Digital Commons Network^™

Secondary Teachers' Experiences In International Professional Development For Convergence Research In Stem And Tradition, Rachel Sparks White, Kristie S. Gutierrez, James K. Ferri

Teaching & Learning Faculty Publications

Convergence education promotes learning experiences that integrate science, technology, engineering, and mathematics (STEM) to address complex real-world problems. However, secondary teachers often report limited access to professional development (PD) and curricular resources that support transdisciplinary instruction. This exploratory case study examines how four secondary teachers (three chemistry; one engineering) made sense of a transdisciplinary PD model, Convergence Research in STEM and Tradition (CReST), that leverages cultural heritage artifacts (Renaissance frescoes) as boundary objects to connect chemistry, engineering, world history, and technology. Teachers participated in a four-day immersive PD experience in Firenze (Florence) and Pisa, Italy, that included site-based learning, interaction …

Pre-Service Elementary Teachers' Science Content Knowledge And Confidence: Teaching Science Methods With Metacognitive Awareness Activities, Demetrice Smith-Mutegi, Erika Wise

Teaching & Learning Faculty Publications

Few elementary teachers are confident in teaching science or in their science knowledge. This study sought to address this concern by investigating the impact of a science methods course on confidence and science knowledge for pre-service elementary teachers (PSETs). In this study, 23 participants enrolled in a teacher education program at a Midwest US university participated in a quasi-experimental pretest-posttest design. The participants engaged in course content, including metacognitive awareness activities, for a full semester and qualitatively described their confidence within the pre-post assessment survey. Results were analyzed using an independent samples t-test, mean content assessment scores, and paired samples …

Artifact Centered Interdisciplinary Instruction Supports Secondary Student Learning In Chemistry History And Engineering, Rachel Sparks White, Kristie S. Gutierrez, James K. Ferri

Teaching & Learning Faculty Publications

Secondary STEM instruction often remains organized in disciplinary silos, limiting opportunities for students to apply Concepts across domains incoherent, authentic contexts. This mixed methods implementation study examined Convergence Research in STEM and Tradition (CReST), an Artifact centered interdisciplinary curriculum model designed to connect chemistry, world history, and engineering through a shared instructional context. In this implementation, Italian frescoes served as a boundary object anchoring a six-day sequence on mural materials, deterioration, and restoration. The sequence integrated targeted concepts in inorganic chemistry (e.g., the lime cycle and thermal processes), renaissance era historical contacts and the engineering design process within tasks related …

Girls Stem Institute: Impacting Black Girls' Self-Efficacy And Interest In Stem Careers, Crystal Morton, Demetrice Smith-Mutegi, Danka Maric, Vidushi Adlakha, Robin Jackson

Teaching & Learning Faculty Publications

Nationally and globally, STEM serves as a gatekeeper to the labor market and higher education opportunities. Many Black girls find themselves locked out of the gate. Historically and contemporarily, Black girls are seldom viewed as capable or worthy of educational investment and face unique and ongoing challenges in K-12 STEM learning spaces due to their gender and racial identities. Research suggests that informal STEM learning spaces can serve as a counter to Black girls’ experiences in K-12 schools and help enhance Black girls’ self-efficacy and STEM career interests. This study explores the impact of a four-week informal STEM program, employing …

Pre-Service Teachers' Perceptions Of Literacy In Stem Classroom Instruction By Implementation Of Project-Based Lessons, Sarah Ferguson, Maryam Enderson, Jamie Colwell

Teaching & Learning Faculty Publications

This study examines how project-based learning (PBL) supports pre-service STEM teachers (PSTs) in understanding and applying disciplinary literacy in classroom instruction. Conducted in a semester-long PBL course at a mid-sized public university, the research explores PSTs’ shifting perceptions of literacy in STEM and the challenges and successes they experience. Using qualitative methods grounded in student voice and case study frameworks, data were collected through focus groups, reflections, and lesson plan analyses. Findings show PSTs initially held narrow views of literacy but developed more nuanced understandings through PBL. Key successes included increased confidence and use of inquiry-based strategies; challenges involved time …

Monarch: Old Dominion University Magazine, Victoria Bourne (Editor)

Monarch Magazine

Spring/Summer 2026 issue of Monarch, the Old Dominion University Magazine.

Subtitled: Honoring a HEROIC Monarch

Shaping The Future: Emerging Technologies And Their Role In Industry 4.0 And Beyond, Liuliu Qin

Information Technology & Decision Sciences Faculty Publications

This paper provides a comprehensive review of emerging technologies driving the transition from Industry 4.0 to Industry 5.0. It examines the foundational concepts and pillars of Industry 4.0 and explores the transformative roles of Artificial Intelligence (AI), Extended Reality (XR), Collaborative Cobots (Cobots), Brain–Computer Interfaces (BCIs), quantum technologies, and next-generation connectivity (5G/6G). By integrating technological, human-centric, and sustainability perspectives, the study outlines how these emerging technologies reshape industrial systems and enable intelligent, adaptive, and inclusive futures.

Analytical And Semi-Analytical Modeling Of Solar Cells Using The Lambert W Function: A Comprehensive Review Of Equivalent Circuits, Adel El-Shahat, Martin Ćalasan, Snežana Vujoševic, Shady H. E. Abdel Aleem

Engineering Technology Faculty Publications

The modeling of photovoltaic (PV) cells through equivalent circuits forms a central element in the analysis, simulation, and optimization of solar energy systems. Traditional approaches often depend on iterative numerical methods to solve the implicit current–voltage (I–V) equations. In contrast, the Lambert W function has emerged as an effective mathematical tool that enables closed-form or semi-analytical expressions for a wide range of PV models. This paper presents a Lambert W-centered review of analytical and semi-analytical formulations for PV equivalent-circuit models, covering classical single-diode and multi-diode structures and modern variants incorporating additional elements, voltage-dependent parameters, and topology rearrangements. The models are …

Interpretable Machine Learning For Bridge-Pier Scour Prediction And Flood Resilience, Adil Khan, Dalya Ismael

Engineering Technology Faculty Publications

Bridge-pier scour is a leading cause of flood-induced bridge failure, yet practice still lacks transparent, physics-informed tools that link data-driven prediction with design guidance. This study develops an interpretable, physics-aware machine-learning framework to predict equilibrium scour depth and translate those predictions into actionable strategies for flood-resilient infrastructure. Using the 2014 U.S. Geological Survey Pier-Scour Database (569 laboratory cases), five models: Gradient Boosting, AdaBoost (Tree), XGBoost, Gaussian Process (RBF kernel), and Kernel Ridge (polynomial), were trained and evaluated with K-fold cross-validation. Model performance was evaluated using R², RMSE, and MAE. Gradient Boosting performed best, achieving training and testing R² of 0.99 …

Srgan-Based Deep Learning Framework For Wind Turbine Damage Detection From Sentinel-2 Imagery, Kübra Çakir, Onur Elma, Murat Kuzlu

Engineering Technology Faculty Publications

The operational reliability of wind turbines is critical for sustainable energy production in smart grids. This study proposes a remote monitoring approach using perceptually enhanced satellite imagery. Sentinel-2 multispectral data (10 m resolution) has been processed with a Super-Resolution Generative Adversarial Network (SRGAN) to improve visual quality to a perceptual resolution of 30 cm. Although true spatial refinement is not achieved, the sharper structural details enhance classification accuracy. The data set comprises 15,000 images—10,000 SRGAN-enhanced and 5000 augmented through rotation, zoom in, increasing brightness, noise addition, and blurring. A custom Convolutional Neural Network (CNN) has been trained to classify turbines …

Generative Ai And Llm Applications In Renewable Energy And Smart Grids: A Systematic Review For The Sustainable Energy Transition, Umit Cali, Ugur Halden, Merlinda Andoni, Ferhat Ozgur Catak, Si Chen, Benoit Couraud, Emre Kantar, Samuel Knapper, Ibrahim Kucukdemiral, Huseyin Kusetogullari, Murat Kuzlu, Yashar Mousavi, Sonam Norbu, Taha Selim Ustun, David Flynn

Engineering Technology Faculty Publications

The global energy transition toward decarbonization and digitalization requires advanced methods to manage decentralized, data-intensive cyber-physical energy systems. This systematic review analyzes 106 research studies on Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in renewable energy and smart grids, organized into seven application clusters covering forecasting, system design, operation, reliability, data and cybersecurity, and energy markets. The review situates these applications within a Cyber-Physical-Social Systems (CPSS) framework. Results show that GANs dominate current applications (47.2%), followed by LLMs (10.4%) and VAEs (9.4%), with growing adoption of diffusion and score-based models (7.5% each). Selected studies report improved probabilistic forecasting …

A Large Language Model-Based Academic Advising Assistant For Engineering Technology Students, Murat Kuzlu, Vukica M. Jovanovic, Katherine Smith, Otilia Popescu, Adel El-Shahat, Ryan Cotton, Kayla Marie Seegers, William Austin Henderson

Engineering Technology Faculty Publications

In recent years, Artificial Intelligence (AI)-based solutions, particularly Large Language Models (LLMs), have been applied to a variety of domains, such as energy, finance, transportation, healthcare, and education. Among these domains, education has become increasingly popular due to strong interest among educators and students. This study proposes an academic advising assistant system that uses LLMs to help Engineering Technology (ET) students plan their course load based on their educational history, departmental course offerings, and personal constraints, such as their preferred semester course load. The proposed LLM-based academic advising assistant system maintains a database of students' course histories and upcoming course …

Explainable Ai-Driven Predictive Maintenance Curriculum For Smart Manufacturing, Abdullah Al Mamun, Murat Kuzlu, Katherine Smith, Vukica Jovanovic, Dalya Ismael, Adel El-Shahat, Angela Sicaja, Md. Hedayetul Islam Chy

Engineering Technology Faculty Publications

Nowadays, Industry 4.0 has transformed manufacturing industries into a data-rich system driven by IoT, automation, and Artificial Intelligence (AI). Within this context, Predictive Maintenance (PdM) provides a proactive strategy that leverages heterogeneous sensor data such as vibration, acoustic, electrical, and visual signals along with historical performance and advanced analytics to forecast equipment failures before they occur. Usually, AI-driven PdM (AI-PdM) enhances this capability by integrating AI-based sensor analytics to automate fault prediction and optimize system reliability. However, traditional AI-PdM often functions as a “black box,” providing limited interpretability of its decision-making process and posing challenges for trust, validation, and human …

Wip: Arduino-Based Pbl To Foster Entrepreneurial Mindset, Nathan Q. Holland, Vukica M. Jovanovic

Engineering Technology Faculty Publications

This work-in-progress paper examines a semester-long project-based learning initiative begun in an introductory engineering course during the Fall 2025 semester. The project aims to enhance students' hands-on experience by integrating information literacy, the engineering design process (EDP), and an entrepreneurial mindset (EM) [1]. The objective is to boost student confidence in teamwork, technical problem-solving, and application of skills, preparing them for future courses in their discipline. Students in this introduction to engineering course received an Arduino Uno R3 Controller board kit and additional sensors. They were tasked to develop a device addressing engineering in the medicine challenge of their choosing. …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

Mxene-Enabled Wearable Biosensors: A Design Framework For Autonomous Biosensing, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

MXenes, a rapidly expanding family of two-dimensional transition metal carbides and nitrides, have emerged as leading materials for wearable bioelectronics due to their metallic conductivity, termination-rich surfaces, mechanical compliance, and tunable interlayer structures. However, wearable biosensor performance does not arise from conductivity alone, but from coupled interactions among surface termination chemistry, heterointerface engineering, hierarchical architecture, and device integration under dynamic physiological conditions. This review establishes a predictive structure-interface-device framework linking MXene chemistry to system-level performance across electrochemical, mechanical, gas, optical, and energy-storage modalities. We analyze how termination-controlled adsorption governs charge transfer and selectivity, how heterojunction formation modulates carrier density and …

Radial And Carotid Arterial Pulse Signals For Assessing Cardiovascular Function At Rest And During Post-Exercise Recovery In A Heart Transplant Patient: A Case Study, Md Mahfuzur Rahman, Mamun Hasan, Jennifer F. May, John M. Herre, Leryn Reynolds, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Aim: This study investigates the feasibility of using radial and carotid arterial pulse signals to assess cardiovascular (CV) function at rest and during post-exercise recovery in a heart transplant (HTx) patient. Method: Two micro-fabricated tactile sensors were used to simultaneously acquire arterial pulse signals at the radial artery (RA) and carotid artery (CA). Measurements were taken at rest and at multiple time points post-exercise on three subjects: an HTx patient, a percutaneous coronary intervention (PCI; coronary stent) patient and a healthy control. An SDOF-TF-based time-frequency analysis algorithm was applied to extract a comprehensive set of CV parameters, including heart rate …

Ecological Feedbacks In The Earth System, Eugene J. Murphy, Jessica J. Williams, Isla H. Myers-Smith, Vivienne P. Groner, David M. P. Jacoby, Lester Kwiatkowski, Jess Melbourne-Thomas, Emma Ransome, Cristina Banks-Leite, Laurent Bopp, Marion Gehlen, Eileen E. Hofmann, Babette Hoogakker, Nadine M. Johnston, Yadvinder Malhi, Emma L. Cavan

CCPO Publications

Ecological feedbacks are fundamental features of the Earth system, affecting physical processes and chemical cycles. Our understanding of the interactions underlying these feedbacks at different spatial and temporal scales and the extent to which feedbacks affect Earth system functioning remains limited. Climate change and other anthropogenic pressures are already negatively affecting ecological processes in marine, freshwater, and terrestrial ecosystems. These will most likely be amplified in the coming decades under our current warming and socioeconomic pathways. The knock-on impacts on ecological feedbacks have the potential to cause rapid perturbations to the Earth system, and may significantly impact the structure and …

Basal Melting Variability Of The Ross Ice Shelf From Mixing Ratios Of Simulated Water Masses (1993-2018) And Potential Climatic Drivers, Enrico Pochini, Andrea Bergamasco, Florence Colleoni, Manuel Bensi, Giorgio Budillon, Pasquale Castagno, Michael S. Dinniman, Pierpaolo Falco, Emanuele Forte, Vedrana Kovačević, Stefanie L. Mack

CCPO Publications

Several water masses circulate under the Ross Ice Shelf (RIS), the largest ice shelf in Antarctica, each causing basal melting with a specific spatio-temporal pattern. To investigate these patterns and their variability, we applied a mixing ratio analysis to simulated water masses from a new numerical ocean model of the Ross Sea. The simulation, which was run over 26 years (1993–2018) and which includes the RIS cavity, shows good agreement with seaborne and mooring observations. The total RIS basal melt rate is 90 Gt/yr on average, and is caused mostly by High Salinity Shelf Water (HSSW) (68%), which enters the …

Artificial Intelligence And Consumer Well-Being: A Cross Domain Systemic Review, Setar Lytle, Mahesh Gopinath

Marketing Faculty Publications

Artificial intelligence (AI) is increasingly embedded in everyday consumption, yet evidence on its longer-term implications for consumer eudaimonic well-being remains dispersed across disciplines and application contexts. This review integrates that literature to clarify the domains, theoretical explanations, and conditions through which AI shapes consumer well-being. Following PRISMA and SPAR-4-SLR procedures, we reviewed research published from January 2010 to January 2026. From 6058 records, 480 studies across psychology, business, and human-technology interaction met the inclusion criteria. The evidence is organised through psychological, social, and technological perspectives and identifies six interconnected domains: mental health, cognitive development, physical health, personal growth, autonomy and …

Radial And Carotid Arterial Pulse Signals For Assessing Cardiovascular Function At Rest And During Post-Exercise Recovery In A Heart Transplant Patient: A Case Study, Md Mahfuzur Rahman, Mamun Hasan, Jennifer F. May, John M. Herre, Leryn Reynolds, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Aim: This study investigates the feasibility of using radial and carotid arterial pulse signals to assess cardiovascular (CV) function at rest and during post-exercise recovery in a heart transplant (HTx) patient. Method: Two micro-fabricated tactile sensors were used to simultaneously acquire arterial pulse signals at the radial artery (RA) and carotid artery (CA). Measurements were taken at rest and at multiple time points post-exercise on three subjects: an HTx patient, a percutaneous coronary intervention (PCI; coronary stent) patient and a healthy control. An SDOF-TF-based time-frequency analysis algorithm was applied to extract a comprehensive set of CV parameters, including heart rate …

Development Of Thermal Joints For Conduction-Cooling Applications, J. Lewis, G. Ciovati

Mechanical & Aerospace Engineering Faculty Publications

In support of the development of conduction-cooled superconducting radiofrequency (SRF) niobium cavities for use in continuous-wave linear accelerators, an experimental study of thermal contact resistance was performed on bolted joints using high-purity niobium, aluminium, and copper along with Apiezon N grease and indium foil as interfacial materials. The geometry of each joint investigated aims at replicating the design adopted in conduction-cooled SRF cavities currently under development at Jefferson Lab. The materials' thermal conductivity and the joints' thermal resistance were measured in the temperature range of 3.5 - 10 K. The results showed that the low thermal contact resistance of 2-4 …

A Computational Approach To Graduated Centrifuge Profiles For Partial Gravity Planetary Environments, Cabell W. Jones

Mechanical & Aerospace Engineering Faculty Publications

Missions such as NASA’s Artemis and SpaceX’s Starship aspire towards creating permanent settlements beyond Earth. In order to achieve this goal, it must be considered that the gravity present on planetary surfaces such as the Moon (0.165 g) and Mars (0.378 g) may be insufficient to support human physiology for long term habitation. On near-Earth missions, issues such as muscular atrophy, neuro-ocular changes, cardiopulmonary variations, and bone mineral density loss have been observed proportional to the duration spent in microgravity. Further studies have suggested that the severity of these conditions scales linearly with decreasing gravity, meaning that astronaut health can …

Stiffening Of Soft Silicone Upon Deep Uv Treatment As Characterized Using Nanoindentation, Amanda Wilder, Zaria Booth, Caden Obermeyer, Saika Sharmin, Venkat Maruthamuthu

Mechanical & Aerospace Engineering Faculty Publications

Silicones are elastomers that have a wide variety of uses, including biomedical applications such as the coating of biomedical devices and as implants. Soft silicones with mechanical properties similar to those of biological tissues have particularly gained use as substrates for cell culture in mechanobiology studies. In this context, it would be desirable to be able to alter their surface mechanical properties with a relatively simple physical treatment. While deep ultraviolet (deep UV) or ultraviolet C (UV-C) treatment has been previously used as a surface treatment method for stiffer silicones formulations, the effect of this treatment on soft silicones relevant …

Ideational Behavior And Occupational Identity Achievement: A Study Of Emerging Adult College Students Preceding Entry Into The Fouth Industrial Revolution Workforce, Carrington M. Faulk, Michael F. Kosloski, Philip Reed

Marketing Faculty Publications

As emerging adults transition into the Fourth Industrial Revolution (4IR) workforce, it is essential to understand the factors that predict successful occupational identity achievement, as automation will impact human occupational identity crises. This descriptive cross-sectional study employed a correlational design to determine the degree to which ideational behavior predicts occupational identity achievement prior to entry into the 4IR workforce. Using a sample of 166 emerging adult college students from a Mid-Atlantic, diverse, four-year university, data were collected using Runco's Ideational Behavior Scale (RIBS) and Melgosa's Occupational Identity Achievement subscale (OIA). Results showed that ideational behavior significantly predicted occupational identity achievement …

The Presidential Address To The Association For Career And Technical Education Research: Cte Research Ecosystem Growing Scholars And Workforce Capacity, Michelle E. Bartlett

Educational Leadership & Workforce Development Faculty Publications

Career and Technical Education (CTE) research has advanced knowledge, strengthened communities, informed policy, and expanded pathways to opportunity for decades. As ACTER begins a new chapter, we are invited to imagine the future of our field beyond a linear pipeline. We can embrace a view of CTE research as a living ecosystem that grows talent, supports collaboration, and sustains discovery over time. This presidential address emphasizes three priorities for that future: applied research that reaches practice, mentorship that nurtures the next generation of scholars, and partnerships that ensure knowledge becomes action. By centering learners and communities in our work, we …

Infusing Authenticity Into A Service-Learning Program: Examining Long-Term Impacts On Professional Development, Mohan Yang, Jonathan Harbor, Belle Li, Jacqueline Nikiema

Educational Leadership & Workforce Development Faculty Publications

Purpose

The employability of postgraduate students remains a critical concern in higher education, as postgraduate programs, particularly at the doctoral level, traditionally focus on disciplinary and research competencies. This leads to a lack of adequate preparation for employment, especially for non-academic roles. This study examines the long-term impacts of an authentic service-learning program on trainees' professional lives, with a particular emphasis on academia. This addresses the need for insight into the long-term impacts of initiatives that enhance postgraduate programs with opportunities for students to acquire transferable competencies prior to entering employment.

Design/methodology/approach

We adopted a narrative inquiry approach to investigate …

Atrial Fibrillation Detection From At-Rest Ppg Signals Using An Sdof-Tf Method, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

At-rest PPG signals have been explored for detecting atrial fibrillation (AF), yet current signal-processing techniques do not achieve perfect accuracy even under low-motion artifact (MA) conditions. This study evaluates the effectiveness of a single-degree-of-freedom time–frequency (SDOF-TF) method in analyzing at-rest PPG signals for AF detection. The method leverages the influence of MA on the instant parameters of each harmonic, which is identified using an SDOF model in which the tissue–contact–sensor (TCS) stack is treated as an SDOF system. In this model, MA induces baseline drift and time-varying system parameters. The SDOF-TF method enables the quantification and removal of MA and …

Simulating Social Attitudes With Llms: Accuracy, Demographic Effects, And Refusal Behavior In The Sensitive Domain Of Suicide Prevention, Cristina J. Perez, Michael P. Vasquez Jr., Philippe J. Giabbanelli, Patrick Y. Wu

VMASC Publications

Large language models (LLMs) are increasingly used to simulate public opinion, yet their validity in sensitive policy domains remains underexplored. We evaluate whether LLMs can reproduce attitudes toward suicide prevention policies using 32 questions drawn from seven nationally representative U.S. surveys (2023-2025). We systematically vary demographic conditioning (race/ethnicity, gender, age, education, income, party), prompt framing (direct elicitation, respondent embodiment, specialist embodiment), and model architecture (GPT-5 Nano, DeepSeek V3.2, Meta Llama 3.1 8B, Mistral Small 24B). Across 811,560 prompts, the mean absolute error—the average gap between predicted and human response distributions—is 23 percentage points. We also find that LLM responses to …