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Personalized Learning Instruction (PLI) is the practice of personalizing instructional practices, scaffolding, and assessing the schoolwork of each individual student based on their specific learning needs and the standards of the curricular content. It involves student choice and interest within a flexible structure. Currently, most of the research that has been conducted on PLI has focused on math instruction, older secondary students (grades 9-12), and relatively small samples of students. Little research has been conducted to determine if and what impacts PLI may or may not have on English Language Arts achievement. Nor has much emphasis been placed on middle schoolers, where routines and patterns for future success in secondary school are established. The purpose of this study was to understand middle school principals’ perceptions of (1) Personalized Learning Instruction (PLI), (2) the effects of Personalized Learning Instruction on middle grades English Language Arts achievement, and (3) the impact of COVID-19 on the implementation of Personalized Learning Instruction in their schools. This qualitative case study involved in-depth interviews of four middle school principals who had experience with the implementation of PLI in their schools. Four themes emerged from these case studies and are expressed through thematic sentences; (1) Principals perceive a positive impact on student achievement through Personalized Learning Instruction, largely through increased engagement with reading in English Language Arts classes, (2) A misalignment exists between using PLI strategies and current instructional practices, (3) Staffing issues, inexperience, and vacancies have pushed instructional leaders away from Personalized Learning Instruction, and (4) Personalized Learning Instruction is not a priority post-COVID-19.
Group purchasing (GP) is a procurement strategy by which the retailers can negotiate better prices by increasing their negotiation power through collaboration with each other. GP problem can be modeled as a generalized newsvendor problem, although it is more realistic to model this problem with stochastic demand, current literature on GP is mostly focused on problems with deterministic demand. Comparing the single retailer newsvendor vs. a newsvendor problem with multiple retailers, there has been more attention paid to the newsvendor problem with single retailer. When there are multiple retailers, competition would be another important aspect to consider, which is lacking in parts of the literature and will be considered in this research. Different contracting scenarios such as revenue-sharing and buyback contracts are other aspects which can be considered in the GP problem which has not been studied so far. Given that; four research questions are defined to investigate in this study: 1) the first question investigates the newsvendor problem with quantity discount pricing from supplier by exploring an analytical approach to solve this problem building on existing solutions from the literature; next a second novel solution approach is proposed which solves the problem in fewer steps; answering this question makes the foundation for our subsequent research questions. 2) the second research question studies the GP problem with multiple symmetric retailers; this research question is an extension of the first research question which investigates the GP supply chain consisting of multiple symmetric retailers. 3) third research question explores the solution to GP with multiple asymmetric retailers and suppliers; since this problem is complex to solve, the GP problem is divided into two sub-problems, retailers’ problem, and suppliers’ problem which are solved separately and then brought together to provide an answer to the overall GP problem, and 4) finally, fourth research question introduces different supply chain contracts to the GP problem and investigates studying the effect of these contracts on the retailers’ profit. Mathematical results as well as managerial insights are provided for each model through sensitivity analysis and numerical experiments.
Materials science aims to explore the properties and behaviors of different materials, from metals to advanced carbon structures. This dissertation focuses on three distinct areas of study: Inconel Alloy 740H, polycrystalline graphene, and tetragraphene (TG).
The first part of this work concentrates on developing and validating a Chaboche unified constitutive model. This model incorporates both nonlinear isotropic and kinematic hardening rules to accurately predict the stress-strain behavior of Inconel Alloy 740H, a high-temperature nickel-based superalloy. The material parameters of the model are determined and its accuracy validated through experimental data obtained from uniaxial strain-controlled loading tests across a wide temperature and strain ranges.
The second part explores the mechanical properties of polycrystalline graphene, bridging scales from nanoscale to macroscale through a multiscale molecular dynamics (MD)–finite element (FE) modeling approach. By studying the behavior of graphene sheets with different grain boundaries and atomic structures, insights are gained into the influence of grain size on mechanical properties like the Young modulus and fracture stress.
The third part of this dissertation investigates the mechanical properties of tetragraphene (TG), a quasi-2D semiconductor carbon allotrope, with a focus on addressing graphene's limitations in electronic applications. Through MD simulations, the research examines TG's fracture properties under mixed mode I and II loading, considering variables such as loading phase angle, crack structure, and temperature.
Since the early 1980s, American educational reformers have tried to improve schools through standards, high-stakes tests, and punishments for those schools that failed to meet the mark. In North Carolina, many schools with diverse populations and low socioeconomic status have struggled to succeed, receiving the state performance grade of D or F and the consequent “low-performing” label. Meanwhile, some teachers in these schools have achieved at high levels and attempted to improve not only their classrooms, but their schools and districts. Few researchers have sought the opinions and expertise of high-performing teachers in order to better understand their experiences, their role as change agents, and their recommendations for other so-called “low-performing” schools. This qualitative multiple case study used in-depth interviews with these high-performing teachers in “low-performing” elementary schools in North Carolina. Specifically, this research gathered information about their backgrounds, their actions for school transformation, and their lessons learned about education and equity. Findings from the study indicated that high-performing elementary teachers tried to reform their “low-performing” schools through teacher agency but were blocked by multiple factors. School administrators and district officials reduced teacher agency and opportunities for school improvement. North Carolina’s “low-performing” schools policy harmed children, reinforced school failure, and produced discriminatory and inequitable results. Teacher agency theory provided a promising approach for the state to change course and improve failing schools.
Recent advancements in deep learning have significantly propelled the field of computer vision, especially in 3D human model recovery from monocular images. This work is centered on developing efficient deep learning models for digitizing human subjects, thereby laying a solid foundation for various subsequent applications. 3D human mesh estimation from monocular images often requires complex deep learning models. In addressing this, we propose a hybrid approach combining deep learning models with analytical inverse kinematics to precisely estimate 3D pose and shape.
Our precise 3D pose estimations facilitate three high-impact downstream applications. Firstly, we aim to create a real-time biomechanics analysis system that provides low-cost, real-time, and accurate estimations of kinematic sequences for managing joint human health-performance. Herein, our system integrates mobile modular 3D pose estimation with model-based inverse kinematics optimization seamlessly. The next downstream task entails skeleton-based human action recognition (HAR), with extensive applications in smart homes, cities, and retail. By rendering 3D pose sequences as RGB images and utilizing conventional CNN architectures alongside various data augmentation schemes, we have achieved results comparable to sophisticated Graph Neural Network models. Lastly, in scenarios where visual cues are scarce yet human monitoring is essential, radar-based sensing offers a non-intrusive solution for tracking human movements and vital signs. Given the paucity of extensive radar datasets, we introduce a "virtual radar" framework in our third downstream task. This framework, driven by 3D pose and physics-informed principles, generates synthetic radar data, presenting a novel avenue towards a nuanced understanding of human behavior through privacy-preserving radar-based methodologies.
Autism Spectrum Disorders (ASD) are characterized by pervasive impairments, inhibiting social interaction and learning opportunities, often with ensuing behavior challenges. Studies estimate that 25-30% of children with ASD do not develop flexible and consistent language. Communication skills are essential to supporting individuals with ASD to communicate their needs, navigate their chosen environments independently, and establish relationships. Fortunately, researchers have identified several practices to address social communication challenges. Naturalistic teaching (NT) and parent-mediated intervention (PMI) are two practices derived from applied behavior analysis that are evidence-based and highly effective language acquisition methods. Caregiver-implemented interventions, often facilitated via coaching, provide families with supportive practice to increase their children’s language within natural contexts. By equipping parents with tools, strategies, and support, these interventions leverage the strength of the family unit to facilitate language-rich learning opportunities. Despite empirically-supported communication models for ASD and solid evidence supporting NT and PMI, insufficient access to high-quality interventions remains a barrier for families. Barriers such as inequalities in access to services, challenges in customizing training, schedule constraints, and family pressures remain significant concerns for caregivers.
The purpose of this study was to examine the effects of a naturalistic caregiver coaching package on the accuracy of parents' implementation of Referent-Based Instruction (RBI), evaluate their children's verbal behavior repertoires subsequent to intervention, and explore caregivers’ experiences in participating in RBI. Results suggest that caregivers improved their fidelity and implementation of RBI procedures following the introduction of the coaching package. Child participants' communicative repertoires increased after caregivers participated in the intervention, and they reported their experiences in this training as highly positive.
A key component of team performance is participation among group members. One widespread organizational function that provides a stage for participation is the workplace meeting. With the shift to remote work, roughly half of all meetings are now conducted virtually (Cisco, 2022). In this new context, meeting participation is mediated through technology – which presents new challenges and opportunities for meeting leaders and attendees. One encouraging opportunity that can elevate meeting participation is the use of written chat during virtual meetings. Text-based chat offers a second avenue of participation during a meeting, where attendees can synchronously contribute to the conversation through writing, in a manner that typically does not disrupt the verbal discussion. The current study leverages research and theory on (a) individual differences (i.e., status characteristics theory), (b) employee perceptions of psychological safety and (c) work group participation in a virtual context to explore potential antecedents of engaging in chat during virtual meetings. Results suggest women and those high in job level participate in the meeting chat more frequently than their counterparts. We find perceptions of psychological safety moderate the relationship between job level and chat participation. Employees low in job level who have high perceptions of psychological safety participate in chat more frequently compared to their counterparts who report low perceptions of psychological safety. Results contribute to our understanding of written communication in virtual meetings, unpacking the individual differences in chat participation in a technology-mediated space. Further, our findings enhance our understanding of psychological safety; and how creating a psychologically safe environment can influence one’s method of participation in virtual meetings.
Total knee arthroplasty (TKA) is a prevalent solution for severe knee osteoarthritis, yet the comparative efficacy between posterior stabilized (PS) and bi-cruciate stabilized (BCS) implants remains undefined, as does performance variance in daily activities. In this study, sixty individuals (20 per group in PS-TKA, BCS-TKA, and controls) were recruited and evaluated at pre-op and six-month post-op. Human motion analysis was performed during five daily activities, such as level walking. Knee joint biomechanics, muscle activities, and a newly formulated Knee Biomechanics Index (KBI), along with clinical assessment, were compared among three groups.
Patients exhibited significant functional improvement at post-op, more pronounced in level walking, with stair climbing remaining problematic. Both TKA groups demonstrated comparable performance enhancements and pain relief, albeit with nuanced distinctions in joint range of motion during stair ambulation. Notably, unilateral TKA patients still experienced bilateral discrepancies at six-month post-op, evident in strenuous tasks due to enduring imbalances in knee forces and muscle activities. There were noticeable differences in performance and persistent bilateral differences at post-op between TKA groups. These insights are critical for surgeons in tailoring implant choices and for therapists in optimizing rehabilitation strategies, ensuring focused recovery plans that cater to individual patient needs and activity-specific demands.
Sexually transmitted infections (STIs) affect an estimated 347 million people worldwide. These diseases can potentially incur significant long-term negative health outcomes, including lifetime treatment regimens, cancer, or infertility. Outcome severity, clinical manifestations, and acquisition rates show a sexually dimorphic variability, with women experiencing a higher disease burden than men. While the exact mechanism for this disparity is unknown, it is likely due to a combination of biological and social influences disproportionately affecting the sexes. This study investigates some of these gendered variables, particularly those involving birth control and sexual healthcare, and their relationship with STI acquisition. Data analysis using the National Health and Nutritional Examination Survey, and a cross-sectional sexual health survey disseminated to college women concluded that women in the United States follow the classic gendered trend with higher rates of STIs. Our cross-sectional sexual health survey included information from 522 sexually active women. We found significant associations regarding a positive self-reported STI history with sexual partner number and inconsistent screening frequency. We also found associations between women who do use some form of hormonal contraceptive with condom use, STI screening frequency, and age. Free-response questions also gave us qualitative insight regarding comfort with sexual health physicians, feelings regarding positive STI diagnosis, and physician’s approach toward their positive STI history. This study addressed several variables associated with women's sexual health care and outcomes and was able to identify several risk factors that may influence the gendered disparity we see in STI prevalence.
This dissertation proposal examines the relationship between corporate growth/expansions and entrepreneurial start-up activity and failures, the number of jobs created, and wages paid by the corporate relocation. Using data sourced from the North Carolina Secretary of State, Census Bureau, and Job Development Investment Grant, I set out to evaluate changes in entrepreneurial startup activity and failures, tax incentive payouts, and salaries arising from large (greater than 251 employees) corporate expansions located in the state of North Carolina. The analysis suggests that expansions of existing corporations directly affect entrepreneurial start-up activity and failures. We conclude by highlighting the study's theoretical contributions to help further the conversation and direct startup and failure business strategies for small businesses.
