Work

Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social–cognitive choice model by gender and race/ethnicity.

Year: 2018

Type: article

Study designs: Systematic Review, Meta-Analysis

Abstract: We tested the interest and choice portion of social-cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) in the context of science, technology, engineering, and mathematics (STEM) domains. Data from 143 studies (including 196 independent samples) conducted over a 30-year period (1983 through 2013) were subjected to meta-analytic path analyses. The interest/choice model was found to fit the data well over all samples as well as within samples composed primarily of women and men and racial/ethnic minority and majority persons. The model also accounted for large portions of the variance in interests and choice goals within each path analysis. Despite the general predictive utility of SCCT across gender and racial/ethnic groups, we did find that several parameter estimates differed by group. We present both the group similarities and differences and consider their implications for future research, intervention, and theory refinement. (PsycINFO Database Record

Source: Journal of Counseling Psychology

DOI: 10.1037/cou0000243

Authors: Robert W. Lent, Hung-Bin Sheu, Matthew J. Miller, Megan E. Cusick, Lee T. Penn, Nancy N. Truong

Institutions: University of Maryland, College Park, University at Albany, State University of New York

Language: English

Topic: Career Development and Diversity

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: hybrid

Funder: National Science Foundation