The underrepresentation of females in STEM fields negatively affects productivity growth and contributes to labour market inequalities. In countries where children are tracked in educational trajectories from high school (as in Italy, 8th grade), it is crucial to understand what drives gendered pathways before educational segregation starts. Collecting experimental and survey data from Italian 8th graders, we find that perceived comparisons with peers are predictors of the likelihood that girls choose a math-intensive track during high school. Policy initiatives improving girls' expectations about their relative math performance may thus encourage female students to pursue a STEM track.
Math ability, gender stereotypes about math ability, and educational choices. Combining experimental and survey data.
Dominique Cappelletti;
2022-01-01
Abstract
The underrepresentation of females in STEM fields negatively affects productivity growth and contributes to labour market inequalities. In countries where children are tracked in educational trajectories from high school (as in Italy, 8th grade), it is crucial to understand what drives gendered pathways before educational segregation starts. Collecting experimental and survey data from Italian 8th graders, we find that perceived comparisons with peers are predictors of the likelihood that girls choose a math-intensive track during high school. Policy initiatives improving girls' expectations about their relative math performance may thus encourage female students to pursue a STEM track.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
