Unpacking the M in STEM: A Latent Class Analysis of STEM Graduates on High School Mathematics Attitudes

• In Event: 56.043 - Mining Large-Scale Data Sets for Different Purposes: National and International Examples

Abstract

The purpose of this study is to identify the extent to which there are significantly different subgroups of high school students who graduate with STEM college degrees using the nationally generalizable dataset Education Longitudinal Study of 2002 (ELS:2002). Prior studies have focused on demographic factors that influence the number of STEM pursuers. However, little is known about the variation of STEM college graduates’ performance in high school. Using Latent Class Analysis (LCA) of n=3,389 high school students, we identify four significantly different subgroups: Achieving, Striving, Capable and Ambivalent mathematics students. Contextual factors, such as gender and ethnicity, are significantly associated with membership across subgroups, which in turn influence students’ postsecondary education outcomes, such as undergraduate GPA for STEM courses.

Authors

• Yihan Zhao, Teachers College, Columbia University

• Alex J. Bowers, Teachers College, Columbia University