Do Teachers Dream of GenAI Widening Educational (In)equality? Envisioning the Future of K-12 GenAI Education from Global Teachers' Perspectives

2025-09-12

AI Summary

This study examines the dual impact of generative artificial intelligence (GenAI) integration in K–12 education on educational equity—both exacerbating and mitigating preexisting inequalities. Drawing on in-depth interviews with K–12 teachers across 23 countries and grounded in educational sociology and technology ethics frameworks, it is the first systematic investigation of teacher agency and structural constraints in navigating the tension between AI-driven inequity and equity promotion. Findings reveal that while teachers routinely employ differentiated instructional design and ethical scaffolding to counteract inequities, they face significant barriers: infrastructural deficits, insufficient professional development, and entrenched sociocultural norms. The study contributes an “educator-centered, equity-oriented AI education framework,” positing that inclusive, fair GenAI implementation necessitates institutional enablers—including equitable resource allocation, sustained pedagogical training, and cross-sectoral policy alignment—to transform teacher practice into scalable, just outcomes.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Machine Learning: Ethics, Bias, and Fairness
• Humans and AI: AI for Accessibility

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Responsible Web: Fairness, accountability, transparency and ethics of web technologies

Abstract

Generative artificial intelligence (GenAI) is rapidly entering K-12 classrooms worldwide, initiating urgent debates about its potential to either reduce or exacerbate educational inequalities. Drawing on interviews with 30 K-12 teachers across the United States, South Africa, and Taiwan, this study examines how teachers navigate this GenAI tension around educational equalities. We found teachers actively framed GenAI education as an equality-oriented practice: they used it to alleviate pre-existing inequalities while simultaneously working to prevent new inequalities from emerging. Despite these efforts, teachers confronted persistent systemic barriers, i.e., unequal infrastructure, insufficient professional training, and restrictive social norms, that individual initiative alone could not overcome. Teachers thus articulated normative visions for more inclusive GenAI education. By centering teachers' practices, constraints, and future envisions, this study contributes a global account of how GenAI education is being integrated into K-12 contexts and highlights what is required to make its adoption genuinely equal.

Problem

• Examining GenAI's impact on educational equality in K-12
• Identifying systemic barriers to equitable GenAI implementation
• Exploring teacher perspectives on inclusive GenAI education

Innovation

• Teachers frame GenAI for equality-oriented practice
• Address systemic barriers like infrastructure and training
• Articulate normative visions for inclusive GenAI education