Research on the Influence Mechanism of Adolescent Participation in STEM Activities

• In Event: Open Refereed Roundtables
  In Refereed Roundtable (90 minute): Table 15: Education and Inequality

Abstract

Amid international restrictions on core technologies, China faces growing shortages of scientific and technological talent, while reforms toward diversified college entrance examination pathways have accelerated the expansion of STEM education. Existing studies have primarily focused on educational expansion, family capital endowments, and childrearing practices as determinants of educational opportunities. However, insufficient attention has been paid to how family childrearing patterns align with educational selection mechanisms within the specific domain of STEM education, or how families secure educational opportunity advantages in this field. Drawing on participant observation and in-depth interviews, and grounded in Bourdieu’s theory of social practice, this study finds that in-stitutional rules and the STEM education white-list system structure parental decision-making, while differences in parents’ interpretations of these rules generate stratified participation patterns. Fur-thermore, families’ participation strategies differentiate concerted cultivation into cultur-al-capital-dominant and economic-capital-dominant childrearing patterns. The former emphasizes converting multiple forms of capital into high-quality educational resources to pursue measurable achievements and rankings, whereas the latter prioritizes interest-driven exploration, skill development, and experiential engagement in science and innovation activities. By extending Lareau’s framework and dynamically examining capital conversion processes under specific institutional conditions, this study provides new empirical evidence and theoretical insights into the localized mechanisms under-lying educational opportunity inequality.

Authors

• Chenmin XIE, School of Social Development and Public Policy, Fudan University

• Luye Zhang, Shanghai University