Resumo

LIU, Yunlai  e  ZHANG, Yuwei. Revisiting Techno-Optimism: Multidimensional Inequalities in AI Education across Urban, Suburban, and Rural Primary Schools in China. Educ. as change [online]. 2025, vol.29, n.1, pp.1-25. ISSN 1947-9417.  https://doi.org/10.25159/1947-9417/18869.

This study challenges the technologically optimistic narrative that artificial intelligence (AI) naturally promotes educational democratisation by delving into systemic inequalities in AI education across urban, suburban, and rural primary schools in China. Utilising a constructivist grounded theory approach, the research conducted six months of qualitative fieldwork, including in-depth interviews with 15 students, five parents, and five teachers, along with classroom observations at three primary schools located in Shenzhen (urban), Anqing (suburban), and Shangluo (rural). The findings unveil four interconnected layers of inequality: policy-driven infrastructure disparities favouring elite urban schools, regional stratification exacerbating urban-rural divides under standardised policies, intergenerational transmission of cultural and economic capital reinforcing educational privilege, and individual disparities in AI literacy widening the "new digital divide". These insights resonate with the maximally maintained inequality theory, highlighting how AI education policies may inadvertently perpetuate existing inequities. The study advocates for equity-oriented reforms in AI education, emphasising the necessity to address structural barriers such as unequal resource allocation, inadequate teacher training, and disparities rooted in family backgrounds. By illuminating the socio-technical dynamics of AI integration in education, this research not only contributes to theoretical understandings of educational inequality but also offers practical implications for policymakers and educators striving to achieve more equitable AI education outcomes.

Palavras-chave : AI education inequality; urban-rural divide; cultural capital; digital divide; China.

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