AI as a Catalyst for Educational Equity: Addressing Global Teacher Shortages and Learning Disparities

Nupur Jain

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 69-76

Abstract: The global education system is grappling with a critical shortage of teachers, threatening the achievement of universal quality education. This article examines how artificial intelligence (AI) technologies can revolutionize educational access and equity by addressing these systemic challenges. Through a comprehensive article analysis of AI-enabled solutions, including personalized learning mechanisms, virtual tutoring systems, and intelligent content distribution platforms, the article explores the transformative potential of these technologies in democratizing education. The article investigates the implementation of AI across established educational platforms, examining their effectiveness in providing adaptive learning experiences, breaking down language barriers, and ensuring cultural relevance. The article demonstrates that strategic AI integration can significantly impact learning outcomes while helping to bridge the global teacher shortage gap. The article also addresses critical implementation challenges, providing policy recommendations and resource allocation frameworks for successful AI adoption in education systems worldwide. This article analysis contributes to the growing body of knowledge on educational technology by offering practical insights into how AI can be leveraged to create more inclusive, effective, and accessible learning environments, ultimately advancing the goal of quality education for all.

Keywords: Artificial Intelligence in Education (AIEd); Educational Equity; Teacher Shortage Solutions; Adaptive Learning Technologies; Educational Resource Democratization (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25111200
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:652

DOI: 10.32628/CSEIT25111200

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