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ABSTRACT
Culturally Responsive Teaching is a holistic pedagogical approach that appeals to the “whole child,” “whole school,” and “whole community” (Gay, 2001; Teschers, 2020); it is a multicultural practice that improves teaching and learning, promotes quality education, taps into the potential and uniqueness of students, and impacts learners intellectually, emotionally, kinesthetically, and physically (Gay, 2010; Widodo, 2019). This qualitative phenomenological case study examines the concepts and pedagogical practices of culturally responsive teaching through the shared experiences of educators and implementers of culturally responsive pedagogy to find out how effective those concepts and practices are in improving the academic outcomes of marginalized students (K-12) in urban classrooms. A purposive case sampling method (PCSM) and semi-structured interview were instrumental elements of the data collection process. A grounded theory method was used to both collect and analyze the data. Themes that emerged from the data of the interviews conducted with the participants were amalgamated to form four main themes for the study. Though this study may be limited by generalizability, it however provides answers to some lingering limitation questions of existing studies on culturally responsive practices. This study draws on and adds to the works of Geneva Gay on Culturally Responsive Pedagogy.
Keywords: holistic education, education equity, educational inequity, multicultural education, opportunity gap, culturally responsive pedagogy
Social studies education has garnered significant national attention as state governments throughout the country have waged an intentional, political attack against the teaching of Critical Race Theory (CRT) and “divisive concepts” in K-12 public schools. Even though CRT is often conflated with diversity, equity, and inclusion (DEI) initiatives and not actually taught at the elementary or secondary level, since January 2021, over one hundred anti-CRT (or divisive concepts) bills have been introduced in more than thirty different state legislatures throughout the country that would prohibit educators from teaching about concepts rooted in race. For Black women teachers, these legislative restrictions create a teaching context that pressures them to divert from the historical work of their predecessors and go against the grain of Black female identity. As such, this phenomenological study explored how Black female social studies teachers teach about race, racism, and oppression given today’s hostile sociopolitical climate.
U.S. school achievement has been the subject of much discussion. In the case of science, technology, engineering, arts, and mathematics (STEAM), the national underperformance across the country, as well as the underrepresentation of minorities are key issues (Anderson et al., 2023; Handelsman & Smith, 2016; National Research Council, 2015; The White House, 2017). Particularly, there is a small, but growing body of research on the low numbers of Black women in STEAM, and the Black girls' STEAM pipeline. Extracurricular STEAM programs have shown some success in increasing minority STEAM participation. As such, this dissertation seeks to investigate the following research questions: RQ1: How do online extracurricular STEAM programs created for Black girls serve as a potential counterspace to increase STEAM identity? RQ2: Are there identifiable features that exist in online extracurricular STEAM programs that are important for creating a counterspace for adolescent Black girls? Through a qualitative case study, this dissertation explored Black girls’ participation in online STEAM programs. The findings of the study reveal that the extracurricular STEAM programs helped to foster STEAM identities in young Black girls. The programs also helped students build a sense of community and created a safe space for Black girls. The study provides implications and recommendations for educators and policymakers who are interested in increasing minority STEAM participation.
The emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in December 2019 triggered a global pandemic, causing the urgent need for effective surveillance measures to combat its spread and monitor the evolution of new variants. Sequencing SARS-CoV-2 is an essential tool for surveilling the circulating and emerging variants. This thesis addresses key challenges and proposes advancements in sequencing SARS-CoV-2, focusing on both clinical and wastewater samples.The primary objective of this thesis is to optimize sequencing protocols for SARS-CoV-2 variants from clinical and wastewater samples, specifically targeting improved sequencing capabilities for low viral concentrations using the Oxford Nanopore Promethion platform. Through protocol modifications and refinements, we achieved notable enhancements in sequencing output metrics, such as amplicon amplification, sequencing depth, and the generation of high-quality consensus sequences. The second objective evaluates the performance of wastewater deconvolution software for identifying SARS-CoV-2 variants, employing a meticulous assessment approach with controlled mixtures of synthetic variants and amplicon-based sequencing. In this objective we highlight the effectiveness of Freyja, a widely utilized tool, in producing variant abundance calls closely aligned with expected ratios. In the third objective, we investigate factors contributing to ambiguous variant calls in next-generation sequencing data from two distinct platforms, shedding light on potential sources of variability in variant abundance estimation. Through comprehensive analysis, significant disparities in genome coverage and mutation profiles between platforms were identified, suggesting possible biases or variations in error rates. While Freyja demonstrates excellent performance with controlled datasets, challenges arise with real-world wastewater samples. Through these objectives, the thesis aims to offer insights into optimizing sequencing protocols, enhancing variant detection algorithms, and improving data reproducibility across different sequencing technologies. Ultimately, this research contributes to ongoing efforts in infectious disease surveillance by advancing our understanding of SARS-CoV-2 sequencing from diverse sample sources and providing valuable guidance for future research in viral pathogen sequencing.
The past decade has provided unprecedented insights into the molecular evolutionary pathways that have given rise to the present day diversity of vertebrates. Comparative genomic studies have repeatedly revealed that many key ecological traits, novel functional phenotypes, and even disease states are governed by genomic regions characterized by frequent mutations, duplications, or deletion events. However, the evolutionary origins and early diversification history of many of these regions remain poorly understood. My work focuses on providing a resolution to this history, focusing on the evolution of the vertebrate mobilome and a clustered gene family of innate immune receptors with putative links to the origin of the adaptive immune response. To accomplish this, I sequenced the genomes of Polypterus bichir and Lepisosteus osseus, two taxa that fill critical genomic sampling gaps for early diverging vertebrate lineages. Integrating these genomes into a comparative dataset of over 100 genomes that span all major ray-finned fish lineages, I investigated the effect of teleost genome duplication (TGD) on the diversification of the ray-finned fish mobilome. My findings reveal no substantial shift in mobilome composition following the TGD event, in line with a growing body of evidence that this historical ploidy event has not left a signature of a burst of molecular diversification and innovation across half of living vertebrates. I next expanded my taxonomic coverage to include all major vertebrate lineages to investigate the evolutionary origin of signal regulatory proteins (SIRPs) and their ligand CD47. In mammals, SIRPs are essential for regulating macrophage function and have become important targets for cancer therapy. These receptors also contain variable and joining exons and are hypothesized to have arisen in tetrapods out of a complex of innate immune receptor gene families that also gave rise to recombining T-cell receptors and antibody encoding Immunoglobulin domains. My work demonstrates this is not the case. Instead, SIRPs have evolutionary origins coincident with the origin of the adaptive immune response. In contrast, we find no evidence for an ancient origin of the CD47 ligand, which interacts with SIRPs. Instead, CD47 appears to have arisen at the beginning of amniote evolution, suggesting a decoupling of the evolutionary origins of this ligand and receptor pair. These findings provide a new perspective on the origins and diversification of innate immune receptor gene families and their relationship to the emergence of the adaptive immune system.
This qualitative study examines how Black women mid-level leaders navigate the superwoman schema. The findings extend Woods-Giscombé’s (2010) work by exploring the schema’s impact on Black women working in mid-level leadership administrative positions at HWIs. A descriptive phenomenological study was employed to understand and describe the lived experiences of Black women mid-level leaders and how the superwoman schema impacts work, leadership style, and personal care. The research questions addressed were: (1) How do Black women mid-level higher education administrators experience the superwoman schema at HWIs?; and (2) How do Black women mid-level higher education administrators respond to the superwoman schema at HWIs? Semi-structured interviews were conducted with 10 Black women who identified with the characteristics of the superwoman schema, worked at a HWI, and served in a mid-level leadership role. Data were analyzed utilizing Colaizzi’s seven-step descriptive, phenomenological data analysis process (Appendix F). Findings from one-on-one interviews indicate Black women mid-level leaders experience the exhaustion of misogynoir and use resistance responses focusing on their personal advocacy and joy. In relation to the superwoman schema, participants were aware of their emotions, exhausted from external pressures to succeed without the proper resources, and committed to the preservation of self and survival. There was consistent commitment to help others and preserve the Black community while also finding community for themselves.
Sensor placement and Informative Path Planning (IPP) are fundamental problems that frequently arise in various domains. The sensor placement problem necessitates finding optimal sensing locations in an environment, enabling accurate estimation of the overall environmental state without explicitly monitoring the entire space. Sensor placement is particularly relevant for problems such as estimating ozone concentrations and conducting sparse-view computed tomography scanning. IPP is a closely related problem that seeks to identify the most informative locations along with a path that visits them while considering path constraints such as distance bounds and environmental boundaries. This proves useful in monitoring phenomena like ocean salinity and soil moisture in agricultural lands—situations where deploying static sensors is infeasible or the underlying dynamics of the environment are prone to change and require adaptively updating the sensing locations.
This thesis provides new insights leveraging Bayesian learning along with continuous and discrete optimization, which allow us to reduce the computation time and tackle novel variants of the considered problems. The thesis initially addresses sensor placement in both discrete and continuous environments using sparse Gaussian processes (SGP). Subsequently, the SGP-based sensor placement approach is generalized to address the IPP problem. The method demonstrates efficient scalability to large multi-robot IPP problems, accommodates non-point FoV sensors, and models differentiable path constraints such as distance budgets and boundary limits. Then the IPP approach is further generalized to handle online and decentralized heterogeneous multi-robot IPP. Next, the thesis delves into IPP within graph domains to address the methane gas leak rate estimation and source localization problem. An efficient Bayesian approach for leak rate estimation is introduced, enabling a fast discrete optimization-based IPP approach. Lastly, the thesis explores sensor placement in graph domains for wastewater-based epidemiology. A novel graph Bayesian approach is introduced, facilitating the placement of sensors in wastewater networks to maximize pathogen source localization accuracy and enable efficient source localization of pathogens.
The dissertation explores the challenges and transformations in modernizing the electrical grid, characterized by increased electric power grid interconnectivity, the widespread integration of Distributed Generation (DG), and frequent network reconfigurations. These transformations pose significant challenges to traditional grid technologies and operations, including power quality issues, protection scheme challenges, and complications in energy market dynamics. This study delves into the challenges of power system protection schemes from two perspectives: the misoperation of directional elements and the miscoordination of directional overcurrent elements. The proper operation of the protection system is critical to ensuring grid reliability.
The first perspective investigates the misoperation of directional elements; we model and analyze the fault behaviors of various generators, including Synchronous and Inverter-Based Generators (IBDGs) with differing control architecture, to comprehensively understand their fault characteristics. Furthermore, we explore the misoperation of negative sequence directional elements, proposing and validating a mitigation strategy using Real-Time Hardware-in-the-Loop (RT-HIL) setups.
The second perspective addresses the miscoordination of Directional Overcurrent Relays (DOCRs) and aims to minimize their operating times. The dissertation illustrates the advantages of employing optimization algorithms over numerical iteration methods for relay coordination. It examines the coordination performance using Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), presenting an enhanced variation of PSO that yields improved performance validated through virtual HIL setups.
Additionally, the dissertation investigates the issue of DOCR miscoordination due to variations in fault current during fault isolation. It introduces a dynamic Time-Current Characteristic (TCC) formulation adapted to these variations, validated using IEEE test systems. It also investigates DG instability and miscoordination stemming from changes in network topology and generation short circuit capacity. A mitigation strategy that combines clustering and optimization algorithms is proposed and validated. Moreover, a co-optimization strategy is presented and validated to mitigate DOCR miscoordination while maintaining DG stability, ensuring that the Critical Clearing Time (CCT) associated with a fault is greater than the operating time of the relays assigned to isolate the fault.
This work significantly advances the understanding of how grid modernization impacts power system protection and lays the groundwork for future research in this evolving field. It highlights the need for a collaborative approach between inverter manufacturers and protection engineers to facilitate a seamless and reliable grid transformation.
Tornadoes are among the most destructive natural disasters, posing significant risks to communities and infrastructure, underlining the need for robust methodologies to assess building vulnerability and enhance structural resilience. This research addresses the gap in current tornado vulnerability studies by investigating the impact of material deterioration on building fragility, focusing on commercial buildings at the end of their useful life. The overarching goal is to comprehensively quantify the effects of material deterioration on tornado vulnerability, including its implications for EF-scale ranking and associated wind-speed thresholds for Degree of Damage (DOD) classifications.
The research develops predictive models to forecast deterioration trends for various building components. Focusing on deterioration rates for poorly maintained buildings at the end of their useful life and using probabilistic modeling approaches, the research develops time-dependent deterioration fragility curves to quantify the changing vulnerability of materials used in commercial buildings.
The results reveal decreased wind speed thresholds for EF-scale ranking, indicating notable changes in tornado-induced damage potential due to material deterioration. Additionally, changes in EF-scale ranking and DOD wind speed thresholds underscore the probable inadequacy of existing evaluation protocols that do not account for material deterioration. This research enhances resilience and promotes sustainable development in tornado-prone regions by illuminating the dynamic nature of tornado vulnerability.
