Digital Commons Network^™

Growing Change: A Gis Spatial Analysis To Plan Urban Gardens In Chattanooga, Carson A. Chalk

Honors Theses

Food insecurity and limited access to fresh nutritious food in Chattanooga is a prevalent issue, primarily among lower socioeconomic households, and can put strain on overall well-being. This study aimed to identify suitable vacant parcels in Chattanooga where urban gardens could be developed using a GIS-based spatial analysis. Spatial data involving vacant parcels, slope, zoning, and proximity to grocery stores was cross referenced with socioeconomic data focused on poverty rates, vehicle ownership, and mean household income to identify the most suitable sites in areas of greatest need. Sites identified as suitable through GIS were then visited to verify their suitability. …

Techno-Imagination: Elevating Creativity Through Xr And Ai, Christopher Spitzer

Creativity and Change Leadership Graduate Student Master's Projects

Techno-Imagination: Elevating Creativity Through XR and AI explores the history of creativity and computing technology, supported by research and academic literature, and looks at the possibilities of a convergence between the two. In parallel, a brief biographical story of the author shares how a passion for creativity emerged, along with a growing interest in science and technology—specifically extended reality—which ultimately came together in the creation of this master’s project. The project also highlights how the Creative Problem Solving (CPS) process was used alongside AI bots and twenty research-based creative thinking skills in developing the business model canvas. Finally, the outcome …

Conceptualizing A Responsive Design Pedagogy To Support Teachers' Responsiveness To Students' Mathematical Ideas Through Making, Denish Ogweno Akuom

Theses, Dissertations and Culminating Projects

This study develops Responsive Design Pedagogy (RDP), a conceptual and analytic model of teacher responsiveness in design-based environments, to account for how responsiveness emerges through interactions among students, tools, and tasks. Although responsiveness has been widely studied in mathematics education, limited attention has been given to responsiveness within mathematical design activity and to how teachers attend to the multiple modes through which students express their mathematical ideas. Addressing these gaps, this qualitative study examined one teacher’s enactment of responsiveness in a Learning-by-Design classroom where students designed and used 3D-printed mathematical tools. Data sources included classroom video, student design artifacts, teacher …

The Space In Between, Cailyn Dawson

Theses and Dissertations

This paper asks the question: is it possible for our bodies to hold contradicting identities at the same time?  Through monochromatic self- portraits, the artist creates a link between quantum mechanics and painting, using the principle of superposition to depict these multiple unformed states of being.

Prism: Priming Relationships In Syntax And Mathematics, Michelle J. Zhu

Honors Scholar Theses

The implementation of sheltered education programs has become increasingly prevalent in schools as new research in second language acquisition emerges. Yet despite this growing attention to ESL instructional practice, far less is known about the cognitive processes that underlie how bilingual students engage with academic content. This study investigates cross-domain structural priming between mathematical and linguistic processing in monolingual and bilingual individuals, focusing on how bilingual experience influences syntactic attachment preferences. Prior research suggests that mathematical and linguistic structures share underlying cognitive representations, and that exposure to structures in one domain can influence processing in another. Additionally, bilingualism has been …

Stability Of Paraffin-Insulated Nitrogen-Doped Carbon Fiber Ultramicroelectrodes, Maxwell H. Kwakwah

Electronic Theses and Dissertations

Nitrogen-doped carbon materials can facilitate the reduction oxygen-oxygen bonds, a key step in electroreduction of both O₂ (an important reaction in energy applications) and H₂O₂ (an important reaction in sensing and biosensing). Our lab previously demonstrated that thermal decomposition of urea in the presence of carbon fiber (CF) results in an N-doped carbon material that exhibits good electrocatalytic properties for H₂O₂ reduction. However, previous methods of insulating single N-doped CF via laser heating of borosilicate capillaries and epoxy to prepare ultramicroelectrodes (UMEs) seemed to adversely affect surface nitrogen contents and electrocatalytic properties. More recent work that utilized paraffin to …

A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari

Theses and Dissertations

Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 5 [2026], Número 1 (Issue 1), Romano Ponce-Díaz Phd, Cristo Leon, Ivan Avila, Sarah Lynne Bowman, Kjell Hedgard Hugaas, Alexandra Schreiber Ma, Jaime Eduardo García Maya, Víctor Emmanuel Quintana Villarreal Vic Emma, Francisco Gonzalez Ing., Daniel Romero Benguigui, Antonio Roda-Martínez

Journal of Roleplaying Studies and STEAM

El presente número del Journal of Roleplaying Studies and STEAM examina la convergencia entre las prácticas lúdicas, el diseño narrativo y los procesos de mediación sociocultural en la investigación contemporánea. Las contribuciones reunidas en este número abordan el juego de rol como un dispositivo de producción de conocimiento, intervención psicoeducativa y reelaboración de representaciones culturales. Nos podemos atrever a señalar que la educación es la convergencia entre la ludología, las ciencias sociales, los estudios visuales y el análisis cultural; entendiendo a la educación como la actividad consciente e intencionada de transmitir información y conocimientos a las siguientes generaciones.

Martin Heidegger …

Quantifying Macrophyte Ecosystem Services And Improving Environmental Nonprofit Messaging, Peyton R. Hughey

All Theses

Environmental nonprofits are essential to the management and restoration of our natural spaces. They are also tasked with engaging the public via outreach, education, and advocacy. As natural spaces are degraded, the ability of environmental nonprofits to deliver on their missions will become increasingly important. This study aimed to improve two approaches to environmental nonprofits’ missions: ecological restoration and social media communication.

Environmental nonprofits operate with limited resources, and ecological restoration can be an exhaustive task; therefore, we explore functional restoration as a tool. In this study, we focus on the use of functional, trait-based restoration to restore ecological function …

Sevoauth: Secure Voiceprint Authentication With Hash-Based Feature Transformation, Rui Zhang, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

While voiceprint authentication offers convenient user authentication and access control through voice feature recognition, a critical research gap remains: existing voiceprint authentication systems fail to simultaneously achieve sound security against replay, spoofing, and adversarial attacks, preserve voice privacy leakage, and satisfy usability demand. Previous efforts have struggled to balance these issues comprehensively. To bridge this gap, we present SeVoAuth, a cloud-based Voiceprint Authentication as a Service (VAaaS) system designed to provide privacy preservation, robust security, and enhanced usability. SeVoAuth stores a synthesized voiceprint of a user in the cloud during user registration, thereby safeguarding the privacy of the real voiceprint …

Synthesis And Evaluation Of Long-Term History-Aware Medical Dialogue, Hebin Hu, Renke Dai, Ah-Hwee Tan, Yilin Kang

Research Collection School Of Computing and Information Systems

An effective healthcare agent must be able to recall and reason over a patient’s longitudinal medical history. However, the absence of datasets with realistic long-term dialogue timelines limits systematic evaluation. Real clinical text is constrained by privacy and ethics, while existing benchmarks focus on isolated interactions, failing to capture cross-session reasoning. We introduce a framework for synthesizing high-quality, long-term medical dialogues with LLMs. Our approach entails a knowledge-guided decomposition into three stages: constructing synthetic patient profiles with diverse disease and complication trajectories, generating multiturn dialogues per encounter, and integrating them into a coherent longitudinal history dataset, MediLongChat. We establish three …

Open Source Software Development Tool Installation: Challenges And Strategies For Novice Developers, Larissa Salerno, Christoph Treude, Patanamon Thongtanunam

Research Collection School Of Computing and Information Systems

As the world of technology advances, so do the tools that software developers use to create new programs. In recent years, software development tools have become more popular, allowing developers to work more efficiently and produce higher-quality software. Still, installing such tools can be challenging for novice developers at the early stage of their careers, as they may face issues such as compatibility problems (e.g., with operating systems) and unclear instructions. Therefore, this work aims to investigate the challenges novice developers face when installing software development tools and the strategies they employ to overcome them. To investigate these, we conducted …

Generation Of Elaborated, Targeted And Effective Feedback For Novice Programmers Using Llm, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Programming errors and misconceptions are pervasive in novice programmers which causes difficulty in the learning of computer programming. Large Language Models (LLMs), with their ability to comprehend and generate programming codes have shown promising results in the automatic identification of errors. This can potentially benefit student programmers by providing them with timely formative feedback at efficiencies and scale that were not attainable previously. In this study, we leveraged an LLM - OpenAI o4-mini for the generation of elaborated, targeted feedback for novice programmers across PHP and JavaScript exercises. We contend that the feedback needs to be effective and targeted other …

Fighting Against Recruitment Scams: Theory-Driven Supervised Learning And Empirical Analysis For Digital Fraudulent Recruitment Posting Behavior, Tom (Tianteng) Wang, David (Jingjun) Xu, Keng Siau, Zhongju (John) Zhang

Research Collection School Of Computing and Information Systems

The number of recruitment postings on digital recruitment hiring platforms has increased since the COVID-19 pandemic. However, the weak surveillance and operations of these platforms, combined with the fact that most job seekers have relatively low vigilance and a strong desire for recruitment offers, enable scammers to easily deceive job seekers for their money and confidential information. In this work, we combine prevailing text mining techniques (i.e., ChatGPT with prompting engineering and supervised machine learning) with interpersonal deception theory (IDT) from social science to design an interpretable IT system to predict fraudulent recruitment postings on digital recruitment-hiring platforms. We compare …

Analyzing The Writing Style Of Generative Ai When Prompted With Writing Samples, Samuel Mcdowell

Senior Honors Theses

Authorship attribution is an important topic in today’s world of Large Language Models (LLMs). It is the technology that helps to verify the author of a written work. This study explores whether LLMs can successfully mimic an individual’s writing style if they are given a text sample. A dataset of human-written texts was collected and used to prompt several LLMs to generate new texts that attempt to replicate the original author’s stylistic characteristics. The generated texts were then tested with modern authorship attribution models to determine whether they would be identified as being written by the original author. The results …

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Securing Cloud-Native Systems: From Vulnerability Analysis To External And Insider Threat Detection, Jiongchi Yu

Dissertations and Theses Collection (Open Access)

Cloud-native systems have become the backbone of modern software infrastructure. However, their dynamic resource orchestration and complex configurability introduce a large attack surface and intricate security challenges. Adversaries can externally exploit vulnerabilities in cloud components or perform insider movement within cloud environments to launch attacks. As these systems increasingly support critical services, security breaches can lead to severe operational and economic consequences.

Despite extensive efforts in vulnerability detection and attack monitoring, existing approaches struggle to remain effective in cloud-native environments characterized by rapid evolution and inherent heterogeneity. In particular, they exhibit three fundamental limitations: (1) Insufficient understanding of defect patterns …

Intersectionality And Belonging: Higher Education Mathematics, Ashley Natalie

Mathematics and Statistics

Students with intersecting marginalized identities (such as race, gender, socioeconomic status, disability, or first-generation background) often face unique challenges in advanced mathematics that affect confidence, participation, amounting to a sense of belonging. These experiences remain underrepresented in mathematics education research. This qualitative, narrative-based study examines how these students experience classroom dynamics and belonging in upper-level mathematics courses. Semi-structured interviews will be analyzed thematically to identify patterns related to identity, classroom culture, instructor behavior, and peer interactions. Findings aim to highlight barriers and supportive practices, informing more inclusive teaching strategies and equitable learning environments in advanced mathematics.

Intersectionality And Belonging: Higher Education Mathematics, Ashley Williams

Mathematics and Statistics

Students with intersecting marginalized identities (such as race, gender, socioeconomic status, disability, or first-generation background) often face unique challenges in advanced mathematics that affect confidence, participation, amounting to a sense of belonging. These experiences remain underrepresented in mathematics education research. This qualitative, narrative-based study examines how these students experience classroom dynamics and belonging in upper-level mathematics courses. Semi-structured interviews will be analyzed thematically to identify patterns related to identity, classroom culture, instructor behavior, and peer interactions. Findings aim to highlight barriers and supportive practices, informing more inclusive teaching strategies and equitable learning environments in advanced mathematics.

Ai Institute Summer Camp Webinar Summary, Dora Nguyen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This report summarizes the AI Institute Summer Camp informational webinar hosted by the Paul English Applied Artificial Intelligence Institute (PEAAII) at the University of Massachusetts Boston. The webinar introduced the structure, curriculum, learning objectives, and student outcomes associated with the 2026 AI Institute Summer Camp. In addition to summarizing the webinar content, this report analyzes participant questions, engagement trends, and areas of audience interest. Findings indicate strong interest in coding accessibility, mentorship opportunities, student outcomes, research experiences, and program flexibility. The report also identifies opportunities for improving future webinar delivery, including expanded eligibility guidance, pre-camp learning resources, enhanced presentation of …

Real-Wastewater-Derived-Struvite Effects On Micronutrients In Runoff Water, Lauren E. Pruitt

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Phosphorus (P) is an essential nutrient needed in agriculture for proper plant growth and development and is often introduced into agricultural systems in the form of synthetic P fertilizers. Mined rock phosphate is the primary P source for the production of synthetic P fertilizers and is a finite resource. Struvite (MgNH₄PO₄·6H₂O) is a compound that can be precipitated from municipal wastewater, recovering P, and is currently being evaluated for its potential use as an alternative fertilizer-P source. The objective of this study was to evaluate the effects of fertilizer-P source [i.e., synthetic electrochemically precipitated …

Datapeer: A Hybrid Interaction Model Web Application Integrating Llms For Human–Llm Collaboration In Data Analysis And Exploration, William I. Bumcum

Honors Theses

DataPeer is a web application that combines open-ended high agency (OHA) and structured low-agency (SLA) interaction paradigms to support human-LLM collaboration in exploratory data analysis. DataPeer integrates a large language model (LLM) with a React frontend and FastAPI backend, allowing both qualitative and quantitative analysis of user-uploaded CSV datasets through a chat-based interface. Users can attach datasets and provide natural language queries, while the LLM provides data analysis to the user. This thesis investigates the integration of LLMs into data analysis workflows and addresses gaps in interaction design and user agency in LLM-driven data tools by offering a responsive interface …

Prediabetes Prediction Before Disease Onset Using Multimodal Health Data: A Machine Learning Approach, Luisa Veronica Gracia Mazuca

Open Access Theses & Dissertations

Prediabetes is a critical health condition that increases the risk of developing type 2 diabetes. The hemoglobin A1c (HbA1c) test diagnoses patients with prediabetes, but the disease has already caused metabolic alterations. Early detection is essential for timely interventions, and machine learning models offer a promising approach to identify prediabetic individuals through the analysis of biomarkers such as cytokines. We compared four classifiers-logistic regression, decision tree, random forest, and k-nearest neighbors - using cytokines (TNF-α, MCP-1, IL-1β, IL-6, IFN-γ), age, BMI, and waist-to-hip ratio (WHR). Models were evaluated using stratified 5-fold cross-validation and ROC-AUC. K-Nearest Neighbors (k-NN) achieved the highest …

An Ordinal Categorical Data Analysis Using The Stereotype Model Within A Bayesian Framework With A Logistic-Normal Prior, Nathaniel A. Sakyi

Open Access Theses & Dissertations

Ordinal categorical data are pervasive in applied research, yet their analysis is often compromised by modeling strategies that implicitly assume equidistant category spacing or impose restrictive structural constraints. Metric regression models and latent-variable threshold approaches routinely misrepresent ordinal information, leading to biased inference, distorted uncertainty quantification, and loss of structural insight. This paper develops a Bayesian framework for ordinal regression that explicitly accommodates \textbf{unequal spacing among ordered response categories} while preserving ordinal structure and interpretability.

The proposed approach builds on the stereotype regression model, which embeds ordinal categories into a latent one-dimensional continuum through estimable score parameters. While the stereotype …

How Novices Write Code: Discovering Best Practices, Matt Rau

All Graduate Theses and Dissertations, Fall 2023 to Present

Learning to program is a difficult endeavor, leading to chronically high failure rates in introductory programming courses. One thing that makes teaching programming difficult is that we don’t fully understand what problem solving habits and writing strategies separate successful programmers from struggling ones. Knowing how to teach these habits to a new programmer is an equally difficult challenge,

Studying the way people write code has proved difficult. Until recently, there was very little relevant publicly available data, and no good ways to analyze student programming behavior at a large scale. In this thesis, I address both issues. I publish a …

Environmental Movements In El Paso And Ciudad Juarez: Possibilities And Limitations Of Cross-Border Organization At The U.S.-Mexico Border, Vanessa Maria Almada

Open Access Theses & Dissertations

At the U.S.-Mexico border, the anthropogenic and nationalistic construction of the landscape has accelerated urbanization and unequal development without establishing effective binational institutions for governance over a shared commons. Borderlanders, then, contest unsustainable development with the added complexity of navigating a barrier which creates diverse socioeconomic and political realities that challenge cross-border cooperation. This qualitative research analyzes environmental organizations in El Paso and Ciudad Juarez. Through ethnographic study of mobilization in response to environmental legislation and administrative action in each city, the immediate barriers to cross-border cooperation and limitations of nationalistic institutions in the borderlands can be better understood.

Geothermal Gradient And Lithium Co-Generation Power Potential In Lafayette County, Arkansas, Juan Agustin Falquez

Graduate Theses and Dissertations

The Smackover formation in south Arkansas is a known reservoir for brines with high temperature and salinity. Recently, Smackover formation brines in Lafayette County, Arkansas are a target for lithium extraction. A county-wide dataset of Bottomhole Temperatures (BHT) is used to estimate a lower bound geothermal gradient of 36 C/km and a reservoir temperature of 116 C at an approximate depth of 2725 m. The high temperatures make the brines a candidate for geothermal power co-generation. Geothermal power co-generation can be achieved by implementing an Organic Rankine Cycle (ORC) power plant. The Southwest Arkansas Lithium project anticipates a total of …

Decision Making For Large-Scale Problems Under Uncertainty And Conflict, Benjamin J. Hamlin

All Dissertations

Large-scale decision-making problems appear in many areas including long-range forecasting such as energy generation forecasting. Many such problems are subject to conflicting objectives and uncertain data, and can be modeled as linear optimization problems. We study novel theoretical results and algorithms for large-scale linear decision problems under conflict and uncertainty. First, we propose a parametric Benders decomposition algorithm for solving large-scale linear optimization problems with multiple objectives or deterministically uncertain objectives. Second, we extend the parametric Benders decomposition to a multi-stage setting, developing a parametric stochastic dual dynamic programming algorithm, which enables decision-making when conflicts and uncertainty have planning impacts …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Ecological Insights And Management Implications Of The Global Migratory Connectivity Of Green Turtles, Jaime Restrepo, Dina Nisthar, Harris Wei-Khang Heng, Lily K. Bentley, Corrie Curtice, Sarah Deland, Ei Fujioka, Patrick N. Halpin, Sarah K. Poulin, Roldán A. Valverde

School of Earth, Environmental, & Marine Sciences Faculty Publications

Aim

Green turtles are a widely distributed and highly migratory species; despite extensive data on their movement, there is no species-specific global synthesis on the subject. Based on three decades of published literature and building on previous global analyses, we developed a global network model of migratory connectivity for green turtles to better understand their spatial biology.

Location

Global.

Time Period

1990–2022.

Major Taxa Studied

Green Sea Turtle (Chelonia mydas).

Methods

We conducted a structured literature review extracting georeferenced information on the movement of green turtles from 1990 to 2022, aggregating this information into a single connectivity model, …