Exploring Gender Differences in Computational Thinking Among K-12 Students: A Meta-Analysis Investigating Influential Factors

Abstract

This study employs meta-analysis to synthesize findings from 30 articles investigating gender differences in computational thinking (CT) among K-12 students. Encompassing 51 independent effect sizes, the meta-analysis involves a participant pool of 9181 individuals from various countries, comprising 4254 males and 4927 females. Results indicate statistically significant gender differences in CT (Hedges’s g = 0.091, p < .05), albeit with a modest effect size, revealing higher CT scores among males compared to females. Further moderation analyses unveil the multifaceted nature of these gender differences. Specifically, while gender differences become significant during high school, recent studies suggest a gradual reduction in CT gender differences with societal progress among K-12 students. Moreover, findings illustrate variations in gender differences across geographical regions. Notably, while the overall gender disparity in CT is non-significant in the “East Asia and Pacific” region, it widens in “North America” and “Europe”, with males scoring higher than females. Conversely, in “Europe and Central Asia”, such gender differences present inconsistent outcomes, with females scoring higher than males. Importantly, assessment tool type does not significantly influence gender differences. Lastly, this study offers recommendations to address CT gender gaps, providing valuable insights for promoting gender equality in education.