MacDonald, Abbi

Abbi MacDonald is an Educational Specialist student in the area of School Psychology within the Department of Educational Psychology. She completed her BS in Psychology at Central Michigan University. During her time there, she was an undergraduate research assistant in both the Family Studies department examining culturally responsive early childhood education, and in the Behavior Analysis lab examining choice behavior and extinction burst phenomenon in rats. While in Michigan, Abbigail also worked as an assistant preschool teacher. Her academic interests include social-emotional and behavioral health for middle school students.

Meng, Lionel

Lionel Meng is a doctoral student in the Quantitative Methods area within the Educational
Psychology department studying with Dr. Daniel Bolt. His research interests are related to theory and application of psychometric modeling, particularly in relation to International Large-Scale Assessments.

Zhang, Jingru

Jingru Zhang is a doctoral student in the Quantitative Methods area within the Department of Educational Psychology. She is currently working with Dr. Jee-Seon Kim and Dr. Pustejovsky. Her research interests lie in the development of statistical methods that probe into questions in educational research, which serves better evaluation of educational programs and further informs policies and practice. Jingru is currently working as a project assistant at the UW Testing & Evaluation Center in Madison.

Feagins, Victor

Victor Feagins is a doctoral student in the Quantitative Methods area within the Department of Educational Psychology and studying with Dr(s). Jee-Seon Kim and James Pustejovsky. His research interests include Experimental Design, Causal Inference, and Dependent Data.

Buhrman, Graham

Graham Buhrman is a doctoral student in the Quantitative Methods area within the Department of Educational Psychology and studying with Dr(s). Jee-Seon Kim and James Pustejovsky. His research interests include causal inference, observational data, robust regression, and machine learning.