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Artificial Intelligence-Driven Personalization in ODeL for Marginalized Communities
Author(s): Barno Matchanova (Urgench State Pedagogical Institute, Urgench, Uzbekistan), Sardor Buriyev (Termez University of Economics and Service, Termez, Uzbekistan), R. N. Ravikumar (Marwadi University, Rajkot, India)and S. Aarthi (Marwadi University, Rajkot, India)
Copyright: 2026
Pages: 28
EISBN13: 9798260021491
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Abstract
This chapter explores how Artificial Intelligence (AI) can transform Open and Distance e-Learning (ODeL) to provide inclusive, personalized, and accessible education for marginalized communities. It examines AI applications such as adaptive learning, predictive analytics, and Natural Language Processing (NLP) to address key challenges like language barriers, learner disengagement, and lack of real-time support. Real-world case studies from India and Kenya demonstrate the impact of AI-driven tools in improving learner outcomes, reducing dropout rates, and increasing equity in education. The chapter also discusses ethical, technical, and implementation barriers, proposing strategic policy recommendations and future research directions. AI is positioned not just as a technological innovation, but as a tool for educational justice and empowerment in low-resource settings.
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