Home

Welcome! I’m Xingyao (Doria) Xiao, Ph.D., a Postdoctoral Scholar at Stanford University Graduate School of Education. I currently work with the LEVANTE Project under the mentorship of Ben Domingue, Mike Frank, and Nilam Ram.

My research bridges methodological innovation with practical assessment design and large-scale data analysis. I specialize in:

• Statistical Psychometrics: Implementing Multidimensional IRT (mIRT) and Many-Facet Rasch Models (MFRM).
• Bayesian Modeling: Developing Bayesian longitudinal and latent variable models, specifically Growth Mixture Modeling (GMM).
• AI-Integrated Measurement: Evaluating machine learning-based scoring and the integration of large language models (LLMs) in educational assessment.

Methodology • Psychometrics • AI in Education

---

🚀 Research & Projects

• LEVANTE Project: Contributing to the design and validation of internationalized measures for learning and development in children aged 5–12.
• Hybrid Scoring Systems: Investigating how scoring design and rater bias (Human vs. ML) affect latent proficiency recovery.
• Mental Rotation Framework: Developing tools for cognitive assessment via the levante-framework.

---

📰 Recent Highlights

• New Publication (2026): “Revisiting reliability with human and machine learning raters under scoring design and rater configuration in the many-facet Rasch model” in British Journal of Mathematical and Statistical Psychology.
• New Publication (2026): “Gendered pathways to self-efficacy: moderating and mediating roles of family, school, and sibling contexts in early adolescence” in European Journal of Psychology of Education.
• In Press: “On the consistency of automatic scoring with large language models” in Educational and Psychological Measurement.
• Editorial Service: Serving as an Editorial Board Member for Measurement: Interdisciplinary Research and Perspectives.

---

Quick Links

📄 Download CV (2026) 🎓 Google Scholar 🔗 GitHub

Recent Posts