Profile picture of Cengiz Zopluoglu

Cengiz Zopluoglu

Associate Professor
College of Education, Special Education
Phone: 541-346-3578
Office: HEDCO 359


Cengiz Zopluoglu is an Associate Professor in the Department of Special Education and Clinical Sciences at the University of Oregon. His research interests are centered around item response theory, psychometrics, latent variable modeling, and integrating machine learning methods into educational measurement. Dr. Zopluoglu has published and contributed numerous articles on psychometrics and statistical methods, and their applications in educational and behavioral sciences. Dr. Zopluoglu has taught advanced courses on psychometrics and statistical methodology including General Linear Models, Item Response Theory, Measurement and Psychometric Theory, Categorical Data Analysis, and Data Analysis with R in Educational and Behavioral Research. Dr. Zopluoglu holds a masters and doctorate degrees in Quantitative Methods in Education from the Department of Educational Psychology, University of Minnesota. Before joining the faculty at the University of Oregon, Dr. Zopluoglu served seven years as a faculty in the Research, Measurement, and Evaluation Program in the Department of Educational and Psychological Studies (EPS) at the University of Miami.


Ph.D., 2013, University of Minnesota, Twin Cities, MN
Major: Educational Psychology (Quantitative Methods in Education)

M.A., 2009, University of Minnesota, Twin Cities, MN
Major: Educational Psychology (Quantitative Methods in Education)

B.A., 2005, Abant Izzet Baysal University, Bolu, Turkey
Major: Mathematics Education (K-8)

Honors and Awards

2023 National Center for Education Statistics, Mathematics Automated Scoring Challenge for NAEP, Runner-up Prize

2023 Top Cited Article in Educational Measurement: Issues and Practice, among work published in an issue between Jan 1, 2021 and Dec 15, 2022

2021 National Institute of Justice, Recidivism Forecasting Challenge, 3rd place in Large Team Category

2017 Top 5 Most Cited Papers in Journal of School Psychology 2014-2016

2013 Graduate Student Research Award, University of Minnesota

2007 – 2013 Fellowship for Graduate Education in the U.S., Ministry of National Education, Turkey


* The following is a list of methodological publications in the past five years. Please see CV for the full list of publications.

Kasli, M., Zopluoglu, C., & Toton, S. (2023). A Deterministic Gated Lognormal Response Time Model to Identify Examinees with Item Preknowledge. Journal of Educational Measurement, 60(1), 148-169.

Wang J., Combs T., Zopluoglu C. (2022). Fitting hyperbolic cosine unfolding models using the Stan Language. Journal of Applied Measurement, 23(1/2), 61-73.

Zopluoglu, C., Kasli, M., & Toton, S. (2021). The Effect of Item Preknowledge on Response Time: Analysis of Two Datasets Using the Multiple-Group Lognormal Response Time Model with a Gating Mechanism. Educational Measurement: Issues and Practices, 40(3), 42-51.

Patel, Z.S., Jensen-Doss, A. & Zopluoglu, C (2021). Illustrating the Applicability of IRT to Implementation Science: Examining an Instrument of Therapist Attitudes. Administration and Policy in Mental Health Services Research, 48, 921-935.

Park, S.E., Ahn, S., & Zopluoglu, C. (2021). Differential item functioning effect size from the multigroup confirmatory factor analysis for a meta-analysis: A simulation study.Educational and Psychological Measurement,81(1), 182-199.

Zopluoglu, C. (2020). A Finite mixture item response theory model for continuous measurement outcomes. Educational and Psychological Measurement, 80(2), 346–364.

Zopluoglu, C. (2019). Computation of response similarity index M4 in R under the dichotomous and nominal item response models. International Journal of Assessment Tools in Education, 6 (5), 1-19.

Zopluoglu, C. (2019). Detecting examinees with item preknowledge in large-scale testing using Extreme Gradient Boosting (XGBoost). Educational and Psychological Measurement, 79(5), 931–961.

Sideridis, G.D., & Zopluoglu, C. (2018). Validation of response similarity analysis for the detection of academic cheating: An experimental study. Journal of Applied Measurement, 19(1), 59-75.