Artificial Intelligence In The Global Classroom: An Analysis Of The Impact On Education Quality And Access
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Abstract
The rapid integration of Artificial Intelligence (AI) into education systems worldwide has transformed teaching practices and expanded access to learning. This study examines the transformative impact of AI on the quality and equity of education on a global scale. The aim is to evaluate how AI-based technologies can enhance personalised learning, improve teaching strategies, and reduce disparities in educational opportunities. Using a mixed-methods approach, this research combines bibliometric analysis of international literature with qualitative case studies from various educational contexts. Quantitative analysis identifies key research themes, patterns of geographical collaboration, and publication trends, while qualitative findings reveal practical applications and contextual challenges encountered.
The results of the study show that AI-based tools such as adaptive learning platforms, automated assessment systems, and intelligent tutor models significantly improve student engagement and learning outcomes. In addition, AI helps expand access to quality education in resource-poor areas by addressing teacher shortages and infrastructure limitations. However, challenges such as the digital divide, ethical issues related to data privacy, and low teacher readiness remain obstacles to fully utilising the potential of AI in education. Theoretically, this study enriches the discourse on AI-based pedagogy; practically, it provides policy recommendations for the fair, inclusive, and sustainable application of AI in global education.
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References
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