Research Interests
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:
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Latent variable modeling: missing data, response times, diagnostic classification, Bayesian estimation;
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Longitudinal models for learning and interventions;
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Analysis of complex data (e.g., log data) in computer-based testing and learning environments.
Education
Quantitative Psychology, Ph.D., University of Illinois at Urbana-Champaign
Applied Mathematics, MS, University of Illinois at Urbana-Champaign
Psychology, BA, Bryn Mawr College
Mathematics, BA, Haverford College
Courses Taught
- Psyc 490 - Fall 2020
- Online workshop on Statistical Learning of Process Data (Video recording)
Additional Campus Affiliations
Assistant Professor, Statistics
External Links
Recent Publications
Chang, H-H., Wang, C., & Zhang, S. (Accepted/In press). Statistical Applications in Educational Measurement. Annual Review of Statistics and Its Application.
Wang, S., Zhang, S., & Shen, Y. (2020). A joint modeling framework of responses and response times to assess learning outcomes. Multivariate Behavioral Research, 55(1), 49-68. https://doi.org/10.1080/00273171.2019.1607238
Zhang, S., & Chang, H. H. (2020). A multilevel logistic hidden Markov model for learning under cognitive diagnosis. Behavior Research Methods, 52(1), 408-421. https://doi.org/10.3758/s13428-019-01238-w
International ASEBA Consortium, Rescorla, L. A., Jordan, P., Zhang, S., Baelen-King, G., Althoff, R. R., & Ivanova, M. Y. (Accepted/In press). Latent Class Analysis of the CBCL Dysregulation Profile for 6- to 16-Year-Olds in 29 Societies. Journal of Clinical Child and Adolescent Psychology. https://doi.org/10.1080/15374416.2019.1697929
Zhang, S., Douglas, J., Wang, S., & Andrew Culpepper, S. (2019). Reduced Reparameterized Unified Model Applied to Learning Spatial Rotation Skills. In M. von Davier, & Y-S. Lee (Eds.), Handbook of Diagnostic Classification Models: Models and Model Extensions, Applications, Software Packages (pp. 503-524). (Methodology of Educational Measurement and Assessment). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-05584-4_24