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Course Insight Portfolio: Math 1020 Business Calculus I, Ibrahim Khalilullah, M.G.M. Al Faruque, Jessica Ratovondranto, Leslie Spahr

Publications

This portfolio presents an overview of the student educational context, key course concepts, and some approaches to clarify student misconceptions associated with MATH 1020 (Business Calculus I). The portfolio includes a concept map illustrating the major topics of the course and an overview of common student misconceptions, and lesson plans designed to address those misconceptions through research informed instructional practices.

The concept map highlights the interconnected nature of topics such as functions, limits, continuity, differentiability, derivatives, optimization, graph interpretation, and applications of calculus. Particular attention is given to areas where students commonly experience difficulty, including distinguishing domain, codomain, and range; …

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 …

Factors Affecting Pedestrian-Vehicle Conflicts: An Empirical Analysis, Christo D. Jamo

Honors Scholar Theses

The number of pedestrian deaths increased by 78% between 2009 and 2023, while other motor vehicle crash deaths increased by 13% in the same period [1]. To identify potential pedestrian safety measures, this study analyzed the effects of location-based demographics, pedestrian phasing type, and other physical infrastructure and behavior variables on the probability of pedestrian-vehicle conflicts at signalized intersections, which is a surrogate measure of crash risk. Data were collected from 55 intersections in Connecticut, and the pedestrian-vehicle interactions were classified by severity based on the Swedish Traffic Conflict Technique: undisturbed passage, potential conflict, minor conflict, or serious conflict. Because …

General Chemistry Students' Perceptions Of How Various Course Resources Affect Their Learning And Exam Preparation, Jennifer Scoggin Cortez

Theses and Dissertations

The tertiary-level first-semester general chemistry course has a large range of material with different complexities that can be difficult for students to master within one semester. In the general chemistry I course under study here, students were provided with a variety of resources to help with their learning and understanding, with various components of the course, including the lecture, online textbook, Peer-Led-Team-Learning (PLTL) study sessions, and exams, having associated resources. This study aims to analyze students’ experiences with these various resources. Students were given semi-structured interviews where they talked about their experiences with the resources and provided insight into more …

Bayesian Change-Point Detection In Stock And Cryptocurrency Markets Using Shrinkage Priors, Yosalin Sanchez

Theses and Dissertations

Financial markets often undergo abrupt structural changes driven by political, economic, and geopolitical events, leading to substantial volatility. Detecting such change-points is crucial for identifying structural breaks, improving risk management, and enhancing forecasting performance in financial time series. This study proposes a Bayesian change-point detection framework that incorporates both the t-shrinkage prior and the Horseshoe shrinkage prior. These priors enforce strong regularization on successive differences in mean parameters, enabling the identification of piecewise constant structures in time series data. Posterior inference is conducted using Markov Chain Monte Carlo (MCMC) methods, specifically a Gibbs sampling algorithm, which iteratively samples from the …

Pesticides And Poverty: How Socioeconomic Factors Relate To Pesticide Application In The Continental Us, Reed Smetter

Theses and Dissertations

Pesticides are often used to help reduce the populations of weeds, insects, and pathogens in agricultural and urban settings, reducing the risk of outbreaks and losses of agricultural yield. The communities that surround agricultural areas often bear the brunt of the negative community and environmental health effects of these chemicals, and are frequently rural, poor, and lack critical infrastructure resources. Pesticide application volumes are often linked closely with specific health effects. In this study, I apply social vulnerability theory to compare the potential connections between the application rates of pesticides and socioeconomic variables across the United States using a nationwide …

Los Juegos De Rol Como Una Herramienta Psicoeducativa, Víctor E. Quintana Villarreal

Journal of Roleplaying Studies and STEAM

Los juegos de rol han funcionado durante mucho tiempo como un medio para compartir y crear historias en conjunto con colegas y amigos. De ellos, se desprenden también habilidades y herramientas fundamentales para la vida, por lo que un método para sistematizar estos juegos de tablero y dados a funciones educativas es necesario para potenciarlos como herramientas psicoeducativas.

La siguiente, es una propuesta planteada desde el marco constructivista para generar espacios con los juegos de rol como eje central del aprendizaje, y se relatan a través de un marco teórico, seguido de una proposición metodológica, una serie de pasos para …

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 …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …

Between Chronicle And Legend: A Two-Scene Environment And Visual Effects Examination Of Physical Accuracy And Emotional Exaggeration On The Honey Creek Bridge Collapse, Alison R. Gaddy

All Theses

This thesis explores how truth and dramatization intersect in digital storytelling by comparing realistic and stylized simulations of the Honey Creek bridge collapse within the context of the Kate Shelley animated short. At the core of storytelling lies a tension between factual accuracy and dramatic stylization. We investigate that tension by examining how narrative truth is conveyed, distorted, or enhanced through visual dramatization by focusing on the psychology of audience perception and the motivations behind creative embellishment. The practical contribution of this research is the development of two distinct digital scene setups depicting the same Honey Creek bridge collapse event. …

Evaluating Modern Neural Network Architectures For Suicide Prediction, Kyle Brown

Master's Theses

Suicide remains a leading cause of death among adolescents despite more access to healthcare information than ever before. Medical professionals struggle to make accurate diagnoses and catch warning signs with the overwhelming amount of data available. Machine learning algorithms, including neural networks, have previously been employed for this task, yet it remains an understudied domain.

This research aims to evaluate the capabilities of Multi-Layer Perceptron (MLP) and a selection of its successors, ResNet and MLP with a category embedding layer, at the task of predicting suicidal ideation among high-school students. This research finds ResNet to be the most capable at …

Manned Exploration Of Satellites Of The Outer Planets: An Analysis Of Current Technologies And A Discussion Of Advancements Required, Joshua Carson Meador

Theses and Dissertations

The Solar System’s outer planets have many satellites, some of which are known to be the most likely places to find extraterrestrial life in our celestial backyard. Multiple scientific missions have been sent to glean information from these satellites, yet the possibility of a manned expedition has long been exclusive to science fiction stories. This paper intends to collect and analyze the current state of space travel technology to explore the feasibility of such a mission with modern technology and to discuss which future advancements should be the focal point for making such missions a reality. To begin, data on …

Moodify: A Mood-Based Music Recommendation System, Meghana Kagitha

Theses and Dissertations

Music has long been recognised as a powerful tool for emotional regulation, yet existing music streaming platforms often fail to align song recommendations with a user's current emotional state. Moodify is a mood-based music recommendation system designed to bridge this gap by delivering personalised playlists that reflect how a user feels in real time.

This project presents the design, development, and evaluation of Moodify, a mobile application that leverages the Circumplex Model of Emotion to capture user mood through an intuitive two-dimensional valence-arousal interface. Rather than relying on text input or manual search, users plot their emotional state directly onto …

Analysis Of Collective Behavior In Living And Nonliving Systems, Kaitlyn Cohan

Theses, Dissertations and Culminating Projects

This thesis aims at understanding the phenomenon of of self-organization in complex dissipative systems, living and nonliving. Dissipative systems are characterized by their search for energy, interactions with their surroundings and the production of entropy, all of which result in the creation of stable structures or patterns, which persist as long as the initial environmental conditions are maintained. The two specific models that we chose to study here are (a) Futbol (or Soccer) and (b) a chemical system involving free-floating menthol crystals floating on a fluid surface to represent nonliving systems. Using experiments and mathematical models, we will try to …

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 …

Analyzing The Evolution Of Science: Topological Cycles And Community Detection In Knowledge Networks, Frances C. Mcconnell

Mathematics, Statistics, and Computer Science Honors Projects

How scientific knowledge grows and organizes itself is a central question in the study of science. This thesis uses tools from topology and network science to detect and characterize knowledge gaps—places in a field’s literature where related concepts do not co-occur. We develop a metric to quantify the degree of interdisciplinarity of each gap, using the community structure of the underlying network as a proxy for subfields. Across a wide range of fields, gaps reliably span multiple subfields and evolve in recognizable temporal patterns, highlighting new insights into how scientific fields are structured and their stage of development.

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.

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 …

Social And Institutional Factors Influencing Restoration Decisions In Sagebrush Plant Communities In The Great Basin, Carmen Calzado-Martínez

All Graduate Theses and Dissertations, Fall 2023 to Present

Sagebrush landscapes of the Great Basin in the western United States have changed dramatically over the past century. Invasive grasses, repeated wildfires, and past land-use practices have made it increasingly difficult for native plant communities to recover once they are damaged. Most restoration efforts occur after disturbances such as wildfire, when ecosystems may already be severely degraded. An alternative approach is proactive restoration, which aims to strengthen ecosystems before major damage occurs. 

This dissertation examines whether proactive restoration strategies could realistically be used in sagebrush rangelands and what factors influence their adoption. The research combines three complementary approaches. First, interviews …

Advancing Context-Aware Detection Of Socially Harmful Discourse Using Transformer-Based Models, Santosh Chapagain

All Graduate Theses and Dissertations, Fall 2023 to Present

Social media platforms are a central part of modern communication, shaping how people share ideas, build communities, and discuss social issues. While these spaces can support connection and self expression, they also enable the spread of harmful language such as hate speech. At the same time, social media is an important place where members of marginalized communities, including sexual and gender minorities, express stress, discrimination, and emotional challenges in ways that are often indirect and context dependent.

This research examines whether modern artificial intelligence systems can better identify harmful language and expressions of minority stress in online posts. The study …

Student Programming Behavior With And Without Phone Notification Suppression, Gavin T. Eddington

All Graduate Theses and Dissertations, Fall 2023 to Present

Many students work on programming assignments while receiving notifications from their phones, such as text messages or social media alerts. These notifications can interrupt focus and make it harder to stay engaged with a task. This study examines whether silencing phone notifications helps students stay more focused while programming. 

We collected data from students in an introductory computer science course while they worked on programming assignments. Students completed some assignments with notifications silenced and others without. We measured their activity using software that records typing behavior and identifies when students take long pauses, which can indicate interruptions or loss of …

A Survey On Digital Reading Materials And Personal Study Of Christian Religious Texts, Teancum Price

All Graduate Theses and Dissertations, Fall 2023 to Present

Religion, including reading from religious texts such as scriptures, are a part of the daily lives of many people. Modern technology has influenced the way that this religious reading takes place, but its effects have not yet been studied. Existing research of the effects of technology on reading focus on topics such as reading comprehension, but the study of religious texts is often focused on achieving a religious experience, so the existing research does not capture the whole scope of these changes. In our study, we surveyed two universities (Utah State University and Abilene Christian University) to ask individuals how …

Spike-Sorting Algorithm For Neuropixel Probes, Luis David Davila

Open Access Theses & Dissertations

Modern extracellular neural probes like Neuropixels, allow for high-density extracellular neural probes to record terabytes of electrophysiological brain data. Spike sorting is the process of isolating individual neurons on this data through various clustering and filtering techniques. Modern spike sorting algorithms are held back by their need for human intervention to separate high-quality from low quality clusters, due to the volume of data that can be collected a completely automated approach is required. To address this requirement, we have developed a framework to preprocess, cluster, grade, and separate high/low quality clustering results using custom models trained on the grades. To …

Three Essays On Workplace Ethics And Ai: Conceptualizing, Scale Development, And Validation Of Self-Value Actualization, And Ai-Enabled High-Performance Work Systems, Mansura Nusrat

Open Access Theses & Dissertations

This dissertation advances understanding of workplace ethics and responsible AI integration across three interconnected essays unified by social cognitive theory. My first essay introduces self-value actualization (SVA), a novel construct defined as the dynamic, integrated psychological process through which individuals continually strive to align and fulfill their core moral values through observable professional behavior. Drawing on social cognitive theory and emotional intelligence theory, I conceptualize SVA as a higher-order self-regulatory orientation comprising three mutually reinforcing processes: value congruence, moral reflection, and adaptive morality. I developed and validated a 9-item SVA scale across four studies using expert panels, exploratory factor analysis, …

Understanding Machine Learning Model Behavior Under Fairness And Privacy Constraints, David Anthony Sanchez

Open Access Theses & Dissertations

Machine learning systems deployed in high-stakes domains are increasingly expected to satisfy demands beyond predictive accuracy-including fairness across demographic groups, protection of sensitive information, and explanations that human stakeholders can inspect and trust. This thesis investigates how those demands can be met through learning frameworks that explicitly govern the relationship between data and models, arguing that trustworthiness is a design problem rather than a post hoc correction. The thesis is organized around three studies, each targeting a distinct point of data-facing control. The first develops CondFairGen, a fairness-aware conditional generator for tabular data that improves subgroup equity by dynamically reweighting …

Advancing Apparel Education Through 3d Simulation In Vstitcher: Confidence, Competence, And Career Readiness In Higher Education, Jonah Diniakos Graham

Graduate Theses and Dissertations

The rapid adoption of 3D garment simulation in the apparel industry has created new demands of higher education to better prepare students with both technical proficiency and confidence within digital design platforms to better enable them for many career avenues. This study examines the integration of Browzwear’s VStitcher in an undergraduate apparel production course, addressing the need to assess both competence and self-confidence in digital garment construction while also fostering broader career readiness competencies. Guided by a combination of Self-Determination Theory (SDT) and Situated Expectancy-Value Theory (SEVT), the study emphasizes the role of autonomy, competence, and relatedness in the shaping …

Probing Representational Emergence In Large Language Models, Shawn Ismail

Master's Theses

This thesis investigates whether abrupt behavioral gains in large language models under scaling are accompanied by systematic changes in internal representations. It combines a behavioral screen of 65 tasks per family with targeted layerwise probing across eight decoder-only, open-weight model families. Behavioral emergence is defined for each family-task trajectory using an empirical jump detector, with segmented regression retained only as a diagnostic. The representational follow-up analyzes 27 selected MMLU subtasks shared across all families, spanning 37 checkpoints and 216 family-task units.

For each follow-up checkpoint, frozen linear probes are trained on every layer's hidden states to measure how much task-relevant …

Exploring The Evolution Of Preservice Elementary Teachers' Mathematics Identity And Possible Selves: A Multi-Case Study Approach, Christa R. Mawn

Theses, Dissertations and Culminating Projects

This study explores the nature of preservice elementary teachers’ mathematics identity and possible selves and identifies shifts in their mathematics identity or possible selves over the course of a place value unit during the semester during a course on mathematics content for elementary teachers. Drawing on narrative identity and possible selves theory, this qualitative multi-case study examined the mathematics identity and possible selves of preservice elementary teachers enrolled in a mathematics content course. Course assignments were used as data sources and included written narratives, future-oriented reflections, drawings, and course artifacts. Individual cases were analyzed, and were followed by a cross-cases …

Detecting Doubt In Reflective Learning: A Learning Analytics Study With Large And Small Language Models, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Reflective learning enhances understanding, especially when instructors promptly address difficulties raised in student reflections. Automated doubt detection can reduce time for instructors, yet existing classification approaches take substantial time for manual annotation and model training. This paper investigates whether large and small language models (LLMs, SLMs) can automate doubt detection without time-consuming training. Using a dataset of anonymized student reflections, we evaluate zeroshot, few-shot prompting, and multi-step reasoning against prior supervised classification baselines. We show that LLMs (GPT-4o, Claude-4, Gemini-2.5) surpass earlier F1 scores without prompting, while prompting further improves their performance. However, using proprietary LLMs can raise cost and …