Talks & Presentations
Invited Presentations
Xiao, X., & Cheng, Y. (2027, February). What do I know about AI beyond everyday knowledge? Unveiling misconceptions using item response theory analyses and cognitive interviews. Invited journal paper presentation, ACM SIGCSE Technical Symposium, Sacramento, CA.
Xiao, X. (2025, September 9). When growth mixture models break: Identifiability failures and misleading model evaluation. BEAR Seminar, UC Berkeley, Berkeley, CA. · Blog post · Event details
National Council on Measurement in Education (NCME)
Xiao, X., Patz, R., & Wilson, M. (2025). Integration of machine learning and human rater scores using the many-facet Rasch model. Denver, CO.
Xiao, X., Gochyyev, P., & Wilson, M. (2025). Comparing the difficulty of selected-response and constructed-response items. Denver, CO.
Xiao, X., Razavi, P., & Powers, S. (2024). Bridging bilingual gaps: An in-depth exploration of ChatGPT's transadaptation capabilities. Philadelphia, PA.
Xiao, X., Patz, R., & Wilson, M. (2024). Designing scoring reliability and instructional support into classroom-based math assessments. Philadelphia, PA.
Xiao, X. (2023). Bayesian comparison of growth mixture models. Chicago, IL.
Xiao, X. (2022). Bayesian growth mixture models for classifying and measuring individual trajectories. San Diego, CA.
American Educational Research Association (AERA)
Xiao, X., Rabe-Hesketh, S., & Cheng, Y. (2023). Bayesian comparison of growth mixture models: To better pursue truth. Chicago, IL.
International Meeting of the Psychometric Society (IMPS)
Xiao, X., & Rabe-Hesketh, S. (2025). When model evaluation fails in growth mixture models: Diagnostic and comparative perspective. Minneapolis, MN.
Xiao, X., & Rabe-Hesketh, S. (2023). Bayesian model evaluation and local identifiability for growth mixture models. College Park, MD.
Xiao, X., Ji, F., & Ernst, A. (2023). Sample heterogeneity in dynamic psychological processes. College Park, MD.
Other Conferences
Xiao, X., Rabe-Hesketh, S., & Skrondal, A. (2024). Bayesian approaches to identifiability and estimation of growth mixture models. Royal Statistical Society International Conference, Brighton, UK.
Xiao, X., Rabe-Hesketh, S., & Skrondal, A. (2024). Bayesian identification, estimation, and diagnostic techniques for growth mixture models using Stan. StanCon, Oxford, UK.
Xiao, X. (2023). Bayesian model evaluation using marginal likelihood for growth mixture models. Modern Modeling Methods (M3) Conference, Storrs, CT.
Xiao, X., Li, Y., & Park, Y. (2022). Automating book-to-curriculum mapping using representation learning. Association for Education Finance & Policy, Denver, CO.
Earlier presentations: SRCoS 2019; NEERO 2019; URS 2018.