Yinghan Chen, Assistant Professor in the Department of Mathematics and Statistics, was awarded a $229,951 National Science Foundation (NSF) grant for her research project "Bayesian Inference for Attribute Hierarchy in Cognitive Diagnosis Models." Chen’s research is at the forefront of psychometrics, a field that is revolutionizing techniques used in psychological diagnosis, educational testing, behavior genetics, neuroscience and other social sciences.
“The project will advance statistical methods for estimation and inference on attribute hierarchy within the framework of cognitive diagnosis models (CDM),” Chen said. “CDMs have been widely applied to the field of educational assessment, psychiatric diagnosis, and other social sciences, to determine the fine-grained classification of the latent attributes. Hierarchical structure of the underlying attributes or skills is important for designing effective diagnostic assessment and promoting adaptive learning.”
The project will develop a series of Bayesian approaches, an important technique used in statistics based on Bayes’ theorem, to estimate the hierarchy structure. Chen’s proposed methods will be useful for applied research in education and psychology, as well as other social science disciplines. Applied researchers in these areas can gain information from subject responses and develop new intervention strategy for better mastery of underlying skills.
The funding period began on September 1 and will continue through August 31, 2023. One graduate student will be supported during the two-year project period, publicly available software package will be developed for applications in real world, and Chen and her team will collaborate with researchers from University of Georgia on diagnosis of spatial reasoning skills.
More information about Chen’s grant can be viewed on the NSF website.
