Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs

This article explores the transformative potential of artificial intelligence in special education, addressing the persistent challenges faced by students with diverse learning needs. In the article of implementation studies across various educational contexts, we explore how AI-powered applications create personalized learning experiences through adaptive algorithms, cognitive assessment capabilities, and data-driven content customization. The article shows accessibility features including multi-modal content delivery, assistive technology integration, adaptive user interfaces, and real-time feedback mechanisms. Empirical evidence demonstrates significant improvements in academic outcomes, engagement levels, and cost-effectiveness compared to traditional interventions, with particularly strong effects in mathematics and reading comprehension. The article concludes with an examination of ethical considerations including data privacy, optimal technology-human instruction balance, emerging AI capabilities, and policy recommendations for equitable implementation, providing a framework for the development and deployment of AI-powered educational technologies for students with special needs.

Authors

Publication Details

Journal
Technix International Journal for Engineering Research
Published
2025-01-01
DOI
https://doi.org/10.56975/tijer.v12i6.158587
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs

Raghav Sai Cheedalla
Technix International Journal for Engineering Research
Online Learning and Analytics
article

Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs

Raghav Sai Cheedalla
article en

Abstract

This article explores the transformative potential of artificial intelligence in special education, addressing the persistent challenges faced by students with diverse learning needs. In the article of implementation studies across various educational contexts, we explore how AI-powered applications create personalized learning experiences through adaptive algorithms, cognitive assessment capabilities, and data-driven content customization. The article shows accessibility features including multi-modal content delivery, assistive technology integration, adaptive user interfaces, and real-time feedback mechanisms. Empirical evidence demonstrates significant improvements in academic outcomes, engagement levels, and cost-effectiveness compared to traditional interventions, with particularly strong effects in mathematics and reading comprehension. The article concludes with an examination of ethical considerations including data privacy, optimal technology-human instruction balance, emerging AI capabilities, and policy recommendations for equitable implementation, providing a framework for the development and deployment of AI-powered educational technologies for students with special needs.

Technix International Journal for Engineering ResearchVol. 12(6)
Openalex Percentile: Top 86%
Online Learning and Analytics
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Personalized Learning Pathways: AI-Adaptive Educational Technology Supporting Diverse Learning Needs — Raghav Sai Cheedalla · Technix International Journal for Engineering Research (2025) | TGRS Research Map | TGRS