Chia-Yi

Profile: Chia-Yi Chiu

Associate Professor
Faculty

Chia-Yi Chiu's research focuses on the development and improvement of quantitative methods and models in educational testing and measurement. She is particularly interested in establishing the theoretical foundations highly relevant to practical applications for developing new kinds of assessments and analyzing assessment data. Her ambition as a researcher is to provide instrumental and easy-to-access tools that can be used to carry out analyses effectively and efficiently for educational programs of all sizes.

 

Current Grant

2016-2021, PI, CAREER: Cognitive Diagnosis in E-Learning: A Nonparametric Approach for Computerized Adaptive Testing, NSF.

 

Education

Ph.D., Educational Psychology
University of Illinois at Urbana-Champaign
 
M.S., Statistics 
University of Illinois at Urbana-Champaign
 
M.A., Mathematics in Teaching
University of Northern Colorado
 
B.S., Mathematics
National Taiwan Normal University

Expertise & Research Interest

Nonparametric Cognitive Diagnosis
Latent Class Analysis
Multidimensional Models in Educational Measurement and Testing

Recent & Selected Publications

Chiu, C.-Y., & Köhn, H.-F. (accepted). Consistency theory for the general nonparametric classification Method. Psychometrika.

Chang, Y.-P., Chiu, C.-Y. & Tsai, R.-C. (in press). Nonparametric CAT for CD in educational settings with small samples. Applied Psychological Measurement.

Köhn, H.-F., & Chiu, C.-Y. (in press). Attribute hierarchy models in cognitive diagnosis: Identifiability of the latent attribute space and conditions for completeness of the Q-matrix. Journal of Classification.

Köhn, H.-F., & Chiu, C.-Y. (2018). How to build a complete Q-matrix for a cognitively diagnostic test, Journal of Classification, 35, 273-299.

Chiu, C.-Y., Sun, Y., & Bian, Y. (2018). Cognitive diagnosis for small educational programs: The general nonparametric classification method, Psychometrika, 83, 355-375.

de la Torre, J., & Chiu, C.-Y. (2017). On the consistency of Q-matrix estimation: A rejoinder. Psychometrika, 82, 528-529.

Köhn, H.-F., & Chiu, C.-Y. (2017). A procedure for assessing the completeness of the Q-matrices of cognitively diagnostic tests. Psychometrika, 82, 112-132. 

Chiu, C.-Y., Köhn, H.-F., Zheng, Y., & Henson, R. (2016). Joint maximum likelihood estimation for cognitive diagnostic models. Psychometrika, 81, 1069-1092.

Chiu, C.-Y., Köhn, H.-F., & Wu, H.-M. (2016). Fitting the Reduced RUM with Mplus: A Tutorial.  International Journal of Testing, 16, 331-351.

Köhn, H-F., & Chiu, C.-Y. (2016). A proof of the duality of the DINA model and the DINO model. Journal of Classification, 33, 171-184.

Chiu, C.-Y., & Köhn, H.-F. (2016). Consistency of cluster analysis for cognitive diagnosis: The Reduced Reparameterized Unified Model and the General Diagnostic Model. Psychometrika, 81, 585-610.

Chiu, C.-Y., & Köhn, H.-F. (2016). The Reduced RUM as a logit model: Parameterization and constraints. Psychometrika, 81, 350-370.

de la Torre, J., & Chiu, C.-Y. (2016). A general method of empirical Q-matrix validation. Psychometrika, 81, 253-273.

Chiu, C.-Y., & Köhn, H.-F. (2015). A general proof of consistency of heuristic classification for cognitive diagnosis models. British Journal of Mathematical and Statistical Psychology, 68, 387-409.

Chiu, C.-Y., Köhn, H.-F., Zheng, Y., & Henson, R. (2015). Exploring joint maximum likelihood estimation for cognitive diagnosis models. In L. A. van der Ark, D. M. Bolt, W. C. Wang, J. A. Douglas, S.-M. Chow (Eds.), Quantitative Psychology Research: The 79th Annual Meeting of the Psychometric Society (pp. 263-277). New York: Springer.

Chiu, C.-Y., & Köhn, H.-F. (2015). Consistency of cluster analysis for cognitive diagnosis: The DINO model and the DINA model revisited. Applied Psychological Measurement, 39, 465-479.

Köhn, H.-F., Chiu, C.-Y., & Brusco, M. (2015). Heuristic cognitive diagnosis when the Q-matrix is unknown. British Journal of Mathematical and Statistical Psychology, 68, 268-291.

Köhn, H., Chiu, C.-Y., & Brusco, M. J. (2013). The comparison of two input statistics for heuristic cognitive diagnosis. In R. E. Millsap, L. A. van der Ark, D. M. Bolt, C. M. Woods (Eds.), New Developments in Quantitative Psychology: Presentations from the 77th Annual Psychometric Society Meeting (pp. 335-344). New York: Springer.

Chiu, C.-Y. (2013). Statistical refinement of the Q-matrix in cognitive diagnosis. Applied Psychological Measurement, 37, 598-618.

Chiu, C.-Y., & Douglas, J. (2013). A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns. Journal of Classification, 30, 225-250.

Camilli, G., Jackson, D., Chiu, C.-Y., & Gallagher, A. (2011). The Mismatch Hypotheses in Law School Admissions. Widener Journal of Law, Economics & Race, 2.

Camilli, G., de la Torre, J., & Chiu, C.-Y. (2010). A Non-central t Regression Model for Meta-Analysis. Journal of Educational and Behavioral Statistics, 35, 125-153.

Chiu, C.-Y., & Seo, M. (2009). Cluster Analysis for Cognitive Diagnosis: An Application to the 2001 PIRLS Reading Assessment. IERI Monograph Series, 2, 137-159.

Chiu, C.-Y., Douglas, J., & Li, X. (2009). Cluster Analysis for Cognitive Diagnosis: Theory and Applications. Psychometrika, 74, 633--665.

Honors & Awards

Chancellor’s Scholar Award: Innovation in Research, 2018-2020, Rutgers University

Brenda H. Loyd Outstanding Dissertation Award, 2010, National Council on Measurement in Education (NCME)