Digital Commons Network^™

The Day You Begin: A Case Study Of Culturally Responsive Pedagogy In Early Childhood Classrooms, Kim Shelton

Dissertations

Culturally responsive pedagogy (CRP) has garnered growing attention in early childhood education due to its potential to cultivate inclusive and equitable learning environments for increasingly diverse student populations. This qualitative case study examines how early childhood educators perceive and implement CRP in classrooms with high concentrations of immigrant and culturally diverse students. Additionally, it explores the perceived impact of these practices on instructional effectiveness, classroom climate, and teacher-student interactions.

Data was collected through semi-structured interviews, classroom observations, and document analysis. Thematic analysis yielded four central findings: (1) teachers’ understandings of CRP varied considerably, with some demonstrating strong intentionality and others …

Social Media And The Effect On Student Engagement, Lara Mcelveen

Dissertations

The purpose of my study was to determine the impact of social media on student engagement and behaviors in high school classrooms. The overarching research question that guided my study was: What is the impact of social media on student engagement? I used a mixed methods approach of quantitative and qualitative data to research my topic. I collected the data using surveys of two stakeholder groups in the study: young adults and educators. The survey results showed that both educators and young adults perceived a decline in class engagement and the rise of behavior in the classroom from social media …

The Premature Loss Of The Black Male And Its Implications On The Black Family System And Community: A Proposed 12-Step Grief Support Group Model, Alicia Smith

Dissertations

Premature deaths, ages 15–44, and loss of Black males through homicide, along with suicide and systemic violence, and incarceration, create lifelong emotional and psychological trauma for those who remain behind in Black family settings and society. U.S. social injustices against Black communities and multigenerational losses and racial harm create specific population-based challenges, such as questioning care, lack of accessibility to competent resources, and Black identity issues, which traditional grief recovery programs struggle to help adequately. Even though approaches such as cognitive-behavioral therapy, complicated grief treatment, present-centered therapy, trauma-focused therapy, including eye movement desensitization and reprocessing (EMDR) therapy, and forgiveness therapy …

Through The Wire: Examining The Experiences Of Formerly Incarcerated Students In Prison Education Programs And The Wraparound Services Needed To Support Their Success, Isabel Castro

Dissertations

This qualitative study examines the experiences of formerly incarcerated individuals in Prison Education Programs (PEPs) and the wraparound services necessary to support their success. Through Schlossberg’s Transition Theory, this study explores how incarcerated students navigate educational transitions and how educators facilitate transformative learning. Using case study and narrative inquiry, interviews were conducted with fifteen formerly incarcerated PEP participants and seven educators.

Thematic analysis revealed six major themes: Access to Education in Carceral Settings, the Impact of Education on Incarcerated Individuals, Wraparound Services and Student Support, Experiences of Formerly Incarcerated Students, the Role of Educators and Program Facilitators, and Best Practices …

Seen And Heard: A Visual Testimony Of Purity Culture Using Qualitative Photovoice Methodology, Amanda Brown

Dissertations

Purity culture, rooted in Christian teachings, has profoundly shaped individuals’ identities, relationships, and perceptions of sexuality, gender, and faith. While popular culture is talking about the effects of purity culture, scholarly literature is lacking. This study employed photovoice methodology to center the voices of those who grew up in purity culture, using photography and personal narratives to explore its long-term effects. The study focused on how individuals who have experienced purity culture articulate and visualize their stories, revealing nuanced insights across seven thematic domains: gender expectations, romantic relationships, faith, mental health, identity formation, sex and sexuality, and healing and …

The Correlation Between Depression And Gendered Racism Among Black Women, Charmagne M. King

Dissertations

Black women face unique challenges related to intersecting racial and gender-based discrimination, often referred to as gendered racism. Previous research has indicated this form of oppression may significantly affect mental health, particularly depression. However, few studies have examined how gendered racism interacts with racial identity and demographic factors (e.g., age, marital status, geographical location) to predict depressive symptoms. Using a sample of 164 self-identified Black women, this study investigated the correlational relationship between gendered racism and depression among Black women and examined how gendered racism, racial identity, and key covariates (age, marital status, and geographical location) predict depressive symptomatology. The …

Uncovering Best Practices For Professional Learning: A Focus On Dialogic Discourse, Belinda Jaquez

Dissertations

The education system rests in a paradox with an ever-changing world and classrooms frozen in time. Though technological advancements, societal changes, and policy reforms are continuously reshaping the world, classrooms have remained anchored in traditional teaching and learning practices. This study examined the relationship between professional learning programs and the quality of classroom instruction with a focus on implementing more collaborative and dialogic approaches to both student and professional learning. This research involved a multifaceted program evaluation of the learning environment centered on the learning experiences of both students and teachers. A utilization-focused evaluation approach was implemented to ensure the …

Identifying Success Characteristics Of First-Generation College Students: A Framework For Early Intervention In K-12 Education., Christopher Harmon

Dissertations

This dissertation examines how K–12 educators can better support first-generation college students by identifying the characteristics that promote success and developing early interventions using Wagner et al.’s (2006) 4 C’s model: Competencies, Conditions, Culture, and Context. Guided by Michael Quinn Patton’s Utilization-Focused Evaluation (UFE), it closely investigates how factors such as family background, academic preparation, finances, and social support shape first-generation students’ capacity to persist and excel in college. The research draws on interviews with first-generation doctoral students, offering a detailed, first-hand account of their educational journeys from early schooling through advanced degrees. Notably, the findings highlight the importance of …

An Assessment Of Youth Perceptions Of Youth Employment Initiatives And Attachment To Community As Determinants Of Migration Decisions Among The Youth In Keta Municipality Of Ghana, Fortune S. Zaglago

Dissertations

Youth migration from rural to urban areas in Ghana, particularly to cities like Accra, Tema, Kumasi, and Takoradi continues to rise, despite ongoing efforts to improve youth employability and reduce urban influx. This study examined the extent to which youth attachment to community and participation in employment initiatives predict migration intentions. Guided by the network, sense of community, neoclassical, and empowerment theories, the research employed a mixed-method correlational design. Data was collected from 249 participants, including 109 youth employment initiative participants, 126 non-participants, and 10 agency staff through surveys, as well as interviews with 4 heads of agencies. Quantitative data …

Bridging The Gap: Exploring The Intersection Of Formal Mental Health Services And Informal Social Supports In Bipoc Communities, Patrice D. Patton-Campbell

Dissertations

Despite growing awareness of mental health disparities, BIPOC (Black, Indigenous, and People of Color) communities continue to face significant barriers in accessing culturally responsive mental health care. This dissertation explores the intersection between formal mental health services and informal social supports such as family, religious institutions, and community networks to understand which systems are more trusted, accessible, and effective for BIPOC individuals. Grounded in Urban Liberation Psychology and guided by decolonial and culturally responsive care frameworks, this qualitative study draws from focus groups and interviews with 33 participants, including both community members and service providers from the Chicagoland area and …

Narratives Of Jewish American Public School Educators Amid Rising Antisemitism Post October 7, 2023, Cassandra Schwartz

Dissertations

This study investigated how Jewish American public school educators are responding to rising antisemitism post-October 7, 2023. While research exists on global antisemitism, the experiences of Jewish educators within the unique context of American public schools represent a significant and under-explored gap in academic literature. A qualitative narrative research approach, grounded in critical theory, was employed. Data were collected through semi-structured interviews with eight Jewish American public school educators and analyzed thematically. The findings revealed participants’ experiences of a heightened sense of fear and silence from colleagues and institutions, leading to feelings of isolation and being unsupported. Critically, this study …

The Rose That Grew From Concrete: Exploring The Romantic Experiences Of Black Men With Histories Of Childhood Sexual Abuse, Tatyana Nichelle Smith

Dissertations

Contemporary research typically characterizes Black heterosexual relationships by dismal marriage and divorce rates, largely ignoring the reality of how Black men develop attachments with their romantic partners and therefore continuing to perpetuate deficit perspectives of Black men (e.g., the cause of conflictual romantic relationships and “broken” Black families). What may be less understood about these relationships is the influence of childhood trauma, such as childhood sexual abuse, and Black men’s experiences of gender role conflict. Research shows that Black men’s experiences of childhood sexual abuse and socialization about masculinity have important implications for how they come to view themselves and …

Design And Development Of Hip Implants For Longevity Through Integrating Advanced Groove Structures And Additive Manufacturing, Asarudheen Abdudeen

Dissertations

This doctoral research concerns the design and optimization of hip implants (HIs) to enhance performance, durability, and improve patient outcomes by addressing the key issues of wear, deformation, and stress distribution. Innovative surface groove designs have been introduced to both a solid and a hollow femoral head with the aim of reducing friction and wear. The addition of grooves, with both a hemispherical and rectangular cross-section, onto the femoral head reduced friction, as debris produced by the inner liner was trapped within the grooves, significantly reducing adhesive wear. A numerical simulation study compared the effects of surface modifications both grooves …

Comparative Genotoxicological Analysis Of Occupational Pesticide Exposures: An Experimental Approach And Systematic Review, Moustafa Samy Sherif

Dissertations

This dissertation investigates the genotoxic and cytotoxic effects of pesticide exposure through three complementary research components: a systematic review of occupational pesticide exposure in Arab countries (AraSys), a systematic review on encapsulated versus conventional pesticide formulations (Encap-Sys), and experimental toxicological assessments of various pesticide formulations in human cell lines (Pyr-Ex). This experimental component includes cytotoxicity assays using propidium iodide and DNA damage assessments via alkaline comet assays in HL60 and HepG2 cell lines exposed to pyrethroid insecticides and glyphosate-based formulations.

The AraSys systematic review revealed a critical positive association between occupational pesticide exposure and DNA damage in agricultural workers in …

Experimental And Computational Study Of Slow Crack Growth Of High Density Polyethylene, Abdulla Fawzi Almomani

Dissertations

This dissertation investigates the slow crack growth (SCG) behavior of High-Density Polyethylene (HDPE) under various mechanical and environmental conditions. The study combines experimental analysis and computational modeling to enhance the understanding of SCG mechanisms in HDPE, particularly in pressurized pipes and under the exposure to hydrocarbons. A novel Crack Layer (CL) theory-based SCG model is developed and validated through experimental data, offering a predictive framework for HDPE failure assessment. The main objective of this dissertation is to quantify and model the viscoelastic-viscoplastic behavior of HDPE under monotonic and cyclic loading conditions while addressing SCG kinetics in structural applications. The study …

Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz

Dissertations

Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.

Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …

Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli

Dissertations

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder, characterized by developmentally inappropriate levels of inattention, hyperactivity, and impulsivity. Children with family history of ADHD are at an elevated risk of having ADHD as well as a higher risk of persistent ADHD into adulthood, reflecting a source of etiological heterogeneity in ADHD. This heterogeneity in terms of both biological and environmental risk factors may explain differences in neural correlates, outcomes, cognitive, behavioral as well as developmental trajectories. It is therefore critical to understand the influence of having, or not having positive family risk factors on the neuroanatomical structures of the …

On The Design Of A Framework For Large-Scale Exploratory Graph Analytics, Oliver Andres Alvarado Rodriguez

Dissertations

Large-scale exploratory graph analytics merges data science with high-performance computing to extract critical insights from network-representable data. Data scientists routinely analyze data from the natural, social, and computing sciences by representing it as networks, or graphs, where objects become vertices and their relationships become edges. This representation allows data scientists to add graph analytics to their toolbox. However, designing tools for large-scale exploratory graph analytics is challenging due to the complexities of graph algorithms, such as high communication in distributed systems and large memory demands. These challenges can lead to overly complex software, which limits usability and development to a …

Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku

Dissertations

This dissertation presents a series of innovative machine learning and optimization model designs that address complex operational challenges across logistics and power systems. By integrating advanced neural architectures with robust optimization techniques, the work delivers scalable solutions designed to improve efficiency, reliability, and decision-making in dynamic and real-world environments. The first study introduces a two-stage approach to effective vaccine distribution. This framework tackles the capacitated vehicle routing problem by combining adaptive clustering techniques with reinforcement learning and a simulated annealing pickup policy. Through extensive computational experiments, the approach demonstrates substantial improvements in routing efficiency, reducing both computational time and logistical …

Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan

Dissertations

This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.

The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

The Role Of Excitatory Neuromodulation In Managing Variability Of Neural System Output, Omar Itani

Dissertations

Neural systems can generate consistent outputs across a population despite substantial variability in the underlying components of individuals. This dissertation aims to identify mechanisms through which neuromodulation influences the relationship between parametric and output variability in neural systems. Through a combination of theoretical analysis, computational modeling, and data-driven approaches, the research addresses how excitatory neuromodulation can shape population-level activity variability and identifies key patterns that govern the production of consistent neural population output despite underlying parameter variability.

The theoretical foundation is established by considering how excitatory neuromodulation affects population variability in simplified neuronal models. Two fundamental patterns of variability reduction …

Modulation Of Cerebellar Cells By Transcranial Ac Stimulation In Anesthetized Rats, Qi Kang

Dissertations

Noninvasive brain stimulation (NIBS) is increasingly utilized in clinical trials for the treatment of neurological disorders. Each NIBS technique offers distinct advantages. Transcranial electrical stimulation (tES) is easy to apply and requires only simple equipment, while transcranial magnetic stimulation (TMS) can penetrate deeper than tES into the brain and it is more focal. Transcranial focused ultrasound stimulation (FUS) is superior to both in terms of penetration and focal stimulation. This study focuses on the modulation of the cerebellum, traditionally believed to be associated with motor coordination but increasingly recognized for its role in cognition and emotion as well. While tES …

Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal

Dissertations

Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …

An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock

Dissertations

Flocculation and clarification are two essential processes to deliver safe water at a reasonable cost to consumers. There are two major thrusts to the research presented in this dissertation. The first is to better characterize the physics and mixing parameters used for the design of hydraulic flocculators in the context of drinking water treatment plants. The second major thrust is to investigate floc filtration as a mechanism for the removal of primary particles during floc blanket clarification.

The intensity of mixing in environmental and chemical engineering applications is often characterized by the Camp and Stein velocity gradient. This parameter has …

Fact-Checking As A Multi-Step Process: From Ambiguity Resolution To Claim Validation, Wenbo Wang

Dissertations

The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. Fact-checking—the process of verifying claims against credible evidence—has emerged as a critical safeguard against misinformation. Yet, the task is fraught with challenges: claims are often ambiguous, context-dependent, or composed of multiple intertwined assertions, while automated systems struggle to replicate the nuanced reasoning of human experts. This dissertation addresses these challenges by reimagining fact-checking as a multi-step, knowledge-guided process that systematically resolves ambiguity, decomposes complexity, and validates claims through structured reasoning. Additionally, the proposed …

Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado

Dissertations

Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.

MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …

Enriching Vision Representation By Deep Neural Networks And Self-Supervised Learning, Yucong Shen

Dissertations

Nowadays, more and more interesting computer vision tasks are tackled by deep learning approaches. However, the increasing model complexity imposes significant computational and storage costs. To address this challenge, this dissertation explores efficient deep learning techniques, proposing morphological layer, an efficient feature extraction layer. It achieves competitive image classification accuracy with significantly decreased model parameters. Another attempt at efficient deep learning is a proposed channel pruning approach that compresses deep neural networks by identifying and removing redundant channels using optimal transport theory. This approach achieves significant reductions in model size and computational cost while maintaining or even improving performance across …

From Neural Networks To Large Language Models: Innovations In Financial Ai, Mathematical Reasoning, And Structured Data Representation, Junyi Ye

Dissertations

This dissertation explores the evolution and application of artificial intelligence techniques across three critical domains: financial modeling, mathematical reasoning, and structured data analysis. The dissertation presents seven research projects that chart a progression from specialized neural architectures to sophisticated large language models (LLMs), contributing novel methodologies and frameworks at each stage.

In the financial domain, the research first introduces TS-Mixer, a MLP-based architecture for time-series forecasting that captures both feature relationships and temporal dependencies through a simple yet effective design, outperforming more complex models in S&P500 index prediction. The dissertation then presents DySTAGE, a dynamic graph representation learning framework that …

Towards Explainable Ai On Graph Neural Networks: Xaig, Jiaxing Zhang

Dissertations

In the evolving landscape of artificial intelligence (AI), Graph Neural Networks (GNNs) have garnered growing prominence for their adeptness in processing graph-structured data. Despite this, the interpretability of their predictions often remains elusive. The demand for transparency and explainability in complex prediction models has reached unprecedented levels. To address this, post-hoc instance-level explanation techniques have emerged, aiming to unveil the rationale behind GNN predictions. These techniques endeavor to unearth substructures that elucidate the predictive behavior of trained GNNs.

This dissertation embarks on an exploration of Explainable AI (XAI) technologies within the realm of GNNs. Amid the challenges posed by the …