SHAREOK Repository
Not a member yet
49261 research outputs found
Sort by
“THEY NOT LIKE US” A COLLECTION OF COUNTERNARRATIVES ABOUT BLACK SECONDARY STUDENTS’ EXPERIENCES IN EDUCATIONAL SPACES
No full textThis qualitative study, “They Not Like Us”, examined the experiences of Black students in urban educational settings in Oklahoma. The purpose of this study was to provide foundational data about the lived experiences of Black students within educational sites utilizing counternarratives that center their voice. This study aimed to understand how Black students describe their experiences, how they conceptualize belonging, and if educational spaces values and support Black students’ identities, cultures, and funds of knowledge. These counternarratives were developed utilizing aspects of Critical Race Theory, BlackCrit, and Afropessimism. Themes that emerged from this research were belonging rooted in connection and community, lack of connection to non-Black teachers, lack of Black contributions in curriculum, and an overall lack of Black teachers and administrators in educational spaces. The implications of this research are that educational spaces must be structured in ways that connect with Black students, integrate Black contributions to educational spaces, create avenues to employ more Black professionals in educational settings, and give Black students agency and voice. Additional opportunities for expansion of this study include but are not limited to a more longitudinal study exploring how Black students' conceptions of belonging change over time, a case study into non-Black teachers who successfully connect with Black students, and a replication study with a larger number of students
Leveraging Virtual Reality to Promote Transformative Experience: Investigating The Role of Presence and Agency
No full textThis study investigates the role of Immersive Virtual Reality (IVR) in facilitating Transformative Experiences (TE) and enhancing everyday engagement with learning. Using the Teaching for Transformative Experiences in Science (TTES) model, this research integrates IVR's unique affordances—presence and agency—to examine how immersive learning environments can bridge classroom concepts and real-world applications. A convergent parallel mixed methods design was employed, involving both quantitative and qualitative analyses, to capture the nuanced impacts of IVR-supported instruction on TE. Findings reveal that IVR can deepen students' engagement by fostering a stronger sense of presence, contributing to meaningful and lasting changes in students' perspectives and interest in content beyond traditional educational settings. This research contributes significantly to both TE theory and the growing field of immersive learning, providing evidence-based insights that inform future instructional designs aimed at maximizing engagement, equity, and ecological validity in learning environments. Practical implications suggest that IVR, when integrated thoughtfully into instructional practices, can catalyze enduring interest and active engagement across a variety of educational contexts
Evaluating the Role of Quantum Algorithms in Supervised Machine Learning
Get PDFQuantum computing (QC) has emerged as a disruptive technology, promising exponential speedups for certain computational problems. At the same time, machine learning (ML) continues its transformative journey across scientific domains with its ability to locate patterns within data. The intersection of both disciplines, Quantum Machine Learning (QML), offers efficiency and optimization speedups in certain learning tasks, captivating the interest of both researchers and business leaders. The power of QML lies in its ability to harness quantum properties, such as superposition and entanglement, to solve complex business problems more efficiently than classical algorithms. These quantum properties can be applied to ML in numerous ways, depending on the complexity of the problem.
This thesis delves into Quantum Kernel Support Vector Machines (QKSVMs), a specific QML technique that leverages quantum computing for supervised learning, particularly support vector machines (SVMs). The reason behind focusing on this technique specifically lies in the fact that quantum algorithms can map data points into a higher dimensional feature space. Through this process, quantum kernels aim to locate atypical patterns in data for classification tasks. The discrete logarithm problem (DLP) is a common mathematical problem widely used in cryptography due to its one-way-function nature and resistance to classical algorithms. It has been argued that the case of DLP is a scenario where quantum-inspired algorithms can enhance their classical counterparts in terms of accuracy and other machine learning performance metrics. Utilizing this mathematical problem as the distribution within a dataset could potentially prove quantum advantage, suggesting that using quantum algorithms in certain situations may be beneficial.
This thesis presents empirical evidence of quantum algorithms’ performance enhancements within the DLP framework. This work concludes that in specific scenarios like DLP-distributed datasets, even near-term quantum algorithms operating with fewer qubits can have an advantage over existing algorithms. Furthermore, the findings from this work offer valuable insights to researchers and business leaders interested in investing in the design and implementation of QML models in scenarios beyond DLP, where quantum algorithms have an advantage over classical algorithms
Quantifying Nanoparticle Attachment to Produce Surfaces
No full textIn recent years, nanoparticles have emerged as an intriguing tool in the field of agriculture, showing capabilities to increase performance and efficiency in several areas throughout the process of crop production. For many applications, their beneficial abilities depend on their resistance to detachment. However, this quality can have detrimental effects to human health once produce has left the farm. Therefore, it is important to accurately quantify attachment and detachment, as well as provide insight into what factors influence these qualities. Nanoparticles of different structure and concentration were applied to organic surfaces in 5 µL drops. A rinsing procedure was then developed to simulate a process by which produce is washed before consumption. Samples were then imaged with a scanning electron microscope (SEM) using both backscatter and secondary electron modes. Using the SEM’s backscatter electron detection, an image thresholding program was developed. Images were broken into pixels and segmented by brightness intensity. A threshold was then calculated from the derivative of reverse-cumulative brightness intensity frequency, from which pixels were binned into nanoparticles and non-nanoparticles. Images were taken of both rinsed and unrinsed surfaces, allowing a visual comparison and computerized quantification of detachment rates. At higher nanoparticle concentrations, significant detachment took place for nanoparticles studied. No decrease in particle frequency could be observed at the low end of concentrations. Addition of extracellular polymeric substances (EPS) as well as variations in pH had no observed significant effect on detachment
Running with Rosalie Fish: (Over)Laps in Rhetorical Race Spaces
Get PDFRosalie Fish (Cowlitz/Muckleshoot) is an activist who runs for The University of Washington and Missing and Murdered Indigenous Women. During her races, she dons red paint, and her body exists as a living archive, carrying stories of ancestors throughout time and space. In this thesis, I “story with” (Archibald) Fish to compose an in-flux framework of the rhetorical “race space” using a story of Fish’s 3200-meter race for Renee Davis, my experience racing a 1500-meter race, and Momaday, Bruchac, and Lyons’s spatial rhetoric concepts. Then, I use this framework to consider how Fish and I (over)lap across culture and geography to make meaning of my ethical responsibilities as a scholar-runner-human and work towards rhetorical alliance. Finally, I consider how the race space can potentially be used in other contexts of cross-cultural discourse. This thesis views the “race space” as a discursive space full of cross-cultural discourse, shaped by personal stories, where runners of all intersecting identities—race, class, culture, gender, sex, age, sexuality, and religion—value racing, storytelling, and writing as means of communication to disrupt, talk back, resist, and build community to talk across and with difference. Towards these purposes, I respond to two framing questions: what does it mean to overlap in space with someone different than myself? As a non-Native researcher, how do I ethically engage with Indigenous people and research while occupying Native land
ADVANCING POLYMER MEMBRANES THROUGH CONFIGURATIONAL FREE VOLUME AND MEASUREMENT INNOVATIONS
Get PDFThis dissertation explores the impacts of configurational free volume, introduced through triptycene units, on the transport properties of condensable vapors and gases in thermally rearranged polybenzoxazole-based polymers as well as their polyhydroxyimide precursors which are not thermally treated. Through a series of in-depth studies, we elucidate the fundamental mechanisms governing solubility, diffusivity, and selectivity in these materials, offering insights into their potential applications in molecular separations. Chapter 1 presents pioneering findings on how triptycene-containing polybenzoxazoles (TPBOs) mediate condensable vapor transport, demonstrating size-controlled (entropically driven) sorption and diffusion, quite unlike conventional glassy polymers. This configurational free volume facilitates the tuning of sorption and diffusion selectivity, potentially unlocking routes to de-bottleneck limitations in current state-of-the-art membrane performance. Chapter 2 extends this investigation to light gases (N2, CH4, and CO2), proposing a mechanism for molecule transport in configurational free volume. By varying triptycene content, we analyze the effects (and lack thereof) on the components of CO2/CH4 selectivity, uncovering that configurational free volume exclusively regulates light gas diffusion selectivity in the Langmuir mode without affecting the other components of selectivity. Chapter 3 addresses the critical issue of data reliability in solubility measurements, proposing a standardized methodology for estimating uncertainty in sorption and adsorption measurements. This study lays out a framework for understanding factors that contribute to measurement error, and comprehensively addresses accurate comparison between solubility measurements within a single lab, as well as across laboratories worldwide, which is critical in the previous two chapters. Chapter 5 investigates the swelling behavior of TPBOs, revealing that configurational free volume and thermal rearrangement collectively and synergistically enhance swelling resistance, a crucial factor for membrane stability and performance in real-world applications. It also brings in techniques from Chapter 3 and data science to demonstrate a novel dilatometry analysis method. This comprehensive study not only lays out an advancement in our understanding of configurational free volume, but also provides measurement and error analysis standardizations in the membrane field. The work may be of practical use to researchers seeking to improve the rational design of membranes and the design of extremely accurate apparatuses geared towards membrane and polymer sciences, such as the sorption and dilation apparatuses discussed herein
Maternal social environment shapes yolk testosterone allocation and embryonic neural gene expression in tree swallows
Get PDFOffspring from females breeding in competitive social environments are often exposed to more testosterone (T) during embryonic development, which can affect traits from growth to behavior in potentially adaptive ways. Despite the important role of maternally derived steroids in shaping offspring development, the molecular mechanisms driving these processes are currently unclear. Here, we use tree swallows (Tachycineta bicolor) to explore the effects of the maternal social environment on yolk T concentrations and genome-wide patterns of neural gene expression in embryos. We measured aggressive interactions among females breeding at variable densities and collected their eggs at two timepoints, including the day laid to measure yolk T concentrations and on embryonic day 11 to measure gene expression in whole brain samples. We found that females breeding in high-density sites experienced elevated rates of physical aggression and their eggs had higher yolk T concentrations. A differential gene expression and weighted gene co-expression network analysis indicated that embryos from high-density sites experienced an upregulation of genes related to hormone, circulatory, and immune processes, and these gene expression patterns were correlated with yolk T levels and aggression. Genes implicated in neural development were additionally downregulated in embryos from high-density sites. These data highlight early neurogenomic processes affected by the maternal social environment and provide new insights into how offspring phenotypic plasticity could arise later in life
The Nature, Determinants, and Consequences of Congressional Distributive Politics
Get PDFThe allocation of public resources is a core responsibility of the United States federal government, and geographically targeted spending is both practically important and central to major theories of the US Congress. This dissertation advances the study of congressional distributive politics by incorporating a diverse array of methodological approaches to clarify the nature, determinants, and public opinion consequences of the geographic allocation of federal funds by the US Congress. The first two chapters use observational data on federal spending to clarify the nature of distributive policy change and show how legislative procedure shapes policy outcomes. The third and fourth chapters leverage survey experiments to shed light on the role of distributive politics in congressional elections. Together, the four chapters approach congressional distributive politics from different perspectives to generate insights on policymaking, representation, and electoral strategy
Investigating AI Chatbot Integration in Academic Libraries: A Case Study
Get PDFAI chatbots have recently received great attention due to the advancement of large language models, such as OpenAI's GPT series and Google's Gemini, which have shown excellent performance and applicability. Therefore, many academic libraries endeavor to integrate AI chatbots into their services. The University of Oklahoma (OU) Libraries started an AI chatbot project in 2017, ahead of most other academic libraries, and developed an original AI chatbot. In July 2019, OU Libraries launched an AI chatbot service using Ivy.ai, which utilized cutting-edge technology at the time. The chatbot service, launched before COVID-19, continued to operate even when the OU Libraries was closed due to the pandemic and remained operational until recently, providing valuable log data recording interactions between users and AI chatbots over the past few years. This study used mixed methods to investigates (a) how the AI chatbot has been implemented at the OU Libraries, (b) the usage patterns of OU Libraries’ AI chatbot, and (c) how users of OU Libraries’ AI chatbot evaluate its performance by exploring the important factors influencing users’ chatbot evaluation and questions the chatbot was unable to provide answers. The study provides practical recommendations for institutions planning to implement AI chatbots, and also lays the foundation for future research on AI chatbot technology to improve library services