My research agenda is grounded in quantitative methods, focusing on how institutional structures shape educational outcomes over time. I employ multilevel modeling, longitudinal and survival analysis, and large-scale administrative datasets to examine how policy decisions, resource allocation, and organizational constraints influence behavior within education systems, with particular attention to timing, heterogeneity, and institutional context.
As a Research Assistant in Temple University’s General Education Program, I analyzed population-level administrative data to model trends in class size, grading practices, course sequencing, and student outcomes. Using cross-classified multilevel models that accounted for student-, instructor-, and course-level variation, I produced analytic reports used in institutional decision-making and accreditation review. This work strengthened my ability to translate complex statistical findings into policy-relevant insights for non-technical audiences while maintaining methodological rigor.
A defining feature of my scholarship is its emphasis on policy implementation and institutional design. I am interested not only in whether policies “work,” but in how they are enacted, constrained, and reshaped by organizational structures and professional behavior. Across research and teaching, including graduate-level courses in policy analysis, statistics, and law, my work bridges empirical analysis, governance, and practice.
I have co-authored a study examining the relationship between class size and student achievement in Temple University’s General Education Program, using a quasi-experimental multilevel model that encompasses more than 170,000 course grades across 14 academic terms. The analysis demonstrated that class size effects vary by discipline, student characteristics, and instructor experience, with implications for program evaluation and resource allocation. Complementing this work, I contributed to an experimental study examining how institutional training interventions shape teachers’ behavior in the early identification of student mental and behavioral health risks. Using structural equation modeling, the study showed that targeted training improved the defensibility and utility of screening data, strengthening links between identification practices and student outcomes.
My scholarship centers on school finance and labor markets in K–12 education, with particular attention to workforce trends, district budgets, and the translation of economic theory into policy and practice. My doctoral dissertation examined how compensation levels and district-level spending patterns influence teacher retention across Pennsylvania using population-level administrative data. Using Cox proportional hazards survival models, I estimated how salary and auxiliary spending affected the risk of turnover over time. Rather than treating compensation effects as uniform, the analysis disaggregated turnover dynamics by region, experience level, Title I status, and high-need subject area, framing teacher mobility as an institutional and policy-mediated phenomenon rather than a purely individual labor-market choice. In parallel with this research, I have engaged in public scholarship and conference presentations on workforce planning, budgetary policy, and institutional governance.
In recent years, my professional roles, including service as Executive Director of a statewide labor organization and as Director of Human Resources in two public school districts, have provided a complementary venue for translating this research agenda into actionable policy and practice through compensation design, collective bargaining strategy, workforce stabilization, and long-term personnel budgeting under constrained fiscal environments.