AccessiLearnAI: An Accessibility-First, AI-Powered E-Learning Platform for Inclusive Education

Online education has become an important channel for extensive, inclusive and flexible learning experiences. However, significant gaps persist in providing truly accessible, personalized and adaptable e-learning environments, especially for students with disabilities, varied language backgrounds, or limited bandwidth. This paper presents AccessiLearnAI, an AI-driven platform, which converges accessibility-first design, multi-format content delivery, advanced personalization, and Progressive Web App (PWA) offline capabilities. Our solution is compliant with semantic HTML5 and ARIA standards, and incorporates features such as automatic alt-text generation for images using Large Language Models (LLMs), real-time functionality for summarization, translation, and text-to-speech capabilities. The platform, built on top of a modular MVC and microservices-based architecture, also integrates robust security, GDPR-aligned data protection, and a human-in-the-loop to ensure the accuracy and reliability of AI-generated outputs. Early evaluations indicate that AccessiLearnAI improves engagement and learning outcomes across multiple ranges of users, suggesting that responsible AI and universal design can successfully coexist to bring equity through digital education.

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Publication Details

Journal
Education Sciences
Published
2025-08-29
DOI
https://doi.org/10.3390/educsci15091125
Citations
5
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
8.47
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article

AccessiLearnAI: An Accessibility-First, AI-Powered E-Learning Platform for Inclusive Education

Florin Sandu, Dan Robu, George Alex Stelea
5 citations
Education Sciences
Online Learning and Analytics
8.47
article

AccessiLearnAI: An Accessibility-First, AI-Powered E-Learning Platform for Inclusive Education

Florin Sandu, Dan Robu, George Alex Stelea
article en
5 citations

Abstract

Online education has become an important channel for extensive, inclusive and flexible learning experiences. However, significant gaps persist in providing truly accessible, personalized and adaptable e-learning environments, especially for students with disabilities, varied language backgrounds, or limited bandwidth. This paper presents AccessiLearnAI, an AI-driven platform, which converges accessibility-first design, multi-format content delivery, advanced personalization, and Progressive Web App (PWA) offline capabilities. Our solution is compliant with semantic HTML5 and ARIA standards, and incorporates features such as automatic alt-text generation for images using Large Language Models (LLMs), real-time functionality for summarization, translation, and text-to-speech capabilities. The platform, built on top of a modular MVC and microservices-based architecture, also integrates robust security, GDPR-aligned data protection, and a human-in-the-loop to ensure the accuracy and reliability of AI-generated outputs. Early evaluations indicate that AccessiLearnAI improves engagement and learning outcomes across multiple ranges of users, suggesting that responsible AI and universal design can successfully coexist to bring equity through digital education.

Education SciencesVol. 15(9)
Transylvania University of Brașov (RO)
Openalex Percentile: Top 2%
Online Learning and Analytics
8.47
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AccessiLearnAI: An Accessibility-First, AI-Powered E-Learning Platform for Inclusive Education — Florin Sandu, Dan Robu, et al. · Education Sciences (2025) | TGRS Research Map | TGRS