Shiyu Wang

Areas of Expertise

  • Latent Variable Modeling
  • Computerized Adaptive Testing
  • Cognitive Diagnosis Models
  • Educational Statistics


  • Multistage Adaptive Testing
  • Restrictive Latent Class Modeling
  • Process Data Analysis
  • Longitudinal Analysis
  • Dynamic Learning Models



  •  PhD in Statistics, 2016
    University of Illinois at Urbana-Champaign
  •  BS in Statistics, 2011
    Beijing Normal University


 706-542-3717 (office)

Research Summary

My research focuses on methodological innovations and advances in three areas: 1) developing innovative adaptive testing designs that can provide efficient individualized assessments and an examinee-friendly testing environment; 2) establishing statistical foundations for a family of restricted latent class models to provide guidelines for model estimation and selection; and 3) developing novel dynamic psychometric models that can measure and predict students’ learning outcomes based on various assessment data, including product data (i.e., students’ responses) and process data (i.e., response time, learning time, eye-tracking data.).

Check My NewGen Psychometrics and Data Science Lab ( for more information.

I am looking for self-motivated master and Ph.D. students to join my research group in Fall 2024.


Intelligent, Adaptive Program with Just-in-time Feedback for Preservice Teachers (NSF)
Revision and Review Behavior in Large-Scale Computer-Based Assessments: An analysis of NAEP Mathematics Process data (AERA-NSF)

Awards and Accolades

Norton Prize for Outstanding Doctoral Thesis in Statistics

University of Illinois at Urbana-Champaign, 2015

Early Career Faculty Research Award

University of Georgia, 2018

Early Career Researcher Award

International Association for Computerized Adaptive Testing, 2019

NAEd/Spencer Postdoctoral Fellow

National Academy of Education and Spencer Foundation, 2019

Jason Millman Promising Measurement Scholar Award

National Council on Measurement in Education (NCME), 2020