Dissertation Defense Announcements

Black women doctoral students in counselor education and supervision (CES) programs represent about 18% of enrolled students in CES programs accredited by the Council for Accreditation of Counseling and Related Educational Programs (CACREP). Previous data on Black women doctoral students at historically White institutions, including those enrolled in CACREP-accredited CES programs, demonstrate that Black women endure intersectional experiences such as felt exclusion, isolation, and differential treatment, all of which can threaten degree persistence. Black women doctoral students report that formal and informal mentorship positively influenced degree persistence; however, they often lean more heavily on informal mentorship due to deficits in programmatic formal mentorship. Black feminist thought (BFT) and relational-cultural theory (RCT) were utilized as the theoretical frameworks to best illuminate the intersectionality of Black women doctoral students in CES programs at historically White institutions (HWIs) and their experiences with mentorship and doctoral degree persistence. The voices and wisdom of sixteen total participants were analyzed across seven focus groups via interpretative phenomenological analysis. Six group experiential themes (GETs) emerged from the data: Black Women’s Intersectional Experience in CES, Formal Mentorship, Informal Mentorship, Black Faculty and Counselor Educators, External and Internal Persistence, and Critique of Programmatic Intentionality. Eighteen subthemes also emerged. The findings corroborate previous literature on Black women doctoral students at HWIs and further the need to better incorporate mentorship within CES programs for Black women doctoral students at HWIs. This research provides implications for counselor education and supervision doctoral program administrators and counselors who work clinically with Black women doctoral students enrolled in CES doctoral programs at HWIs.

Gamification and games-based learning (GBL) have gained increasing attention in higher education as strategies to enhance student engagement, motivation, and learning outcomes. Despite their documented benefits, faculty adoption of gamification in online teaching remains limited. This study examines the factors influencing faculty attitudes toward gamification and GBL in online courses at four-year public universities. Using a quantitative survey-based research design, the study explores the relationships between political climate (PC), anxiety (ANX), institutional gamification readiness (IGR), perceived usefulness of gamification (PUG), perceived ease of use (PEUG), attitudes toward gamification (ATG), subjective norms (SN), and intention to use gamification (IUG).

The study indicates that faculty autonomy and confidence are crucial in gamification adoption. PC and ANX significantly predict PUG, while IGR does not. However, IGR is a key determinant of PEUG, suggesting that structured faculty support reduces implementation barriers. The study also confirms that PEUG fully mediates the relationship between PUG and ATG, demonstrating that faculty are unlikely to develop positive ATG unless they also find it easy to implement. Furthermore, ATG is the strongest predictor of faculty intention to adopt gamification, while SN is not significant.

These results highlight that faculty adoption of gamification is driven more by individual attitudes and perceptions of usefulness than by institutional mandates or peer influence. The implications of these findings suggest that universities seeking to increase gamification adoption should focus on faculty-centered support strategies rather than relying solely on administrative encouragement. Structured professional development programs, instructional design consultations, and financial incentives may enhance faculty confidence and ease the adoption process.

Future research should explore disciplinary differences in gamification adoption, assess its long-term impact on faculty and student outcomes, and investigate how institutional incentives influence faculty engagement with gamified teaching strategies. This study contributes to the growing body of research on technology adoption in higher education, reinforcing the importance of faculty autonomy, structured support, and ease of implementation in the successful integration of gamification and GBL into online learning environments.

West Nile Virus (WNV) remains a persistent public health threat in North America, necessitating accurate forecasting models to guide disease surveillance and vector control. This dissertation integrates genomic, epidemiological, meteorological, ecological, and demographic data in an effort to better understand the drivers of WNV outbreaks with the ultimate goal of improving WNV predictions. First, a population genetics analysis of Culex tarsalis, a key WNV vector, identified four distinct locally adapted populations shaped by multiple climatic factors—particularly temperature, precipitation, wind patterns, and daylight length. Second, a national-scale machine learning model incorporating these and other climate variables along with land cover, avian diversity, and human demographics was developed to try and predict WNV case numbers across the continental U.S., but this model ultimately exhibited poor performance due to surveillance data imbalance, inconsistency, and poor temporal granularity. To address the temporal granularity issue, a high-resolution regional model for California was developed, leveraging finer-grained surveillance and environmental data. This model, integrating time-series autoregression and iterative updates, significantly outperformed the national model and showed that the same climate factors driving mosquito adaptation were the most consistent predictors on WNV outbreaks. These findings not only highlight the connection between vector species biology and the diseases they transmit, but also emphasize the need for standardized, higher-quality surveillance data. As climate and ecological shifts continue to influence vector species dynamics and disease spread, data-driven models will be essential for guiding proactive public health interventions.

This dissertation investigates the interactions between the gut microbiome and hematopoietic stem cell transplant (HCT), with the goal of helping us understand microbial diversity and their functional implications in HCT outcomes. The dissertation is composed with three main projects: 1) analysis of gut microbiota diversity in patients with Graft-versus-Host disease (GVHD), 2) examination of the effect of care given and infusion site on gut microbiome composition and antimicrobial resistance gene diversity, and 3) a focused evaluation of differential abundance analysis (DAA) methods for microbiome data, including DESeq2, edgeR, t-test, and Wilcoxon test.
To achieve these objectives, we have employed high-throughput sequencing techniques, different bioinformatics tools and statistical analysis. The main findings of these projects include observable differences in certain microbial species and calprotectin levels between GVHD statues; site specific variations in microbiome composition for HCT patients; and insights into the performance and suitability of different statistical methods for microbiome data DA analysis.
Our results highlight the importance of considering microbial diversity in HCT and provide insights in improving patient outcomes through microbiome analysis. Additionally, our findings emphasize the importance of carefully selecting the statistical methods in microbiome studies to ensure accurate interpretation of differential abundance analysis results. This dissertation aims to contribute to add knowledge on microbiome research and show potential directions for future studies.