Digital Commons Network^™

"A Door To The Future." A Case Study In Exploratory And Culturally Sustaining Theater Curriculum, Verónica Meza

Dissertations

This study addresses the persistent inequities in access to quality arts education for Latino immigrant and linguistically diverse communities in California. Despite progressive initiatives such as Proposition 28 (The Arts and Music in Schools Act) and the California Arts Council's Racial Equity Statement, systemic barriers prevent Latino and immigrant students from benefiting equitably from the arts. The central objective of this project is to understand how an exploratory, culturally sustaining theater curriculum can serve as a transformative and healing vehicle for adult immigrant Latino students, providing emotional protection, cultural affirmation, and language preservation within a U.S. educational context. This qualitative …

An Untouched Gem: Understanding Parental Perceptions On Community College Attendance, Harshdeep Singh Nanda

Dissertations

Community colleges serve as critical entry points into higher education, yet they continue to carry stigma, particularly within affluent communities where four-year institutions are often positioned as the expected pathway. While existing research has examined student and public perceptions, little attention has been given to how parents in affluent regions shape and transmit these narratives. This study investigated how parents in an affluent region of the San Francisco Bay Area perceive community college as a starting point for their children’s academic careers and how parents may contribute to shifting those perceptions. Using a convergent parallel mixed methods design, survey data …

Toward Intentional Praxis: A Design Thinking Multi-Case Study Of Cognitive-Constructive Toolkit Implementation In An Elementary Professional Learning Community, Azam Nathaniel

Dissertations

Among several learning theories that were dynamic and constantly evolving with time, cognitive and constructive theories were predominant in the field of education. However, these theories often included overlapping and contrasting concepts, contributing to confusion in terminology among teachers and limited explicit use in instructional practice. Within the context of K-12 education, teachers demonstrated conceptual awareness of cognitive and constructive learning theories; however, the theories were not a part of day-to-day conversations and were minimally identified in practice. Instead, the theories were implicitly applied as teachers balanced competing professional responsibilities, including daily routines, syllabus requirements, district standards, new initiatives, differentiated …

Examining The Effect Of Assistant-Centered Peer Interventions On Student Belonging And Academic Performance In Introductory Physics And Introductory Astronomy College Courses, Shiva Basir

Dissertations

Physics education research (PER) plays an important role in improving teaching strategies and student outcomes in STEM education. This study examined relationships among academic preparedness, sense of belonging, and academic performance in introductory physics and introductory astronomy courses at the University of Missouri–St. Louis (UMSL). Diagnostic assessments, belonging surveys, and academic performance measures were used across multiple instructional phases. The study also explored the implementation of assistant-centered peer interventions model, targeted math reviews, and motivational starts designed to support student engagement and belonging. Findings suggested meaningful relationships among belonging, confidence, and academic performance, while highlighting the importance of supportive instructional …

Merleau-Ponty On The Crisis Of Natural Philosophy: A Critique Of The Metaphysical Foundations Of Natural Science And Investigations Into The Ontology Of Nature, Kevin Mager

Dissertations

In this dissertation, I show that Merleau-Ponty’s philosophy of nature is also a radical critique of the metaphysical foundations of natural science. This critique leads us to a new ontology for science, grounded in the lifeworld. I focus on how his philosophy offers a detailed critique of both physicalism and mechanism. For Merleau-Ponty, mechanism is not just the strict adherence to classical causality, but any view that asserts that classical causality has any role to play in reality at all. To replace mechanistic causality, Merleau-Ponty argues that we must conceive of nature as grounded in meaningful possibility. Merleau-Ponty's emphasis on …

Enhancing Postsecondary Outcomes For Students With Emotional And Behavioral Disorders: A Design-Based Mixed Methods Approach To Transition Planning, Kate M. Schrum

Dissertations

Students with emotional and behavioral disorders (EBD) experienced significantly lower postsecondary outcomes when compared to same-aged peers. These outcomes included lower graduation rates, higher unemployment rates, and difficulty establishing independent living arrangements (Wagner & Newman, 2015). Following a human-centered, design-based approach, the scholar-practitioner found a lack of consistent and meaningful transition support specifically designed for students with EBD. Working with a stakeholder team of educational professionals directly involved in supporting transition for students with EBD at an alternative special education program, the scholar-practitioner developed a "Transition Toolkit". The toolkit contained scaffolded grade-level checklists (for grades 6–12) with self-advocacy and goal-setting …

Enhancing The Metacognitive Thinking Of Middle-Grade Multilingual Learners: A Design-Based Research Study Leveraging Dialogic Teaching, Renee R. Burns

Dissertations

This study explores how dialogic teaching can enhance metacognition and self-efficacy among middle school multilingual learners (MLs) who face challenges with the academic language demands of literacy tasks. Using a design-based research (DBR) methodology, specifically formative experiment, the Metacognitive Dialogic Teaching Protocol (MDTP) was implemented over seven iterative cycles. The research questions were as follows: How do dialogic interactions impact metacognition in middle-grade MLs? How does Metacognitive Dialogic Teaching affect comprehension development in these students? And how does it influence their self-efficacy? The participants included six middle-grade MLs engaged in a Tier 2 literacy intervention who initially exhibited fake reading …

Reduced Product Type Monoid-Module Extensions, Darryl Jent

Dissertations

In 1955, I. M. James introduced the James Construction, a free topological monoid that models the loops on the suspension of a given space. In 1969, S. Y. Husseini generalized this idea to RPT monoids: topological monoids with a free-like monoid structure that can be used to model a broader class of loop spaces. In order to prove that these topological monoids are models of loop spaces, both I. M. James and S. Y. Husseini constructed contractible spaces on which these topological monoids act. We define a topological module as a space equipped with an action by a topological monoid. …

From Total Domination To Graph Coloring, Sawyer Isaac Osborn

Dissertations

A question involving a chess piece called a prince on the 8×8 chessboard leads to a concept in graph theory involving total domination. We say a vertex u in a graph G totally dominates a vertex v if u is adjacent to v. A subset S of the vertex set of a graph G is a total dominating set for G if every vertex in G is totally dominated by at least one vertex of S. If S is a total dominating set of G, then σ_S(v) denotes the number of …

Effectiveness Of Tiered Supports In Mathematics, Dominique L. Brown

Dissertations

Mathematics proficiency has remained a persistent national challenge, with many students failing to meet grade-level expectations. This mixed-methods program evaluation examined the effectiveness of mathematics intervention strategies within Multi-Tiered Systems of Support (MTSS) for students in Grades 3–8. Guided by utilization-focused evaluation, the study explored educator perceptions, implementation practices, and system-level challenges. Quantitative data were collected through an anonymous survey (n = 19), and qualitative data were obtained from one semi-structured interview. Descriptive statistics and inductive coding were used for analysis, with extant data providing contextual support. Findings indicated that small-group instruction was perceived as highly effective; however, inconsistencies in …

Quantum And Conventional Informatics Studies Of Synthesis Energetics And Defect Formation In Nitride Crystal Epitaxy, Andrew Steven Messecar

Dissertations

Machine learning is a valuable approach for the processing and analysis of complex information. By estimating relationships from recorded data, machine learning methodologies can be effective strategies for pattern recognition, enabling investigations and technological applications based thereon. The potential for improved understanding of high-dimensional data has drawn interest towards machine learning from across the sciences, including the research and development of new and improved material systems. In the context of experimental materials research, much of the reported efforts to incorporate machine learning into conventional practice have been primarily focused on either the enhanced analysis of characterization experiment data or the …

Enhancing Postsecondary Outcomes For Students With Emotional And Behavioral Disorders: A Design-Based Mixed Methods Approach To Transition Planning, Kate M. Schrum

Dissertations

Students with emotional and behavioral disorders (EBD) experienced significantly lower postsecondary outcomes when compared to same-aged peers. These outcomes included lower graduation rates, higher unemployment rates, and difficulty establishing independent living arrangements (Wagner & Newman, 2015). Following a human-centered, design-based approach, the scholar-practitioner found a lack of consistent and meaningful transition support specifically designed for students with EBD. Working with a stakeholder team of educational professionals directly involved in supporting transition for students with EBD at an alternative special education program, the scholar-practitioner developed a "Transition Toolkit". The toolkit contained scaffolded grade-level checklists (for grades 6–12) with self-advocacy and goal-setting …

Deployment-Aware Deep Learning For Computer Vision: Efficient Architectures From 3d Segmentation To Mixed Reality, Bahar Uddin Mahmud

Dissertations

Deep learning has become the dominant approach for solving vision-centric problems; however, its successful deployment in real-world applications remains limited by high computational cost, data dependency, and insufficient integration with practical and human-centered environments. While state-of-the art deep learning models often achieve impressive performance in controlled settings, they frequently fail to generalize or operate efficiently under deployment constraints such as limited resources, complex data modalities, and real-time interaction requirements. These limitations motivate the need for a deployment-oriented deep learning framework that balances accuracy, efficiency, and practical usability.

This dissertation investigates the design and deployment of efficient deep learning architectures for …

Perceptual And Geometric Advances In Crowd Simulation, Bilas Talukdar

Dissertations

Simulating realistic crowd motion remains a fundamental challenge in computer graphics and multi-agent systems, as it requires modeling both physically plausible interactions and perceptually natural behaviors. Existing crowd simulation methods typically employ simplified geometric abstractions, most commonly circular agent representations, and model navigation using either analytical interaction formulations (e.g., force, velocity, or constraint-based methods) or learned policies derived through reinforcement learning. Despite their effectiveness, these approaches often overlook detailed geometric structure and do not explicitly account for perceptual realism. This dissertation addresses these challenges by improving the realism of virtual crowd simulation through two key advancements: perceptual preference learning and …

Principles Of Privacy And Security In Artificial Intelligence And Applications, Khang Tran

Dissertations

Modern artificial intelligence (AI) systems have transformed critical domains such as healthcare, software engineering, finance, and the legal system. Despite their broad impact, concerns about trustworthiness, especially regarding privacy and security, remain major obstacles to wider adoption. Addressing these concerns requires both a systematic understanding of the privacy and security risks inherent in AI systems and the development of principled foundations for trustworthy AI that safeguard client privacy and security. This goal is particularly challenging because of the complexity of modern large-scale AI systems, the trade-offs between privacy and model utility, and the need to simultaneously ensure other important properties …

Mechanics And Physical Attributes Of Nature-Based Alterations: Rock Reinforcement And Urban Heat Island Assessment, Mary Chikondi Ngoma

Dissertations

Ground improvement is critical to geotechnical and geo-engineering systems, where modification of the properties of geomaterials (rocks and soils) is required to maintain stability and prevent failure of infrastructure installed within and around them. This need has become increasingly important with rapid urbanization and population growth, which intensify demands on surface and subsurface systems and further challenge the performance of supporting geomaterials. As a result, there is growing interest in nature-based solutions, particularly biologically mediated processes such as biocementation, which can enhance the physical, hydraulic, and mechanical properties of geomaterials while offering environmentally sustainable alternatives to conventional ground improvement techniques. …

Enabling Ml/Ai In 6g And Future Wireless Communication With Privacy Preservation, Mec Offloading And Quantum Computing, Changshi Zhou

Dissertations

The forthcoming sixth-generation (6G) and future wireless networks are envisioned to support an unprecedented range of services, delivering ultra-low latency, massive connectivity, and intelligent real-time responsiveness. These capabilities will enable emerging applications such as extended reality (XR), autonomous vehicles (AVs), industrial robotics, and the Internet of Things (IoT) to reach their full potential. Achieving this vision requires the integration of enabling technologies such as artificial intelligence and machine learning (AI/ML) and quantum computing, which are poised to play central roles in shaping the landscape of wireless communication systems.

In AI-native, data-driven, and computing-centric 6G networks, ML models will be deeply …

Differential-Geometric Methods For Neural Signed Distance Fields: Parameterized Surface Extraction And Curvature Regularization For Cad Models, Haotian Yin

Dissertations

Neural signed distance fields have emerged as a powerful framework for representing three-dimensional geometry through continuous and differentiable neural functions. Their flexibility, resolution independence, and compatibility with gradient-based optimization make them especially attractive for surface reconstruction and geometric learning. However, despite these advantages, two fundamental challenges remain for engineering-grade applications. First, higher-order geometric properties such as curvature are difficult to model reliably during training and often require computationally expensive second-order differentiation. Second, while neural signed distance fields provide implicit surface representations, they do not directly yield a globally consistent forward map or parameterization for downstream geometric processing.

This dissertation addresses …

Holistic Dram Enhancements: From Intrinsic In-Memory Operations To Robust Security Mechanisms, Ranyang Zhou

Dissertations

Dynamic Random-Access Memory (DRAM) is both the performance bottleneck and a critical security boundary of modern computing systems. Its physical properties make it an attractive substrate for near-data computation—yet those same properties expose it to disturbance-based hardware attacks. This dissertation argues that these two dimensions are not independent: the architectural choices that make DRAM efficient also reshape its threat landscape. Addressing both requires a unified approach to memory architecture and security co-design.

The first part of this dissertation attacks the memory wall through four processing-in-DRAM (PIM) frameworks. ReD-LUT and LT-PIM unify lookup-table arithmetic with charge-sharing logic, achieving up to 37.8x …

Disentangling Non-Thermal Electron Injection And Decay In Solar Flares Using Multi-Wavelength Radio Observations, Brian Eugene O’Donnell

Dissertations

The broadband microwave imaging spectroscopy capability provided by the Expanded Owens Valley Solar Array (EOVSA) allows new diagnostics of high-energy processes in solar flares, providing spatially and temporally resolved spectra rich in information about the acceleration and transport of energetic electrons.

In this work, injections and transport of energy and particles into the solar corona during flares are studied. This is accomplished through the development and use of the PIP_Decomp Fitter, an automated fitting tool made by the author to fit injection and precipitation/decay parameters using the spatially resolved radio spectra obtained by EOVSA. These tools are used to study …

A Generative Ai-Driven Computational Framework For Industry-Scale Discovery Of Novel Battery Materials, Joy Datta

Dissertations

The growing demand for sustainable, high-energy-density electrochemical storage has motivated the exploration of multivalent-ion batteries based on earth-abundant elements such as aluminum, calcium, magnesium, and zinc. While multivalent charge carriers offer higher theoretical energy density than lithium, their practical deployment is hindered by sluggish ion transport, strong ion-host interactions, and structural degradation of electrode materials. Identifying host materials that can reversibly accommodate multivalent ions while maintaining structural integrity remains a fundamental challenge. The dissertation develops a scalable, end-to-end computational framework that integrates density functional theory (DFT), machine learning (ML), and generative artificial intelligence (GenAI) to accelerate the discovery of next-generation …

Toward Learning-Based Reconstruction And Part Decomposition Of Man-Made 3d Geometry: Neural Implicit Representations And Scalable Supervision, Shen Fan

Dissertations

Digital three-dimensional (3D) models are central to engineering design, analysis, and manufacturing, but learning pipelines for man-made geometry often operate on sampled carriers that do not preserve all of the structure present in exact CAD representations. This dissertation studies learning-based reconstruction and part decomposition for structured man-made 3D geometry, from general object benchmarks to CAD-derived datasets, with a focus on neural implicit representations trained from signed-distance samples, point clouds, and tessellated meshes. The goal is to make these models more accurate, more part-aware, and more consistently supervised.

First, signed distance function (SDF) reconstruction with implicit neural representations is improved through …

Anonymity And Accountability In Secure Messaging, Erin Kenney

Dissertations

Encypted messaging has become more and more prevalent as time moves on, and its benefits in assuring privacy cannot be overstated, but it also brings along with it concerns on how to moderate platforms where all messages are hidden. Message Franking, followed by Traceback systems, addressed these concerns by allowing the sender of a message to be proven when reported, even for forwarded messages in the case of Traceback, however these systems damage the privacy guarantees that originally motivated encrypted messaging to begin with.

In practice, even without those concerns encrypted messaging alone is not enough to prevent the most …

Glass Transition Temperature Of Plga Nanoparticles And The Application In Drug Delivery, Guangliang Liu

Dissertations

The glass transition temperature (T_g) of poly(D,L-lactic-co-glycolic acid) (PLGA) nanoparticles plays a crucial role in governing molecular mobility, diffusion, and consequently, drug release kinetics. However, the interaction among residual surfactant, drug effect, nanoscale confinement, and release medium on T_g remains insufficiently characterized. This study aims to bridge this gap by correlating the thermal behavior of PLGA nanoparticles with their drug release behavior under physiologically relevant conditions.

In the present study, PLGA nanoparticles were synthesized using both nano-emulsion and surfactant-free nano-precipitation approaches. The influence of residual surfactants - poly(vinyl alcohol) (PVA) and didodecyldimethylammonium bromide (DMAB) - was systematically …

Parameter Density Estimation For Cardiac Electrophysiology Models Using Data Consistent Deep Learning, Michael Luo

Dissertations

Mathematical models of biological rhythms and excitable systems can provide insights into mechanisms underlying cardiac electrical dynamics. However, estimating the parameters of these models from experimental observations is often difficult due to noise, heterogeneity, and unobserved variables. For example, in an electrocardiogram (ECG) recording, information about the electrical properties of different regions of the heart is compressed into a single voltage trace. Additionally, variability within these signals may contain important information about population heterogeneity, regional differences in electrophysiology, and time-dependent modulation.

This dissertation develops, explores, and evaluates methods that perform feature-based distributional inference for complex nonlinear dynamical systems. The objective …

Decision-Making In Early-Stage Startups: How Venture Capitalists And Angel Investors Evaluate Uncertainty, Andrew M. Pence

Dissertations

The purpose of this dissertation is to examine how venture capitalists (VCs) and angel investors (AIs) make investment decisions regarding early-stage startups. Using an Interpretative Phenomenological Analysis (IPA) framework—consisting of three core components: phenomenology, hermeneutics, and idiography—this study draws upon three decision-making models: the Rational Actor Model (RAM), the Heuristics and Biases model (H&B), and the Naturalistic Decision-Making model (NDM) to explore what motivates VCs and AIs to choose, for instance, “Company A over Company B.” Semi-structured interviews were conducted with 10 experienced venture investors to examine how they evaluate risk, assess founders and teams, and navigate the persistent uncertainty …

Elementary Students' Science Attitudes And Teachers' Implementation Of The Ngss Science Practices: A Mixed Methods Study, Michelle Laborn

Dissertations

It has been recorded in the literature that student science interest drops as students enter and transition to middle and high school. This dissertation takes up the areas of student science interest and the teaching of the science practices in the context of elementary education. This study seeks to understand student science interest in elementary students in the years before entering middle school where a drop of interest is frequently reported. It is hypothesized that an increased use or implementation of the NGSS science practices by classroom teachers would generate higher science interest in elementary students. In a framework of …

From Stranger To Self: The Role Of Familiarity In Modulating The N170 And N250 Erp Components, Tabish Gul

Dissertations

This study investigated how varying levels of face familiarity modulate the N170 and N250 event-related potential (ERP) components, two neural markers of face perception and recognition. While the N250 is widely considered familiarity-sensitive, the N170 has traditionally been linked to the structural encoding stage of face perception. However, recent research suggests that face familiarity may also influence N170 amplitude and latency. While most previous studies have compared up to three familiarity levels, the present study examined five levels of familiarity: own face, friend’s face, famous face, experimentally familiar face, and unfamiliar face. Twenty-six participants viewed face images while completing a …

Exploring Alternative Curriculum Implementation In Special Education Settings, Amber R. Wilson

Dissertations

The purpose of this qualitative case study was to understand teachers’ perceptions of implementing an alternative curriculum in their self-contained special education settings and grade levels, as well as their perceptions of the training and ongoing support provided for its implementation. This study used a case study research design. Findings revealed that the participants experienced several challenges related to training, ongoing support, and curriculum implementation, including issues aligning the alternative curriculum with state standards and assessments. This study is significant because alternative curriculum implementation is under-researched in the United States, and the international literature on this topic is limited.

Secondary Teachers’ Perceptions On The Wida Framework To Support Academic Literacy In Multilingual Learners, Laura G. Faris

Dissertations

The purpose of this study was to determine teachers’ perceptions of benefits and barriers to using the WIDA Framework to support academic literacy in multilingual learners (MLs).  Content-area teachers of MLs who continue to learn English are teaching academic literacy through complex linguistic structures for students to both comprehend and produce informative textual structures which occur in secondary textual reading and written assessments in the literature and historical content areas. Qualitative methods including reflective journal entries, semi-structured teacher interviews, and classroom observations were used to collect data on teachers’ perceptions of the effectiveness of using the WIDA Framework to better …