Top-performing math students in 82 countries

Periodical
Journal of Educational Psychology
Volume
114
Year
2022
Issue number
5
Page range
966-991
Relates to study/studies
PISA 2012
PISA 2015

Top-performing math students in 82 countries

An integrative data analysis of gender differences in achievement, achievement profiles, and achievement motivation

Abstract

The present integrative data analysis examined gender differences in achievement, achievement profiles, and achievement motivation in mathematics, reading, and science among 113,864 top-performing adolescent math students (top 5% in their respective countries). To do this, we applied the same analysis protocol to representative individual participant data from six cycles of the Programme for International Student Assessment (PISA 2000–2015; 82 countries) and integrated the results by using meta-analytical random coefficient models. We found that in the group of top-performing math students, male students were overrepresented (mean female-to-male ratio 1:1.50, 95% CI [1:1.58, 1:1:43]). Furthermore, female students possessed better reading skills (mean d = –0.23, 95% CI [–0.25, –0.21]) and more positive reading attitudes (–0.64, 95% CI [–0.69, –0.60] ≤ mean d ≤ –0.38, 95% CI [–0.46, –0.30]). Male students had stronger math self-efficacy (mean d = 0.32, 95% CI [0.28, 0.35]) and demonstrated mathematics-oriented achievement profiles, whereas female students’ profiles were more balanced across domains. Moreover, female students were more interested in organic and medical fields (–0.44, 95% CI [–0.48, –0.40] ≤ mean d ≤ –0.30, 95% CI [–0.34, –0.25]), whereas male students showed greater interest in physics-related topics (0.39, 95% CI [0.36, 0.43] ≤ mean d ≤ 0.54, 95% CI [0.50, 0.58]). Gender equality indicators moderated the proportion of female students in the top 5% in mathematics and explained variability in achievement profiles across countries. Results are explained by social role theory and situated expectancy–value theory, and implications for women’s underrepresentation in (specific) STEM fields are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved)