Digital Commons Network^™

Efforts To Improve General Chemistry Student Success: Describing Stoichiometry Solution Patterns And Investigating Challenge Perceptions, Dianna Kim

USF Tampa Graduate Theses and Dissertations

There is a need for capable STEM graduates to fill needed STEM career gaps, particularly for people who have been historically under-represented in the STEM field (e.g., women, people of color, people of lower economic status, etc.). A course that have great impact would be General Chemistry which typically acts as a pre-requisite for manty STEM majors and careers. The efforts to be described in this thesis was conducted at a large, public doctoral granting university in the southeastern United States of America. The first effort described in this thesis explores how students solve different types of stoichiometry-based problems along …

Evaluating The Meditation Practices And Barriers To Adopting Mindful Medicine Among Physicians, Tiffany Champagne-Langabeer, Chelsea G Ratcliff, Christine Bakos-Block, Francine Vega, Marylou Cardenas-Turanzas, Aila Malik, Radha Korupolu

Faculty, Staff and Student Publications

Background: Chronic pain affects over 25% of U.S. adults and is a leading cause of disability. Mindfulness meditation (MM) is a nonpharmacologic approach to manage pain and improve well-being. Despite mounting evidence supporting its efficacy, MM remains underutilized in medical practice. Understanding physicians' engagement with MM and the barriers they face can inform strategies for integration into clinical care. This study assessed physicians' attitudes toward MM, including barriers to practice and their likelihood of recommending it to patients.

Methods: A cross-sectional survey of U.S. physicians was conducted from April to July 2024. Participants provided information on demographics, health struggles, and …

Bayesian Nonparametric Hypothesis Testing Methods On Multiple Comparisons, Qiuchen Hai, Zhuanzhuan Ma

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we introduce Bayesian testing procedures based on the Bayes factor to compare the means across multiple populations in classical nonparametric contexts. The proposed Bayesian methods are designed to maximize the probability of rejecting the null hypothesis when the Bayes factor exceeds a specified evidence threshold. It is shown that these procedures have straightforward closed-form expressions based on classical nonparametric test statistics and their corresponding critical values, allowing for easy computation. We also demonstrate that they effectively control Type I error and enable researchers to make consistent decisions aligned with both frequentist and Bayesian approaches, provided that the …

Designing Accessible Ui/Ux For Epileptic Patients: A Scalable Solution For Music Therapy Delivery, Amethyst G.H. Mckenzie

Computer Science Senior Theses

How can we design an accessible, scalable UI/UX system tailored to the cognitive, visual, and motor impairments of epileptic patients, that ensures safe and effective interactions with music therapy applications? This research explores the intersection of accessibility, user-centred design, and digital health, using an iterative design process to develop and refine the SONATA app—a clinically deployable music therapy platform.

Through two prototype iterations, usability testing, and quantitative event logging, this study compares the effectiveness of structured versus flexible navigation in improving user experience. Key findings reveal that structured navigation reduces unintended detours, while progressive disclosure techniques enhance instructional clarity. Additionally, …

A Bland–Altman Comparison Of The Lead Care® System And Inductively Coupled Plasma Mass Spectrometry For Detecting Low-Level Lead In Child Whole Blood Samples, Christina Sobin, Tanner Schaub, Natali Parisi, Eva De La Riva

Departmental Papers (PH)

Chronic childhood lead exposure, yielding blood lead levels consistently below 10 μg/dL, remains a major public health concern. Low neurotoxic effect thresholds have not yet been established. Progress requires accurate, efficient, and cost-effective methods for testing large numbers of children. The LeadCare® System (LCS) may provide one ready option. The comparability of this system to the “gold standard” method of inductively coupled plasma mass spectrometry (ICP-MS) for the purpose of detecting blood lead levels below 10 μg/dL has not yet been examined. Paired blood samples from 177 children ages 5.2–12.8 years were tested with LCS and ICP-MS. Triplicate repeat tests …

The Future Of Ai: Join The Conversation, Jennifer Wojton, Cassandra Branham, Vijay Tummala, Laxima Niure Kandel, Kayla D. Taylor

Publications

Join the Conversation! The Future is AI? There is so much conflicting information about what AI is capable of, how it could/should be used, by whom and for what purpose. In this panel discussion, we hope to provide a baseline of information that will help all participants think critically and articulate thoughtful questions about the mechanics of AI, ethical use or non-use of AI in particular contexts (school, industry, business, art, etc.), and the impacts we are currently experiencing or are likely to experience. Hear from ERAU faculty of different disciplines to discuss what the current state of AI technology …

This One Weird Trick Gets Users To Stop Clicking On Clickbait, Ankit Shrestha, Arezou Behfar, Sovantharith Seng, Matthew Wright, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Clickbait, masked behind interesting headlines and thumbnails, is often used to spread misinformation and trick users into clicking on social media posts or links that direct them to malicious websites. To help users protect against clickbait, we examined interventions based on persuasion theories including designs that used social consequence, personal consequence, and badges. To this end, we first conducted a preliminary study to translate the participants’ feedback into improving our initial designs, followed by a lab study with 20 participants (60% Male, 40% Female; 18-44 years old) aimed at understanding their perceptions of the improved interventions; we further updated our …

Language Processing: The Precedence Of Neural Networks On The Account Of Hidden Markov Models, Dia Eddin Abuzeina

An-Najah University Journal for Research - B (Humanities)

Background: since its discovery at the beginning of the last century, Markov models gain a great popularity, and have been widely used in different domains. However, the most prominent use was in computational linguistics, or what is known as natural language processing (NLP). Abstractly, Markov models are nothing but a statistical representation of a particular system. The mathematical statistical representation of a given system is the heart of Markov theory. Markov models characterized by solid mathematical representation, which significantly promotes using it. No doubt, Markov models are mainly used in prediction and classification, to serve computational linguistics as well as …

Children Suspected For Developmental Coordination Disorder In Hong Kong And Associated Health-Related Functioning: A Survey Study, Kathlynne F. Eguia, Sum Kwing Cheung, Kevin K.H. Chung, Catherine M. Capio

Health Sciences Faculty Publications

Children with developmental coordination disorder (DCD) have motor difficulties that interfere with their daily functions. The extent to which DCD affects children in Hong Kong has not been established. In this study, we aimed to estimate the prevalence of children suspected of DCD (sDCD) in Hong Kong and to examine the relationship between motor performance difficulties and health-related functioning. We conducted a cross-sectional survey of parents of children aged 5 to 12 years across Hong Kong (N = 656). The survey consisted of the Developmental Coordination Disorder Questionnaire (DCDQ) and short forms on global health, physical activity, positive affect, and …

Energy Saving Through Climate Education: Climate Sensitization In School For Mindful Consumption At Home, Haritha Saranga, Satyajit Roy, Kanchan Mukherjee

Working Papers

An effective fight against climate change requires both a “top-down” approach and “bottom-up” changes; that is, adopting sustainable practices at the individual and household levels, which requires knowledge, belief, and willingness to engage in climate action. Extant research has shown a number of challenges in bringing about persistent changes in human behavior. We propose to bring about mindful energy consumption behavior at the household level by using children as the conduit for behavior change. Scalable interventions that create awareness about climate change and its impact through early self-regulation in middle and high schools are a promising and cost-effective opportunity to …

If You Were A Sesame Street Character, Which One Would You Be? Natural Language Processing And Personality With Big Bird And Friends, Joseph Uran Meyer

Doctoral Dissertations

This paper examined and compared several natural language processing and machine learning techniques in predicting self-reported Big Five personality traits from text responses. The models were validated on the open-source 2019 SIOP Machine Learning Competition dataset (N = 1,689). The techniques evaluated included bag-of-words, Empath dictionary, LSTM networks, fine-tuning Transformer models, and stacked generalization. Results indicated that the present study’s models had lower error in four of the five constructs analyzed. Limitations of the study include use of an MTurk sample and small sample size. Future research should explore similar techniques on larger applicant samples. Practical implications and contributions to …

A Feedback-Guided Analysis Of Environmental, Health And Socio-Economic Factors Affecting Drivers’ Willingness To Shift To E-Jeepneys, Charlotte Kendra Gotangco Gonzales, Katrina Abenojar, Carlos Rosauro Manalo, Melliza Templonuevo Cruz, Maria Obiminda L. Cambaliza, James Bernard Simpas, Imee Delos Reyes, John Wong, Bernell Go, Krizelle Cleo Fowler, Rene Marlon Panti, Emma E. Porio, Jean Jardeleza Mijares

Environmental Science Faculty Publications

The Jeepney Modernization Program involves the replacement of traditional jeepneys with more efficient alternatives, including modern enclosed electric vehicles, alongside operational improvements to the public transportation system. This study aims to assess the environmental, health and socio-economic factors impacting drivers’ willingness to shift to e-jeepneys. Feedback-Guided Analysis was used as a framework for designing an interdisciplinary approach towards understanding the decision-making paradigms of drivers plying a specific route in Quezon City, Metro Manila. Measurements of drivers’ exposure to PM2.5 and associated health parameters were complemented by key informant interviews delving into income, expenses, valuation of benefits and decision-making paradigms. A …

The Virtual Wunderkammer: Integrating Neuroinclusive Design And Ai-Augmented Technologies For Immersive Museum Experiences, Piper Hutson, James Hutson

Faculty Scholarship

The Virtual Wunderkammer represents an innovative paradigm in museum exhibition design, integrating neuroinclusive principles with artificial intelligence (AI)-augmented technologies to foster immersive and cognitively accessible visitor experiences. Historically, the Wunderkammer, or "cabinet of curiosities," served as a precursor to modern museums, offering eclectic collections that stimulated intellectual curiosity and sensory engagement. The contemporary reimagining of this concept utilizes emerging technologies such as augmented reality (AR), virtual reality (VR), haptic feedback, and olfactory-enhanced digital environments to create personalized, adaptive museum experiences. This study explores the critical intersection of neuroaesthetics, cognitive science, and AI-driven interactivity in digital exhibitions, emphasizing their potential to …

Alfred Russel Wallace Notes 35. Natural Selection By Evolution., Charles H. Smith

Faculty/Staff Personal Papers

Alfred Russel Wallace (1823?1913) is remembered, with Charles Darwin, as the co-originator of the concept of evolution by natural selection. But Wallace’s framing of the idea increasingly became one in which natural selection itself was regarded as a law of nature, not a theory per se.

False Narratives, Real Consequences, Russell W. Cantrell, Matt Campbell

Shelby Hall Graduate Research Forum Posters

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation's role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This …

Topical Text Segmentation For Stream Of Consciousness Writing, Yuwei Lu, Ryan Benton

Shelby Hall Graduate Research Forum Posters

Stream of consciousness writing has a long history, including novelists James Joyce and Virginia Woolf. However, there has been little work done in automated and semi-automated analysis of such writing, which is the focus of this work. We plan to divide real streams of consciousness writing into distinct topical units and then capture different momentary meaningful topics from these units. By doing this, researchers and readers could gain a more nuanced understanding of the narrative structure and thematic elements. In addition, it would also support applications in fields like psychology and linguistics, where understanding thought processes and narrative structures is …

Wright State University's Celebration Of Student Research, Scholarship & Creative Activities From Thursday, March 13, 2025, Wright State University

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Abstract Books

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Celebration of Student Research, Scholarship & Creative Activities on March 13, 2025.

A New Measure Of Non-Parametric Correlation For Variables In The Likert Scale, Shubhabrata Das

Working Papers

We propose a new measure of nonparametric correlation that is especially suited for measuring association between variables measured in the Likert scale where data is ordinal and tied observations are extremely common. The proposed general structure of the measure is based on graded level of concordance and discordance between the pairs of metrics. The general form of the measure has all the desirable properties except the measure is not necessarily zero for independent variables. This limitation is acceptable given only ordinal nature of the metrics. Three versions of the measure are studied. The first is based on simple equi-distant weights. …

Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph

Theses and Dissertations

Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …

Managing Beyond Water: Utilizing Community Well-Being Interviews In The Upper Yakima River Basin, Usa, For Climate Change Adaptation, Rebecca Gustine, Alexander Theophilus, Courtney G. Flint, Jessica D. Ulrich-Schad, Emma Epperson, Claudia Mendez Wright, Jennifer C. Adam

Sociology, Social Work and Anthropology Student Research

In contemporary, natural resources dependent and specialized communities, community well-being is connected to the environment. Understanding the local connections between community well-being and the environment can provide a more complete understanding of how to manage social-ecological systems and promote community resilience. Herein, we combine semi-structured community well-being interviews with hydrologic modeling using the variable infiltration capacity (VIC) model to suggest climate adaptation pathways for a diverse set of community interests. We found that community well-being across the Yakima River Basin was connected to water, snow, and the environment through recreation opportunities, aesthetics, livelihoods, and having clean water and air. Additionally, …

The Ethics Of Ai Nudges: How Ai Influences Decision-Making, Seema Chokshi

Asian Management Insights

And why decision-makers should care about it. Artificial intelligence (AI) systems, through mechanisms like nudges and choice architecture, actively, yet often subtly, shape human decision-making in everyday life and professional settings. AI systems can prioritise profit or efficiency at the expense of human agency, fairness, and well-being, highlighting the need to balance AI’s capabilities with ethical considerations. The EU AI Act is a landmark framework designed to curb manipulative AI practices, emphasising the protection of human autonomy and accountability in decision-making.

Standardizing Canine Breed Data In Veterinary Records Is Challenging, But Computer Vision Offers An Alternative Perspective On Breed Assignment, Glenvelis Perez, Yixuan He, Zihan Lyu, Yilin Chen, Nicholas Howe, Halie M. Rando

Computer Science: Faculty Publications

Dog breed is fundamental health information, especially in the context of breed-linked diseases. The standard-ization of breed terminology across health records is necessary to leverage the big data revolution for veterinary research. Breed can also inform clinical decision making. However, client-reported breeds vary in their reliability depending on how breed was determined. Surprisingly, research in computer science reports that AI can assign breed to dogs with over 90% accuracy from a photograph. Here, we explore the extent to which current research in AI is relevant to breed assignment or validation in veterinary contexts. This review provides a primer on approaches …

Plural Water Narratives: An Environmental Justice Lens On A Systematic Review Of Q-Methodology Water Research, Melissa Haeffner, Alida Cantor, Janet Cowal, Andrea Bryant, Darius Mani Yaw, Kinna Je Palacios, Daniela Serna, Bryce Sprauer, Abigail Tran-Gruver

Environmental Science and Management Faculty Publications and Presentations

Environmental justice research has shown that people's experiences and perceptions of water differ because systematic inequalities shape the extent to which people access clean water and are exposed to water hazards. Q‐methodology is one technique that has been used to aggregate multifaceted subjective narratives and understand different perspectives on a topic. In this paper, we systematically review 77 case study articles applying Q‐methodology to water‐related topics, to inventory how people perceive their relationships with water. We create a classification system based on environmental justice theory to examine (1) distributive justice issues around alternative water sources and agricultural and urban water …

Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii

Theses and Dissertations

The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.

Geo-Spatial Mapping Of Sentiment Analysis With Transformer-Based Models, Dugan J. Turnbow

Theses and Dissertations

The public sentiment of events of interest, and their impacts, is vital for decision makers to allocate resources. This research develops a robust algorithm for aggregating sentiment analysis from social media and published articles, while contextualizing results through spatial and temporal mapping. The methodology employs two transformer-based language models for sentiment analysis and named entity recognition (NER). Sentiment scores are generated and augmented using explicit location data, such as latitude and longitude, and implicit location data derived through NER or location features. Results are mapped using a geo-tagged location dictionary, enabling visualization of sentiment trends at state and county levels …

Analyzing U.S. Army Recruiter Productivity Through Cohort Differentiation And Behavioral Tendency Composition, Mary M. Bates

Theses and Dissertations

This research analyzes differences among aggregate achievements of U.S. Army recruiting cohorts, determines which behavioral tendencies are indicative of performance level, and investigates aggregate behavioral composition with cohort achievement. Analyses require implementation of OLS regression, ANOVA, Tukey’s Test, Mann-Whitney U test, Holm-Bonferroni adjustment, XGBoost decision tree, logistic regression, and the Kolmogorov-Smirnov test. The results show insignificant achievement differences among cohorts and weak yet prevalent abilities of select measures of behavioral tendencies to indicate recruiter performance.

Evaluating Learning Outcomes In A Serious Game: A Practical And Model Checking Approach, Matthew D. Douglas

Theses and Dissertations

This research introduces a novel computational framework to evaluate and predict the educational impact of serious games during development. By using finite state machines (FSM) and model-checking techniques, this study evaluates two serious games. Traditional evaluation approaches, often reliant on resource-intensive human trials, lack scalability and fail to provide early insight into the alignment of game mechanics with learning objectives. This study addresses these challenges of traditional evaluation methods.

Quantifying The Role Of Active Listening And Reassurance In Virtual Health Coach Interactions, Ghulam Hussain, Brian Keegan, Robert Ross

Conference papers

Conversational Agents have the potential to support healthcare through coaching exercise routines, but are still lacking in demonstrating authentic social behaviours to support engagement. To this end, we present a series of experiments that we conducted in order to investigate how automated health care coaches can be more effective when their interaction style is tailored to demonstrate qualities associated with a good bedside manner, namely active listening and reassurance. To test this, we first developed a dataset of 135 dialogue excerpts from three distinct sources, i.e., original, handcrafted and LLMs, the latter two of which were tuned to demonstrate specific …

Gender Biases Within Artificial Intelligence And Chatgpt: Evidence, Sources Of Biases, And Solutions, Qi Hui Jerlyn Ho, Andree Hartanto, Andrew Koh, Nadyanna M. Majeed

Research Collection School of Social Sciences

The growing adoption of Artificial Intelligence (AI) in various sectors has introduced significant benefits, but also raised concerns over biases, particularly in relation to gender. Despite AI's potential to enhance sectors like healthcare, education, and business, it often mirrors reality and its societal prejudices and can manifest itself through unequal treatment in hiring decisions, academic recommendations, or healthcare diagnostics, systematically disadvantaging women. This paper explores how AI systems and chatbots, notably ChatGPT, can perpetuate gender biases due to inherent flaws in training data, algorithms, and user feedback loops. This problem stems from several sources, including biased training datasets, algorithmic design …

Exploring Ai Technology In Grammar Performance Testing For Children With Learning Disabilities, Dimitra V. Katsarou, Evangelos Mantsos, Soultana Papadopoulou, Maria Sofologi, Efthymia Efthymiou, Ilias Vasileiou, Kalliopi Megari, Maria Theodoratou, Georgios A. Kougioumtzis

All Works

The study explores the application of artificial intelligence (AI) in addressing grammar challenges among children with learning disabilities, aiming to assess the efficacy of an AI-driven tool for personalized interventions. A sample of 100 children aged 8–12, diagnosed with learning disabilities, was recruited from special education programs. Participants were divided into an experimental group (n = 50), which used an AI-based grammar assessment tool with personalized feedback, and a control group (n = 50), which completed conventional paper-based grammar tests without feedback. The AI tool administered adaptive grammar tasks, including sentence correction and verb conjugation, and performance was evaluated over …