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The Impact School Leaders Have On Special Education Teacher Retention: A Cross-Case Analysis of Two Elementary School Leaders
Full text linkSchool leaders shape school culture and job satisfaction, impacting teachers’ decisions to remain or exit schools. The demand for special education teachers has continued to increase. I studied the impact school leaders have on increasing special education teacher retention by answering the following research question: How can school leaders increase the retention rates of special education teachers? This qualitative case study was guided by two theoretical frameworks, transformational leadership theory and critical disability theory, which informed the research design. I conducted the research at two public elementary schools in a suburban community in South Carolina. The findings revealed school leaders can increase special education teacher retention rates through intentional support, job acknowledgement, and advocacy. Findings also identified transformational leadership practices that improve special education teacher experiences
Regulatory Tension in Highly Structured Organizations
Full text linkThis study examines the psychological mechanisms by which employees with a pronounced propensity for risk-taking navigate highly formalized organizational environments. Utilizing a longitudinal, three-wave cross-sectional design with temporal separation, the research surveyed 220 employees with psychometrically validated instruments to assess personality traits, role conflict, and organizational identification. Anchored in an integrative framework that combines regulatory focus theory (Higgins, 1997) and identity theory (Burke & Stets, 2009), the study hypothesized that self-verification striving and a growth mindset mediate the relationships between risk-seeking tendencies and the outcomes of role conflict and organizational identification, with organizational structure serving as a moderating variable. Structural equation modeling (SEM), supported by comprehensive psychometric assessments including reliability analysis and confirmatory factor analysis, demonstrated a significant direct effect of risk-seeking on role conflict (β = 0.229, p \u3c 0.001).
This finding indicates that employees who embrace risk experience heightened role conflict in structured settings due to a regulatory non-fit between their promotion-focused orientation and the prevention-focused demands of such environments. Neither self-verification striving nor growth mindset mediated these relationships, though both exhibited marginally significant direct effects on organizational identification, suggesting independent contributions to organizational attachment. Organizational structure did not moderate the hypothesized pathways. These findings contribute to regulatory focus theory by demonstrating that regulatory non-fit, driven by risk-seeking tendencies, primarily manifests as role conflict rather than diminished organizational identification
Discovering High-redshift BL Lacs and Localizing GRBs for MeV missions
Full text linkBlazars are active galactic nuclei (AGNs) with their jets aligned towards Earth. Gamma-ray bursts (GRBs) can be classified into long and short types. Long GRBs are produced by the collapse of massive stars, while short GRBs are formed by binary mergers (neutron star - neutron star or neutron star - black hole mergers). Both objects are the key probes of extreme physics processes and cosmic evolution, providing us an unique window to understand the Universe. My research aims to measure the redshift of blazars and localize GRBs for proposed and upcoming gamma-ray telescopes. BL Lac objects (BL Lacs) are a subclass of blazars whose optical spectra exhibit no or weak emission lines, posing significant challenges for redshift measurement using traditional spectroscopic methods. As a consequence, the known population of high-redshift () BL Lacs remains small, with only 13 BL Lacs reported in the Third Fermi-LAT AGN Catalog (3LAC). To address this limitation, an alternative method known as the photometric approach is employed to estimate photometric redshifts (photo-) for BL Lacs. In my research, I have performed observations with the Southeastern Association for Research in Astronomy (SARA) ground-based telescopes, obtaining photometric data from near-infrared (nIR) to optical bands. Additionally, I requested ultraviolet (UV) observations from the {\it Swift} observatory. The photometric data are fitted to a set of spectral energy distribution (SED) templates to determine the photometric redshifts or upper limits. The photo- campaign has discovered 23 new high-redshift BL Lacs, seven of which were discovered through my work. The results demonstrate that the photometric approach is highly efficient for identifying the previously missing population of high-redshift BL Lacs. Besides the nIR to UV observations, my research also extends to high-energy gamma-ray regime. Specifically, I contributed to evaluating the GRB localization capability for the All-sky Medium-Energy Gamma-ray Observatory eXplorer (AMEGO-X) and developing localization methods for the Compton Spectrometer and Imager (COSI). AMEGO-X is a proposed space telescope designed to probe the underexplored medium-energy gamma-ray (MeV) band. To assess its GRB localization performance, I employed the Medium-Energy Gamma-ray Astronomy library (MEGAlib) and developed a Python-based pipeline to streamline the localization simulations. The results indicate that AMEGO-X can localize short GRBs with an accuracy ranging from 0.5 to 2.1 degrees, which is included in the AMEGO-X mission proposal submitted to NASA. In addition, COSI is an upcoming gamma-ray telescope that also aims to probe the MeV band. I contributed in developing COSI\u27s data analysis package, \texttt{cosipy}, focusing on the GRB localization algorithm for GRBs. I employed a likelihood-based approach using Poisson log-likelihood ratio (LLR) test statistics (TS) to fit COSI data to models in Compton data space. Parallel computing techniques and a multi-resolution TS map were implemented to accelerate the fitting process, enabling COSI to localize GRBs within an hour of detection. Moreover, I developed the \texttt{SpacecraftFile} and \texttt{SourceInjector} modules, responsible for coordinate conversions and generating mock COSI data, respectively. Overall, my photo- research enhances our understanding of the blazar population by discovering the missing high- BL Lacs, while localization work develops the method to accurately localize GRBs. Both work improves our knowledge of extreme astrophysical phenomena and optimizes scientific returns for proposed and upcoming gamma-ray telescopes
Exploring the Impact of Co-teaching on High School Math Achievement for Students with Disabilities
Full text linkThis Dissertation in Practice explores the implementation of a co-teaching model in Algebra 1 classrooms at Green High School, part of the Excellent School District. The study was conducted due to the persistent underperformance among students with disabilities (SWD) on the Algebra 1 End of Course test, which led to the school’s designation as an Additional Targeted Support and Improvement (ATSI) site by the South Carolina Department of Education. Developed using the principles of improvement science, the study utilized the Plan-Do-Study-Act (PDSA) cycle as a framework to guide and evaluate change.
The change idea centered on embedding co-teaching in two Algebra 1 classrooms during the spring semester of 2025, pairing general education and special education teachers with scheduled common planning and targeted professional development. Teachers received tiered support throughout the implementation phase, and consistent process measures such as classroom observations, collaborative planning, and feedback to assess fidelity to the intervention.
The intervention showed positive early signs of impact. Teacher confidence increased as a result of professional development designed to introduce the co-teacher model, common planning fostered stronger relationships and shared ownership of instruction, and student engagement improved in classrooms where teaching responsibilities were equally shared. Despite these gains, barriers such as limited planning time, content expertise disparities, and challenges balancing instructional voices were noted.
Findings reflect a successful first PDSA cycle and provide hope that further implementation and improvements could result better gains for SWD, even across content areas. The collaboratively developed theory of improvement largely held true in practice, particularly the role of professional learning and co-planning as key drivers of change. The results align with existing research emphasizing the complexity of high school co-teaching (Friend et al., 2010) and highlight the importance of relational dynamics in instructional partnerships.
Although the scope was limited to two classrooms over one semester, the study provides actionable insights for implementing the model across additional schools and even the entire district in the future. Recommendations include extending co-teaching support to additional content areas, building coaching capacity, and reinforcing teacher preparation through hands-on instructional modeling. This work contributes to broader conversations about inclusive instruction, teacher collaboration, and the practical application of improvement science to address equity gaps in secondary education
Teacher Efficacy in Reading Intervention: The Role of Coaching and Professional Development in Foundational Literacy
Full text linkThis Dissertation in Practice utilized improvement science methods to increase teacher self-efficacy in foundational reading practices and to address the oral reading fluency (ORF) challenges of elementary students who consistently score below proficiency. Rooted in Bandura’s theory of self-efficacy and the Active View of Reading, the study aimed to build teacher confidence in delivering foundational reading instruction while improving student ORF rates. A Plan-Do-Study-Act (PDSA) cycle was implemented with second-grade teachers and targeted the following aim: increase ORF by 12 words correct per minute (wcpm) for students receiving Tier 3 intervention over an eight-week cycle. Coaching, using the student-centered coaching model, supported teachers in analyzing student data and planning for skilled phonics instruction. Structured professional development through LETRS, phonics instruction using UFLI, and embedded coaching facilitated the implementation of Science of Reading-aligned instructional practices. Data collection included teacher efficacy rating scales, qualitative teacher interviews, and student progress monitoring scores. Findings indicated minimal gains in ORF, but a notable increase in teacher confidence in phonics instruction. These results highlight the potential of ongoing, structured coaching to support the effective implementation of professional development. The findings also underscored the importance of continuous, focused coaching to promote equitable literacy outcomes and build capacity for sustainable instructional improvement
Structural Design Using Conditional-Gan Fused With Property Text Information: A Case for Masonry Structures
Full text linkStructural design, by nature, is a complex process that requires a considerable amount of time, expertise, and knowledge. In such a process, the structural designer must navigate various codal provisions to crystallize a proper and adequate design. As the role of automation continues to shape the domain of structural engineering over the past few decades, a new front leverages artificial intelligence (AI). Currently, AI acts as a copilot, collaborating to advance workflow speed and accelerate the design process. Among all the different collaborations between humans and AI, GANs (Generative Adversarial Networks) are seen to complement human creativity by automating specific facets of the design process. GANs can assist in creating structural designs and exploring the possibilities of different design scenarios. More specifically, conditional GANs usually neglect important parameters such as material properties and allow structural designs to be aligned with the engineer’s notion without compromising the design standards. To fully understand the advantages of using such copilots, it is necessary to identify, generate, and validate the accuracy of the models. As a result, this thesis aims to help examine the feasibility of having generative models, verify and assess this model\u27s performance, and deploy a companion software for structural drawing generation from architectural drawings
Decoding the Mobile App Playbook: How SDKs and Cross-Promotions Drive Market Performance
No full textThis dissertation investigates the strategic determinants of mobile app success within the evolving mobile platform ecosystem, focusing on app development choices and user acquisition strategies. Drawing on large-scale longitudinal data from the iOS platform, the research comprises two empirical studies contributing to the literature on digital platforms, modular design, and mobile advertising.
The first study examines how the integration of software development kits (SDKs)—a central mechanism of modular innovation—affects app market performance. The analysis identifies SDK popularity as a dual-edged strategic attribute. While popular SDKs can enhance app quality by enabling access to reliable, widely adopted functionalities, their widespread adoption also increases collective exposure to security vulnerabilities, adversely affecting app usage. Notably, the study introduces the concept of SDK data transparency, defined as the extent to which SDK providers disclose data collection, usage, and security practices, as a critical moderating factor. The findings show that high data transparency enables app developers to better assess and mitigate SDK-related risks, thereby buffering the negative effects of SDK popularity. This study advances platform-based modular design research by uncovering how third-party components\u27 interdependent technical and informational characteristics shape downstream innovation outcomes.
The second study investigates the effectiveness of cross-app promotion as a user acquisition strategy, focusing particularly on the role of cross-app dynamics in shaping promotional outcomes. It theorizes and tests how the market performance of the cross-app (i.e., the app hosting an advertisement) and the degree of user overlap between the focal and cross-apps jointly affect advertising success (app downloads). Using data from the top 1,000 iOS game apps, the study finds that advertising in outperforming cross-apps tends to reduce focal app downloads due to lower receptivity among highly engaged users. However, this negative effect is attenuated when user overlap is high, suggesting shared usage patterns foster receptiveness. Conversely, advertising in underperforming cross-apps proves more effective when user overlap is low, indicating that less engaged and demographically distinct users are more open to exploring new apps. This study contributes to the literature on mobile advertising and digital marketing by demonstrating the contingent effects of cross-app dynamics on promotional outcomes.
Together, these studies offer novel theoretical and empirical insights into the strategic tradeoffs app developers face within mobile app platform ecosystems. By integrating perspectives from platform governance, modularity, and digital marketing, the dissertation provides a coherent and evidence-based framework for understanding how SDK characteristics and cross-app dynamics jointly influence app success. The findings have implications for scholars of digital innovation as well as practitioners seeking to optimize product design and user acquisition in highly competitive app platform markets
Are They Ready? Impacting Kindergarten Readiness Through the Science of Reading
Full text linkThe purpose of this research study was to investigate how Science of Reading (SOR) professional development for preschool teachers, implemented through collaborative teaching and assessment cycles, influences the kindergarten readiness of preschool students.
Students from impoverished families start kindergarten at a considerable disadvantage regarding literacy. Literacy-focused curricula and professional development for teachers strongly affect reading outcomes. Multi-Tiered Systems of Support (MTSS) provides a systemic framework for data-based problem solving and decision-making. The MTSS framework aligns literacy interventions with tiered supports to ensure all students receive the assistance they need to achieve reading proficiency.
The South Carolina Child Early Reading Development and Education Program (CERDEP) funds full-day, four-year-old kindergarten for qualified at-risk children to support school readiness. Promise County School District’s kindergarten readiness rate for children served in CERDEP is 44%.
Guidelines require districts to have a comprehensive, systemic approach to reading that follows the State Reading Proficiency Plan. This research study identified inconsistencies and misalignment in emergent literacy evidence-based instruction and assessment in preschool classrooms.
In this study, preschool teachers were trained in evidence-based emergent literacy practices through LETRS EC professional development. Teachers applied oral language, phonological awareness, and print knowledge in collaborative teaching and assessing cycles to impact preschool language and literacy outcomes.
This study used a convergent, mixed method design through the Plan-Do-Study-Act inquiry cycle of improvement science. Qualitative and quantitative data regarding SOR training and teacher performance were reviewed. Quantitative data regarding student performance was explained. Findings included gains in teacher knowledge of early literacy and student gains in early literacy skills. Improvement science foundational principles provide a framework to define the problem, understand the system, identify changes, and test changes to determine if an improvement is achieved. Changes become impactful when knowledge is transferred and scaled to different systems and settings. This study informed the efforts to increase foundational literacy skills by improving kindergarten readiness of impoverished students
Breeding Biofortified Protein Rich Organic Pulses For Better Human Health
No full textPulse crops are dry grains of legumes, the second most consumed plant crops in the world after cereals. These crops are one of the primary sources of plant-based protein and contain high concentrations of pre-biotic carbohydrates, minerals and vitamins. Recognizing the health benefits of pulses intake, their demands as sustainable food and changes in people’s diet preferences for plant-based protein have increased awareness for pulses consumption. With this scenario, improving the nutritional profile of pulse crops for rich nutrition has been an opportunity for breeders to explore and tailor the available germplasm to develop nutrient dense pulses. Furthermore, the genomic resources developed for pulse crops in recent decades would be crucial tools to define the genetics of quality traits to narrow the knowledge gap for central genes contributing towards seed nutrition. To bridge the gap for genes leading to nutritional phenotypes, the present research includes nutritional evaluation of Lentil (Lens culinaris Medik.) and chickpea (Cicer arietinum L.) which are two major pulse crops consumed globally. The study performs nutritional profiling of germplasm phenotypically and genotypically for protein quality traits (protein concentration, Sulphur containing amino acids-SAAs concentration and percent protein digestibility-PDg) in lentil and for fatty acids composition (Palmitic acid-PA, linoleic acid-LA, alpha linoleic acid-ALA and oleic acid-OA) and minerals composition (Calcium-Ca, copper-Cu, iron-Fe, magnesium-Mg, manganese-Mn, phosphorus-P, potassium-K, selenium-Se and zinc-Zn) in chickpea. Another chickpea study compares the agronomic (Days to maturity-DTM, canopy height-CP and 100-seed weight-HSW) and nutritional traits (Total starch-TS, total fats-TFA, total protein-TP and PDg) in commercial chickpea cultivars grown in conventional and organic cropping systems. Phenotyping indicates the wide range for these nutritional traits while genome wide association studies aid to identify several significant single nucleotide polymorphisms (SNPs) markers and candidate genes associated with these traits. Cultivar comparisons in chickpea for nutritional traits in organic vs. conventional cropping system illustrate the impacts on nutritional quality in each system. This research, thus, emphasizes the key role of nutritional studies in achieving the breeding goals for consumer and market dependent objectives with improved or new germplasm and development of genomic sources for scientific communities for future
Development and Characterization of Pearl Millet Starch Films Reinforced With Lignocellulose Nanofiber for Sustainable Packaging Application
No full textTraditional polymers used for food packaging have raised concerns about their negative impact on the ecological system. In order to meet environmental and health requirements, this has sparked extensive study into the development of biodegradable packaging films. The use of starch-based films in place of petroleum-derived polymers is one of the viable options. Significant characteristics of starch include biodegradability, availability, and suitability for polymer blending or modification. However, because of shortcomings including poor mechanical properties and insufficient water resistance, its use in food packaging is limited, requiring more innovation to increase its profitability in this field. To overcome these challenges, in this study, pearl millet starch is reinforced with lignocellulose nanofibers (LCNFs) to improve its mechanical and water barrier properties.
LCNFs with a diameter ranging between 3-6 nm were isolated from peach pits by a combination of chemical and mechanical treatment, and the effect of lignin concentration (28, 18, 7, and 5%) on the characteristics of LCNFs was investigated. Among all LCNFs with 5% (LCNFs-16) and 7% (LCNFs-8), lignin showed the best thermal resistance and crystallinity, and therefore was used to reinforce the starch matrix.
Varying concentrations (25%, 50% and 75%) of LCNFs-16 and LCNFs-8 were incorporated into the starch (3%) matrix, and glycerol (30%) was used as a plasticizer to develop films named L-16 and L-8, respectively, via the solvent casting method. In terms of appearance, the control and LCNFs-reinforced films showed no noticeable visual difference. All the films had a thickness of around 0.1 mm, were transparent, and displayed no apparent defects like bubbles or cracks. Among all the films, L-8 films with 50% of LCNFs-8 concentration (L8-50) showed the best mechanical property, with around 628% and 1263% increase in tensile strength and Young’s modulus, respectively, compared to the control starch films. There was a 21% increase in crystallinity and a slight improvement in water barrier property (around 8%) of L8-50 film. Interestingly, LCNFs-reinforced film samples could be printed using an inkjet printer without ink spread or significant color variation.
Further, anthocyanin (BA) was extracted from blueberries using acidified ethanol. Anthocyanins have the property to change color, which is associated with their various chemical structures and varies depending on the pH level, due to their ionic nature. The buffer solution with BA ranged in color from reddish/pink to purple and then to yellow-green, during a change in pH from acidic to alkaline. Then, BA (10%, 25% and 50% of starch weight) was incorporated into starch/LCNFs film matrix (L8-50) to develop pH-sensitive film via the solvent casting. The uniform dispersion of BA through physical interactions within the matrix was confirmed by structural analysis of the starch/LCNFs/BA films using scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). The color shift of films in the buffer solutions from reddish-pink to greenish-yellow demonstrated that films are sensitive to pH over a wide pH range of 2 to 13. Among all the films, colorimetric analysis of starch/LCNFs/BA films with 50% BA (starch/LCNFs/BA50) showed the highest ∆E (color difference) values across the pH range of 2 to 13, and therefore, these films were considered for intelligent packaging of chicken to monitor its freshness and quality during storage at 4 °C and 23 °C. The starch/LCNFs/BA50 films exhibited potent antioxidant activity, with a DPPH radical scavenging rate of 53%. On the 10th day of storage (at 4 °C), the pH and TBARS value of chicken were recorded as 6.93 and 1.43 mg/MDA, which indicated the spoilage. Along with the spoilage of chicken, starch/LCNFs/BA50 film showed a prominent change in color from red to grayish purple. Thus, the findings of this study suggest that the developed pH-sensitive films have the potential to be used as effective indicators for monitoring freshness and also offer antioxidant protection, supporting their potential use in smart and active food packaging systems