Project Activities
More specifically, the researchers will synthesize latent growth curve modeling, Bayesian model averaging (BMA), and probabilistic scoring rules into a comprehensive modeling framework for forecasting international trends in education outcomes over time. The researchers will concentrate on gender gaps in literacy and numeracy, with a particular focus on forecasting the impact of COVID-19 on these trends.
People and institutions involved
IES program contact(s)
Products and publications
Products: The main product of the grant is a Shiny app (ShinyBPF) that will enable applied researchers to use the combined modeling framework for different forecasts using large-scale assessment data. The research team will provide extensive tutorials on the use of the software. They also plan to conduct workshops on the use of the Shiny app, present technical and applied findings at conferences, and publish technical and applied findings in peer-reviewed journals.
Supplemental information
Co-Principal Investigator: Jude, Nina
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.