An Assessment of Professional Development for Astronomy and Physics Faculty: Expanding Our Vision of How to Support Faculty's Learning About Teaching

In this thesis, we will explore approaches to faculty instructional change in astronomy and physics. We primarily focus on professional development (PD) workshops, which are a central mechanism used within our community to help faculty improve their teaching. Although workshops serve a critical role for promoting more equitable instruction, we rarely assess them through careful consideration of how they engage faculty. To encourage a shift towards more reflective, research-informed PD, we developed the Real-Time Professional Development Observation Tool (R-PDOT), to document the form and focus of faculty's engagement during workshops. We then analyze video-recordings of faculty's interactions during the Physics and Astronomy New Faculty Workshop, focusing on instances where faculty might engage in pedagogical sense-making. Finally, we consider insights gained from our own local, team-based effort to improve a course sequence for astronomy majors. We conclude with recommendations for PD leaders and researchers.

COLLEGE STUDENTS’ ATTITUDES TOWARD SEEKING PROFESSIONAL HELP: THE ROLE OF SOCIAL CLASS, CLASSISM, AND STIGMA

Research on attitudes toward seeking professional help among college students has examined the influence of social class and stigma. This study tested 4 theoretically and empirically derived structural equation models of college students’ attitudes toward seeking counseling with a sample of 2230 incoming university students. The models represented competing hypotheses regarding the manners in which objective social class, subjective social class, classism, public stigma, stigma by close others, and self-stigma related to attitudes toward seeking professional help. Findings supported the social class direct and indirect effects model, as well as the notion that classism and stigma domains could explain the indirect relationships between social class and attitudes. Study limitations, future directions for research, and implications for counseling are discussed.

Applying Mathematical Models to Study the Role of the Immune System in Chronic Myelogenous Leukemia

Although tyrosine kinase inhibitors (TKIs) such as imatinib have transformed chronic myelogenous leukemia (CML) into a chronic condition, these therapies are not curative in the majority of cases. Most patients must continue TKI therapy indefinitely, a requirement that is both expensive and that compromises a patient's quality of life. While TKIs are known to reduce leukemic cells' proliferative capacity and to induce apoptosis, their effects on leukemic stem cells, the immune system, and the microenvironment are not fully understood. A more complete understanding of their global therapeutic effects would help us to identify any limitations of TKI monotherapy and to address these issues through novel combination therapies. Mathematical models are a complementary tool to experimental and clinical data that can provide valuable insights into the underlying mechanisms of TKI therapy. Previous modeling efforts have focused on CML patients who show biphasic and triphasic exponential declines in BCR-ABL ratio during therapy. However, our patient data indicates that many patients treated with TKIs show fluctuations in BCR-ABL ratio yet are able to achieve durable remissions. To investigate these fluctuations, we construct a mathematical model that integrates CML with a patient's autologous immune response to the disease. In our model, we define an immune window, which is an intermediate range of leukemic concentrations that lead to an effective immune response against CML. While small leukemic concentrations provide insufficient stimulus, large leukemic concentrations actively suppress a patient's immune system, thus limiting it's ability to respond. Our patient data and modeling results suggest that at diagnosis, a patient's high leukemic concentration is able to suppress their immune system. TKI therapy drives the leukemic population into the immune window, allowing the patient's immune cells to expand and eventually mount an efficient response against the residual CML. This response drives the leukemic population below the immune window, causing the immune population to contract and allowing the leukemia to partially recover. The leukemia eventually reenters the immune window, thus stimulating a sequence of weaker immune responses as the two populations approach equilibrium. We hypothesize that a patient's autologous immune response to CML may explain the fluctuations in BCR-ABL ratio that are regularly seen during TKI therapy. These fluctuations may serve as a signature of a patient's individual immune response to CML. By applying our modeling framework to patient data, we are able to construct an immune profile that can then be used to propose patient-specific combination therapies aimed at further reducing a patient's leukemic burden. Our characterization of a patient's anti-leukemia immune response may be especially valuable in the study of drug resistance, treatment cessation, and combination therapy.

Bacterial communities of the specialty crop phyllosphere: response to biological soil amendment use, rainfall, and insect visitation

Microorganisms in the plant rhizosphere, the zone under the influence of roots, and phyllosphere, the aboveground plant habitat, exert a strong influence on plant growth, health, and protection. Tomatoes and cucumbers are important players in produce safety, and the microbial life on their surfaces may contribute to their fitness as hosts for foodborne pathogens such as Salmonella enterica and Listeria monocytogenes. External factors such as agricultural inputs and environmental conditions likely also play a major role. However, the relative contributions of the various factors at play concerning the plant surface microbiome remain obscure, although this knowledge could be applied to crop protection from plant and human pathogens. Recent advances in genomic technology have made investigations into the diversity and structure of microbial communities possible in many systems and at multiple scales. Using Illumina sequencing to profile particular regions of the 16S rRNA gene, this study investigates the influences of climate and crop management practices on the field-grown tomato and cucumber microbiome. The first research chapter (Chapter 3) involved application of 4 different soil amendments to a tomato field and profiling of harvest-time phyllosphere and rhizosphere microbial communities. Factors such as water activity, soil texture, and field location influenced microbial community structure more than soil amendment use, indicating that field conditions may exert more influence on the tomato microbiome than certain agricultural inputs. In Chapter 4, the impact of rain on tomato and cucumber-associated microbial community structures was evaluated. Shifts in bacterial community composition and structure were recorded immediately following rain events, an effect which was partially reversed after 4 days and was strongest on cucumber fruit surfaces. Chapter 5 focused on the contribution of insect visitors to the tomato microbiota, finding that insects introduced diverse bacterial taxa to the blossom and green tomato fruit microbiome. This study advances our understanding of the factors that influence the microbiomes of tomato and cucumber. Farms are complex environments, and untangling the interactions between farming practices, the environment, and microbial diversity will help us develop a comprehensive understanding of how microbial life, including foodborne pathogens, may be influenced by agricultural conditions.