Paper Title
Beyond Standardization: Evaluating the Role of AI-Enabled Personalized Learning in Creating Inclusive and Adaptive Education Systems
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Registration ID: IJNRD_328582
Published ID: IJNRD2609280
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Keywords
Artificial Intelligence; Personalized Learning; Educational Inequality; Adaptive Learning Technologies; Human Capital Development
Abstract
This paper examines how AI-enabled personalized learning can address the limitations of traditional education systems and influence broader socio-economic outcomes. Traditional education models, largely shaped by industrial-era priorities, often emphasize standardization and uniform progression, limiting their ability to support diverse learning needs. Through an analysis of personalized learning principles and artificial intelligence technologies, including machine learning, adaptive platforms and natural language processing, this paper explores how AI can provide individualized support at scale. The research evaluates the potential of AI-enabled learning systems to improve inclusivity, support neurodivergent and disadvantaged learners, enhance workforce readiness and contribute to greater social mobility. However, it also considers challenges including unequal access to technology, algorithmic bias and data privacy concerns. The paper argues that while AI is not a complete solution to educational inequality, responsible implementation of personalized learning technologies can create more adaptive, accessible and future-oriented education systems.
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How To Cite (APA)
Arshiya Sachdev (September-2026). Beyond Standardization: Evaluating the Role of AI-Enabled Personalized Learning in Creating Inclusive and Adaptive Education Systems. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(9), c792-c799. https://ijnrd.org/papers/IJNRD2609280.pdf
Issue
Volume 11 Issue 9, September-2026
Pages : c792-c799
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Paper Reg. ID: IJNRD_328582
Published Paper Id: IJNRD2609280
Research Area: Science All
Author Type: Indian Author
Country: Gurugram, Haryana, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2609280.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2609280
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