Digital Commons Network^™

Predicting Student Academic Performance Using Behavioural And Parental Engagement Data From Learning Management Systems, Saeed Alfalasi

Theses

This paper explores how behavioral, academic, and parental engagement data provided within the xAPI-Edu-Data dataset can be used to predict the academic performance of students when training on machine learning models with supervised learning. Due to the developing demands of the data-driven initial selection of the learners under risk, the study will create a valid and explainable predictive model that can consider the most significant factors of student success in Learning Management System (LMS). The research is based on behavioral engagement and self-regulation learning theories; the observations included in the analysis of student interaction, i.e. resource usage, classroom engagement and …

Predicting Undergraduate Fallout And Success, Ammar Ahmed Alzarooni

Theses

Universities need to uncover students who are likely to drop out early and do something about it. It should be easy to find and use this information. This thesis evaluated interpretable machine-learning models (MLMs) for predicting three final student outcomes including Dropout, Enrolled and Graduate, using solely demographic, administrative/financial and first-semester academic variables. Study employed publicly accessible Portuguese UCI student retention dataset (4,424 records) and incorporated end-of-Semester-1 feature window to prevent look-ahead leakage and align with actual advising cycles. We trained and compared models using stratified validation, explicit class-imbalance handling and decision-threshold optimization to make dropout detection most critical factor. …

Early Drowsiness Detection Via Second-Order Derivative Analysis Of Heart Rate Variability: A Non-Contact Ecg Approach With Machine Learning, Fabrice Vaussenat, Abhiroop Bhattacharya, Julie Payette, Alireza Saidi, Victor Bellemin, Geordi-Gabriel Renaud-Dumoulin, Sylvain G. Cloutier, Ghislain Gagnon

Études primaires

Drowsy driving contributes to roughly 20% of traffic fatalities, yet most detection systems rely on behavioral cues that appear only after impairment has set in. Here we ask whether first and second derivatives of heart rate variability (HRV) can detect pre-crash states earlier than conventional approaches. Twenty-five participants completed 49 driving simulator sessions while we recorded cardiac activity through capacitive ECG electrodes embedded in the seat backrest—a non-contact method that avoids the privacy concerns of camera-based monitoring. To prevent circular evaluation, ground truth labels were based solely on crash proximity rather than HRV-derived scores. The combined HRV feature set (conventional …

Le Parcours Des Travailleurs Immigrants Blessés Et Son Incidence Sur L’Alliance Thérapeutique : Une Étude De Cas Longitudinale En Contexte De Réadaptation Au Travail Au Québec, Maude Arsenault, Jessica Dubé, Daniel Côté

Études primaires

Cette étude explore l’incidence du parcours prélésionnel des travailleuses et travailleurs immigrants (TI) blessés sur l’alliance thérapeutique (AT) en réadaptation au travail. À partir d’une ethnographie longitudinale menée dans une clinique québécoise, sept trajectoires ont été analysées selon leurs dimensions migratoires, socioprofessionnelles et linguistiques. Les résultats montrent que le déclassement professionnel, la précarité de l’emploi, les barrières linguistiques et les expériences de racisme fragilisent la construction du lien de confiance et la définition partagée des objectifs de retour au travail. Lorsque l’emploi prélésionnel est perçu comme transitoire ou inadéquat, l’obligation institutionnelle d’y retourner crée une rupture symbolique qui entre en …

Computer Vision-Based Collision Prevention In Construction: Bridging Academic Advances And Industrial Requirements, Marwa Ziadia, François Gauthier, Damien Burlet-Vienney

Études primaires

Computer vision (CV) technologies have emerged as promising tools for real-time collision risk management. This paper examines CV-based collision-prevention systems from academic and industrial perspectives with a focus on identifying technical and implementation challenges affecting their deployment on construction sites. A scoping review of 158 publications was conducted, alongside an assessment of commercial CV-based collision-prevention systems currently used in construction. The analysis focused on five key functions: object detection, distance measurement and proximity estimation, tracking, worker re-identification (ReID), and deployment robustness. Academic studies demonstrate substantial progress in detection accuracy, real-time processing, trajectory tracking, and predictive risk assessment through deep learning …

Looking Forward, Reflecting Back: The Promise Of Dispute Resolution To Reform The Criminal Legal System, Cynthia Alkon

Faculty Scholarship

The criminal legal system in the United States is plagued by serious and systemic problems. There have been countless efforts at reform over the last many decades that have included changes in what is a crime, how crimes are punished, how prosecutors do their job, and changes in policing. Yet, despite these efforts, problems such as mass incarceration remain deeply embedded. It is easy to be swept up in pessimism when discussing the criminal legal system. Change is hard, at best incremental, and we seem to be in the beginning of an era of backlash against recent reforms. This is …

Moral Progress In Legal Doctrine, Philip Petrov

Faculty Scholarship

This article integrates the concept of moral progress – here, moral improvement in the thinking and behavior of individuals over time – into the study of legal doctrine. The article first presents a naturalistic account of what moral progress is and describes three of its most historically and analytically important forms: (1) moral circle expansion, (2) moral domain expansion, and (3) increasing sensitivity to proportionality. The article then analyzes three historical developments in U.S. tort law that qualify as instances of moral progress: (1) the partial demise of the “suicide rule” beginning around the 1980s (according to …

Digital Assets And The Property Question, Andrea Tosato, Christopher K. Odinet

Faculty Scholarship

Is crypto property? The proliferation of digital assets such as cryptocurrencies, stablecoins, memecoins, and NFTs has confronted legal systems worldwide with three interdependent challenges: determining whether they are property, identifying their appropriate classification within property taxonomies, and establishing rules for their circulation in commerce. Our Article addresses this tripartite question—the Property Question—within American law.

The stakes here are significant. Billions of dollars in digital assets are traded daily, used as collateral, and held by custodial platforms. Yet all these transactions rest on an unresolved premise: that digital assets can be owned and are governed by established property rules. This fundamental …

Upr Report Submissions, Sarah Dávila A., Lauren E. Bartlett

Faculty White Papers

No abstract provided.

Operation Midway Blitz: How Federal Immigration Agents Violated International Human Rights, Sarah Dávila A., Alejandra Palacios, Roberto A. Valdez Jr.

Faculty White Papers

No abstract provided.

Timothy M. Mulvaney, Timothy M. Mulvaney

Faculty CVs

No abstract provided.

Katherine Mims Crocker, Katherine Mims Crocker

Faculty CVs

No abstract provided.

A Conceptual Framework For Cognitive Engagement And Human Agency In Ai-Mediated Learning, Sam Rhodes, Zuhal Yilmaz, Terrie Galanti, Younggon Bae, Victoria Delaney, Zareen Gul Aga, Stephen Hutt

School of Mathematical & Statistical Sciences Faculty Publications

The purpose of this chapter is to propose a conceptual framework that unpacks AI use in instructional practice across three interrelated dimensions: human agency, cognitive demand, and AI orchestration. We ground this work in historical perspectives on technology's mediating role in education. We then propose the conceptual framework and three characterizations of the use of AI in school instruction: cognitive load reducer, cognitive capacity builder, and cognitive companion. We then illustrate a worked example of each, including a curricular example and sample student prompts, and conclude with questions that educators might ask themselves as they consider if and how to …

Mariano Torres And Lester Wilson V. James Carlson, Et. Al., Brief Of Amicus Curiae Center For Jewish Legal Studies In Support Of Plaintiffs-Appellants And Reversal, Rona Kaufmann, Lee Wolosky, Andrew J. Lichtman, Machol Benmelech

Law Faculty Publications

Amicus curiae the Center for Jewish Legal Studies (“CJLS”)¹ is an academic organization dedicated to establishing and advancing the emerging field of Jewish Legal Studies, which examines the intersection of law and Jewish peoplehood. CJLS convenes legal and interdisciplinary scholars whose research examines antisemitism and anti-Zionism across historical periods and ideological movements, including how ostensibly political language can express hostility toward Jews as a people. Through this scholarship, CJLS develops historical and legal frameworks that assist courts in recognizing and evaluating contemporary manifestations of anti-Jewish discrimination.

Reclaiming Sophia In The Age Of Ai: Theological And Ethical Reflections On Consecrated Technology And Human Dignity, Matthew H. Sauber

Faculty Scholarship 2026

The cultural emergence of artificial intelligence systems named after figures of divine wisdom—most notably the Hanson Robotics humanoid Sophia, granted Saudi citizenship in 2017—reveals a gap between the language of the wisdom traditions and that of contemporary technology. This paper treats that gap as the occasion for theological and ethical reflection on AI. Drawing on the Sophia tradition across its Hebrew, Hellenistic-Patristic, Gnostic, Russian Sophiological, perennialist, and Sufi articulations—especially Sergei Bulgakov’s account of Sophia as mediation between divine wisdom and created order—it develops a framework termed Consecrated Technology. The argument unfolds in three moves: (1) a structural critique showing how …

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

The Tax Governance Triangle: An Attitudinal Theory Of State Capacity And Tax Compliance., Abdul Wahid Uqaily

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Tax Governance Triangle: An Attitudinal Theory of State Capacity and Tax Compliance

Abdul Wahid Uqaily

Variation in states' extractive capacity is a central puzzle in comparative politics and political economy. Existing scholarship explains this variation largely through institutional quality, administrative capability, or coercive enforcement, with less attention to the attitudinal foundations that shape key actors' willingness to sustain an effective fiscal system. This dissertation addresses that gap by asking: how do the attitudes and behaviors of citizens, bureaucrats, and elites shape variation in a state's extractive capacity?

To answer this question, the dissertation develops the “Tax Governance Triangle” and …

Promoting The Use Of Smoke Evacuation Systems In The Operating Room: A Quality Improvement Initiative, Andrea Leigh Drayer

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: Surgical smoke produced during procedures poses serious health risks to operating

room (OR) staff and patients, yet many hospitals, including an academic medical center in

northern West Virginia, have underutilized smoke evacuation systems. The imminent

enforcement of West Virginia House Bill 4376, mandating smoke evacuation use, provided both

urgency and opportunity for an intervention.

Purpose: The purpose of this Doctor of Nursing Practice (DNP) quality improvement project

was to increase timely compliance with the use of smoke evacuation systems during all smoke-

producing procedures, ensuring alignment with safety standards and legislative requirements.

Methods: A systematic evidence review of academic …

Influences Of Response Rate And Distribution On Accuracy Estimates: The Value Of Replications Based On Analytic Approach, Olivia Brianne Harvey

Graduate Theses, Dissertations, and Problem Reports (ETD)

Accurate observational data are essential for drawing correct conclusions about behavioral phenomena and ensuring the replicability of research findings. Accuracy is the extent to which an observer’s recorded responses correspond with true values (i.e., the actual occurrence of behavioral events). Correspondence is quantified using one of several percentage-based algorithms. However, these accuracy estimates may be influenced by characteristics of the data, such as response rate and response distribution, as well as the algorithm used to calculate them. The purpose of this dissertation was to evaluate how response rate, response distribution, and the algorithm used to evaluate accuracy influences estimates. Across …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Dataless Neural Networks For Boolean Satisfiability And Network Optimization, Andrew Evan Gautier

Graduate Theses, Dissertations, and Problem Reports (ETD)

Combinatorial optimization problems (COPs) require searching over a finite solution space subject to constraints, with the goal of satisfying an objective function. They arise in operations research, scheduling, resource allocation, circuit design, and many other fields. Many problems in combinatorial optimization (including satisfiability and network design) are NP-hard. Traditionally, researchers have built approximate solvers that return near- optimal solutions efficiently by developing increasingly sophisticated heuristics and meta- heuristics. Deep learning has provided new opportunities for improving combinatorial solvers by leveraging neural guidance to prune the search space. Traditional neural networks have distinct drawbacks in this context: separate training and …

Multimodal Representation Learning For Face Understanding: From Caption Supervision To Foundation Model Adaptation, Md Mahedi Hasan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of intelligent surveillance systems and the increasing demand for reliable biometric identification in border security, public safety, and digital forensics require robust face understanding under unconstrained conditions, including low resolution, pose variation, and occlusion. While Vision Transformer (ViT)-based foundation models have greatly improved visual representation learning, their patch-based tokenization and lack of spatial inductive bias limit their ability to capture fine-grained details in low-resolution inputs. This dissertation investigates multimodal representation learning for face understanding through natural language supervision, large-scale face-caption pre-training, and parameter-efficient foundation model adaptation. It hypothesizes that textual supervision provides complementary semantic cues that improve …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Energy Partition And Heating Mechanisms In Asymmetric Antiparallel Magnetic Reconnection, Aleksandra Abova-Volkova

Graduate Theses, Dissertations, and Problem Reports (ETD)

Magnetic reconnection is a fundamental plasma physics process whereby a change in magnetic field connectivity drives the conversion of magnetic energy into energy of the surrounding plasma, often explosively. One of the many settings where it occurs is at the dayside magnetopause of Earth and other planets, where the magnetic field, number density, and/or temperature in the plasmas on the two sides upstream of the reconnection site are asymmetric. How the incoming magnetic energy gets partitioned into outgoing energies during asymmetric reconnection remains an outstanding question; of special interest is the fraction that gets converted into internal energy of ions …

Racial Resentment, Immigration Attitudes, And The Politics Of State Immigrant Policy Adoption In The United States, Cindy Osei Agyemang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Immigration remains one of the most contested public policy issues in the United States, and racial attitudes have become increasingly important in shaping public opinion and political debate. While prior research has shown a strong relationship between racial resentment and restrictive immigration attitudes, less is known about whether these attitudes extend to legislative discourse and the adoption of immigrant-inclusive state policies. This dissertation addresses that gap by examining the relationship between racial resentment and immigration politics across three levels of analysis: public opinion, legislative discourse, and state policy adoption. Using a mixed-methods research design, the study combines quantitative and qualitative …

Nuclear Aurka-Driven Early Dissemination Of Breast Cancer Uncovers Opposing Roles Of Hif-1a And Hif-1b In Metastasis, Abha Maskey

Graduate Theses, Dissertations, and Problem Reports (ETD)

Metastatic progression is the primary cause of mortality in the majority of solid tumors, including breast cancer (BC). The triple-negative breast cancer (TNBC) is the most aggressive BC subtype with the highest recurrence rates within 1-3 years post-diagnosis, and worst overall survival outcomes. Early distant recurrence of cancer is enabled by early disseminated tumor cells (eDTCs), yet the mechanisms of early dissemination remain poorly defined. Hypoxia-inducible factor 1 (HIF1) is a transcription factor normally induced under hypoxia to enable cell survival. It is the major cause of metastasis from hypoxic tumors. In our work, we demonstrated that the nuclear Aurora …

How Do Reading Specialists Shape Their Identities As Literacy Leaders? An Exploration Of Competence, Performance, And Recognition Within Communities Of Practice, Christina Glance Petrone

Graduate Theses, Dissertations, and Problem Reports (ETD)

This qualitative multiple-case study explored how reading specialists enact literacy leadership within elementary schools in West Virginia. Although reading specialists are increasingly expected to support schoolwide literacy improvement, leadership responsibilities are not always explicitly defined within their roles. Guided by a communities of practice framework and an identity model, this study examined how reading specialists develop and demonstrate literacy leadership through their daily interactions with teachers, administrators, and other school personnel. Data sources included participant questionnaires and semi-structured interviews with participants, their principals, and colleagues from their school. Participants in this study included three reading specialists (interventionists) working in K-5 …

Self-Leadership And Perceptions Of Artificial Intelligence: A Single-Case Study, Patrik Garren

Graduate Theses, Dissertations, and Problem Reports (ETD)

The purpose of this single-case qualitative project is to uncover how self-leadership’s behavioral and cognitive strategies influence perceptions of Artificial Intelligence (AI) and AI adoption. While existing literature acknowledges that there is an association between self-leadership, technology’s perceived usefulness and ease of use, as well as comfort with AI preparedness and its professional impact, there is limited research on how self-leadership shapes perceptions of AI and AI adoption in real-life contexts. To fill this gap in contemporary literature, this project analyzes qualitative semi-structured interviews with 25 healthcare professionals involved in the implementation of ‘AI Model 1’ at their mid-sized United …

Programs Of Support For Wardship Experienced Students: Exploring Program Directors' Expectations And Experiences Through A Bioecological Framework, Adalheid Faith Crum

Graduate Theses, Dissertations, and Problem Reports (ETD)

The purpose of this research is to explore the expectations and experiences of program directors of campus support programs which center wardship experienced students. This research question guided the current study: What expectations and experiences influenced program directors’ development and reform of a wardship-centered campus support program? This inquiry applies Ürie Bronfenbrenner’s Person–Process–Context–Time (PPCT) bioecological model. Semi-structured interviewing was utilized for this case study. In this research, six directors of campus support programs centering wardship experienced students were interviewed. Additionally, this work employs content analysis of twenty-eight National Research Collaborative for Foster Alumni and Higher Education (NRC-FAHE) publications, introducing fourteen …

Survival In The Stigmatized Industry (Bitcoin Atm), Brooks Mcadam

Graduate Theses, Dissertations, and Problem Reports (ETD)

ii ABSTRACT Survival in the Stigmatized Industry (Bitcoin ATM) Brooks McAdam This paper examines how companies can survive in a stigmatized industry where the same message may attract customers while simultaneously generating skepticism. The study posed the following research question using the Bitcoin ATM industry as the context: Does the message presented on company websites influence the degree of exit risk in a market characterized by moral concerns, exposure to fraud, and unstable regulation? The answer is clear. Messaging is important; however, not every message is equally important. Fee-related messaging emerged as the most consistent predictor of exit risk. Messaging …