Digital Commons Network^™

Modeling The Psychological And Technical Factors Influencing The Use Of Artificial Intelligence Tools Among Non-Native Arabic Learners: A Comparative Study In Egypt, Saudi Arabia, And Jordan., Mohammad Odeh, Alaa Al Din Musa, Ahmed Ragab Ali Ghalish, Montaser Adel Sayed Ahmed

All Works

This study aimed to develop a predictive longitudinal model of the psychological and technical factors influencing the use of artificial intelligence tools among non-native Arabic learners (international students) in three Arab countries: Egypt, the Kingdom of Saudi Arabia, and Jordan. The study adopted an extended Technology Acceptance Model (TAM) incorporating two psychological variables: trust in artificial intelligence and artificial intelligence anxiety. A quantitative longitudinal design with two time waves (T1 and T2) over a full academic semester was employed using Hierarchical Multiple Regression Analysis and PROCESS Macro for mediation. The sample consisted of 812 international students from public universities in …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Can Kinematics Specify Tool Use Affordances?, Tyler Duffrin

All Dissertations

Object properties such as length, shape, and heaviness, as well as affordance-based properties such as strike-with-ability and poke-with-ability, can be perceived via dynamic touch as functions of inertia tensor invariants. The primary question addressed here was whether people can perceive these same power and precision properties for purely virtual objects, which lack dynamic physical forces. The Kinematic Specification of Dynamics (KSD) principle asserts that missing dynamics are lawfully specified by kinematic (visual) motion patterns, such that kinematic information alone may support successful interactions with virtual objects. In three experiments, we investigated (1) whether virtual reality (VR) users could calibrate to …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

Modeling Mean And Variability Of Anxiety In Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models, Trenzy Odero

Electronic Theses and Dissertations

Ecological Momentary Assessment is a method of collecting repeated measures of people in real time within natural environments. This results in hierarchical data that has a significant amount of variation at the person level. The traditional linear mixedeffects models assume that the residual variance is constant, which might not be true when the residual variance varies among individuals as well as in time. This thesis uses mixed-effects location-scale (MELS) models to model the mean and variance of an EMA outcome together. By introducing the possibility of variability in residual variance within and across individuals and with covariates, the MELS framework …

Domain Adaptation Of Facial Age Estimation For Law Enforcement Mugshot Repositories, Jorge Alejandro Pacheco Roque

Open Access Theses & Dissertations

Facial age estimation supports law enforcement via image-based, age-filtered queries, age-progressive re-identification, and bulk record labeling, where prediction accuracy determines if the resulting decisions can be trusted. State-of-the-art models excel on web imagery but incur higher error on mugshots due to domain shift between the professionally lit, filtered, and posed web photographs used during pre-training and the uniform backgrounds, uncooperative expressions, and decades of evolving capture technology found in mugshot collections. We address this gap by adapting SwinFace - a state-of-the-art multi-task Swin Transformer with public code and pretrained weights, trained on color face imagery for face recognition, facial expression …

Viability Assessment Of Bovine Embryos: A Public Dataset And Deep Learning Baselines, Erfan Khayyati

All Graduate Theses and Dissertations, Fall 2023 to Present

Improving the success rates of cattle breeding is essential for sustainable agriculture, global food security, and high-quality livestock production. Currently, determining whether a lab-grown bovine embryo is healthy enough for a successful pregnancy requires highly trained experts to manually evaluate days of continuous time-lapse video footage. This process is not only incredibly time-consuming but also highly subjective; human reviewers often suffer from visual fatigue when tracking subtle, microscopic cellular changes over a seven-day period, leading to significant disagreement among even top experts on an embryo’s true potential. Furthermore, assessing bovine embryos is notoriously difficult due to their dark, lipid-dense cellular …

Fostering Safe Space For Children In Online Navigation And Parent-Child Interactions, Rizu Paudel

All Graduate Theses and Dissertations, Fall 2023 to Present

As children and teenagers spend increasingly more time online, digital devices have become a major source of family friction. Disagreements frequently arise over privacy boundaries, and online activities. When these conflicts are unresolved, they often lead to broken trust and secretive behavior, leaving children vulnerable to digital harms like cyberbullying, toxic content, or account hacking. Therefore, it is important to create a safe and open environment for children where in order for them to share their feelings with parents. This dissertation investigates the human and technological dynamics of parent-child interactions, developing new ways to support collaborative conflict resolution and online …

The Impact Of State Insulin Copayment Caps On Diabetics In The United States, Ryan C. Meyer

All Theses

Insulin is a life-saving medication for people with diabetes that helps regulate blood glucose levels throughout the body. A Type 1 diabetic cannot survive without insulin, and a Type 2 diabetic’s quality of life greatly diminishes without access and use of this drug. Currently, many diabetics skip, ration, or abstain from insulin due to financial barriers. As of June 2026, 29 states have enacted insulin copayment caps for state-regulated commercial health insurance plans to reduce the financial burden of insulin costs. This study examines the impact of these caps on all commercially insured diabetics in the United States, particularly on …

When The Best-Fit Model Is Not Best: The Glass Slipper Fallacy And Latent Growth Mixture Modelling, Jonathan L. Chia, Markus Wettstein, Andree Hartanto

Research Collection School of Social Sciences

Despite the use of latent growth mixture modelling (LGMM) to study longitudinal changes, existing practices may inadvertently impede this very investigation. Although subgroup trajectories may theoretically differ in their structure (e.g., some subgroups being linear, some curvilinear), the current convention advocates overreliance on the baseline model to derive subsequent profile trajectories, which may obscure these structural differences. In this article, we provide a brief description of extant LGMM practices, after which we explicate the pitfalls of the current approach. Finally, we provide a principled approach for LGMM research moving forward. Specifically, we recommend specifying a set of theoretically plausible models …

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

Caring With Ai: The Efficacy Of A Customised Chatgpt-Delivered Self-Compassion Intervention On College Students' Well-Being And Academic Functioning, Tracy Xi Chen, Chi-Ying Cheng, Andree Hartanto

Research Collection School of Social Sciences

College students face various challenges, including academic pressure, social stress, and the transition into adulthood, which can lead to increased anxiety and other mental health issues. By recognizing personal struggles as part of a shared human experience and responding with kindness, self-compassion serves as a powerful strategy for enhancing resilience, facilitating better well-being and performance outcomes. Although effective, Compassion-Focused Therapy often requires substantial resources and time, limiting its applicability to college students. To overcome these barriers, the current study designed and evaluated Your Self-Compassion Companion, a ChatGPT-powered AI chatbot intervention grounded in self-compassion theory and delivered over three weekly 20-min …

A Longitudinal Analysis Of Hospital Consumer Evaluation In Virginia, Tulay Akmandor Inac

Health Services Research Dissertations

Suboptimal patient experience signals a need to improve clinical efficacy, patient safety, and healthcare quality. The COVID-19 pandemic intensified hospital resource and staffing demands, reducing hospitals’ capacity to invest in patient experience improvement. Prior studies remain limited because many lack longitudinal structure and organized theoretical models, making temporal inference difficult and weakening analyses of patient experience disparities. To address these limitations, this dissertation incorporates three studies examining patient experience and pandemic-related effects.

In state-level markets comparable to Virginia, limited research has examined longitudinal patient experience trends across regional hospital systems using HCAHPS scores. The first study uses descriptive trend analysis …

Exploring The Determinants Of User Discontinuance In Ai-Driven Usage-Based Insurance, Wenzhuo Li

Theses and Dissertations in Business Administration

While interest in algorithmic decision-making continues to grow, limited research has examined the post-adoption phase. This study examines how users evaluate their post-adoption experiences with algorithmic decision-making in the context of usage-based insurance (UBI), focusing on how expectation disconfirmation shapes satisfaction and the intention to discontinue use. It explores two key questions: What factors influence users’ discontinuance intention toward AI-based UBI systems? And how do specific algorithmic characteristics alter how users form these post-adoption evaluations? To investigate these questions, this study develops a comprehensive theoretical model that integrates the Expectation Confirmation Model and Reactance Theory, incorporating additional factors such as …

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Numbers, Patterns, And Memories: Early Experiences Of Mathematicians And Mathematics Education Researchers, Constantinos Xenofontos

Journal of Humanistic Mathematics

This paper offers a reflective analysis of early mathematical experiences shared by fifty-six mathematicians and mathematics education researchers, including my own, as part of Cambridge Mathematics’ “Seven Questions with . . . ” interview series. Drawing on thematic analysis, I identify five key patterns across participants’ recollections: the context of early mathematical engagement, the influence of significant others, emotional responses, shifts in mathematical thinking, and mathematics as a social or competitive experience. Many accounts emphasise informal, everyday encounters with mathematics—often preceding formal education—as central to developing interest and confidence in the subject. The findings challenge the notion of innate mathematical …

Impact Of Covid-19 Pandemic On Mathematics Achievement And Problem-Solving Ability: Insights From Secondary Schools In India, Laishram Nirtish Singh, Anand Jyoti Sanasam, Jocyline Thokchom, Ningombam Cha Cogent, Laisom Sharmeswar Singh

Journal of Humanistic Mathematics

The COVID-19 pandemic disrupted students’ engagement with mathematics. This study aims to contribute to our understanding of the extent of this disrupting by examining differences in mathematics achievement and problem-solving ability between adjacent cohorts who learned Class 8 under different schooling conditions in India: Group A (pandemic-exposed Class 8 cohort) and Group B (post-reopening Class 8 cohort). Using a descriptive design in a natural setting, we selected a stratified sample of 1,200 students from Class 9 and Class 10 across 21 secondary schools in Manipur, India. The sample was stratified by gender, family type, school type, and locality to ensure …

Piracy, Terrorism, And The Law: Differential Equations In Hostage Situations, Gabriel Hallevy

Journal of Humanistic Mathematics

Pirates have taken the crew of an American ship hostage. They promise to release the hostages only if another pirate who is held in an American prison for commission of piracy crimes against American citizens, is released. Should the U.S. government enter into negotiations with them? Should they send armed forces and risk the hostages? Should they release the prisoner immediately and unconditionally? The article models and analyzes possible policies regarding sensitive situations involving hostages and other related risks using differential equations. The solutions are surprisingly simple, but not necessarily intuitive. Our analysis aims to demonstrate how powerful mathematics is …

Front Matter

Journal of Humanistic Mathematics

No abstract provided.

Psychological Needs And Ai Delegation Across Four Social Domains - A Cross-Cultural Analysis Of 35 Nations, Magnus Liebherr, Ala Yankouskaya, Mohamed Basel Almourad, Justin Thomas, Guandong Xu, Raian Ali

All Works

As artificial intelligence (AI) systems increasingly assume roles with social, educational, and emotional significance, understanding the psychological drivers behind individuals' readiness to delegate such roles to AI is crucial. Drawing on Self-Determination Theory (SDT), this study examines how the satisfaction of basic psychological needs (autonomy, competence, and relatedness) predicts individuals' readiness to delegate socially significant roles to AI across four domains (education, healthcare, mental health, and companionship) and 35 nations. Using data from over 35,000 participants in the 2023 Global Digital Wellbeing Survey, we applied Bayesian multilevel multivariate modelling to assess both global and culture-specific motivational associations. Results revealed that …

Enhanced Transdermal Immunization Via Solid-In-Oil Nanodispersions Incorporating Dendritic Cell-Targeting Peptide, Md Samiul Islam, Md. Shahin Ekka Sarker, Yoshirou Kawaguchi, Rie Wakabayashi, Noriho Kamiya, Muhammad Moniruzzaman, Masahiro Goto

Publications and Research

Transdermal immunization represents a promising needle-free alternative to conventional vaccination. However, efficient antigen delivery and robust immune activation remain major challenges. In this study, a solid-in-oil (S/O) nanodispersion system comprising a dendritic cell-targeting peptide (HR8), ovalbumin (OVA), and an adjuvant was developed for transdermal immunization. The HR8 peptide along with OVA was successfully incorporated into an S/O nanodispersion with an optimal hydrodynamic diameter of particles (< 200 nm) and exhibited stable physical properties for up to 90 days. In vitro and in vivo studies demonstrated enhanced antigen delivery with insignificant skin irritation in C57BL/6N mice. Moreover, in vivo transdermal immunization studies demonstrated that the addition of the HR8 peptide enhanced OVA-specific IgG responses (~1.5-fold). Notably, the HR8 peptide also promoted an approximately 2.5-fold increase in IgG2c levels, suggesting a shift toward a more T helper type 1-biased immune response, as reflected by an increased IgG2c/IgG1 ratio. Overall, these findings demonstrate that the incorporation of HR8 peptide into an S/O nanodispersion enables efficient transdermal antigen delivery and improved immunogenicity, highlighting its potential as a simple, non-invasive, and patient-friendly immunization strategy.

Governance, Culture, And Law: The Expanding Scope Of Environmental Science And Sustainable Development Research, Ahyaudin Sodri, Herdis Herdiansyah

Journal of Environmental Science and Sustainable Development

Environmental science emerged as a discipline based on physical measurements, such as soil pollutant levels (Ailijiang et al., 2022), ecological restoration (Yue et al., 2026), city surface temperature (Shafizadeh-Moghadam et al., 2025), and microbial density in air samples (Hayleeyesus & Manaye, 2014). However, its objects of study increasingly extend beyond the confines of the laboratory. Questions that were once sufficiently answered with measurement data now require answers through draft laws, Constitutional Court decisions, financial reports of mining companies, and even traditional ritual discourses governing community access to forests. In other words, environmental …

A Mathematical Decision-Making Framework For Athlete Development In A Collegiate Taekwondo Community: Prioritizing Coaching Interventions Using Statistical Analysis And The Analytic Hierarchy Process, King Harold A. Recto, Hazel Jade L. Antonio, Jhyrald Anthony P. Dalida

Electronics, Computer, and Communications Engineering Faculty Publications

Athlete development within collegiate sports communities requires informed decisions regarding the prioritization of coaching interventions and allocation of developmental resources. However, such decisions are frequently guided by experience and intuition, limiting opportunities for systematic and evidence-based decision-making. This study develops a mathematical decision-making framework for athlete development by integrating statistical analysis and the Analytic Hierarchy Process (AHP) within a collegiate taekwondo community. Data were collected from 25 collegiate taekwondo athletes who satisfied established eligibility criteria, including participation in University Athletic Association of the Philippines (UAAP) competitions during the previous three seasons. Athletes evaluated coaching practices across five dimensions: Training and …

A Data-Driven Framework For Mitigating Breast Cancer Overdiagnosis: From Estimation To Risk-Adjusted Computer-Aided Diagnosis, William M. Brown Jr.

LSU Doctoral Dissertations

In Computer-Aided Diagnosis (CAD) of cancer, standard cost metrics (false-positives and false-negatives) fundamentally fail to account for overdiagnosis. Overdiagnosis is a critical scenario where a disease is correctly detected (true-positive) but is biologically indolent and would never have caused the patient harm or symptoms. While widely recognized in the medical community as a major healthcare crisis driving stressful and invasive overtreatment, overdiagnosis remains severely under-researched within computer science and engineering. This dissertation addresses this interdisciplinary gap by defining the three key computational challenges of overdiagnosis: (i) accurate estimation, (ii) harm quantification, and (iii) algorithmic mitigation. To overcome the estimation challenge, …

Interpretable Case-Control Inference Through Log-Linear General Location Models, Zacharia Stuart

Mathematics & Statistics ETDs

This dissertation analyzes one of the few publicly available NFL injury datasets to study field type and non-contact lower-limb injuries. Field type is studied jointly with other risk factors to understand how these factors interact to affect injury risk. The data were gathered through a case-control sampling scheme, which limits direct inference on absolute injury probabilities. While not the most common approach for case-control data, this dissertation models the retrospective distribution directly through Log-Linear General Location Models (Log-Linear GLOMs). Through a log-linear structure placed on a log-odds-ratio reparameterization, the model provides directly interpretable marginal and interaction contributions to injury log-odds …

Timelines Over Tokens: Summarization, Prompting, And Explainable Fine-Tuning For User-Level Suicide Risk Detection, Aditya Tekale

Master's Theses

This research presents a two-stage pipeline for user-level suicide risk detection from Reddit: first, inference-only prompting with summarization; second, fine-tuned encoder classification with explainability and expert validation. The data are user-level: each of the 500 C-SSRS Reddit items is one user’s chronologically concatenated posts and comments (a user timeline), annotated by psychiatrists. Stage one: six prompting strategies zero-shot, few-shot, chain-of-thought, tree-of-thought, least-to-most, and self-consistency are evaluated across six LLMs on multi-class and binary formulations; simple zero-shot achieves the highest balanced accuracy (0.53 multi-class). Error analysis shows longer inputs associate with misclassification (p = 0.002); domain-specific summarization (timelines >2,000 tokens) reduces …

Surveyception: An Exploration Of Deceptive Survey Forms, Muhammad Danish

Computer Science ETDs

Survey platforms such as Google Forms and Microsoft Forms are widely used for feedback, data collection, and engagement, but scammers increasingly exploit them to distribute phishing and deceptive attacks. This thesis presents a large-scale study of survey-form abuse across ten major providers. We collected 140,000 forms from three sources: public posts on X, search-engine results, and web pages from the top 10 million DomCop-ranked domains. Using automated filtering and manual qualitative review, we identified 2,645 forms requesting sensitive information and classified 566 as scams. These forms used techniques including phishing, private-secret theft, account and personal-data harvesting, financial deception, and psychological …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Escaping The Cyberstorm: A Gamified Social Engineering Training Program, Noah Mcclanahan, Fadi Abu-Amara, Ali Khattab, Travis Jett, Andre Jackson

Journal of Cybersecurity Education, Research and Practice

In this research work, we explored the effectiveness of gamification in improving cybersecurity awareness and training users on targeted social engineering attacks. Traditional cybersecurity training focuses on lectures and videos. These training methods may not actively engage employees, which reduces their knowledge retention and ability to recognize social engineering attacks. This lack of involvement is a concern, as social engineering continues to be one of the most prevalent attack methods faced by end-users. A gamified training program, Escaping the Cyberstorm, was developed using the Godot game engine to address key challenges in spreading cybersecurity awareness. The game includes real-life …

Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas

Master's Theses

The presented expectation maximization informed evidential reasoning model extends the ability of the evidential reasoning calculus to support decision making by integrating an adaptive model learning capability. Compatibility relationships in Evidential Reasoning models are traditionally built by human domain experts. This process is labor-intensive, especially for large and complex models. Additionally, when new data becomes available, compatibility relationships must be reconstructed. Using machine learning and the expectation maximization algorithm, it is demonstrated that compatibility relationships can be constructed that learn relationships between domain knowledge that is used to make decisions. Using drug development as a domain of application, a traditional …