Digital Commons Network^™

My First Conversation With Chatgpt (February 22, 2023): Origins Of A Generative Dialogue, David Smith

Publications and Research

This working paper presents the first recorded interaction between the author and the generative AI system ChatGPT, written on February 22, 2023 during the initial weeks of a faculty sabbatical in Boston. The document preserves a complete and unedited transcript of an exploratory conversation conducted without predetermined research aims, marking the author’s first encounter with a large-language-model conversational interface. Although the exchange includes creative experimentation—including musical and poetic prompts—the discussion remains informal and wide-ranging, and no theoretical framework is articulated at this stage. Rather, this transcript is published as primary-source material documenting the moment of discovery and experimentation that precedes …

Bayesian Alignment Prior To Connectionist Temporal Classification Loss, Lawry Sorenson

Theses and Dissertations

We propose revisions of Connectionist Temporal Classification (CTC) loss and forced alignment to support longer input sequences. CTC loss is normally used for training in speech and handwriting recognition tasks when the labels are not fully aligned with the data, while forced alignment is a downstream task that finds the optimal path for segmentation purposes. The current implementations consider all possible alignments between the input and label, which grows exponentially with the size of the input. We show that in cases when silence is removed and speaking rate is consistent, the true alignment is a mostly straight line across time …

Toward Understanding Multi-Agent Decision Making In Complex Societies, Jonathan Skaggs

Theses and Dissertations

This dissertation investigates Multi Agent Decision Making (MADM) within Complex Societies (CS), systems of interdependent agents whose collective behaviors emerge from local interactions. Such emergent dynamics are nonlinear and difficult to predict, posing significant challenges towards understanding how individual decisions scale to societal outcomes. Existing approaches often fall short of capturing the combined attributes of CS, including asymmetry, decentralization, and adaptivity. To address this gap, we introduce new models and analyses of agent strategies that explain how cooperation and stability can arise in CS. Structured around three interrelated projects, this dissertation enhances our comprehension of MADM in CS. The research …

Gamification Of A Bimanual Coordination Task, Robby Johnson, Caeden Kidd, Johnathan Oestringer, Jaylin Pigeon, Brandon Woolman

Infinite Loop

Video games are a promising future for research and development. A new way to measure motor skills is to use robots to test individuals. This technology is incredible and has helped the medical field, but there must be a way to allow individuals to use this technology in a similar and affordable manner. Space Trash is a game that was developed with the intent to gamify the object hit detection that is used in the Kin Arm Robot with the intent to see if a person will show signs of Alzheimer’s. The goal is to not only be able to …

Understanding Medical Information And Emotional Support Needs In Mental Health Questions With Large Language Models, Chen Liu, William Yu Chung Wang, Gohar Khan

All Works

Purpose – This study seeks to bridge the gap between users’ multidimensional needs and the single-task capabilities of existing Mental Health Question Answering (MHQA) systems by tackling the underexplored challenge of jointly understanding medical informational needs and emotional support needs within complex consumer mental health inquiries. Design/methodology/approach – Grounded in Rhetorical Structure Theory (RST), the proposed Multi-Needs and Context Recognition (MNCR) framework decomposes mental health question understanding task into four interrelated subtasks: Medical Needs Recognition (MNR), Medical Needs-related Context Extraction (MNCE), Emotional Needs Recognition (ENR) and Emotional Needs-related Context Extraction (ENCE). A new benchmark dataset, MHQ-MedEmo, was constructed through multi-layered …

Large Language Models As Machines Of Beauty: Cognitive Averaging, Latent Space Geometry, And The Entropic Foundations Of Aesthetic Preference, Daniel Plate, James Hutson

Faculty Scholarship

This study advances the position that large language models (LLMs) and human perceptual systems are governed by a shared computational drive toward prototypicality, entropy reduction, and aesthetic coherence. Drawing on developmental evidence that infants exhibit early preferences for facial symmetry and averageness, the analysis situates aesthetic preference within broader research on processing fluency and predictive coding, emphasizing that biological perception rewards stimuli that reduce uncertainty and support efficient information compression. This foundation is used to examine how LLMs, through cross-entropy optimization, perplexity minimization, and latent space clustering, converge on high-density representational regions that operate as statistical prototypes of linguistic and …

A Socio-Technical Analysis Of Market Reactions On Meme Coins: Trump’S Presidential Effect, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Meme coins are a unique type of cryptocurrency whose value is shaped by internet culture and viral trends. This study introduces a socio-technical research model to examine key factors influencing meme coin dynamics and applies it to analyze market reactions to Donald Trump’s 2024 U.S. presidential election victory and inauguration, focusing on the $TRUMP meme coin and other politics-related meme coins, known as PolitiFi. Using a mixed-methods approach, we analyze publicly available news, social media activity, and marketplace data to investigate the interaction between social engagement and technical infrastructure. Econometric analysis shows that Trump-related events triggered short-term price surges, increased …

An Analysis Of Face Synthesis Methods And Their Influence On Human Perception, Maha Habib Almaimani

All Dissertations

Synthetic faces (e.g., computer-generated characters) have been increasingly utilized across various fields, including entertainment, healthcare, and education. Perceptual studies are often conducted to understand how synthetic faces are perceived by humans, aiming to enhance both quality and user experience in these domains. Over the years, numerous methods have been developed to create synthetic faces, ranging from traditional techniques such as image composites, Active Appearance Models, and 3D Morphable Models to more recent machine-learning-based frameworks like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

Despite the growing adoption of synthetic face generation and the variety of algorithms available for their creation, …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Essays On The Economics Of Farmland Valuation And Investment In U.S. Agriculture, Colson Tester

Graduate Theses and Dissertations

This dissertation presents three empirical essays that collectively advance the understanding of farmland valuation in key U.S. agricultural regions, emphasizing the critical advantages of comprehensive, transaction-based data over traditional survey methods. Farmland represents a significant portion of agricultural wealth, and its accurate valuation is crucial for farmers, investors, and policymakers, influencing everything from credit access to investment strategies. Historically, research has often relied on subjective survey data, which can suffer from biases, inaccuracies, and insufficient granularity. This dissertation addresses these limitations by leveraging extensive datasets of arm’s-length farmland transactions, offering a more precise and market-driven perspective on land values. The …

Performance Enhancement For Rufa: Rapid Urban Forest Assessment, Nicholas Tan

Master's Theses

Urban forests are crucial to the livability and resilience of cities, offering critical ecosystem benefits such as air quality enhancement, temperature regulation, and biodiversity. Managing said urban forests is essential to ensure their sustainability and adaptability to rapidly changing environmental and climate conditions. The Rapid Urban Forest Assessment (RUFA) tool was developed to address the need for a standardized approach to evaluating and comparing urban and community forestry programs. By analyzing and aggregating tree-specific data across California, such as canopy cover, tree counts, and diversity scores, RUFA assigns a comprehensive urban forestry score for each city. This score allows for …

Synthesis Of Antibody Functionalized Polyaniline/Polystyrene/N-Gqds Composite Fibermats For Sweat Based Cortisol Biosensing Applications, Ashwin James

Honors Theses

Noninvasive, wearable biosensors capable of detecting stress biomarkers in sweat require electrodes that are flexible, conductive, insoluble in water, and highly sensitive at low concentrations of analyte. In this work, bovine serum albumin blocked and anti-cmab immobilized nitrogen doped graphene quantum dots integrated polyaniline/polystyrene composite fibermat electrodes (BSA/Anti-Cmab/N-GQDs/PANI/PS electrodes) were synthesized and evaluated as a potential platform for an electrochemical cortisol biosensor in sweat based systems. Polyaniline was utilized in order to provide electrical conductivity, while polystyrene served as a carrying polymer for mechanical support and its hydrophobicity. Composite fibermats were manufactured through Forcespinning™, followed by a secondary polyaniline graft …

The Impact Of Screentime In Childhood, Kyla P. Shirley

Informatics

The increased dependency on technological devices as a result of the digital age being upon us impacts a multitude of individuals from all age groups. For older groups, they might find an easier time navigating the world wide web due to their awareness of the potential dangers these digital spaces may bring. On the other hand, younger age groups are more susceptible to the dangers posed due to their lack of maturity which in turn makes them extremely vulnerable to being negatively impacted when using these electronic devices. The goal of this project was to generate awareness concerning screen time …

From Inside The Recording Studio, Mckayla J. Adkison

Capstone Projects and Master's Theses

This project documents the historical, technical, and creative significance of recording studios through both industry examples and the design and construction of a personal backyard studio. By examining iconic studios such as Abbey Road and Capitol Records, the paper highlights how technological innovation, acoustic engineering, and architectural design have shaped the evolution of recorded music. These concepts are then applied to the planning and construction of a custom-built recording studio, emphasizing room dimensions, sound isolation techniques, acoustic treatment, lighting, and sustainable design choices. In addition, the project addresses the importance of aesthetics and emotional comfort in creating a space that …

Emotion Analysis And Neural Language Models For Classification, Andrew Mackey

Graduate Theses and Dissertations

Emotion analysis is a branch of artificial intelligence and natural language processing focused on recognizing emotions hidden throughout various forms of digital data, including text, images, and multi-modal representations. In this dissertation, we present four published and planned works that investigate different methodologies for natural language analysis tasks using deep learning techniques. The first published work we present considers the task of identifying fake news using various text and emotion representations. We demonstrate that emotion representations combined with word embedding techniques can improve the accuracy of fake news classification. Our second published work further investigates the fake news classification task …

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …

Topic Modeling And Culturomic Analysis Of 30,000 Books Over 100 Years Using Gensim, Michael A. Freeman

Electronic Theses and Dissertations

This thesis explores the cultural influence of historical events on English-language fiction published between 1820 and 1929. Using a corpus of 30,256 digitized books from Project Gutenberg, Latent Dirichlet Allocation (LDA) topic modeling was applied to identify recurring themes across eleven decades. The study sought to determine whether historically significant events could be detected within fictional narratives. One clear instance emerged: Napoleon Bonaparte and the Napoleonic Wars appeared explicitly in the 1820s corpus. Beyond this, several thematic patterns were observed—such as maritime language in the 1840s, national identity in the 1880s, and youth-oriented dialogue in the early 20th century—that plausibly …

Understanding Bias And Fairness In Large Language Models: An Empirical Study, Joshua Johnson

Electrical Engineering and Computer Science Undergraduate Honors Theses

This thesis investigates demographic bias in large language models (LLMs) through the use of evaluating outcome disparities when utilized in decision making tasks as well as underlying associations that could contribute to furthering these disparities. Using profiles from the Adult dataset, we analyze how Gemini 2.0 Flash performs in an income prediction task using zero-shot and few-shot prompting methods. Our findings show that models exhibit measurable differences in demographic parity and false positive rates, with the use of few-shot prompting reducing these disparities. Alongside this line of testing, we tested associational bias in Qwen 2.5 using probability based association tests …

Content And Consequences: Impact Of Representation In Stem Higher Education Instructional Content On Marginalized Students, Nichole Ventura

Doctorate in Education

This qualitative study examined representation of historically marginalized students in STEM instructional content at the higher education level and its impact on their learning experiences. Despite growing diversity initiatives in STEM enrollment, curricular materials often fail to reflect the identities of underrepresented students. Using critical theory and interpretivist approaches, this research investigated how representation—or its absence—shapes students' sense of belonging, academic identity formation, and persistence. Through semi-structured interviews with undergraduate students from historically marginalized backgrounds, and purposeful sampling, this study captured the lived experiences of students engaging with STEM instructional materials. Interview protocols explored how students perceive their representation in …

Investigating Programming Behaviors To Understand Student Engagement And Experience In Introductory Programming Courses, Marcus Eugene Gubanyi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Introductory programming courses are foundational to developing students’ problem-solving abilities and shaping their persistence in computing pathways. Engagement with programming tasks plays a central role in student learning and experience. Many research measures, including self-reports and code submissions, offer only a limited view of student engagement with programming tasks. This dissertation leverages programming process data, consisting of keystrokes and compilation events, to capture the programming process as it unfolds and to investigate observable programming behaviors. Guided by educational theories, three studies examine how students’ programming behaviors vary across instructional and assessment contexts, how they relate to motivational profiles, and how …

A Comparative Study Of Novel Methods For Variances, Taoreed Muritala

Boise State University Theses and Dissertations

Understanding variability is fundamental to knowledge advancement across various disciplines, including manufacturing, clinical research, biology and genetics. Population variances play a crucial role in processes such as quality control, treatment evaluation and the interpretation of biological mechanisms. However, statistical procedures for comparing variances across multiple populations remain less developed than those for comparing means. Classical omnibus tests, such as Bartlett's and Levene's, can detect overall variance heterogeneity but fail to identify which populations differ, thereby limiting their usefulness in multi-population analyses and increasing the risk of inflated family-wise error rates through repeated testing.

This thesis develops and evaluates three multiple …

A Generational Analysis Of Psychological Motivators Influencing Seafarer Retention, Perisah Tahanci

The Plymouth Student Scientist

Seafarer retention is a growing concern amid increasing global demand for skilled maritime officers. This study investigates the generational differences in psychological motivators influencing seafarer retention, where ‘psychological motivators’ encompass the cognitive factors, including mental and physical wellbeing, work-life balance, compensation, working conditions, and external factors, that shape retention intentions. A cross-sectional survey (n=214) combined quantitative and qualitative analyses to systematically assess how the perceived importance and experience of these factors vary across Generation Z, Millennials, Generation X, and Baby Boomers.

The findings reveal that significant generational differences exist across most factors, particularly in work-life balance and mental wellbeing, in …

Design And Evaluation Of Gamified Kahoot Modules For Improving Engagement And Conceptual Understanding Of Introductory Physics Students, Yaritza Villarreal

Theses and Dissertations

This study investigates the effectiveness of gamified learning modules in enhancing the engagement and conceptual understanding of introductory physics students. The first phase of this study focused on the design and development of gamified learning modules for selected topics in introductory physics. The modules were developed by integrating principles of Backward Design, following an escape-room theme with interactive scenarios, and incorporating classic game elements (e.g., points and leaderboards).

The second phase examined the effectiveness of the gamified Kahoot modules using a pretest-posttest control-group design. Sixty-eight (68) students were equally randomly assigned to the control and experimental groups. The experimental group …

The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden

Milne Open Textbooks

Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.

Demystifying the Machine

This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …

Towards Inclusive Digital Futures Of Cultural Heritage: Insights From A Critical Discourse Analysis Of Unesco Dialogues, Shiqing Huang, Keng Siau, Xiaoting Chen

Research Collection School Of Computing and Information Systems

Digital technologies are shaping many aspects of cultural heritage, but very little research has examined the implications of digital transformation. Drawing on concepts from Fairclough’s three-dimensional critical discourse analysis, this research examines the discourse using seven online dialogues (available on the UNESCO website) between 18 professionals who have different backgrounds and cultures to identify social practices related to the digital transformation of cultural heritage. We identify four digital transformation discourse types in professional dialogues: documentation, management, interpretation, and interaction. We also identify seven main groups: memory institutions including libraries, archives, and museums (LAMs), governments, international organizations, art and creative supporters, …

Examining The Roles Of Embodiment And Theory Of Mind In Shaping User Perceptions Of Llm-Driven Conversational Agents, Elizabeth A. Schlesener

All Dissertations

Large Language Models (LLMs) have advanced conversational agents, enabling natural, human-like interactions in domains such as education, programming, and workplace collaboration. Yet, user distrust persists over privacy, accuracy, and bias. As developers work to mitigate these issues and human-AI collaboration expands, reinforcing trust in LLM-driven systems is essential. To address this problem, this dissertation explores the role of anthropomorphic form in LLM-driven conversational agents and its impact on user perception.

According to the familiarity thesis, humans attribute human-like characteristics to nonhuman entities — a process known as anthropomorphism — to better comprehend unfamiliar phenomena, based on the assumption that they …

Mountain Communities During A Time Of War: A Case Study Of The Hutsul Region In The Carpathian Mountains Of Ukraine, Pavlo Rybaruk

Electronic Theses and Dissertations

This thesis investigates the ethno-ecological technologies employed by the Hutsul people within the highland agrarian economy of the Carpathian Mountains. Over centuries, the Hutsuls have developed ethno-ecological technologies that maintain ecological integrity while supporting community livelihoods.

The study addresses three primary research questions: What are the most important ethno-ecological technologies of the Hutsul highland economy? How might these traditional ethno-ecological practices be applied to economic, agricultural, and tourism development in the Hutsul region? How might these traditional ethno-ecological practices be combined with contemporary approaches to encourage sustainable development in the region?

The research explores the devastating impact of the Russian …

Accelerating Relationship Discovery In Chronic Lower Back Pain Through Knowledge Graph And Ontology Enhanced Large Language Models, Damon Lin

Master's Theses

Chronic lower back pain (cLBP) is a widespread public health burden linked to anxiety, depression, and opioid addiction. Interventions aimed at treating cLBP have shown minimal improvements in pain outcomes, leading researchers to reexamine our understanding of cLBP through constructing a causal model. However, constructing causal models through Randomized Controlled Trials are often unfeasible, and relying on domain expertise requires extensive and time-consuming research, posing a serious bottleneck for designing effective treatments. To accelerate this process, we apply Knowledge Graphs, Ontologies, and Large Language Models (LLMs) to aid researchers in determining possible causal relationships. First, we demonstrate how LLMs can …

Predictors Of Math Identity In U.S. High School Students, Edwin Flores

Electronic Theses, Projects, and Dissertations

This study explored factors related to high school students’ sense of math identity. Data from the High School Longitudinal Study of 2009 was used which is a nationally representative dataset from the National Center of Education Statistics (NCES). The sample is representative of U.S. high schoolers who began ninth grade in 2009. Multiple regression analysis was performed and factors relating to students’ prior mathematics coursework and attitudes about mathematics were found to predict students’ mathematics identity.

Keywords. Mathematics, identity, high school students

Error Reduction Methodology And Data Simulation For Interval Data, Ranik Christopher Jelinek

Undergraduate Honors Capstone Projects

Chronic kidney disease (CKD) is a progressive condition affecting hundreds of millions of individuals worldwide. However, clinical datasets often record continuous laboratory measurements as categorical intervals rather than precise numerical values. This interval-censored structure presents methodological challenges for standard regression-based classifiers. This study compares three strategies for handling interval-valued predictors prior to fitting a logistic LASSO model: (1) midpoint imputation, which replaces each interval with its arithmetic center; (2) ordinal encoding, which maps intervals to integer ranks; and (3) a Monte Carlo simulation approach, which repeatedly samples uniformly from each observed interval and averages predictions across replications. Using a 10-fold …