Article
Research on the mechanisms by which AI promotes educational equity between urban and rural areas and enhances educational inclusivity for diverse groups in the context of digital transformation
Abstract
Digital education is a core national strategy meant to lift the overall quality of education across China. Artificial intelligence brings down-to-earth new solutions to fix the uneven split of high-quality teaching resources between cities and villages, and also lets all types of students get proper learning support. Right now, basic education still faces obvious practical pain points: top teaching resources are unevenly distributed between urban and rural regions, few schools can design truly personalized lessons for their students, and targeted learning assistance for kids with special learning needs is severely insufficient.
If we only rely on traditional ways to balance school resources, we will quickly hit clear limits. Geographic barriers and the shortage of skilled, experienced teachers only let us patch over surface-level gaps, rather than resolve deep, substantive unfairness in education. This paper sorts out how AI actually drives fair education and inclusive learning amid the digital shift. I put forward a four-part practical working framework, covering resource restructuring, personalized classroom teaching, expanded growth paths for students, and supporting governance systems. I also sort out real problems we’ve spotted in frontline teaching practice: a newly formed digital divide, mismatched cultural logic between intelligent tools and rural classrooms, poorly designed AI products for marginalized student groups, and outdated institutional rules that can’t keep pace with tech development.
In the final section, I put forward targeted improvement ideas based on real classroom work. This paper clarifies the interactive logic between intelligent technology and equal education, and can serve as theoretical and practical reference for frontline teachers and education policymakers. It offers clear ideas on using AI to narrow urban-rural education gaps, and guarantee fair learning chances for vulnerable children including left-behind minors and students with disabilities.
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References
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