Digital Commons Network^™

The Power Of Church Leadership Training And Development: Equipping, Empowering, And Encouraging Church Leaders To Lead Effectively, Monique Kirk

Doctor of Education Dissertations

This study explored perceptions of a church’s ministry leadership team to determine their preparation in the tools, skillsets, and strategies needed to lead themselves and others well. The study sought to understand the needs of these church ministries to meet the spiritual and daily needs of the members they serve. The study used a mixed methods design, employing a survey and focus group that examined perceptions of ministry experiences, training, development, and other support. Results were examined through the lens of Lewin’s (1947) force field analysis to determine both driving and restraining forces on effective ministry leadership (Hussain et al., …

The Implications Of Student-Centered Design On High School Dropout: The Experience Through The Lens Of Students At-Risk Of Dropping Out, Angela R. Alford

Doctor of Education Dissertations

This qualitative study explores the implications of Student-Centered Design on high school completion, particularly for students identified as at risk of dropping out. Grounded in the theory of Student-Centered Design, this research examines how this approach serves as a scaffold for collaborative problem-solving in secondary education and addressing real-world challenges faced by students at-risk of dropping out.

The study uses a qualitative methodology, utilizing a survey and a focus group to gain insight from former students who experienced Student-Centered Design, as well as educators who implemented this approach. By analyzing participant feedback, the research evaluates the effectiveness of Student-Centered Design …

An Analysis Of Elementary Teacher Working Conditions And Retention In North Carolina During The Initial Years Of The Covid-19 Pandemic, Tieshia S. Pickett

Doctor of Education Dissertations

The study aimed to investigate the impact of the COVID-19 pandemic on elementary teachers' perceptions of their working conditions and immediate professional plans in North Carolina. It compared 2018, 2020, and 2024 data to identify differences in perceptions of the pandemic. Using a nonexperimental quantitative design, the study analyzed archived data from the North Carolina Teacher Working Conditions Survey (NCTWCS) obtained from the North Carolina Education Research Data Center (NCERDC). The survey data covered pre-COVID-19 (2018), during COVID-19 (2020), and post-COVID-19 (2024) periods. The analysis focused on eight constructs: time, community support and involvement, facilities and resources, managing student conduct, …

Perception Of Middle School Counselors About How To Increase The Enrollment Of Minority Students, Specifically African American And Hispanic, In The Health Science Curriculum At Empire High School, Charles S. Robertson

Doctor of Education Dissertations

This study explored the perceptions of middle school counselors regarding strategies to increase enrollment of minority students, specifically African American and Hispanic, in the health science curriculum at Empire High School. Utilizing a mixed methods convergent parallel design, this research integrated both quantitative and qualitative data to provide a comprehensive understanding of counselor viewpoints, existing barriers, and potential solutions. Lewin’s Change Model, as outlined by Burnes (2019), provided the theoretical framework for the analysis, guiding it through the stages of unfreezing existing mindsets, implementing change, and refreezing new practices. Quantitative data were collected via surveys administered to middle school counselors …

A Phenomenological Exploration Of Students' Perceptions Of Social-Emotional Factors In Teacher-Student Relationships And Its Impact On Academic Achievement Of Impoverished High School Youth, Jeannine L. Carrington

Doctor of Education Dissertations

This phenomenological study explored the experiences of former students from a Title I high school in a disadvantaged urban community, focusing on how socio-emotional factors in teacher-student relationships influenced academic achievement. Grounded in Bandura’s (1977) social learning theory and the CASEL (2017) social-emotional learning (SEL) framework, the study examined how teacher encouragement, emotional support, and expectations impacted student motivation and persistence. Twenty alumni participated in semi-structured interviews, analyzed using Braun and Clarke’s (2006) thematic analysis. Five themes emerged: teacher encouragement, emotional support, high expectations, cultural awareness, and long-term impact. Findings suggest that emotionally supportive, trusting relationships foster self-efficacy, engagement, and …

Exploring Teacher Perceptions And Implementation Factors Influencing Career Development Plan Completion In Middle Grades: A Study Of The Majorclarity Platform, Keri Marie Brewer

Doctor of Education Dissertations

This qualitative study investigated the implementation fidelity, teacher perceptions, and contextual factors influencing the use of the MajorClarity career readiness platform to support career development plan (CDP) completion among middle grade students in a North Carolina school district. Guided by Bandura’s (1986) Social Cognitive Theory and Darling-Hammond et al.’s (2001) Learning Theory, the study explored how instructional strategies, training quality, leadership support, and systemic barriers shape program outcomes. Data were collected through two rounds of semi-structured interviews with six Career and Technical Education teachers, using inductive thematic analysis to identify patterns across participant responses. Findings revealed that while educators recognized …

A Phenomenological Study On How White Public Middle School Teachers Who Self-Identify As Racial Allies Experience And Navigate Their Implicit Biases, Joyce Faye Patton

Doctor of Education Dissertations

The teaching force in the United States is overwhelmingly White, while the student population is increasingly diverse, reaching a minority majority in 2014. The racial mismatch between a predominantly White teaching force and students of color in public schools presents barriers for those students as they navigate an educational system built on historical injustices and racism. The study examines the lived experiences of White middle school teachers who identify as racial allies in schools having a student population that is greater than 50% students of color. The interviews revealed that participants understood bias on a basic level yet continued to …

Investigating Teacher Self-Efficacy And Teacher Attitudes Toward Stem In North Carolina High School Science And Mathematics Classrooms, Kelly J. Ruff

Doctor of Education Dissertations

The purpose of this investigation was to determine if North Carolina high school science and mathematics teachers differ in their STEM teacher self-efficacy, outcome expectancy, and attitudes toward STEM instructional practices. The data collection instrument used in this study was the T-STEM survey. Science and math teachers voluntarily participated in the study and answered Likert-type survey items focusing on STEM teacher self-efficacy, STEM instructional practices, and outcome expectancy. Additionally, study participants answered demographic questions on gender, years of teaching experience, and the type of degree earned. Sub-scores for each survey section were calculated and analyzed with descriptive and inferential statistical …

Teacher And Parent Perspectives Of Young Children's Development Since The Covid-19 Pandemic In A Rural Public School District, Regina L. Lineback

Doctor of Education Dissertations

Face to face education for young children was interrupted in March of 2020 due to mandatory school closures precipitated by the COVID-19 pandemic. Virtual learning was forced upon teachers and students at a time when many families and teachers had limited or no access to internet. When face to face learning resumed, teachers and students were required to wear facial masks and maintain social distancing protocols. This study sought to explore teacher and parent perspectives of young children’s development in a rural public school district since the COVID-19 pandemic. A qualitative study was completed using teacher interviews, a teacher focus …

Spatial And Temporal Shifts In Bacterial Communities And Nutrient Removal In Two Springfield Wastewater Facilities, Rubina Sherchan

Graduate Theses/Dissertations

Bacterial communities play a central role in the biological nutrient removal and overall performance of wastewater treatment plants (WWTPs). However, very few is known about the spatial and seasonal dynamics of these communities. This study explores the spatial and seasonal variations in bacterial community composition across multiple treatment stages in two municipal WWTPs—Southwest (SWTP) and Northwest (NWTP)—in Springfield, Missouri. Using 16S rRNA gene amplicon sequencing, I analyzed 87 samples collected during summer and winter of 2024 from influent, sludge, aeration basins, clarifiers, and final effluent stages. I retrieved 16.4 million (summer) and 3.2 million (winter) sequences. Proteobacteria dominated both seasons …

Preparing The Built Environment In Grenada For Future Sea Level Rise And Extreme Precipitation Events, Rocco D. Boyd, Meagan P. Duncan, Alivia D. Markham, Adelle K. Novak, Blaizen B. Bloom, Ashawne Edwards, Jai S. Lewis, Hans-Peter Plag

CCPO Publications

[Introduction] Communities across the globe are being affected by climate change in numerous ways. However, those most often affected, especially by sea level rise, are those small island nations that are pressed for space already; this includes the island of Grenada. Grenada is located in the southern portion of the Caribbean and is bordered by the Caribbean Sea (West) and the Atlantic Ocean (East). The planning and development authority (PDA) has been identified as the main stakeholder involved in this case study, but recommendations will be made to all parties involved to best accomplish our mission.

Key stakeholders were initially …

Multi-Model Estimate Of Antarctic Ice-Shelf Basal Mass Budget And Ocean Drivers, Benjamin K. Galton-Fenzi, Richard Porter-Smith, Sue Cook, Eva Cougnon, David E. Gwyther, Wilma G. C. Huneke, Madelaine G. Rosevear, Xylar Asay-Davis, Fabio Boeira Dias, Michael S. Dinniman, David Holland, Kazuya Kusahara, Kaitlin A. Naughten, Keith W. Nicholls, Charles Pelletier, Ole Richter, Hélène Seroussi, Ralph Timmerman

CCPO Publications

Societal adaptation to rising sea levels requires robust projections of the Antarctic Ice Sheet's retreat, particularly due to ocean-driven basal melting of its fringing ice shelves. Recent advances in ocean models that simulate ice-shelf melting offer an opportunity to reduce uncertainties in ice–ocean interactions. Here, we compare several community-contributed, circum-Antarctic ocean simulations to highlight inter-model differences, evaluate agreement with satellite-derived melt rates, and examine underlying physical processes. All but one simulation use a melting formulation depending on both thermal driving (T^⋆) and friction velocity (u^⋆), which together represent the thermal and ocean current forcings at the …

Improving Understanding And Connections For Preparedness, Mitigation, Response, And Recovery For Tornado And Straight-Line Wind Events In Virginia: Summary Of The Inaugural Virginia Tornado And Straight-Line Wind Summit, Wie Yusuf, Monica Arul, Joshua Behr, Kaleen Lawsure, An Huy Pham, Henry Attivor

School of Public Service Faculty Publications

Background

The Virginia Tornado and Straight-Line Wind Summit, the first of its kind in the Commonwealth, was held on October 15, 2025 in Isle of Wight County, Virginia. The Summit had several goals, including:

• Understanding Virginia’s wind risk and learning the science behind it.
• Hearing lessons learned from emergency managers who have experienced extreme wind events.
• Learning about practical steps to prepare, mitigate, and respond to severe wind events.
• Learning best practices for timely and actionable communication with the public before and after events.
• Strengthening interagency coordination and connecting with others to share resources, align priorities, and coordinate resilience planning. …

Ai-Generated Messaging For Life Events Using Structured Prompts: A Comparative Study Of Gpt With Human Experts And Machine Learning, Christopher Lynch, Erik Jensen, Ross Gore, Virginia Zamponi, Kevin O'Brien, Brandon Feldhaus, Katherine Smith, Joseph Martínez, Madison H. Munro, Timur E. Ozkose, Tugce B. Gundogdu, Ann Marie Reinhold, Hamdi Kavak, Barry Ezell

VMASC Publications

Large Language Models (LLMs) play an increasingly integrated and pivotal role in generating diverse types of texts, such as social media messages, emails, narratives, and technical reports, among other textual communication forms. As AI-generated messaging filters into human communication, a systematic exploration of their effectiveness for mimicking human-like communication of life events is needed. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 life event messages for birth, death, hiring, and firing events using OpenAI's GPT-4. From this dataset, we manually classify 2880 messages and evaluate their validity in conveying these life events through the form …

Advances In Bacterial Cellulose-Based Scaffolds For Tissue Engineering: Review, Rewati Raman Ujjwal, Gymama Slaughter

Center for Bioelectronics Publications

Bacterial cellulose (BC) has emerged as a highly versatile and promising biomaterial in tissue engineering, with potential applications across skin, bone, cartilage, and vascular regeneration. Its exceptional properties like high mechanical strength, superior biocompatibility, excellent moisture retention, and inherent ability to support cell adhesion and proliferation, make BC particularly effective for wound healing and skin regeneration. These attributes accelerate tissue repair and foster new tissue formation, highlighting its value in skin-related applications. Additionally, BC's capacity to support osteogenic differentiation, combined with its mechanical robustness, positions it as a strong candidate for bone tissue engineering, facilitating regeneration and repair. Recent advancements …

Electrochemical And Nanomaterial Based Strategies For Nonenzymatic Glucose Detection: A Review, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Electrochemical glucose sensing technologies have undergone significant evolution, with continual advancements aimed at improving sensitivity, selectivity, and user convenience. This review systematically explores the development of emerging nonenzymatic glucose sensor designs. Nonenzymatic sensors are critically evaluated for their ability to overcome enzymatic limitations, leveraging novel materials and catalytic mechanisms. Additionally, the emergence of smartphone-integrated glucose monitoring systems is highlighted as the fifth generation, representing a paradigm shift toward personalized, real-time healthcare management. Emphasis is placed on the strategies employed to reduce the working electrode potential and enhance analytical performance. Key analytical metrics and real-sample applicability are evaluated, and persistent challenges …

Gold Nanoparticle-Enhanced Molecularly Imprinted Polymer Electrode For Non-Enzymatic Lactate Sensing, Christopher Animashaun, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

We are reporting the development of a high-performance, non-enzymatic electrochemical biosensor for selective lactate detection, integrating laser-induced graphene (LIG), gold nanoparticles (AuNPs), and a molecularly imprinted polymer (MIP) synthesized from poly(3,4-ethylenedioxythiophene) (PEDOT). The LIG electrode offers a highly porous, conductive scaffold, while electrodeposited AuNPs enhance catalytic activity and signal amplification. The PEDOT-based MIP layer, electropolymerized via cyclic voltammetry, imparts molecular specificity by creating lactate-specific binding sites. Cyclic voltammetry confirmed successful molecular imprinting and enhanced interfacial electron transfer. The resulting LIG/AuNPs/MIP biosensor demonstrated a wide linear detection range from 0.1 µM to 2500 µM, with a sensitivity of 22.42 µA/log(µM) and …

Evaluating The Long-Term Effectiveness Of Marsh Terracing For Conservation With Integrated Geospatial And Wetland Simulation Modeling, Nick Carpenter, Laura Costadone, Thomas R. Allen

ODU Articles

Coastal marshes provide essential ecosystem services, yet they are vulnerable to anthropogenic stressors and climate change, particularly sea level rise (SLR). Restoration approaches like marsh terracing have emerged as nature-based strategies to enhance resilience and reduce habitat loss. This study applies the Sea Level Affecting Marshes Model (SLAMM) to assess the potential of marsh terraces to mitigate future losses, while also examining the model’s limitations, including its assumptions and capacity to reflect complex marsh processes. A geospatial approach was used to generate 3D representations of terraces through morphostatic modeling within digital elevation models (DEMs). Under a no-restoration scenario, SLAMM projections …

Qos-Aware Link Adaptation For Beyond 5g Networks: A Deep Reinforcement Learning Approach, Ali Parsa, Neda Moghim, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Modern wireless communication systems face increasingly complex challenges due to rapidly changing channel conditions and the growing diversity of application-specific Quality of Service (QoS) requirements. Traditional link adaptation mechanisms primarily aim to maximize throughput and often lack the flexibility to support emerging applications, such as Extended Reality (XR) and Virtual Reality (VR), which demand simultaneous guarantees for high data rates, ultra low latency, and high reliability. These stringent and multidimensional QoS needs call for more intelligent and adaptive solutions. In this paper, we propose QDRLLA (QoS-aware Deep Reinforcement Learning-based Link Adaptation), a novel framework that employs deep reinforcement learning to …

A Trust-By-Learning Framework For Secure 6g Wireless Networks Under Native Generative Ai Attacks, Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Sixth-generation (6G) wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particular, network parameters and metrics in cross-layer design pose fundamentally uncertain conditions and can be compromised through the native GenAI mechanism, which leverages data augmentation and reconstruction capabilities. This work investigates the capabilities of native GenAI to create novel poisoning attacks in wireless networks, while investigating their impact through uncertainty-informed root analysis. Then, detected attacks are mitigated by developing a trustworthy service aggregation in the wireless network. First, a joint decision problem is formulated …

Essays On Innovation And Labor Market Benefits, Kyoungah Noh

Electronic Theses & Dissertations (2024 - present)

The first chapter examines the impact of bank failures on team-based innovation, focusing on the persistence of inventor teams under credit supply constraints. Using U.S. patent and FDIC data from 2000 to 2012, this paper presents three main findings. First, bank failures significantly reduce both the number of team patents and the number of inventors with collaborators. Second, negative banking shocks decrease the likelihood that inventor teams remain together for projects in subsequent periods. However, team-specific factors, including geographic proximity, prior collaboration experience, and smaller team sizes, mitigate the adverse effects of bank failures and help preserve the stability of …

Theoretical Foundations And Applied Performance Of Periodicity-Aware Imputation: Variable Bandpass Block Bootstrap Methods For Incomplete Time Series, Asmaa Ahmad

Electronic Theses & Dissertations (2024 - present)

Time series data are prevalent across a wide range of disciplines, including health surveillance, public policy, and environmental monitoring. In the presence of underlying cyclical patterns, the integrity of time series analysis depends critically on the ability to detect, model, and impute structured missing data without compromising the temporal structure. This dissertation introduces and validates a novel imputation framework that integrates the Variable Bandpass Periodic Block Bootstrap (VBPBB) into multiple imputation procedures, improving the accuracy, robustness, and interpretability of time series models under high rates of missingness and noise. The overarching goal of this dissertation was to develop and evaluate …

Development Of Group Iii-V Quantum Confinement-Enabled Detectors: Bias-Tunable Quantum Well Infrared Photodetector (Qwip) And Quantum Dot Scintillation Detector (Qdsd), Gyana R. Biswal

Electronic Theses & Dissertations (2024 - present)

This dissertation discloses the physics, fabrication, characterization, and analysis of two novel types of group III-V semiconductor detectors relying on quantum confinement of carriers, namely voltage-tunable quantum well infrared photodetectors (QWIP) and a high-yield ultrafast quantum dot scintillation detector (QDSD). Both QWIP and QDSD heterostructures presented here were grown on 3” GaAs (001) substrates using molecular beam epitaxy (MBE).

A major part of the dissertation focuses on development of the voltage-tunable QWIPs targeting detection in the mid-wave infrared region (MWIR) (3μm -5μm) and long-wave infrared region (LWIR) (8μm -12μm) with control of sensitivity by the applied bias. The QWIPs utilize …

Leveraging Custom Gpts For Formative Assessment And Feedback, Nari Kim, Jason Vickers, Shaimaa Alyehaibi, Chikezie Ozuzu, Xinyue Ren, Suhasini Kotcherlakota

STEMPS Faculty Publications

As artificial intelligence (AI) advances, the use of custom generative pre-trained transformers (Custom GPTs) in formative assessments opens new opportunities for improving student learning and engagement. Custom GPTs increase cognitive and emotional engagement by providing timely, context-sensitive, and tailored responses based on unique learner profiles. This paper aims to investigate how custom GPT-driven formative feedback can enhance individualized learning experiences and improve student performance. This paper will discuss the promise of this AI tool, the challenges associated with its application, and recommendations for educators and academics looking to use these technologies for formative assessments.

Technology Integration In Online Feminist Pedagogy, Xinyue Ren

STEMPS Faculty Publications

Feminist pedagogy refers to a liberatory way of teaching to develop democratic and transformative learning experiences in which students can be empowered to make a social change (Grissom-Broughton, 2020). Previous research showed that feminist pedagogy was often used to guide course design and development in various disciplines, such as music, art, language, and environmental education (Cannizzo, 2021; Grissom-Broughton, 2020; Jespersen, 2014; Springgay & Zaliwska, 2017). For example, in music education, instructors increased the representations of multicultural voices in course materials and applied in-depth discussions and essays as learning assessments to develop critical and reflective thinking among students. In a feminist-oriented …

The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis

STEMPS Faculty Publications

Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …

University Of Texas At Tyler Course Catalog, 2025-2026, University Of Texas At Tyler

Catalogs

No abstract provided.

University Of Texas At Tyler Catalog, 2025-2026, University Of Texas At Tyler

Catalogs

No abstract provided.

The Antitrust-Copyright Interface In The Age Of Generative Artificial Intelligence, Daryl Lim, Peter K. Yu

Emory Law Journal

The U.S. government’s antitrust actions against Big Tech have recently surged in response to the growing dominance of Amazon, Apple, Google, Meta, and Microsoft. In fall 2023, the Federal Trade Commission filed a controversial submission in response to the U.S. Copyright Office’s request for comments on artificial intelligence (AI) and copyright. The agency’s submission hinted at its eagerness to fully deploy its enforcement powers in the AI sector, including targeting AI developers that have used copyrighted works without authorization to train AI models. This Article examines the changing interface of antitrust and copyright law in the age of generative AI. …

A Clash Of The Clauses: The Constitutionality Of The Nation’S First Public, Religious Charter School, Alisha Camacho Clegg

Oklahoma Law Review

No abstract provided.