UW-Madison’s David Kaplan recently received an $800,000 grant from the Institute for Education Sciences (IES) to develop and adapt the method of Bayesian dynamic borrowing to large-scale assessment programs, such as the National Assessment of Education Progress (NAEP) and the Program for International Student Assessment (PISA).
The co-PI on the project is Jianshen Chen, who earned her Ph.D. from the Department of Educational Psychology’s quantitative methods program area and is now an associate psychometrician at the College Board.
Kaplan is the Patricia Busk Professor of Quantitative Methods with the School of Education’s Department of Educational Psychology. He also holds affiliate appointments with UW-Madison’s Department of Population Health Sciences and the Center for Demography and Ecology. An elected member of the National Academy of Education, Kaplan has received various awards for his contributions to the field.
Kaplan’s work focuses on the development of Bayesian statistical methods for education research. The method of Bayesian dynamic borrowing provides a method for systematically incorporating prior historical data into current studies.
An attractive feature of this method is that it allows a researcher to account for the fact the not all historical data — even from the same assessment program — are of equal quality. Bayesian dynamic borrowing allows prior information to be systematically adjusted to reflect the analyst’s degree-of-confidence in the importance and/or quality of sources of prior data.