Qiwei (Britt) He is a research scientist in the Research & Development division at ETS. Her research focus is situated in the field of educational and psychological measurement, with specific attention to methodology advancement in large-scale assessments such as Programme for International Student Assessment, Programme for the International Assessment of Adult Competencies, and National Assessment of Educational Progress and to complex new data sources such as process data and textual data. The innovative nature of her research has received high recognition, including the 2019 Jason Millman Promising Measurement Scholar National Council on Measurement in Education (NCME) Award, the 2017 Alicia Cascallar NCME Award for an Outstanding Paper by an Early Career Scholar, and acceptance into the Organisation for Economic Co-operation and Development Thomas J. Alexander Fellowship. She is leading a project funded by the National Science Foundation as one of the principal investigators to develop latent and graphical models for complex dependent data in education. She is also heavily involved in and leads many ETS projects related to process data and large-scale assessments.
She received a Ph.D. in psychometrics and data analysis at the University of Twente, Netherlands, in 2013. Her dissertation, Text Mining and IRT for Psychiatric and Psychological Assessment, showed that text mining, in combination with item response theory techniques, is a promising approach for handling textual data and item-based responses in one systematic framework for psychiatric and psychological assessments. This dissertation won the prestigious Dutch Abbas Dissertation Award for 2013 and Outstanding Dissertation Award in American Psychological Association Division 5 (Quantitative and Qualitative Research Methodologies).