Scott Monroe

Scott Monroe is an Associate Professor at the University of Massachusetts Amherst in the Department of Educational Policy, Research & Administration (EPRA). His research focuses on latent variable modeling, item response theory (IRT), and structural equation modeling, with applied work in state testing and student growth evaluation. He holds a Ph.D. from UCLA's Graduate School of Education & Information Sciences and an M.S. in Statistics from UCLA.

• B.A., University of California San Diego, 2000
• M.S., Brooklyn College, 2007
• M.S., University of California Los Angeles, 2013
• J.D., University of California Los Angeles, 2004
• Ph.D., University of California Los Angeles, 2014

His research interests emphasize methodological advancements in IRT model evaluation, teacher evaluation frameworks, and statistical computing. He has contributed to global discussions on educational measurement, including work published in Multivariate Behavioral Research and Educational and Psychological Measurement.

Prior to academia, Monroe was a high school mathematics teacher in Brooklyn, New York, and Culver City, California. His recent projects include examining learning progressions in middle-school mathematics and evaluating educational interventions like the Green Dot Locke Transformation Project.

His work on IRT model fit evaluation and student growth modeling has been influential in shaping assessment practices. He has collaborated on CRESST reports addressing topics like MIRT-based student growth percentiles and diagnostic classification models.