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Sibling Gender Composition and Preferences for STEM Education

This paper studies how sibling gender composition affects preferences for education within STEM and whether the e?ects on STEM preferences in education persists into labor market outcomes.

Unique Effects and Moderators of Effects of Sources on Self-Efficacy: A Model-Based Meta-Analysis

– Educational level and cultural factors moderate individuals’ learning experiences and subsequently their self-efficacy beliefs,
particularly in science, technology, engineering, and mathematics (STEM) domains.
– The results suggest the importance of intervening early in STEM-related academic and career development and attending to
gender and racial/ethnic influences in the types of learning experiences to which individuals are exposed.
– The authors found that variance explained was significantly higher in non-STEM domains (R2 .37) relative to STEM domains (R2 .22), suggesting that other factors are also important in accounting for self-efficacy beliefs related to STEM subjects.
– In all of the subsamples studied, Performance Accompishment (PA) was the dominant influence on self-efficacy. Once PA was statistically controlled, the other three sources were weakly predictive of self-efficacy.
– The authors note that there was no evidence of race/ethnicity as
a moderator of the sources-to-efficacy relationships in STEM
college samples. This suggests that among college students, the
sources are similarly predictive of STEM self-efficacy for nonWhite
and White individuals.

Choice of Majors: Are Women Really Different from Men?

– High school academic preparation, faculty gender composition, and major returns have little effect on major switching behaviors, and women and men are equally likely to change their major in response to poor grades in major-related courses.
– Women in male-dominated majors do not exhibit different patterns of switching behaviors relative to their male colleagues.
– Women are more likely to switch out of male-dominated STEM majors in response to poor performance compared to men.
– It takes multiple signals of lack of fit into a major (low grades, gender composition of class, and external stereotyping signals) to impel female students to switch majors.