UCLA Doctoral Student Jinwen Luo Wins Prestigious ETS Harold Gulliksen Psychometric Research Fellowship

UCLA Ed&IS doctoral student Jinwen (Jevan) Luo, has been selected as the 2023 winner of the ETS Harold Gulliksen Psychometric Research Fellowship. The prestigious award provides funding for promising graduate students in psychometrics or a related field, and is given each year in support of an outstanding dissertation project in the field of measurement and psychometrics.  The ETS Harold Gullikson Fellowship provides a $25,000 stipend, $8,000 fees/tuition, and a small research grant, in addition to an internship opportunity over the 2023 summer.  Recipients of the award are selected based on the strength their superior academic credentials as well as exceptional promise in the field of measurement, psychometrics or statistics, and the suitability and technical strength of the proposed research.

“ETS is a leading research institution for pioneering and funding groundbreaking psychometrics research and  as a recipient of the ETS Harold Gulliksen Psychometric Research Fellowship, I am excited to collaborate with ETS researchers to unlock the full potential of my dissertation study,” Luo said.  “Working with ETS will provide invaluable opportunities to access diverse data and explore innovative item formats, as well as gain insights into cutting-edge psychometric research. With this fellowship, I can further advance my research and career in measurement and psychometrics and contribute to improving the fairness and accuracy of educational assessments.

Luo is a Ph.D. student studying psychometrics and quantitative methods in the Social Research Methodology Division at the UCLA School of Education and Information Studies.  Before UCLA, Jinwen received a B.S. in economics and an M.S. in the economics of education, both from Huazhong University of Science and Technology (HUST) in China. Jinwen Luo's research interests revolve around investigating how humans learn and develop abilities and skills in social and educational contexts, with a focus on developing fair and effective methods to improve the assessment and measurement of learning. His work in this area has led him to specialize in quantitative methods, including social network analysis, multilevel models, Bayesian modeling, and causal inference methods and their applications for educational contexts. 

Luo will conduct his proposed dissertation research under the mentorship of his academic advisor, Minjeong Jeon, Professor of Advanced Quantitative Methods in the School of Education and Information Studies at UCLA, and in consultation with ETS mentors over the course of the funding.