This proposal involves the analysis of data from the Michigan Study of Adolescent Life Transitions (MSALT) and the Childhood and Beyond Study (CAB), two longitudinal datasets originally created by the principal investigator. The researchers will also collect additional waves of data collection for each of the two datasets. The project draws theoretical support from Expectancy Value Theory, also developed by the principal investigator. The researchers will collect new data to expand the existing datasets as a way to explore issues of generational effects on STEM engagement, analyses of non-STEM and STEM majors from across multiple disciplines, and additional psychosocial variables that may contribute to STEM engagement. Additional issues of interest include predictors of individual differences in STEM career trajectories and labor market experiences as predictors of STEM career choices. Data analytic techniques include structural equation modeling, hierarchical linear modeling, and person-centered techniques such as cluster analysis and latent class analysis.
The major goal of this project is investigate gender differences and within-gender individual differences in the development of STEM-related interests. The under-representation of females in many STEM fields continues to be a striking labor force statistic. This study is designed to improve our understanding of the factors influencing females' choices to pursue specific STEM fields. Such information is vital to devising programs and policies aimed at changing gender-role stereotypes and gender differences in the value of STEM related majors and occupations.
