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Policy Into Practice: Exploring School Counselors' And School Psychologists' Knowledge And Sensemaking Towards The Application Of Alternative Gifted Identification Criteria For Lower Socioeconomic Students, Brittany E. Hague Jan 2026

Policy Into Practice: Exploring School Counselors' And School Psychologists' Knowledge And Sensemaking Towards The Application Of Alternative Gifted Identification Criteria For Lower Socioeconomic Students, Brittany E. Hague

Graduate Studies Theses and Dissertations 2026

Persistent underrepresentation of students from lower socioeconomic status (SES) backgrounds in Gifted education reflects long-standing structural inequities embedded in identification policies and practices. In response, many Florida school districts have adopted equity-oriented identification reforms, including universal screening, local norms, and multiple-measure approaches. However, policy equity does not automatically translate into equitable outcomes; rather, it is mediated through the interpretive work of school-based practitioners. Guided by Sensemaking Theory, this convergent mixed-methods study examines how school counselors and school psychologists construct meaning around alternative Gifted identification criteria and how their beliefs, professional judgment, and organizational contexts shape implementation. The study explores how …


Examining Teachers’ Data Usage Using The Teacher Data Use Survey, Natasha L. Hawkins Jan 2026

Examining Teachers’ Data Usage Using The Teacher Data Use Survey, Natasha L. Hawkins

Graduate Studies Theses and Dissertations 2026

The United States spends approximately 2.7 billion dollars on classroom assessments and local exams for K-12 students (SIMBA, 2019).  However, despite this financial investment and the adoption of data-driven frameworks such as Multi-Tiered System of Support, the U.S. Department of Education found that only 55% of teachers used student data to make instructional decisions (U.S. Department of Education, 2007).  This study aims to explore the psychological and organizational factors that influence teachers’ data use when making instructional decisions.

This study used the Teacher Data Use Survey (TDUS) to investigate the extent that teachers’ use of data could be predicted by …


Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang Jan 2026

Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang

Graduate Studies Theses and Dissertations 2026

Optics and photonics have been one of the most important sciences and technologies that impact modern human life in a big way. For example, fiber-optics for communications and artificial intelligence. Optical probes are critical components for optical imaging and optical sensing technologies that have been actively researched and developed in the past decades. Advanced fiber-optic sensor probes with smaller size, better performance, lower noise, higher photon efficiency, rapid sensing time, and lower cost are needed in many applications, such as nanoscale material science, chemistry, and biomedical fields, etc.  In this project, new fiber-optic sensor probe technologies and integrated micro-optic devices …


Modeling And Mitigating Atmospheric Degradation In Computer Vision With Application In Renewable Energy Prediction, Sumit Laha Jan 2026

Modeling And Mitigating Atmospheric Degradation In Computer Vision With Application In Renewable Energy Prediction, Sumit Laha

Graduate Studies Theses and Dissertations 2026

Weather-induced variability poses significant challenges to the reliability and performance of modern computational systems, particularly those relying on visual perception and environmental prediction. This dissertation focuses on enhancing computer vision and machine learning based predictive models that operate under varying atmospheric conditions. Two representative weather-impacted applications are investigated: image dehazing and solar photovoltaic (PV) power output forecasting. Image dehazing focuses on the restoration of clear, unobstructed visuals from hazy or foggy images, a task that is vital for various applications. On the other hand, photovoltaic (PV) power forecasting aims to predict future solar energy generation based on historical sky images …


Contextual Influences On Algebra 1 Achievement In Florida: A Multilevel Analysis Of Fsa Data And Policy Implications For B.E.S.T., Alberto Leiro Jr Jan 2026

Contextual Influences On Algebra 1 Achievement In Florida: A Multilevel Analysis Of Fsa Data And Policy Implications For B.E.S.T., Alberto Leiro Jr

Graduate Studies Theses and Dissertations 2026

This study examined how school-level and district-level contextual factors are associated with Algebra 1 achievement in Florida using a multilevel modeling framework. Drawing on statewide publicly available data from the Florida Standards Assessments (FSA), the analysis included schools nested within districts to account for the hierarchical structure of educational data. School-level predictors included absenteeism, economic disadvantage, English language learner status, student mobility, and the proportion of students with disabilities, while district-level variables included poverty and crime rates. Results from the null model indicated that a meaningful proportion of variance in Algebra 1 achievement was attributable to differences among districts, supporting …


The Perceptions Of Instructional Coaching On Teacher Efficacy And Retention In Elementary Schools, Stephanie Lucas Jan 2026

The Perceptions Of Instructional Coaching On Teacher Efficacy And Retention In Elementary Schools, Stephanie Lucas

Graduate Studies Theses and Dissertations 2026

Administrators in a large school district in Central Florida encountered challenges regarding teacher retention and sustainability. Flite STEM coaching, a new instructional coaching model, was developed to support teachers in hopes of reducing those challenges. This model includes coaching cycles that encouraged collaboration and reflective thinking aligned with professional learning. This qualitative study focused on implementing the Flite STEM coaching model with teachers and instructional coaches. The coaching cycle consisted of the following: 1) a pre-observation conference, 2) video observation, 3) post-observation conference with feedback, and 4) a professional learning opportunity. It included DebriefScape Observation Dashboard resources to collect and …


Genuine And Meaningful Black Character Narratives In Video Games, Derek L. Manns Jan 2026

Genuine And Meaningful Black Character Narratives In Video Games, Derek L. Manns

Graduate Studies Theses and Dissertations 2026

The lack of Black representation in video games reflects stereotypes and hollow narratives. Authentic and meaningful design of Black characters allows Black players a reflection of emotional attachments everyone wants when playing a game. Examining racial identities through avatars, critiquing the notion that customization equates to racial inclusivity, limited options and predominant, white-coded protagonists reinforce systemic biases in games (Dietrich, 2013). My Afrofuturistic content analysis framework explores Black culture with a future of speculative fiction. Reimagining the past, present, and future through Black narratives for alternate futures (Womack). Integrating these ideas enhance culture and aesthetics in this dissertation to highlight …


Discrete Element Modeling Of Granular Soils: Critical State Behavior Applied To Impact Pile Driving, Esteban Patino Marin Jan 2026

Discrete Element Modeling Of Granular Soils: Critical State Behavior Applied To Impact Pile Driving, Esteban Patino Marin

Graduate Studies Theses and Dissertations 2026

This thesis investigates the use of the Discrete Element Method (DEM) to study two complementary aspects of granular soil mechanics: critical state behavior of granular materials and dynamic response of driven piles in sand, both of which are governed by the same particle-scale mechanisms of dilation, contraction, and fabric evolution.

The first examines the critical state behavior and fabric anisotropy of granular soils through DEM simulations of direct shear, direct simple shear, and true triaxial tests. Sphere-cluster particles representative of a uniform sand are used in two assemblages of approximately twenty-five thousand and one hundred twenty-five thousand spheres to evaluate …


Securing The Energy Transition: Cyber-Physical Security And Resilience In Next-Generation Power Systems, Airin Rahman Jan 2026

Securing The Energy Transition: Cyber-Physical Security And Resilience In Next-Generation Power Systems, Airin Rahman

Graduate Studies Theses and Dissertations 2026

Modern power systems are rapidly evolving into renewable-dominated and digitally interconnected cyber-physical infrastructures due to the increasing deployment of distributed energy resources (DERs), inverter-based technologies, and advanced control platforms. Maintaining reliability under high renewable penetration requires flexible resources capable of shifting energy across extended time horizons. Long-duration energy storage (LDES), particularly hydrogen-based energy systems, has therefore emerged as an important enabler of renewable integration, grid flexibility, and resilience. However, the growing dependence on communication, sensing, and distributed control also expands the cyber-physical attack surface of modern power systems, creating security and resilience challenges that conventional operational paradigms were not designed …


Advancing Cyber-Physical Security And Resilience Of Modern Power Systems: Intelligent Monitoring, Secure Operation, And Resilient Recovery, Md Moshiur Rahman Jan 2026

Advancing Cyber-Physical Security And Resilience Of Modern Power Systems: Intelligent Monitoring, Secure Operation, And Resilient Recovery, Md Moshiur Rahman

Graduate Studies Theses and Dissertations 2026

Modern power distribution systems are rapidly evolving into cyber-physical, DER-rich, and data-driven networks that rely on extensive sensing, communication, automation, grid-edge intelligence, and operator decision support. While this transformation improves flexibility, observability and controllability, it also expands the cyber-attack surface and increases the risk that cyber intrusions can propagate into physical disturbances, compromised DER operation, degraded situational awareness, and interrupted service continuity. This dissertation advances the cyber-physical security and resilience of modern distribution systems by developing a high-fidelity real-time cyber-physical hardware-in-the-loop testbed using OPAL-RT, EXata CPS, industrial relays, SCADA/RTAC, HMI, and grid-edge devices to emulate realistic DER-integrated distribution grid operation. …


Mathematical Modeling And Characterization Of A Variable Stiffness Ankle-Foot-Orthosis, David E.L. Richards Jan 2026

Mathematical Modeling And Characterization Of A Variable Stiffness Ankle-Foot-Orthosis, David E.L. Richards

Graduate Studies Theses and Dissertations 2026

Conventional ankle–foot orthoses (AFOs) typically employ static stiffness profiles that do not replicate the dynamic quasi-stiffness of the human ankle during gait. Variable stiffness mechanisms (VSMs) offer a promising alternative solution for gait pathologies, such as foot drop and post-stroke hemiparesis; however, their implementation is limited by the lack of accurate mathematical models capable of predicting force and stiffness characteristics. The objective of this thesis is to develop and validate comprehensive mathematical models describing the kinematics and kinetics of a novel variable stiffness ankle–foot orthosis (VS-AFO). This study derives governing equations to characterize how mechanical adjustments influence the force transmission …


Examining Principals' Perceptions Of Their Preparedness To Lead In Title I Schools, Tiffany Roebuck Jan 2026

Examining Principals' Perceptions Of Their Preparedness To Lead In Title I Schools, Tiffany Roebuck

Graduate Studies Theses and Dissertations 2026

Principals serving in Title I schools face complex instructional, organizational, cultural, and community related demands that require specialized leadership preparation and support.  The purpose of this qualitative phenomenological study was to explore the lived experience of principals serving in urban Title I schools regarding their preparedness, supports, challenges, and successes as instructional leaders. The study also examined principals' perceptions of culturally proficient leadership and principal preparation program attributes considered essential for leadership readiness in high-needs school settings. Guided by the Culturally Responsive School Leadership (CRSL) framework, data were collected through semi-structured interviews with 10 principals serving in urban Title I …


Visual Cues Of Human-Likeness, Not Salience, Impact Trust-Related Human-Computer Interaction, Jordan Schotz Jan 2026

Visual Cues Of Human-Likeness, Not Salience, Impact Trust-Related Human-Computer Interaction, Jordan Schotz

Graduate Studies Theses and Dissertations 2026

As interactions with digital agents become increasingly integrated into daily life, understanding how visual representations influence social decision-making is critical. Previous research in human-computer interaction has frequently confounded the psychological effects of an agent's perceived human-likeness with the underlying visual salience of the stimuli. To address these persistent gaps, the present study systematically isolated the effects of human-likeness and visual cue trustworthiness on trust behavior while controlling for objective image properties. The present study expanded on and normed the Virtual Avatar Facial Stimuli Set (VAFSS), a comprehensive database comprising hundreds of identity-matched photographs and computer-generated avatars varying across a spectrum …


Concept Drift Detection For Streaming Data Using One-Class Classification, Poorna Sandamini Senaratne Jan 2026

Concept Drift Detection For Streaming Data Using One-Class Classification, Poorna Sandamini Senaratne

Graduate Studies Theses and Dissertations 2026

Modern machine learning systems are increasingly deployed in streaming environments where data arrive sequentially and the underlying data-generating process may evolve over time. This phenomenon, known as concept drift, can significantly degrade model performance if not detected and addressed in a timely manner. This dissertation proposes a principled framework for concept drift detection based on one-class classification, integrating neural network embeddings with Support Vector methodologies.

The proposed approach leverages neural networks to learn compact and informative embeddings of input data, capturing complex nonlinear structures in a lower-dimensional latent space. These embeddings are then used to construct a statistical description of …


Study On Fracture Toughness Under Different Modes Through Continuum Damage Mechanics Based Fracture Locus, Yeting Sun Jan 2026

Study On Fracture Toughness Under Different Modes Through Continuum Damage Mechanics Based Fracture Locus, Yeting Sun

Graduate Studies Theses and Dissertations 2026

Traditional elastic-plastic fracture mechanics (EPFM) relies on crack-tip analysis, whereas continuum damage mechanics (CDM) is typically calibrated from uncracked bodies. This dissertation aims to bridge the gap between these two fundamental branches by explicitly linking fracture toughness with ductile damage models. Based on the assumptions regarding Mode I crack deformation, analytical solutions are derived to establish a novel relationship among Mode I fracture toughness, CDM-based ductile fracture strain, and material strain hardening capability. This theoretical framework is subsequently extended to encompass Mode II and Mode III loading conditions. To validate the proposed relationships, finite element (FE) models are developed in …


Volumetric Fluorescence Microscopy For High-Throughput And High-Sensitivity Imaging: From Single Molecules To Tissues, Le-Mei Wang Jan 2026

Volumetric Fluorescence Microscopy For High-Throughput And High-Sensitivity Imaging: From Single Molecules To Tissues, Le-Mei Wang

Graduate Studies Theses and Dissertations 2026

Fluorescence microscopy is an indispensable tool in the biological sciences, enabling researchers to investigate intricate subcellular structures, particularly for volumetric studies. However, conventional optical microscopy for volumetric imaging remains fundamentally constrained by imaging speed and throughput. To bypass traditional serial z-scanning, we introduce an axially scan-free method using a phase layer cake to modulate the system's point spread function. This approach projects volumetric information onto a 2D plane in a single shot, offering high flexibility in tuning axial depth alongside simultaneous multicolor imaging with high spatial resolution and sensitivity. This dissertation divides these technical advancements into cellular and tissue imaging …


Human And Ai Support In Business Simulations: A Quasi-Experimental Mixed Methods Study Of Performance At Scale, Sara Willox Jan 2026

Human And Ai Support In Business Simulations: A Quasi-Experimental Mixed Methods Study Of Performance At Scale, Sara Willox

Graduate Studies Theses and Dissertations 2026

Large classes change what instruction looks like. In hybrid business courses with high enrollment, it becomes harder to respond to individual students, and performance can suffer as a result. This study looked at what happens when that gap is addressed in different ways during an eight-week business simulation at the University of Central Florida. Six course sections were divided into three study groups. One group worked without support, one received instructor guidance, and one used AI tools that included a course search system and generative responses. Student outcomes were based on weekly profit and loss recorded in Sim Companies. The …


Careless Responding: Testing The Theory Of Vigilance, Rusty Wilson Jan 2026

Careless Responding: Testing The Theory Of Vigilance, Rusty Wilson

Graduate Studies Theses and Dissertations 2026

Careless responding (CR) has been identified as a threat to the psychometric integrity of cognitive and non-cognitive tests, with much of the current research focusing on the identification and removal of carelessness from dataset. While this research has proved fruitful in improving data quality, there has been a recent push to move towards preventing carelessness as opposed to post-hoc removal, which harms statistical power. However, the most common prevention strategy to prevent carelessness (pre-survey warnings) has shown equivocal effects. Additionally, the literature lacks an agreed upon theory to explain why carelessness occurs. To address these gaps I introduce theory from …


Voltage Stability Enhancement Of Large Load Interconnections Using Syncronous Condensers, Muhammad Ibrahim Abbas Jan 2026

Voltage Stability Enhancement Of Large Load Interconnections Using Syncronous Condensers, Muhammad Ibrahim Abbas

Graduate Studies Theses and Dissertations 2026

The rapid integration of hyperscale data centers as large, concentrated loads presents a growing voltage stability challenge in grids weakened by synchronous generator retirement and increasing inverter-based resource penetration. This work proposes a Jacobian-based sensitivity framework for systematically identifying voltage-critical buses and optimally siting synchronous condensers as voltage support resources. A voltage-weighted sensitivity index, extracted from the full Jacobian inverse, is introduced to combine network-wide reactive coupling strength with observed voltage drops into a single deployable placement criterion. Validation on IEEE 14-bus and 30-bus test systems under multiple loading scenarios demonstrates that the proposed criterion consistently identifies the correct placement …


Robust Linking Estimation In Item Response Theory Using Quantile Regression: Applications To The Graded Response And Generalized Partial Credit Models, Ibrahim Almansour Jan 2026

Robust Linking Estimation In Item Response Theory Using Quantile Regression: Applications To The Graded Response And Generalized Partial Credit Models, Ibrahim Almansour

Graduate Studies Theses and Dissertations 2026

This dissertation investigates robust estimation of linking coefficients in Item Response Theory (IRT) using quantile regression and its extensions. Linking procedures are essential for placing item and ability parameters from different test forms onto a common scale, thereby ensuring comparability of examinee scores across administrations. Traditional approaches such as moment methods, characteristic curve methods, and mean-based regression procedures like Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) perform adequately under ideal conditions but tend to lose accuracy when ability distributions deviate from normality or include outliers.

To address these limitations, this research proposes a quantile-based regression framework that estimates …


Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula Jan 2026

Restoring Digital Trust: Decentralized Frameworks For Identity, Consent, And Media Provenance, Raghu N. Avula

Graduate Studies Theses and Dissertations 2026

Digital platforms are deeply embedded in modern society through centralized network architectures. As online interactions transition to the physical world handling sensitive data, user privacy and cryptographic security require enhancement beyond traditional limits. This dissertation presents a decentralized “Tri-Layer Trust Architecture” that leverages Verifiable Trust Registries, Cryptographic Binding, and Edge Verification to prioritize data sovereignty and local authentication. To demonstrate the architecture’s applicability across distinct operational environments, we implement three solutions: (1) Verifiable Presence for peer-to-peer ride-sharing via D-RideX, which encrypts biometric data on physical hardware (TEEs) and Soulbound Tokens (SBTs) to prevent impersonation without cloud database exposure; (2) Verifiable …


Learning-Based Optimization For Collaborative Truck-Drone Routing And Scheduling, Ahmad A. Bany Abdelnabi Jan 2026

Learning-Based Optimization For Collaborative Truck-Drone Routing And Scheduling, Ahmad A. Bany Abdelnabi

Graduate Studies Theses and Dissertations 2026

Modern delivery networks increasingly rely on innovative technologies such as drones working alongside trucks to meet rising demands for fast and efficient last–mile transportation. Hybrid truck–drone delivery offers strong potential, but its effectiveness depends on careful synchronization between trucks and drones. Although drones provide fast, direct travel, their limited endurance and the need to coordinate launch and recovery with trucks create tightly coupled routing and scheduling interactions. Poor dispatch decisions can cause truck waiting, reduce parallelism, and increase mission completion time. These challenges motivate decision frameworks that explicitly model synchronization and develop scalable methods for coordinated truck–drone operations. This dissertation …


An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat Jan 2026

An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat

Graduate Studies Theses and Dissertations 2026

Supply chain management has become increasingly critical as transportation costs rise and urban delivery systems place additional pressure on already congested networks. Last-mile delivery—the movement of goods from distribution centers to end users—represents the most expensive and operationally complex segment of the logistics process, particularly in underdeveloped megacities characterized by unpredictable traffic, limited infrastructure, and sparse real-time data. This dissertation proposes an integrated framework for optimizing last-mile delivery in such environments by combining social media–based traffic intelligence, machine learning, and deep reinforcement learning. The framework leverages unstructured, real-time data from social media platforms to enhance traffic prediction and incorporates these …


Investigation Of Exotic Phenomena In Topological Quantum Materials, Iftakhar Bin Elius Jan 2026

Investigation Of Exotic Phenomena In Topological Quantum Materials, Iftakhar Bin Elius

Graduate Studies Theses and Dissertations 2026

he First Quantum Revolution established quantum mechanics as the foundation of modern physics, enabling transformative technologies such as semiconductors, lasers, and transistors through prin-ciples of quantization, wave-particle duality, and uncertainty. The ongoing Second Quantum Rev-olution harnesses entanglement, superposition, and coherence to advance quantum computation, communication, simulation, and sensing. Central to this endeavor is the study of quantum mate-rials hosting novel electronic structures and emergent phases, including topological insulators and Dirac, Weyl, and nodal-line semimetals. In this thesis, using angle-resolved photoemission spec-troscopy (ARPES), transport measurements, and density functional theory (DFT) calculations, we investigate three classes of materials: (i) magnetic topological semimetals, …


Computational Modeling Of Bubble Dispersion In Alginate Hydrogel Foams For Radiologically Equivalent Biomedical Phantoms, Godson N. Brako Jan 2026

Computational Modeling Of Bubble Dispersion In Alginate Hydrogel Foams For Radiologically Equivalent Biomedical Phantoms, Godson N. Brako

Graduate Studies Theses and Dissertations 2026

The foaming of hydrogels presents a promising strategy for tailoring mechanical and radiological properties to replicate biological soft tissues for biomedical phantoms. Achieving uniform and predictable void fraction distributions in alginate hydrogel foams remains a challenge due to the complex interplay between bubble dynamics, matrix rheology, and interfacial forces during the pre-gelation aeration stage. This thesis develops a Computational Fluid Dynamics framework using the transient Eulerian two-fluid approach to predict void fraction distribution in alginate hydrogel precursor solutions aerated by air injection through a bottom nozzle. The objective is to use the framework for design of the foaming system to …


Detection And Discrimination Of Targets In Infrared Imagery, Adam T. Cuellar Jan 2026

Detection And Discrimination Of Targets In Infrared Imagery, Adam T. Cuellar

Graduate Studies Theses and Dissertations 2026

Automated infrared (IR) imagery analysis is essential for persistent surveillance, defense, and security, yet it remains difficult when sensors move and when unknown objects appear. This dissertation addresses two fundamental problems: (1) detecting small moving targets amid platform-motion induced parallax and (2) distinguishing between known stationary targets and out-of-distribution (OOD) objects.   For detecting moving targets while the platform itself is in motion, auxiliary Global Positioning System and Inertial Navigation System data are combined with image analysis. Direction Cosine Matrices from calibrated inertial measurements enable sub-pixel frame alignment unattainable with purely image-based registration. The stabilized sequence is processed by a Reed–Xiaoli …


Temperature And Speciation Measurements Of Aluminum-Laden Detonation Flows Via A Three-Color Wavelength Modulation Spectroscopic Sensor, Marc B. Etienne Jan 2026

Temperature And Speciation Measurements Of Aluminum-Laden Detonation Flows Via A Three-Color Wavelength Modulation Spectroscopic Sensor, Marc B. Etienne

Graduate Studies Theses and Dissertations 2026

Tunable diode lasers are widely used and are known to be great options for continuous wave lasing applications. Because of their stability and spectral selectivity, they have become an important diagnostic tool for modern combustion research. Previous combustion research, particularly those focused on solid and hybrid rocket systems, have shown that the interaction of aluminum with a reacting flow can greatly affect the dynamics and the thermochemical properties of the surrounding gas, therefore understanding the effects of aluminum-laden flows is critical for the advancement of these propulsion systems. However, due to the high degree of optical interference, high temperatures, and …


An Examination Of The Impact Of School Accountability On Data-Driven Decision-Making By Florida Educational Leaders, Emily Galucho Jan 2026

An Examination Of The Impact Of School Accountability On Data-Driven Decision-Making By Florida Educational Leaders, Emily Galucho

Graduate Studies Theses and Dissertations 2026

This mixed-methods study examined how accountability influences educational leaders' data-driven decision-making (DDDM) practices in Central Florida. Grounded in the principal-agent and consequential accountability frameworks, the study investigated demographic predictors, implementation challenges, and the role of accountability in DDDM. Educational leaders completed online surveys measuring DDDM perceptions across five subscales and responded to open-ended questions. The responses were analyzed through multiple regression, correlation, and thematic coding.

Accountability emerged as DDDM's strongest predictor, significantly exceeding demographic and organizational variables. Five implementation challenges were identified: Data Literacy Gaps, Data Timeliness Issues, Resource Constraints, Implementation Fidelity, and Systemic Barriers. Accountability demonstrated dual effects: many …


Reflection In Still Waters: Generative Ai's Production Of Language, Jonathan D. Hawks Jan 2026

Reflection In Still Waters: Generative Ai's Production Of Language, Jonathan D. Hawks

Graduate Studies Theses and Dissertations 2026

Language is a conceptual process of meaning-making as well as a social construction as defined by Saussure, Bakhtin, and Lacan. Large Language Models (LLMs) engage with neither process and instead present language as a finished and consumable product which undermines its fundamental aspects. The difference between representing language through probability and its structural components instead of its more inherent qualities is not a pointless distinction. This paper utilizes Narcissus as a central metaphor to show how people misread the outputs of LLMs as language which imparts to those reflected words meaning on par with our own conceptualizations of reality. People …


Predicting Safety And Mobility Parameters Based On Comprehensive Analytics Of Connected Vehicle Data, Lei Han Jan 2026

Predicting Safety And Mobility Parameters Based On Comprehensive Analytics Of Connected Vehicle Data, Lei Han

Graduate Studies Theses and Dissertations 2026

Traffic safety and mobility remain critical challenges for modern transportation systems. The emergence of connected vehicle (CV) data offers unprecedented opportunities to capture microscopic, non-aggregated driving dynamics to support precise and finer-grained traffic safety and mobility research. This dissertation develops a comprehensive CV data–driven analytical framework to advance traffic safety and mobility research across multiple roadway contexts, including intersections, segments, freeways, and urban arterial networks. For traffic safety, this research extracts both longitudinal and lateral risky driving behaviors from CV trajectories and integrates them with macro-level roadway, traffic, and visual environment features. A spatial machine learning framework is proposed for …