Area of Expertise:
Statistics and measurement in education and psychology, focusing on developing new statistical models to quantify test-takers’ behaviors and characteristics in technology-enhanced digital assessments (TEDA).
Research Intrests:
- Test security research
- Multimodal process data modeling (e.g., response time, and eye-tracking indicators)
- Educational data mining and machine learning
- Bayesian estimation and inference
- Latent variable modeling.
His research focuses on developing innovative psychometric models and procedures to address learning and testing challenges in technology-enhanced systems, with an emphasis on detecting cheating behaviors using process data (e.g., response times, eye-tracking indicators, keystrokes).
Subject Areas: Educational Measurement/Quantitative Studies
