Ruiwei Cao is a scholar in educational measurement and quantitative research methods whose work focuses on improving the reliability, validity, and fairness of assessments. She has conducted research across multiple contexts, including language assessment, game-based learning analytics, and large-scale national testing.
At UCLA’s National Center for Research on Evaluation, Standards, and Student Testing (CRESST), Ruiwei examined how children’s gaming behaviors can serve as process-based indicators of problem-solving skills. She also worked at Beijing Normal University on large-scale assessment data, studying rater consistency and the equity of national scoring systems. In addition, Ruiwei contributed to diagnostic tool development at the Bilingualism, Mind, and Brain Lab at UC Irvine, validating linguistic assessments for bilingual children.
Her broader research interests include psychometric modeling, process-data-enhanced validity, and the use of AI and data science to design fairer and more interpretable assessment systems. Ruiwei earned her B.A. in Education and Social Transformation with a minor in Statistics from the University of California, Los Angeles.
Specializations and Interests
1. Educational Measurement and Psychometrics 2.Fairness and Validity in Assessment 3.Process Data and Learning Analytics 4. Item Response Theory and Model Development 5. AI-Enhanced and Game-Based Assessments
