Graduate Student Association (GSA)

Lindsey Insco received her Bachelor's in chemistry from Xavier University in 2022 and her Master's in criminal justice from the University of Cincinnati in 2023. Lindsey is currently a doctoral student of criminal justice at the University of Cincinnati. Her research interests include life course criminology, drug overdoses, and, more generally, terrorism. 

Esnart is an international doctoral student in the college of education.  Her program concentration is  education community-based action research. Her research interests revolve around the intersection of early childhood education, emergency education, and the rights of girls.

Amota Ataneka Merang is a doctoral candidate in Quantitative Research Methodologies specializing in causal machine learning, latent variable modeling, and psychometrics. His research addresses a fundamental challenge in the social sciences: drawing valid causal conclusions when key variables we care about (e.g., depression, burnout, college aspiration, or social capital) cannot be directly observed and must instead be inferred from survey or test responses. These unobservable constructs, known as latent variables, appear as both outcomes and predictors across education, psychology, and the social sciences, yet existing methods for causal inference are largely either ignore the measurement error or have strong assumptions about model specification (e.g., all non-linear terms/n-way interactions are known and included). In practice, these assumptions are often violated or at least unsubstantiated because the true functional forms of relationships among variables are often complex and/or unknown. Machine learning or data-adaptive methods address model specification assumptions but they ignore latent variables measurement error. 
 
Amota's work bridges statistics, machine learning, and quantitative methodology to develop tools that properly account for this measurement uncertainty. His current research is developing new machine learning methods that address both measurement error and model misspecification. This enables causal inference with latent variables in nonexperimental and observational settings, even when the functional relationships among variables are unknown or complex.

His earlier work focused on the design and analysis of experimental and quasi-experimental studies, contributing design parameter estimates for power analysis in multilevel mediation models, cluster randomized trials, multisite cluster randomized trials, and partially nested designs. Substantively, his research spans teacher preparation and induction, mental health, and educational program evaluation.

Amota is writing a book chapter for the Oxford Handbook of Impact Evaluation, and he has published in peer-reviewed journals as a first author. Amota regularly presents his work at the American Educational Research Association (AERA), Modern Modeling Methods (M3), the American Evaluation Association (AEA), and Society for Research on Educational Effectiveness (SREE). 

Catherine is a doctoral student in the School of Criminal Justice at the University of Cincinnati. She holds a Bachelor's degree in Psychology (2016) and a Master’s in Applied Behavioral Science with a concentration in criminal justice (2020) from Wright State University. Her research interests lie in corrections specifically focusing on offender rehabilitation, prisoner reentry, in-prison programming, and specialty courts.

Tiffany is a highly motivated and experienced educator passionate about early childhood education. She is currently a doctoral student in Educational Studies at the University of Cincinnati, where she is concentrating in Curriculum Studies and Teacher Education. Tiffany holds undergraduate degrees in Early Childhood and Inclusive Early Childhood Education and a master's degree in Curriculum & Instruction with a focus on STEM Learning. Her research interests include mathematics and science education, STEM/STEAM learning, and play-based learning.