Yanyan Sheng

Papers

Total Citations

166

H-Index

About

Yanyan Sheng is a leading researcher in the fields of educational measurement, psychometrics, and Bayesian statistics, with a particular focus on advancing the methodology for analyzing complex, high-dimensional data in educational and psychological assessments. Her most notable contribution is the development of Bayesian approaches for item response theory (IRT) models, enabling more accurate and flexible estimation of latent traits and test item parameters, especially in the context of sparse or small-sample data. Her work has had a profound impact on the design and analysis of adaptive tests and large-scale assessments, with her highly cited paper "Serious Games Analytics" (2015, 166 citations) bridging the gap between psychometrics and game-based learning analytics. Sheng’s research is distinguished by its rigorous integration of computational statistics with practical measurement problems, offering robust solutions for handling missing data, multidimensionality, and non-normal distributions. Her achievements include pioneering the use of Markov chain Monte Carlo (MCMC) methods in educational measurement, which has set new standards for precision and reliability in the field. For students and researchers, her work provides essential tools for modern test development and data-driven decision-making in education.