Cross-National Generalizability of the Factors That Affect Science Achievement

• In Event: Poster Session for Quantitative Methods and Statistical Theory

Abstract

Policymakers and educational researchers have grown increasingly interested in the extent to which study results generalize across different populations of students. Current generalization research in education largely focused on the compositional similarity among students based on a set of observable characteristics. However, compositional similarity does not consider the role that models play in generalization. The purpose of this paper is to assess the extent to which there is alignment between compositional and model generalization; the latter refers to the generalizability of predictive statistical models across groups of students. In this study, we use observational data from the Programme for International Student Assessment (PISA) 2015 wave to examine the generalizability (both compositional and model) of the factors that affect science achievement.

Authors

• Wan Ren, University of Pennsylvania

• Wendy Chan, The University of Pennsylvania