Research output per year
Research output per year
My primary research pertains to the use of latent variable modeling, machine learning, and other quantitative methods to solve practical problems in educational and psychological testing. Here are a few of my current research interests:
Latent variable modeling: missing data, response times, diagnostic classification, Bayesian estimation;
Longitudinal models for learning and interventions;
Analysis of complex data (e.g., log data) in computer-based testing and learning environments.
IES R324P210005 (co-PI): Analysis of NAEP Mathematics Process, Outcome, and Survey Data to Understand Test-Taking Behavior and Mathematics Performance of Learners with Disabilities
AERA NSF 112057 (PI): Revision and Review Behavior in Large-Scale Computer-Based Assessments: An Analysis of NAEP Mathematics Process Data
Alicia Cascallar Award (NCME, 2022)
Excellent Reviewer Award (JEBS, 2021)
UIUC List of Teachers Ranked as Excellent by Students (SP 2021, FA 2022)
Quantitative Psychology, Ph.D., University of Illinois Urbana-Champaign
Award Date: Aug 22 2018
Applied Mathematics, MS, University of Illinois Urbana-Champaign
Award Date: May 20 2017
Psychology, BA, Bryn Mawr College
Award Date: May 15 2014
Mathematics, BA, Haverford College
Award Date: May 15 2014
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review