About
Shenghai Dai
I am an Associate Professor of Educational Psychology and Methodology in the Department of Kinesiology and Educational Psychology at Washington State University. My research focuses on educational measurement, psychometrics, quantitative methodology, large-scale assessment and surveys, and machine learning. I develop and apply quantitative methods to address complex research problems in education, psychology, and the social sciences.
My work brings together established statistical and psychometric approaches with emerging computational methods, including machine learning. I am particularly interested in how methodological advances can improve the analysis and interpretation of large-scale, longitudinal, and complex data.
Academic Position
I joined Washington State University in 2017 as an Assistant Professor of Educational Psychology and Methodology and was promoted to Associate Professor in 2023. I am also the Director of the Large-Scale Data Laboratory, a position I have held since 2019.
The Large-Scale Data Laboratory supports methodological research and training involving measurement, large-scale data, and advanced quantitative methods. The laboratory provides a research environment for faculty and students working with complex educational and social-science data.
Research Identity
My research is grounded in measurement and quantitative methodology, with an increasing emphasis on computational and machine learning approaches.
My current research spans:
- Educational measurement and psychometrics
- Large-scale assessment and survey data
- Machine learning applications in education and psychology
- Longitudinal and complex data analysis
- Missing data and psychometric harmonization
- Advanced quantitative methodology
A recurring goal across these areas is to develop methods that are both statistically rigorous and useful for substantive research. My work combines methodological development with applications to large-scale educational assessments, longitudinal studies, digital assessment data, and research in health and human development.
Education
I received my Ph.D. in Qualitative and Quantitative Research Methodology from Indiana University Bloomington in 2017, with a focus on Psychometrics and Quantitative Methodology. I also received an M.S. in Applied Statistics from Indiana University Bloomington in 2016.
My earlier training includes an M.A. in Language Testing and a B.A. in Teaching Chinese as a Second Language from Beijing Language and Culture University.
This interdisciplinary training has shaped my approach to research, combining measurement theory, statistical methodology, substantive research, and computational methods.
Research Leadership and Collaboration
I collaborate with researchers across education, psychology, health, and related fields. My research experience includes work with large-scale educational assessments, longitudinal studies, clinical and health-related data, and complex survey data.
I have served as principal investigator, co-principal investigator, statistician, and methodological collaborator on externally and internally funded projects. My current and recent work includes projects involving NAEP and other large-scale assessments, machine learning, longitudinal data, digital assessment, and health-related research.
I also contribute to the methodological research community through editorial and professional service. My service includes roles with journals in educational measurement, psychology, and research methodology, as well as leadership positions in professional organizations including the American Educational Research Association and the National Council on Measurement in Education.
Research Software
An important part of my methodological work is the development of research software. I develop R packages that make quantitative and psychometric methods more accessible and reproducible for researchers.
My software work includes tools for:
- Subscore computation
- Missing item response imputation
- Differential item functioning detection
- Diagnostic test statistics
Teaching and Mentoring
I teach graduate courses in educational measurement, psychometrics, statistics, quantitative methods, data management, large-scale surveys, missing data, and machine learning. My teaching connects methodological foundations with real research problems and emphasizes hands-on analysis using authentic data.
I also mentor graduate and undergraduate students in research design, quantitative analysis, methodological development, conference presentations, publications, and research software.