Digital Commons Network^™

Aiming High: A Narrative Inquiry Of Christian Music Educators’ Higher Purpose, William E. Rhoden Iii

Doctoral Dissertations and Projects

Educators in the United States may question music education’s higher purpose, considering high-stakes testing and an emphasis on non-musical subjects. This qualitative narrative study examines three American protestant Christian music educators’ perceptions of music education’s higher purpose and compares them to Martin Luther’s (1483-1546) writings. The researcher conducted interviews with three participants to record the story of how they developed their higher purpose for music education. The data was tabulated and coded for thematic analysis. This study supports a Christian defense of continued music education in America’s schools, distinguishes modern Christian perspectives, and offers a fresh understanding of the historical …

A Descriptive, Comparative Study Of Preexisting Leadership Qualities And Leadership Effectiveness Of Theologically Conservative United States Army Battalion-Level Chaplains, Aaron Jonathan Fabian

Doctoral Dissertations and Projects

This immediate demand for spiritual and professional leadership can be overwhelming for a new battalion-level chaplain (Blackaby 2001; Howell 2003). They perform or provide religious service for Soldiers who have volunteered to serve their country. By going through the same military training in conjunction with their religious education and experience, chaplains are able to integrate with Soldiers where traditional clergy cannot. There is additional pressure to perform because chaplains, as commissioned officers, are evaluated immediately through an annual Officer Evaluation Report (OER hereafter, DA Form 67-9). With no time to acquire new skills, battalion-level chaplains are forced to rely on …

Resources And Readiness: Exploring The Lived Experiences Of Secondary Teachers In Rural Texas With Being Prepared For Students Diagnosed With Attention-Deficit Hyperactivity Disorder In Their Classrooms, Barbara L. Chase

Doctoral Dissertations and Projects

This dissertation examines how prepared secondary teachers in Texas rural public schools are to work with students diagnosed with attention deficit hyperactivity disorder (ADHD) who are placed in their classrooms. I investigated the professional development and higher educational training experiences of secondary teachers regarding contributions to both their knowledge of the etiology of ADHD and interventions and behavior management strategies. This dissertation was motivated by a curiosity to understand how secondary teachers in rural schools describe the knowledge they obtained regarding ADHD etiology and interventions through their higher education programs and professional development opportunities. As well as a desire to …

Dunning-Kruger And The Reforming Mind: A Causal-Comparative Study Determining The Role That Confidence When Learning Mathematics Plays In Sixth-Grade Students' Mathematics Performance, Rita Renata Davison-Yragui

Doctoral Dissertations and Projects

The purpose of this quantitative non-experimental causal-comparative study was to determine the relationship between sixth-grade students’ confidence level (high, middle, or low) when learning mathematics and their mathematical performance. This study adds to the current body of knowledge on student learning and contributes to a better understanding of the impact of confidence on student performance in mathematics. The sample comprised 132 sixth-grade public school math students in western Washington who completed the i-Ready diagnostic to determine their mathematical performance. The confidence when learning mathematics portion of the Attitudes to Technology in Mathematics Learning Questionnaire was used to measure student confidence …

Investigating The Influence Of Modern And Traditional Instructional Practices On Creating Lifelong Habits Of Music Engagement In The Prospect Mountain Schools System, Thomas D. Stevens Jr.

Doctoral Dissertations and Projects

The purpose of this study was to investigate the impact of modern and traditional pedagogical approaches on student development of music engagement and learning in the Prospect Mountain Schools system during and after high school. Student retention is critical to maintaining music programs; therefore, educators must discover ways to motivate students to continue participating in general music and ensemble courses. Combining modern and traditional pedagogical approaches creates learning experiences that inspire students to continue playing music throughout their lives, both during and after high school. One of these pedagogical practices is incorporating popular music into the classroom, which can enhance …

A Phenomenological Study Of String Teacher Perceptions Of Professional Development At Three Career Stages, Michael James Hanf

Doctoral Dissertations and Projects

This hermeneutic phenomenological study aims to understand the perceptions of elementary and secondary string teachers’ experiences with quality professional development from early-, middle-, and late-career stages. This study analyzes perceptions of quality professional development for music teachers, including content-related, evidence-based, applicable, relevant, collaborative, providing feedback, actively involving teachers in learning, longitudinal, coherent, and allowing for reflection. It follows a hermeneutic phenomenological research design guided by the theory of human motivation and aims to understand how professional development affects teacher needs. Participants include elementary and secondary string teachers across the United States from early-, middle-, and late-career stages. String teachers sampled …

Effects Of Domestic Violence On Third-Grade Students' Academic And Behavioral Performance, Leah N. Gordone

Doctoral Dissertations and Projects

The purpose of this quantitative, causal-comparative study was to investigate the relationship between witnessing domestic violence and third-grade students' academic performance and behavioral conduct, with a focus on gender differences. Additionally, the study explored the connection between exposure to domestic violence and English Language Arts achievement. The research involved 280 third-grade students and parents at the Boys & Girls Clubs of America in southwestern Georgia. Participants were part of social-emotional learning programs. Data collection included parent observation surveys, end-of-grade test scores (using the Georgia Milestones End-of-Grade assessment), and a child survey (the Violence Exposure Scale for Children – Revised). The …

Efficient Fully Bayesian Approach To Brain Activity Mapping With Complex-Valued Fmri Data, Zhengxin Wang, Daniel B. Rowe, Xinyi Li, D. Andrew Brown

Mathematical and Statistical Science Faculty Research and Publications

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. We propose a fully Bayesian model for brain activity mapping with cv-fMRI data. Our model accommodates temporal and spatial dynamics. Additionally, we propose a computationally efficient sampling algorithm, which enhances processing speed through image partitioning. Our approach is shown to be …

Glacial-Interglacial And Millennial-Scale Changes In Nitrous Oxide Emissions Pathways And Source Regions, J. A. Menking, J. E. Lee, E. J. Brook, J. Schmitt, L. Soussaintjean, H. Fischer, J. Kaiser, A. Rice

Physics Faculty Publications and Presentations

During the transition from the Last Glacial Maximum (LGM) to the Holocene, the atmospheric N2O mole fraction increased by 80 nmol mol−1. Using ice core measurements of N2O isotopomer ratios, we show that this increase was driven by increases in both nitrification and denitrification, with the relative partitioning between both production pathways depending on the assumed isotopic end‐member source signatures. Similarly, we also attribute a 35 nmol mol−1 N2O mole fraction increase during the Heinrich Stadial 4/Dansgaard Oeschger 8 (HS4/DO8) millennial‐scale event to increases in both N2O production pathways. In contrast, the 25 nmol mol−1 N2O mole fraction decrease during …

Brain Morphometry In Infants Later Diagnosed With Autism Is Related To Later Language Skills, Luke E Moraglia, Kelly N Botteron, Natasha Marrus, Et Al.

2020-Current year OA Pubs

Autism spectrum disorder (ASD) presents early in life with distinct social and language differences. This study explores the association between infant brain morphometry and language abilities using an infant-sibling design. Participants included infants who had an older sibling with autism (high likelihood, HL) who were later diagnosed with autism (HL-ASD; n = 31) and two non-autistic control groups: HL-Neg (HL infants not diagnosed with autism; n = 126) and LL-Neg (typically developing infants who did not have an older sibling with autism; n = 77). Using a whole-brain approach, we measured cortical thickness and surface area at 6 and 12 …

High-Dimensional Mediation Analysis For Longitudinal Mediators And Survival Outcomes, Lili Liu, Haixiang Zhang, Yinan Zheng, Tao Gao, Cheng Zheng, Kai Zhang, Lifang Hou, Lei Liu

2020-Current year OA Pubs

Mediation analysis with high-dimensional mediators is crucial for identifying epigenetic pathways linking environmental exposures to health outcomes. However, high-dimensional mediation analysis methods for longitudinal mediators and a survival outcome remain underdeveloped. This study fills that gap by introducing a method that captures mediation effects over time using multivariate, longitudinally measured time-varying mediators. Our approach uses a longitudinal mixed effects model to examine the relationship between the exposure and the mediating process. We connect the mediating process to the survival outcome using a Cox proportional hazards model with time-varying mediators. To handle high-dimensional data, we first employ a mediation-based sure independence …

Relationship Between Local Fiscal Effort And High School Graduation Rate, Zachary Michael Haney

Educational Leadership & Workforce Development Theses & Dissertations

Education is an investment in human capital, but the cost to provide this public service is significant. Understanding the return on this investment is essential for informed and effective financial decision-making. While previous school finance studies have examined the relationship between funding and various indicators of student achievement and student attainment, most have focused on spending practices rather than the level of investment itself. Although the literature affirms the need for educational resources, further research is required to determine which types of investment most positively affect student outcomes. Therefore, funding must be analyzed prior to budgetary allocation to evaluate its …

Assessing Chatgpt's Capability As A New Age Standardized Patient: Qualitative Study, Joseph Cross, Tarron Kayalackakom, Raymond E. Robinson, Andrea Vaughans, Roopa Sebastian, Ricardo Hood, Courtney Lewis, Sumanth Devaraju, Prasanna Honnavar, Nikhilesh Anand

School of Medicine Publications

Background: Standardized patients (SPs) have been crucial in medical education, offering realistic patient interactions to students. Despite their benefits, SP training is resource-intensive and access can be limited. Advances in artificial intelligence (AI), particularly with large language models such as ChatGPT, present new opportunities for virtual SPs, potentially addressing these limitations.

Objectives: This study aims to assess medical students' perceptions and experiences of using ChatGPT as an SP and to evaluate ChatGPT's effectiveness in performing as a virtual SP in a medical school setting.

Methods: This qualitative study, approved by the American University of Antigua Institutional Review Board, involved 9 …

Political Threads In Legal Tapestry: A Computational Analysis Of Executive Branch Legal Interpretation, 1934–2022, Reilly S. Steel

Faculty Scholarship

How does the push and pull between law and politics shape the work of executive branch lawyers charged with providing “neutral” interpretations of the law? To shed light on this longstanding question, this Article undertakes the first large-scale computational analysis of legal interpretation in the executive branch of the United States federal government. Using a new dataset comprised of the texts of 12,879 pages of opinions issued by the Office of Legal Counsel (OLC) in the Department of Justice (DOJ), I use machine learning methods to explore markers of partisanship and ideology in these high-profile executive branch decisions.

Several important …

Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

Sporadic-E (E_s) is an ionospheric phenomenon defined by strong layers of plasma which may interfere with radio wave propagation. In this work, we develop deep learning models to improve the understanding of E_s, including the presence, intensity and height of the layers. We developed three separate models. The first, building off earlier work in (J. A. Ellis et al., 2024, link in AFIT Scholar, 10.1029/2023sw003669), includes only the main features from radio occultation (RO) measurements. The second adds to that time, date, location, geomagnetic and solar indices, solar winds, x-ray flux, weather and lightning. A …

Recommendations For Design, Execution, And Reporting Of Studies On Experimental Thoracic Aortopathy In Preclinical Models, Alan Daugherty, Dianna M Milewicz, David A Dichek, Ketan B Ghaghada, Jay D Humphrey, Scott A Lemaire, Yanming Li, Ziad Mallat, Yvan Saeys, Hisashi Sawada, Ying H Shen, Toru Suzuki, Zhen Zhou

Faculty, Staff and Students Publications

There is a recent dramatic increase in research on thoracic aortic diseases that includes aneurysms, dissections, and rupture. Experimental studies predominantly use mice in which aortopathy is induced by chemical interventions, genetic manipulations, or both. Many parameters should be deliberated in experimental design in concert with multiple considerations when providing dimensional data and characterization of aortic tissues. The purpose of this review is to provide recommendations on guidance in (1) the selection of a mouse model and experimental conditions for the study, (2) parameters for standardizing detection and measurements of aortic diseases, (3) meaningful interpretation of characteristics of diseased aortic …

Digital Twins, Synthetic Patient Data, And In-Silico Trials: Can They Empower Paediatric Clinical Trials?, Mohan Pammi, Prakesh S Shah, Liu K Yang, Joseph Hagan, Nima Aghaeepour, Josef Neu

Faculty, Staff and Students Publications

Randomised controlled trials are the gold standard to assess the effectiveness and safety of clinical interventions; however, many paediatric trials are discontinued early due to challenges in patient enrolment. Hence, most paediatric clinical trials suffer from lack of adequate power. Additionally, trials are expensive and might expose patients to unproven therapies. Alternatives to overcome these issues using virtual patient data—namely, digital twins, synthetic patient data, and in-silico trials—are now possible due to rapid advances in digital health-care tools and interventions. However, such digital innovations have been rarely used in paediatric trials. In this Viewpoint, we propose using virtual patient data …

Cortical Structure In Nodes Of The Default Mode Network Estimates General Intelligence, Abhinav Yadav, Archana Purushotham

Faculty, Staff and Students Publications

Introduction: A growing number of studies implicate functional brain networks in intelligence, but it is unclear if network nodal structure relates to intelligence.

Methods: Using MRI, we studied the relationship of the general intelligence factor (g) with cortical thickness (CT), local gyrification index (LGI), and voxel-based morphometry in the nodes of the default mode network (DMN) and task-positive network (TPN) in a cohort of 44 young, healthy adults. Employing a novel strategy, we performed repeated analyses with multiple sets of g estimates to remove false positives.

Results: CT and LGI in medial and temporal nodes of the DMN were reliably …

Estimation Of Breach Hydrograph Resulting From Dam Embankment Failure Due To Internal Erosion Or Overtopping: Comparison Of Simplified Methods With Real-Case Failure Data And Recommendations, Laurent Del Gatto, Jean-Robert Courivaud

5th International Seminar on Dam Protections Against Overtopping

The opening of a breach in an embankment dam, whether due to overtopping or internal erosion, is a critical failure mode for these structures. Estimating the resulting breach hydrograph is essential for assessing downstream risks. While no universal physical model covers all dam types, empirical formulas are commonly used. EDF analyzed 14 such formulas, comparing them with rupture data from 32 embankment dam failures. The best formulas - Froehlich 1995, Xu & Zhang 2009, and CLF 2020 - yield a “best estimate” for peak flow. However, due to variability, results should be interpreted cautiously. Consider estimating breach characteristics like width …

Sabrina Vs Steph: The Battle Between The Wnba And Nba, Naysha Mcgriff

Symposium of Student Scholars

The average salary of a Women’s National Basketball Association (WNBA) player is 110 times less than a National Basketball Association (NBA) player’s. Despite growing WNBA viewership, gender inequality in sports remains high, with critics claiming female athletes are less skilled. Gender bias in sports is severely understudied, making direct comparisons to men’s leagues unfair due to long-term lack of investment in women’s sports. This study investigates whether the perceived disparity in skill levels between WNBA and NBA players' is genuine or influenced more by external factors by developing an unbiased measure of player efficiency to compare athletic performance. This dataset …

Zeros Of L-Functions And Arithmetic, Micah Milinovich

Showcase of Research and Scholarly Activity

The PI currently holds two awards: NSF DMS 2401461 (Zeros of L-functions and Arithmetic) and NSF DMS 2101912 (The Distribution of the Zeros of L-functions and Related Questions). These awards concern research in number theory, a very active area of mathematics. L-functions have played a pivotal role in the modern development of number theory and they can be used to study a wide variety of problems. The tools used to study L-functions draw from many branches of mathematics including analysis, algebra, algebraic geometry, representation theory, and mathematical physics while number theory has important applications outside of mathematics to fields such …

2025 Nsf Career: Portable Wind Tunnel, Wen Wu

Showcase of Research and Scholarly Activity

As part of his NSF CAREER grant, Dr. Wu will collaborate with the University of Mississippi Museum to host the Art of Fluid exhibition. The exhibit will showcase artistic visualizations of fluid dynamics research and include live wind tunnel demonstrations. Dr. Wu will also launch a Mobile Fluid Exposition Program to engage high school students throughout north Mississippi, aiming to inspire interest in STEM through hands-on activities. The Center for Mathematics and Science Education (CMSE) will support this outreach effort.

Structure Disorder And Magnetic Behavior Of An Olivine-Type Cathode Material, Hamida Hassan, Madalynn Marshall

Symposium of Student Scholars

Our research investigates the structure disorder and magnetic behavior of Li(Mn,Fe)PO₄, an olivine-type material relevant for lithium-ion battery applications. Using single-crystal neutron diffraction at Oak Ridge National Laboratory, we precisely determined Mn and Fe occupancy, revealing a 56% Fe and 44% Mn distribution at the atomic 4c site within the Pnma space group. Additionally, we observed significant lithium site vacancies (78% occupied), influencing the material's electrochemical and magnetic properties. The varying Mn/Fe ratio affected spin reorientation transitions, shifting from antiferromagnetic alignment along the a-axis to the b-axis. Our findings provide crucial insights for optimizing olivine-based cathodes, enhancing energy …

Campus Navigator: A Mobile App For Seamless University Navigation, Hafsa Mohammed, Ali Rahimzadehfard, Rachab Wilson, Mathias Rossi, Turaj Ashuri, Amir Ali Amiri Moghadam

Symposium of Student Scholars

Navigation services play a big role in everyone’s daily lives, from directing them on new roads to guiding them through buildings. Outdoor navigation services have evolved from physical maps to digital ones like Google Maps for ease of use and accessibility. Upon conducting literature research, the team found that many navigation apps lack clear and accurate instructions for how to navigate university campuses such as Marietta campus. Due to the size of KSU’s Marietta campus and its buildings, effortless navigation has been a common challenge for students, faculty, and visitors alike. Additionally, all buildings are referred to by letters, numbers, …

Computational Study Of The Proton Transfer In The H7o3+ Cluster, Anna James, Martina Kaledin

Symposium of Student Scholars

Proton transfer (PT) from one molecule to another is among the most studied phenomena in chemistry. PT requires the bond cleavage and the formation of a new one, AH⁺ + B -> A+ BH⁺. In protonated water clusters, such a process consists of the interconversion of hydrogen bonds. Experimentally, such a process can be observed as a significant increase of a dipole moment. However, other vibrational transitions often occur with small changes in the dipole moment while large changes in polarizability. In this work, we study the PT process in a protonated water cluster, H₇O …

Overcoming Motor Imagery Bci Illiteracy: Adaptive Decoding And Knowledge Transfer In Eeg-Based Brain-Computer Interfaces, Zaid Shuqfa Shuqfa

Thesis/ Dissertation Defenses

Brain Computer Interface (BCI), Also known as brain-machine interface (BMI) is a mean of controlling machines without the need to activate peripheral nerves or muscles. It has received the attention of research for decades. Motor imagery-based BCI is a paradigm that is characterized by its user friendliness where users can generate control commands at their freewill, without waiting for a que from the BCI module. Motor imagery brain–computer interface (MI–BCI) has considerable potential in increasing the quality of the lives for people with mobility impairment and the healthy ones as well. Though, its diffusion in application still has many pitfalls …

Deep Learning Algorithms For Traffic Flow Predictions, Adegoke Ojeniyi, Prince Pal Singh, Ankita Vashisht, Swati Kumari, Karan Karan

AUIQ Technical Engineering Science

Given the growing complexity of urban transportation systems, precise traffic flow forecasting is essential for reducing not only issues of congestion but also, for boosting road safety and enhancing mobility management. This study integrates Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Long Short-Term Memory (LSTM), and Recurrent Neural Networks (RNN) to present a hybrid deep learning framework for traffic prediction. Of these, the CNN-LSTM model is a reliable option for real-time traffic forecasting since it successfully captures both spatial and temporal dependencies, resulting in superior predictive performance. The dataset used to assess the framework includes 48,120 records from a traffic monitoring …

Investigating The Impact Of Waterhead, Time And Temperature On Dam Displacement: Application Of Computer Aided Models, Maaz Abdullah

AUIQ Technical Engineering Science

Dam displacement is a crucial indicator for assessing the safety of a concrete dam through structural health monitoring. Since the displacement data exhibits a non-linear and complex relationship with influencing factors like waterhead, time and temperature, machine learning models are deployed to accurately predict dam displacement. Furthermore, the limited availability of monitored data in the majority of the dams renders the studies conducted with a large number of observations valueless. In order to address the aforementioned issues, this study proposes a feature selection approach to predict dam displacement by examining the ability of four ensemble machine learning models on different …

Investigating The Differential Effects Of Smote Variants On Class Imbalance And Exploring Their Applicability To A Thalassemia Prediction Model, Hussam Mezher Merdas, Ayad Hameed Mousa

AUIQ Technical Engineering Science

Researchers work around the clock on many datasets provided by various institutions. These researchers strive to come up with highly efficient Artificial Intelligence models. Often, researchers face the problem of imbalance in the distribution of classes in a particular feature in the selected dataset, which creates an Artificial Intelligence model biased towards one class at the expense of another class that is no less important than the first. On the other hand, thalassemia is a disease that affects people of different ages. The degree of disease varies according to the thalassemia class. This study proposes an improved Machine Learning model …

Large Language Model Enabled Mental Health App Recommendations Using Structured Datasets, Kris Prasad, Md Abdullah Al Hafiz Khan

Symposium of Student Scholars

The increasing use of large language models (LLMs) in mental health support necessitates detailed evaluation of their recommendation capabilities. This study compares four modern LLMs—GPT-4o, Claude 3.5 Sonnet, and dataset-enhanced Gemma 2 and GPT-3.5-Turbo—in recommending mental health applications. We constructed a structured dataset of 55 mental health apps using RoBERTa-based sentiment analysis and keyword similarity scoring, focusing on depression, anxiety, ADHD, and insomnia. Standard LLMs demonstrated inconsistent accuracy and often relied on outdated or generic information. In contrast, our retrieval-augmented generation (RAG) pipeline enabled lower-cost models to achieve up to 55% higher accuracy than baseline models while recommending apps with …