The National University System Repository exists to increase public access to research and other materials created by students and faculty of the affiliate institutions of National University System. Most items in the repository are open access, freely available to everyone.
Recent Submissions
Item Quantitative Exploration of AI's Impact on Financial Cybersecurity: Trends, Data Privacy, and Human Expertise(2026-03)The integration of artificial intelligence (AI) into financial cybersecurity has introduced both significant opportunities and complex challenges, particularly in relation to regulatory compliance, data privacy, and human–AI collaboration. This quantitative, non-experimental correlational study examined the extent to which key innovation attributes, compatibility, complexity, and relative advantage, impact the adoption and effectiveness of AI-driven cybersecurity technologies within U.S. financial institutions. Grounded in the Technology Acceptance Model (TAM) and Diffusion of Innovations (DOI) theory, the study explored relationships between these independent variables and institutional outcomes, including system performance, adaptability, human–AI collaboration, and regulatory compliance. Data were collected from 90 cybersecurity professionals, IT managers, and compliance officers using a structured Likert-scale survey administered via Qualtrics. Statistical analysis was conducted using exploratory factor analysis (EFA) and multivariate analysis of variance (MANOVA), with Pillai’s Trace employed due to assumption violations. Results indicated that relative advantage had a statistically significant impact on institutional outcomes, while compatibility and complexity did not demonstrate significant independent effects. However, the combined model of all three variables produced a significant multivariate effect, highlighting the importance of integrated adoption strategies. The findings contribute to existing literature by emphasizing the critical role of perceived value and holistic implementation approaches in AI adoption within highly regulated financial environments. Practical implications include the need for financial institutions to prioritize strategic alignment, workforce integration, and governance frameworks when deploying AI-driven cybersecurity solutions.Item The Role of Quality Management in Enhancing Stakeholder Engagement and Operational Effectiveness in Nonprofit Organizations(2026-04)This study examined how irregularities in organizational processes within large United States–based health and human services nonprofit organizations, particularly those engaged in fundraising, influence stakeholder engagement and operational effectiveness. The problem addressed is that irregularities in governance, accountability, and transparency may undermine stakeholder trust and operational performance, affecting donors, organizational leaders, and the communities served by these organizations. The purpose of this qualitative descriptive study was to explore how these process irregularities shape stakeholder engagement and operational effectiveness in fundraising-driven nonprofit environments. The study was guided by a conceptual framework integrating quality management, stakeholder theory, and contingency theory to examine how governance credibility, operational reliability, and organizational readiness interact in practice. A qualitative descriptive design was used to capture real-world stakeholder experiences and organizational conditions. Data were collected through open-ended survey responses and archival analysis of publicly available organizational records. A purposive sample included internal stakeholders such as executives and fundraising leaders, and external stakeholders such as donors and volunteers. Data were analyzed using thematic analysis, with triangulation across survey and archival sources to strengthen credibility and interpretive alignment. Findings supported the three research questions. Research question one, irregularities in donor-facing communication and operational transparency were associated with reduced stakeholder trust and engagement, indicating that the reliability of routine processes strongly influences trust. Research question two: structured and incremental quality management practices were perceived as improving coordination, reducing rework, and strengthening operational predictability without requiring a comprehensive organization-wide implementation. For the third, implementation challenges were consistently linked to staffing constraints, workload imbalance, limited training capacity, and technology barriers, indicating that readiness and capacity alignment are central conditions for sustainable improvement. The study's findings suggested that stakeholder trust was associated with consistent operational performance, governance oversight, capacity-aligned quality practices, and readiness-based implementation. Recommendations emphasize strengthening operational transparency in donor-facing processes, embedding trust-related indicators into oversight routines, adopting incremental quality practices aligned with capacity, and conducting readiness assessments before primary process or technology changes. Future research should extend these findings through longitudinal and mixed-methods designs and comparative studies across nonprofit contexts.Item Multi-Modal Features of Trading Candle Chart Imagery & Volume For Predicting Financial Market Movements, Using the Proposed BLENNs Architecture.(2026-04)Financial forecasting models face significant challenges due to reliance on single-source data and lack of transparency required by regulators, impacting institutional investors, retail traders, and regulators who need reliable and interpretable AI systems for market decisions. This study developed and evaluated the Blended Neural Networks model, known as BLENNS, a hybrid deep learning framework integrating convolutional neural networks for pattern recognition, long short-term memory networks for sequential data, attention mechanisms for feature weighting, interpretability techniques, and probabilistic uncertainty estimation. Guided by multimodal learning, signal detection, and explainable AI theories, the study investigated whether multimodal fusion improves forecasting accuracy, if the Blended Filtered Candles preprocessing method enhances noise robustness, and whether interpretability aligns with expert trading rules. Using daily financial data from 2010 to 2025 on six diverse assets with over 21,000 observations, the Blended Filtered Candles method applied a three-stage filtering process including exponential smoothing, an enhanced candle transformation, and adaptive Kalman filtering. Walk-forward validation with multiple expanding windows ensured rigorous out-of-sample testing. BLENNs achieved 97.55% directional accuracy, a 113.77% improvement over traditional models, while BFC preprocessing improved the signal-to-noise ratio by 134.8%, outperforming common smoothing techniques by large margins. Interpretability analysis showed statistically significant, though modest, agreement with expert trading principles, emphasizing the value of explainable AI combined with human oversight. Simulated and live trading demonstrated strong returns and win rates, with live performance reflecting realistic trading costs and execution factors. This framework offers a foundation for meeting regulatory transparency requirements, though further compliance testing, extended live validation, scalability assessment, and transaction cost considerations are needed for practical deployment. The consistent noise reduction by BFC across multiple assets supports its broader application. Resources are available for further research exploring additional markets, higher-frequency data, institutional trading, adaptive parameter tuning, and establishing interpretability standards for regulation.Item The Consequences of Secondary Teachers’ Low Efficacy in Delivering Writing Instruction: A Phenomenological Study(2026-04)The problem addressed by this research study was secondary English teachers’ low efficacy in delivering writing instruction, which results in the deficient writing performance of students in Maryland public high schools. The purpose of this qualitative phenomenological study was to explore the lived experiences of secondary English teachers with low efficacy levels in delivering writing instruction. Pre-service and in-service professional development lacks adequate focus on writing instruction to prepare teachers for success in delivering the content effectively in their role. Teachers’ preparedness influences their psychological well-being and confidence to perform. The study’s final purposeful sample included seven secondary English teachers with more than 1 year of experience teaching students in grades 10 – 12. The research participants were employed in the state of Maryland at one of the three public high schools. Data was gathered through semi structured interviews and a focus group and confirmed through member checking. The three major themes that emerged from data analysis using NVivo 15 software were: (a) culture of learning, (b) strategies to deliver writing instruction, and (c) teacher preparation. Three recommendations for practice were: (a) to revisit the pre-service training for new teachers, (b) for school system leaders to provide more communal in-service training to encourage reflective conversations around writing instruction, and (c) for the leaders of school systems to develop professional learning communities centering on writing instruction delivery and student support. Recommendations for future research were to (a) add an interview question where teachers exemplify their success in delivering writing instruction, (b) delve deeper into instructional writing strategies used by successful teachers in a focus group question, (c) include student writing artifacts to show growth, and (d) include an interview question about students’ preparation for technology competency for success on online high-stakes writing assessments.Item An Exploration of General Education English language arts: reading Teachers' Knowledge and Perceptions of Tier II Response to Intervention in a North Louisiana School District(2026-04)Response to Intervention is an multitiered educational framework intended to support students who are struggling academically. Tier 1 and Tier 2 consist of interventions implemented by the general education teacher in the general education classroom. The problem addressed in this study was the lack of information regarding general education teachers’ knowledge and perceptions about the guiding principles of effective implementation of Tier 2 of Response to Intervention and resources necessary for successful student outcomes. The purpose was to explore the knowledge and perceptions of general education reading teachers in one northeast Louisiana school district regarding the effective implementation of Tier 2 of Response to Intervention. Critical theory aided in highlighting the importance of understanding power structures that influence educational teaching and outcomes. A qualitative, collective case study was conducted through interviews and document analysis. Purposive, criterion sampling was used to recruit nine general education reading teachers of first through third grade. Saldaña’s two-cycle coding method was applied for data analysis to answer the research questions aimed at gathering information on participant knowledge and perception of Tier 2 of Response to Intervention as well as resources needed to improve student learning outcomes. Five themes were revealed to answer the research questions. Participants shared their knowledge and perceptions of Tier 2 Response to Intervention and what resources they believed necessary for positive student reading outcomes. All nine teachers discussed the importance of research-based, individualized, differentiated interventions to meet each student’s specific needs, consistently monitoring progress, and utilizing data to make intervention decisions. The participants’ perceptions of Tier 2 Response to Intervention were based on the district-mandated computer program, Lexia® Core5® Reading (Lexia). They expressed concern that students with difficulty and highlighted the need for administrative support and collaboration.
Communities in National University System Repository
Select a community to browse its collections.