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- Guidelines for Informed Instructional Strategy Selection in Online Higher Education: A Design and Development ResearchAlghamdi, Bushra Abdulkarim (Virginia Tech, 2024-04-25)The demand for online education has significantly increased in recent years, prompting many educational institutions to consider its continued adoption in many ways. However, some faculty members have encountered challenges in teaching online due to a lack of adequate training and guidance on effective online teaching practices. This study aims to provide evidence-based guidance for higher education instructors in selecting effective instructional strategies in online learning environments. It employs design and development research methodology to create instructional strategy selection guidelines for online courses in higher education. The guidelines, rooted in pedagogical approaches, are designed to assist faculty in selecting appropriate instructional strategies for online learning. They comprehensively outline the various instructional strategies and the factors influencing the decision-making process for selecting instructional strategies in online learning environments. The study makes contributions to research and content development by providing strategy selection guidelines for quality online education.
- Indian Wives of Incarcerated Men Tell Their Stories: An Intersectional Narrative Analysis of Disenfranchisement and ResilienceGupta, Shivangi (Virginia Tech, 2024-04-25)When a family member is incarcerated, the task of emotionally and financially supporting the remaining family members and the incarcerated loved one often falls upon women, who are likely to be under-resourced and overwhelmed. Women whose husbands are incarcerated in India are likely to possess multiple marginalized identities, increasing their vulnerability to intersecting forms of oppression. Empirical research is lacking on wives of incarcerated men in India, contributing to their invisibility in policy-making and programmatic interventions. Guided by intersectional feminism and symbolic interactionism, the purpose of this study was to document the stories of women who had experienced spousal incarceration in the Indian context. In-depth, semi-structured interviews were conducted with 14 wives of prison inmates who resided in or around the National Capital Territory of Delhi, all of whom either held a lower caste identity or a Muslim religious identity. Transcribed interviews were analyzed following the steps of narrative analysis. Results illustrate the diversity of storied experiences of wives of incarcerated husbands in India. First, by grouping narratives that conveyed the same overall storyline into the same cluster, I identified three story clusters: Ambivalent but Hanging On, Unconditionally Devoted, and Independent and Disillusioned. Second, by attending to how women's day-to-day lives are shaped by intersecting systems of privilege and oppression, particularly those tied to gender and class, I identified three overarching themes that spanned women's narratives: (a) a complicated relationship with patriarchy, (b) the weight of socioeconomic disenfranchisement, and (c) when resilience is not a choice. The results of this study emphasize the need to distinguish between feminist agency and welfare agency, to recognize women's experiences of ambiguous loss and disenfranchised grief, and to critique the systemic injustices that forced women to be resilient. Documenting their stories is instrumental in bringing attention to the needs, challenges, and triumphs of this underserved and overlooked population.
- Development and Evaluation of a Decision Support Tool to Incorporate Redundancy in the Development of Instructional MaterialsCox II, Larry Alenda (Virginia Tech, 2024-04-25)Novice Instructional Designers (IDs) often struggle to perform at the same level as experts. Specialized knowledge and experience are needed to discover the challenges and device appropriate solutions. Scaffold, guides, and heuristics can help novice when needing to perform tasks that require specialized knowledge. One common instructional design task requiring specialized knowledge is the development of instructional materials. Instructional message design (IMD) is a problem solving process to improve the quality of instructional materials through the application of research based principles. As this process is often not covered in novice IDs training, they will encounter more issues while attempting to address the challenges that come with creating instructional materials. Using a developmental study, a decision support tool was created to assist novice IDs with applying IMD, specifically the redundancy principle due to its ability to improve the communication within the materials. This study describes the operationalization of the principle, the design and development of the tool, expert review and revisions made based on their feedback, and the implications from the development of such a tool.
- The Quantized Velocity Finite Element MethodCook, Charles (Virginia Tech, 2024-04-23)The Euler and Navier-Stokes-Fourier equations will be directly expressed as distribution evolution equations, where a new and proper continuum prescription will be derived. These equations of motion will be numerically solved with the development of a new and unique finite element formulation. Out of this framework, the 7D phasetime element has been born. To provide optimal stability, a new quantization procedure is established based on the principles of quantum theory. The entirety of this framework has been coined the "quantized velocity finite element method" (QVFEM). The work performed herein lays the foundational development of what is hoped to become a new paradigm shift in computational fluid dynamics.
- Exploring the drivers and consequences of emerging infectious disease of wildlifeGrimaudo, Alexander Thomas (Virginia Tech, 2024-04-22)Emerging infectious diseases of wildlife have threatened host populations of diverse taxa in recent history, which is largely attributable to anthropogenic global change. In three data chapters, this dissertation examines the drivers of individual- to population-level variation in how host populations respond to novel and emerging pathogens. Each chapter explores these processes in bat populations of North America, predominantly the Northeast and Midwest regions of the United States, impacted by the emerging fungal pathogen that causes white-nose syndrome, Pseudogymnoascus destructans. In Chapter 2, I disentangle the effects of adaptive host traits and environmental influences in driving host population stabilization of the little brown bat (Myotis lucifugus), finding that host-pathogen coexistence in this system is the product of their complex interaction. In Chapter 3, I characterize the range-wide variation in white-nose syndrome impacts on a federally endangered and poorly studied species, the Indiana bat (Myotis sodalis), as well as environmental and demographic determinants of its declines over epidemic time. In Chapter 4, I explore the role of individual variation in roosting microclimate selection of little brown bats in driving their infection severity, yielding important insights into the pathophysiology and environmental dependence of white-nose syndrome. Ultimately, this dissertation characterizes complex drivers of variation in host responses to emerging and invading pathogens, yielding insights essential to the successful mitigation of their impacts.
- A Multilevel Analysis to Examine Interdisciplinary Research Experience Among Doctoral Graduates and Its Effect on Career OutcomesLawrence, Kacy (Virginia Tech, 2024-04-23)This study was designed to explore the impact of interdisciplinary research on the likelihood of a doctoral student obtaining a faculty job upon degree completion. Additionally, this study examined the important individual and institutional components of socialization that contribute to differences in career outcomes. A socialization framework likely substantiates the extent to which doctoral training environments are consequential to careers. Results were obtained from a sample of 28,928 doctoral students who participated in the 2021 Survey of Earned Doctorates. Hierarchical Generalized Linear Modeling was used because it measures the effects of both student characteristics and institutional factors. The findings from this analysis suggest student demographics are an important predictor, but the significance of those characteristics' changes when doctoral field of study is considered. Additionally, there are institutional characteristics that impact the likelihood of obtaining a faculty job related to the proportion of various student backgrounds, faculty backgrounds, and broad field of study, and the prestige of the institution. The independent variable of interest, interdisciplinary dissertation, was not statistically significant at the student level, but the proportion of doctoral students completing an interdisciplinary dissertation at the institution level was statistically significant and negatively associated with obtaining a faculty position adjusting for other institutional factors. These findings show the importance of applying hierarchical models to research questions related to career outcomes for doctoral students. Without a hierarchical model, this important differential finding across levels would have been hidden.
- Enhancing Security and Privacy in Head-Mounted Augmented Reality Systems Using Eye GazeCorbett, Matthew (Virginia Tech, 2024-04-22)Augmented Reality (AR) devices are set apart from other mobile devices by the immersive experience they offer. Specifically, head-mounted AR devices can accurately sense and understand their environment through an increasingly powerful array of sensors such as cameras, depth sensors, eye gaze trackers, microphones, and inertial sensors. The ability of these devices to collect this information presents both challenges and opportunities to improve existing security and privacy techniques in this domain. Specifically, eye gaze tracking is a ready-made capability to analyze user intent, emotions, and vulnerability, and as an input mechanism. However, modern AR devices lack systems to address their unique security and privacy issues. Problems such as lacking local pairing mechanisms usable while immersed in AR environments, bystander privacy protections, and the increased vulnerability to shoulder surfing while wearing AR devices all lack viable solutions. In this dissertation, I explore how readily available eye gaze sensor data can be used to improve existing methods for assuring information security and protecting the privacy of those near the device. My research has presented three new systems, BystandAR, ShouldAR, and GazePair that each leverage user eye gaze to improve security and privacy expectations in or with Augmented Reality. As these devices grow in power and number, such solutions are necessary to prevent perception failures that hindered earlier devices. The work in this dissertation is presented in the hope that these solutions can improve and expedite the adoption of these powerful and useful devices.
- NF-kB Inducing Kinase (NIK) Influences Eosinophil Development, Survival, and PlasticityTrusiano, Briana Lynn (Virginia Tech, 2024-04-22)Hypereosinophilic (HES) syndrome is an umbrella term encompassing several disease subsets that affects humans and veterinary species, ultimately resulting in >1,500 eosinophils/uL circulating in the blood documented over six-months. This eventually culminates in end-organ infiltration and increased patient morbidity and mortality. In mice where the gene Map3k14 encoding NF -kB inducing kinase (NIK) is knocked out, a HES-like syndrome develops that is dependent on Th2 cells and cytokines. NIK is the upstream regulator of the noncanonical NF-kB pathway and is involved in lymphoid organ development, B cell lymphopoiesis, and myelopoiesis. In addition to regulating the noncanonical NF-kB pathway, NIK is also involved in regulation of kB dimers of the canonical NF-kB pathway and can function independent of NF-kB signaling by regulating lipid and glucose metabolism, mitochondrial, and RIP1 binding to influence cell survival and death. Despite previous studies performed in the Nik-/- model, the mechanisms underlying eosinophil development, plasticity, and fitness in conjunction with the bone marrow and splenic microenvironments have not been fully elucidated. In the present work, we reviewed current data exploring the influence of the noncanonical NF-kB pathway and NIK specifically on the development of acute myeloid leukemias (AMLs) and Myelodysplastic Syndrome (MDS) with a focus on how these mechanisms might induce subvariants of HES. We next examined the effect of NIK loss on eosinophilopoiesis within hematopoietic tissues in vivo and in various cell culture environments in vitro via cytology, histology, flow cytometry, FACS, positive cell selection, MTT assay, BrDU assay, and protein microarray analysis. Overall, our findings suggest that NIK influences eosinophil maturation, proliferation, metabolism, survival, and potentially plasticity in vivo and in vitro under different environmental conditions and Th2 cytokine influence. NIK loss was also associated with altered free and bound TNFR1 levels on day 13 in vitro. TNFR1 acts upstream of RIP1 and suggests that these differences may be due to NF-kB independent functions of NIK. Overall, these results provide further insight into the potential mechanisms underlying eosinophilopoiesis in the Nik-/- murine model. This information may prove useful in discovering new treatment options underlying subvariants of HES in both human and veterinary patients.
- Fruit chemical traits shape bat nutritional ecology: from basic science to applicationsGelambi Desiato, Mariana (Virginia Tech, 2024-04-22)Ripe fleshy fruits contain an enormous diversity of metabolites that influence ecological interactions with mutualistic and antagonistic species. This dissertation investigates the impact of fruit secondary metabolites on the foraging behavior and digestive physiology of bats (Chapters 2-4) while applying insights from basic chemical ecology to inform forest regeneration strategies (Chapter 5). The studies were conducted in northeastern Costa Rica at La Selva Biological Station. Chapter Two examines the variability and associations between nutrients and secondary metabolites within ripe Piper sancti-felicis fruits, showing that intraindividual variation of chemical traits can surpass interindividual variation and associations between chemical traits are scale-dependent, varying in strength and direction. Chapter Three explores how bats balance nutrient acquisition with defensive metabolite avoidance and the impact of metabolite consumption on bat nutrient absorption. It reveals that nutrient composition is the primary driver of bat foraging behavior and that defensive metabolites can interfere with protein absorption. Chapter Four further uses untargeted metabolomics to explore the influence of secondary metabolites on nutrient absorption, demonstrating that four commercial secondary metabolites induce dose-dependent changes in bat fecal metabolome, altering essential nutrient absorption. Chapter Five translates principles of chemical ecology into practical use by demonstrating the effectiveness of synthetic volatiles in attracting fruit bats and increasing seed rain. Taken together, this dissertation shows the impact of defensive metabolites on a key seed disperser while demonstrating the potential application of chemical ecology to address forest regeneration challenges.
- Developing a Prototypical Biophilic Localized Natural Airflow Simulator (BLNAS) for a Modular WorkstationRabab'ah, Ikhlas Oqlah (Virginia Tech, 2024-04-22)
- Reduced-order Adaptive Output Predictor for a Class of Uncertain Dynamical Systems: Application to EEG-Based Control of Working MemoryAnsari, Roghaiyeh (Virginia Tech, 2024-04-18)This dissertation aims to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof, and numerical and experimental studies, such as single pendulum, double pendulum, six-link pendulum, rope as a high-dimensional rope, and EEG data. Then the dissertation goal is to experimentally validate the proposed reduced-order model parameterization technique for tracking uncertain linear time-invariant (LTI) single-input, single-output (SISO) systems. The proposed theory focuses on parameterizing a high-dimensional, uncertain model and introduces a reduced-order adaptive output predictor capable of forecasting the system's output. This predictor utilizes auto-regressive filtered vectors, incorporating the input and output history. The adaptive output predictor is a simplified and known model, making it suitable for controlling high-dimensional, uncertain SISO systems without access to full-state measurements. Specifically, this work establishes the foundation for parameterizing uncertain models, creating a virtual structure that emulates the actual system, and offering a more manageable model for control when the objective is solely to regulate the system's output. The primary focus of this research is to assess the effectiveness and output-tracking capabilities of the proposed approach. These capabilities are extensively examined across diverse platforms and hardware configurations, relying solely on input and output data from the models without incorporating any additional information on the system dynamics. In the first experiment, the predictor's ability to track the angle of a single pendulum, including additional dynamics, is evaluated using only input-output data. The second experiment targets tracking the endpoint of a rope connected to a single pendulum, where the rope emulates a high-dimensional model. A vision system is designed and employed to acquire the rope endpoint position data. Before the rope experiment, a set of experiments is conducted on single pendulum hardware to ensure the accuracy of the vision system's data collection. Comparative analysis between data from object tracking via vision and data acquired through an encoder demonstrates negligible error. Finally, the input and the endpoint output data from the rope experiment are fed into the predictor to assess its capability to track the rope endpoint position without utilizing specific knowledge of the experimental hardware. Achieving negligible error in tracking implies that the predictor provides a simple and accurate representation of the rope dynamics. Consequently, designing a controller for this known model is equivalent to designing a controller for the actual rope system dynamics. The predictor, by closely emulating the behavior of the rope, becomes a reliable surrogate model for control design, simplifying the task of controller design for the complex and uncertain high-dimensional system. Finally, this study introduces a novel approach to enhance controller design for complex brain dynamics by employing a reduced-order adaptive output predictor proposed in [1], fine-tuned with chirp binaural beats. The proposed technique is promising for developing closed-loop controllers in non-invasive brain stimulation therapies, such as binaural beats stimulation, to improve working memory. The study focuses on parameterizing uncertain models and creates a predictor that utilizes auto-regressive filtered vectors to forecast mean phase lock values generated by binaural beats stimulation. The simplified and known model of the predictor proves effective in tracking brain responses, as demonstrated in experiments evaluating its ability to track mean phase locking values. The results indicate negligible tracking error, suggesting the predictor's reliability in representing brain dynamics and simplifying the task of controller design for the complex and uncertain high-dimensional system.
- An Investigation into the Psychological Capital of Second-Career Teachers and Factors Influencing Their ScoresFlanagan, Amanda Grace (Virginia Tech, 2024-04-12)The purpose of this qualitative study was to examine the Psychological Capital (PsyCap) of second-career teachers (SCTs) and their perceptions of what affects their PsyCap in the workplace by surveying and interviewing second-career teachers in public school districts in central eastern and northern Virginia. The research questions were: What is the PsyCap of a second-career teacher? What are the factors that second-career teachers perceive to contribute to their PsyCap? Participants were located in rural and suburban school districts in central eastern and northern Virginia. Data collection consisted of demographic surveys, the Psychological Capital Questionnaire survey (PCQ-24), and semi-structured interviews. Eighteen second-career teachers were purposefully selected from 34 who completed the demographic survey data and PsyCap-24 to participate in semi-structured interviews using the interview questions protocol. Common themes from the interviews were determined using deductive and inductive coding. Major findings were that second-career teachers exhibited a high average workplace positive PsyCapof 4.8; mentorship and strong peer support significantly influence second-career teachers' positive PsyCap; and a teacher's relationships with colleagues and their team's impact second-career teachers' positive PsyCap. Additional findings also showed that positive relationships with administration and prior-life experiences in other fields contributed to an increase in positive PsyCap. Whereas extra duties assigned to second-career teachers negatively impact their overall PsyCap. These results underscored the significance of nurturing positive PsyCap among second-career teachers, adding to the broader research on educators' PsyCap and its impact on teacher retention and job satisfaction in education.
- Studies on Molten Salt Fuels: Properties, Purification, and Materials DegradationPark, Jaewoo (Virginia Tech, 2024-04-12)The molten salt reactor (MSR) is one of the advanced nuclear reactors expected to be alternatives to the conventional water-cooled nuclear reactor systems. Despite many advantages of MSRs, properties of molten salts have not been sufficiently measured in previous studies. In addition, the corrosion of structural alloys by molten salt is the biggest challenge for the operation of MSRs. This study focuses on measurements of thermophysical and thermodynamic properties of fluoride salt fuels, salt purification, and the degradation of structural materials in static and flowing molten-salt fuels. For the measurements of properties, phase transition, specific heat capacity, vapor pressure, contact angle on nuclear-grade graphite, and density were measured. The methodologies for the property measurements used in this study were validated by measuring the properties of metals or salts that have been well studied. For the flow-induced corrosion tests, the salt flow with different velocities was simulated by rotating the stainless steel 316H (SS316H) specimens in molten NaF-KF-UF4 (FUNaK) contained in glassy carbon crucibles at 1073 K. Salt samples were intermittently collected to monitor concentration changes of corrosion products in the salt, and surfaces and cross-sections of post-test SS316H specimens were analyzed to study their corrosion behaviors. Different batches of FUNaK were synthesized using different methods of purification, such as thermal purification, U-metal purification, and hydrofluorination with electrochemical purification (chemical purification) to study impacts of salt purification on the corrosion of SS316H. The corrosion test of SS316H by thermally purified FUNaK showed that the Fe concentration increased at the beginning and then decreased while the Cr concentration continued increasing while the rate decreased. In addition, (Cr, Fe)7C3 layers, Cr-metal particles, and dendritic structures concentrated with Cr and Fe were observed on the glassy carbon crucible after the 2 m/s test. The U-metal purification and hydrofluorination with electrochemical purification reduced concentrations of oxygen and hydrogen in FUNaK and mitigated the corrosion of SS316H significantly. The infiltration of the fluoride fuel salts into graphite and the fluorination of graphite by the salts at different pressures and temperatures were also studied. The salt infiltration into graphite at pressures above its threshold pressure was observed, and the formation of carbon fluorides on the surface of post-test graphite specimens was identified.
- Why Special Educators Stay: A Phenomenological Examination of Factors Impacting Special Educator Retention in Northern Virginia's Urban Public SchoolsGavin, Matthew (Virginia Tech, 2024-04-12)Cultural stigma and a looming teacher deficit, exacerbated by the COVID-19 pandemic, have created an increased need for special educators. Considering these issues, this research used traditional phenomenological qualitative methodologies to understand why public-school special education teachers of students with low incidence disabilities (SETs-LIDs) remained in the profession. The purpose was to better understand the lived experiences of SETs-LIDs, and it was designed as a phenomenological qualitative study. The primary research question was "What factors impact SETs-LIDs who continue to teach in special education during difficult times?" Secondary questions were (a) "What are the lived experiences of SETs-LIDs that influence their retention?" and (b) "How do SETs-LIDs cope with the challenges of their work?" Data were obtained through a demographic survey and independent interviews, which were designed to better understand why public-school SET-LIDs remain in the profession. Participants were selected based on responses to the demographic survey, and inclusion criteria included SETs-LIDs with diverse employment backgrounds. Ninety-six special educators responded to the demographic survey and 15 SET-LIDs were interviewed. Textual descriptions generated from the research were work satisfaction from relationships, intrinsic or altruistic motivation, positive administrative experiences, and external factors. Structural descriptions of the research were frustration, a desire for understanding, inequity and exclusion, and uncertainty. The "what" and "how" of individuals impacted by the difficulties of SET-LID attrition were interpreted. Participants described meaningful relationships with students and administrators as being fundamental to their retention. This research also found that SET-LIDs desired resources, understanding, appropriate professional development, and expert guidance. Implications for professional practices and future research were suggested.
- An Examination of the Challenges Experienced by Novice Principals Leading Rural Schools in VirginiaWheeler III, Frank Thomas (Virginia Tech, 2024-04-11)Novice principals leading rural schools experience unique challenges that define their leadership practices. The purpose of this qualitative study was to examine how novice principals interpret and understand the challenges they experience as developing leaders within a rural school setting in Virginia. The research question for the study was, what challenges do novice principals situated in a rural setting in Virginia experience as leaders of their schools? This study adds to the existing body of research on the challenges novice principals face as leaders of schools situated within a rural community. For this study, six novice principals working in Rural-Remote (Code 43) schools (as defined by the National Center for Education Statistics) in Virginia participated in a 45-minute, one-on-one interview. The findings revealed that the novice rural principals experienced unique challenges with hiring staff, managing limited budgets, wearing multiple hats, distributed leadership, meeting their community's expectations for accessibility and visibility, readily available collaboration opportunities with professionals in similar roles, and intense feelings of ultimate responsibility. Participants hired with previous administrative experience within the district reported smooth transitions to the principalship. Although the participants reported limited activities from their districts to assist with understanding the rural setting, they expressed satisfaction with the overall support provided by their school district. The implications could help school districts, policymakers, and principal preparation programs effectively manage rural principal successions by establishing mentorship programs; providing field experience to aspiring principals; creating robust principal induction programs; and finding creative solutions to attract, hire, and retain rural school staff.
- Investigating Relationships Among School Climate, Academic Growth, and Benchmark Achievement Within Elementary Schools in Three Divisions in Virginia: A Quantitative StudyThompson, Summerlyn Lotz (Virginia Tech, 2024-04-11)Educators have a responsibility to foster a positive school climate while also ensuring that all students meet established educational benchmarks and make adequate growth. The relationship between school climate and student achievement is well-documented, but there is a gap in the literature examining the relationships among school climate, academic growth, and benchmark achievement. Accordingly, the purpose of this study was to investigate relationships among school climate, academic growth, and benchmark achievement at the elementary school level in Virginia. A nonexperimental, correlational design was used to address this research question: What are the relationships, if any, among school climate, academic growth, and benchmark achievement among fourth grade students in three school divisions in Virginia for the 2022-2023 school year? Existing data sets from 73 schools within 3 school divisions in Virginia were used: (a) the 2023 Virginia Survey of School Climate and Working Conditions, (b) fourth graders' Fall 2022 to Spring 2023 growth in reading and mathematics on the Northwest Evaluation Association Measures of Academic Progress assessment, and (c) fourth graders' mean performance on the 2023 Virginia Standards of Learning assessments in reading and mathematics. A correlational analysis was conducted to examine the relationships among these variables. Results were analyzed, and there were 12 findings. The most significant finding was a stronger positive relationship between school climate and benchmark achievement in reading and mathematics than between school climate and academic growth in either subject. This study contributes to the body of research on school climate and benchmark achievement by addressing relationships among school climate, academic growth, and benchmark achievement.
- Teacher Participation in Decision Making and its Relationship to Job Satisfaction in Middle Schools in Riyadh, Saudi ArabiaAlwadi, Abdulmohsen (Virginia Tech, 2024-04-09)Background: Teacher job satisfaction is considered an important topic in the education field. Many variables impact teacher job satisfaction. This study examined teacher participation in decision-making and its relation to teacher job satisfaction in ten public middle schools in the north of Riyadh, Saudi Arabia. It also sought to determine the impacts of gender and teaching experience on job satisfaction and participation in decision-making. Methods: A quantitative method with descriptive and inferential statistics was used, as well as a correlational analysis of the data. Pearson's correlation analysis was used to determine the relationship between teachers' participation in decision making and their job satisfaction. Ten public middle schools (located in north of Riyadh) were randomly chosen for this study. Of these, five were chosen for the male sample, totaling 62 teachers. Another five middle schools were chosen for the female sample, totaling 72 teachers. Accordingly, a total of 134 teachers of both genders participated in the study. Instrument: Two valid and reliable surveys were developed by (Aldeeka and Khasawneh, 2021). The participants were given two surveys to complete. The first survey for job satisfaction included four domains. The second survey for participation in decision-making also included four domains. The surveys had a total of 54 questions. Statistical Package for Social Sciences (SPSS) was used to analyze the data. Job satisfaction was shown as a dependent variable, whereas decision-making participation was the independent variable. Gender and teaching experiences were as controlling variables. Findings: The major finding of the study were as follows: 1) There was a positive correlation between job satisfaction and participation in decision-making (r (134) = .468, p <.001); 2) There was no difference in job satisfaction between males and females; 3) There was no difference in participation in decision-making between males and females; 4) There was a difference for teaching experience in relation to job satisfaction; 5) There was no difference between participation in decision-making in relation to teaching experiences; and 6) The level of job satisfaction and participation in decision making for the total sample considered within average level. The findings aim to support educational policymakers in the education field. Additionally, various recommendations were put forward to boost teachers' job satisfaction.
- Graph-based Time-series Forecasting in Deep LearningChen, Hongjie (Virginia Tech, 2024-04-02)Time-series forecasting has long been studied and remains an important research task. In scenarios where multiple time series need to be forecast, approaches that exploit the mutual impact between time series results in more accurate forecasts. This has been demonstrated in various applications, including demand forecasting and traffic forecasting, among others. Hence, this dissertation focuses on graph-based models, which leverage the internode relations to forecast more efficiently and effectively by associating time series with nodes. This dissertation begins by introducing the notion of graph time-series models in a comprehensive survey of related models. The main contributions of this survey are: (1) A novel categorization is proposed to thoroughly analyze over 20 representative graph time-series models from various perspectives, including temporal components, propagation procedures, and graph construction methods, among others. (2) Similarities and differences among models are discussed to provide a fundamental understanding of decisive factors in graph time-series models. Model challenges and future directions are also discussed. Following the survey, this dissertation develops graph time-series models that utilize complex time-series interactions to yield context-aware, real-time, and probabilistic forecasting. The first method, Context Integrated Graph Neural Network (CIGNN), targets resource forecasting with contextual data. Previous solutions either neglect contextual data or only leverage static features, which fail to exploit contextual information. Its main contributions include: (1) Integrating multiple contextual graphs; and (2) Introducing and incorporating temporal, spatial, relational, and contextual dependencies; The second method, Evolving Super Graph Neural Network (ESGNN), targets large-scale time-series datasets through training on super graphs. Most graph time-series models let each node associate with a time series, potentially resulting in a high time cost. Its main contributions include: (1) Generating multiple super graphs to reflect node dynamics at different periods; and (2) Proposing an efficient super graph construction method based on K-Means and LSH; The third method, Probabilistic Hypergraph Recurrent Neural Network (PHRNN), targets datasets under the assumption that nodes interact in a simultaneous broadcasting manner. Previous hypergraph approaches leverage a static weight hypergraph, which fails to capture the interaction dynamics among nodes. Its main contributions include: (1) Learning a probabilistic hypergraph structure from the time series; and (2) Proposing the use of a KNN hypergraph for hypergraph initialization and regularization. The last method, Graph Deep Factors (GraphDF), aims at efficient and effective probabilistic forecasting. Previous probabilistic approaches neglect the interrelations between time series. Its main contributions include: (1) Proposing a framework that consists of a relational global component and a relational local component; (2) Conducting analysis in terms of accuracy, efficiency, scalability, and simulation with opportunistic scheduling. (3) Designing an algorithm for incremental online learning.
- Rational Design of Poly(phenylene sulfide) Aerogels Through Precision ProcessingGodshall, Garrett Francis (Virginia Tech, 2024-04-02)Poly(phenylene sulfide) (PPS), an engineering thermoplastic with excellent mechanical, thermal, and chemical properties, was gelled for the first time using 1,3-diphenylacetone (DPA) as the gelation solvent in a thermally induced phase separation (TIPS) process. PPS was dissolved in DPA at high temperatures to form a homogeneous solution. The solution was cooled, initiating phase separation and eventually forming a solidified PPS network around DPA-rich domains. Evacuation of DPA from the gel network creates monolithic PPS aerogels, one of few physically crosslinked polymer aerogel systems comprised of a high-performance thermoplastic. In this work, specific properties of PPS aerogels were controlled through the manipulation of various processing parameters, such as polymer concentration, post-process annealing conditions, mode of manufacturing (casting versus additive manufacturing), dissolution temperature, and drying method. The ultimate goal was to elucidate key process-morphology-property relationships in PPS aerogels, to ultimately improve aerogel performance and applicability. The phase diagram of PPS/DPA was first elucidated to determine the phase separation mechanism of the system, which guides all future processing decisions. The phase diagram indicated that the system undergoes solid-liquid phase separation, typical for solutions with relatively favorable polymer-solvent interactions. This assignment was validated by the calculation of the Flory-Huggins interaction parameter through two independent methods - Hansen solubility parameters and fitting melting point depression data. The influence of polymer composition on PPS aerogel properties was then characterized. As polymer concentration increased, aerogel density and mechanical properties increases, and porosity decreased. The particular morphology of PPS aerogels from DPA was that of a fibrillar network, where these axialitic (pre-spherulitic) fibrils are comprised of stacks of PPS crystalline lamellae, as suggested by x-ray scattering and electron microscopy. These interconnected microstructures responded more favorably to compressive load than similar globular PEEK aerogels, highlighting the importance of aerogel microstructure on its mechanical response. Upon solvent extraction, PPS aerogels were annealed in air environments to improve their mechanical behavior. Annealing did not dramatically shrink the aerogels, nor did it appear to affect the micron-scale morphology of PPS aerogels as observed by electron microscopy. The resistance to densification of PPS aerogels was mainly a product of their interconnected fibrillar morphologies, aided by subtle microstructural changes that occurred upon annealing. Exposure to a high temperature oxidative environment (160 – 240 oC) increased the degree of crystallinity of the aerogels, and also promoted chemical crosslinking within the amorphous PPS regions, both of which may have helped to prevent severe densification. With enhanced physical and chemical crosslinking, annealed PPS aerogels displayed improved compressive properties over unannealed analogues. Additionally, the thermal conductivity of both annealed and unannealed aerogel specimens was below that of air (~ 0.026 W/mK) and did not display a dependence on polymer composition nor on annealing condition. Generally, these experiments demonstrate that annealing PPS aerogels improved their mechanical performance without negatively affecting their inherent fibrillar morphology, low density, or low thermal conductivity. To fabricate aerogels with geometric flexibility and hierarchical porosity, PPS/DPA solutions were printed through material extrusion (MEX) and TIPS using a custom-built heated extruder. In this process, solid solvated gels were first re-dissolved in a heated extruder and solutions were deposited in a layer-wise fashion onto a room-temperature substrate. The large temperature gradient between nozzle and substrate rapidly initiated phase separation, solidified the deposited layers and formed a printed part. Subsequent solvent exchange and drying created printed PPS aerogels. The morphology of printed aerogels was compositionally-dependent, where the high extrusion temperature required to dissolve highly-concentrated inks (50 wt % PPS) also destroyed self-nuclei in solution, yielding printed aerogels with spherulitic microstructures. In contrast, aerogels printed from 30 wt % solutions were deposited at lower temperatures and demonstrated fibrillar microstructures, similar to those observed in 30 wt % cast aerogel analogues. Despite these microstructural differences, all printed aerogels demonstrated densities, porosities, and crystallinities similar to their cast aerogel counterparts. However, printed aerogel mechanical properties were microstructurally-dependent, and the spherulitic 50 wt % aerogels were much more brittle compared to the fibrillar cast 50 wt % analogues. This work introduces a widely-applicable framework for printing polymer aerogels using MEX and TIPS. Intrigued by the compositional morphological dependence of the printed PPS aerogels, the dissolution temperature (Tdis), and thus the self-nuclei content, of cast PPS/DPA solutions was systematically varied to understand its influence on aerogel morphology and properties. As Tdis increased, the length and diameter of axialites increased while aerogel density and porosity were relatively unaffected. Thus, the isolated influence of axialite dimensions (analogous to pore size and pore concentration) on aerogel properties could be studied independent of density. At low relative densities (below 0.3, aerogels of 10 – 30 wt %), compressive modulus and offset yield strength tended to decrease with Tdis, due to an increase in axialite length (akin to pore size) and number of axialites (akin to number of pores). At higher relative densities (above 0.3, 40 and 50 wt %), axialitic aerogels were so dense that changes in pore dimensions did not result in systematic changes in mechanical response. All spherulitic aerogels fabricated at the highest Tdis¬ demonstrated reduced mechanical properties due to poor interspherulitic connectivity. The thermal conductivity of all aerogels increased with polymer composition but demonstrated no clear trend with Tdis. A model for thermal conductivity was used to deconvolute calculated conductivity into solid, gaseous, and radiative components to help rationalize the measured conductivity data. This work demonstrates the importance of nucleation density control in TIPS aerogel fabrication, especially at low polymer concentrations. The specific method used to dry an aerogel generally has a great influence on its microstructure and density. Vacuum or ambient drying is the most industrially-attractive technique due to low cost and low energy usage; however, it is typically the most destructive process due to high capillary forces acting on the delicate aerogel microstructure. Three drying methods, vacuum drying, freeze drying, and supercritical CO2 drying, were used to evacuate PPS gels fabricated at three PPS concentrations (10, 15, and 20 wt %). Almost all aerogel specimens displayed excellent resilience against shrinkage as a function of the drying method, besides the 10 wt % vacuum dried sample which shrunk almost 40%. While the micron-scale aerogel morphology captured by electron microscopy appeared to be unaffected by the drying method, other properties such as aerogel surface area, mesoporous volume, and mechanical properties were effectively functions of the degree of aerogel shrinkage. Aerogel thermal conductivity was low for all samples, and in particular, vacuum dried aerogels demonstrated slightly lower conductivities than other ambiently-dried aerogel systems such as silica and carbon. In general, vacuum drying appears to be industrially viable for PPS aerogels at concentrations above 10 wt %.
- Enhancing Safety in Critical Monitoring Systems: Investigating the Roles of Human Error, Fatigue, and Organizational Learning in Socio-Technical EnvironmentsLiu, Ning-Yuan (Virginia Tech, 2024-04-09)Modern complex safety-critical socio-technical systems (STSs) operate in an environment that requires high levels of human-machine interaction. Given the potential for catastrophic events , understanding human errors is a critical research area spanning disciplines such as management science, cognitive engineering, resilience engineering, and systems theory. However, a research gap remains when researching how errors impact system performance from a systemic perspective. This dissertation employs a systematic methodology and develops models that explore the relationship between errors and system performance, considering both macro-organizational and micro-worker perspectives. In Essay 1, the focus is on how firms respond to serious errors (catastrophic events), by exploring the oscillation behavior associated with the organizational learning and forgetting theory. The proposed simulation model contributes to the organizational science literature with a comprehensive approach that assesses the firm's response time to "serious" errors when the firm has a focus on safety with established safety thresholds. All of these considerations have subsequent impact on future performance. Essay 2 explores the relationship between safety-critical system's workers' workload, human error, and automation reliance for the Belgian railway traffic control center. Key findings include a positive relationship between traffic controller performance and workload, and an inverted U-shaped relationship with automation usage. This research offers new insights into the effects of cognitive workload and automation reliance in safety-critical STSs. Essay 3 introduces a calibrated System Dynamics model, informed by empirical data and existing theories on workload suboptimality. This essay contributes to the managerial understanding of workload management, particularly the feedback mechanism between operators' workload and human errors, which is driven by overload and underload thresholds. The model serves as a practical tool for managerial practitioners to estimate the likelihood of human errors based on workload distributions. Overall, this dissertation presents an interdisciplinary and pragmatic approach, blending theoretical and empirical methodologies. Its broad impacts extend across management science, cognitive engineering, and resilience engineering, contributing significantly to the understanding and management of safety-critical socio-technical systems.