting and responding to “How are you?”. The result of the study demonstrated that VM, along with prompting and reinforcement, is an effective intervention in enhancing social outcomes in young children with ASD. Maintenance data also indicated that all the participants were able to maintain the skills acquired two weeks after the intervention. The results of this study align with previous research in supporting the use of VM and prompting procedures as effective interventions in enhancing the social outcomes of young children with ASD.13 0Item Restricted Development and validation of wearable devices for real-time sweat biochemical sensing(Saudi Digital Library, 2025) Addokhi, Abdurrahman; James, GalaganWearable devices have made significant advances in the real-time, continuous monitoring of human physiology, offering higher sampling frequencies for rapidly changing physiological signals than currently achievable through conventional clinical methods. However, nearly all commercially available wearable devices are limited to measuring biophysical parameters, such as heart rate and activity, using electrical, mechanical, or optical sensors. In contrast, medical diagnostics for small-molecule biomarkers typically rely on invasive blood sampling and instrumentation that is costly, complex, and unsuitable for point-of-care or wearable use. Electrochemical biosensors have emerged as a powerful transduction modality for portable biochemical sensing, exemplified by the clinical success of continuous glucose monitors. Yet, there remains a critical need for noninvasive wearable biochemical sensing platforms. Sweat is a promising biofluid in this context, containing a wide array of physiologically relevant biomarkers including ions, amino acids, metabolites, hormones, peptides, and proteins. Sweat can also be accessed noninvasively and stimulated locally on demand via iontophoresis. This dissertation presents the design, development, and on-body validation of wearable sweat-sensing devices. Two distinct device architectures are demonstrated, reflecting different levels of complexity and design considerations. We report real-time, on-body lactate sensing during stationary cycling exercise, as well as successful detection of nicotine in sweat using a novel microbial redox enzyme-based biosensor. Sweat was locally induced for nicotine sensing, and study participants included heavy and light nicotine users as well as non-users. The wearable nicotine sensor exhibited superior analytical accuracy compared to the gold standard of mass spectrometry. Furthermore, we demonstrate multiplexed sensing targeting both nicotine and cortisol in sweat using a single wearable platform. Finally, we explore the use of electrochemical impedance spectroscopy as a system identification tool for the development and optimization of biosensors.22 0Item Restricted From Religious Legitimacy to Cultural Nationhood: How Vision 2030 Coordinates the Reconstruction of Saudi Identity Through Heritage, Architecture, and the Creative Economy(Saudi Digital Library, 2025) Alotaibi, Layla; Acikgoz, GizemThis thesis examines how Saudi Arabia deploys culture as a strategic instrument of governance, identity construction, and soft power under Vision 2030. It addresses a gap in existing scholarship that often treats cultural reform as symbolic or externally oriented, rather than as a tightly coordinated state project entrenched within institutional systems. The central argument is that Vision 2030 represents a shift in Saudi legitimacy. This shift is from an overwhelming reliance on religious authority toward a diversified cultural and nationalist framework that operates domestically and internationally. Methodologically, the thesis employs qualitative analysis of policy documents, institutional structures, cultural initiatives, along with case studies on AlUla, the Saudi Architecture Characters Map Initiative, and the creative economy industry. The findings demonstrate that Saudi cultural governance is highly centralized and deliberate, shaping national identity through curated heritage narratives, spatial and aesthetic regulation, and institutionalized cultural production. The thesis concludes that culture under Vision 2030 functions as a form of symbolic governance, revealing both the generative power and selective limits of state-led cultural transformation.49 0