Summary
This arXiv paper (2603.24536) by Soufiane Jhilal, published March 25, 2026, addresses reading comprehension challenges faced by children with Special Educational Needs and Disabilities (SEND). Such children often require intensive one-on-one reading support, which is difficult for therapists to scale. The authors developed a multilingual, AI-powered interface that automatically enhances text with visual scaffolding, aiming to help therapists extend personalized reading support to more children. The work falls within the field of natural language processing (NLP) applied to assistive and educational technology. By automatically augmenting text with pictogram-based visual supports, the system seeks to improve accessibility and comprehension for SEND learners across multiple languages. Full paper available at https://arxiv.org/abs/2603.24536.
Paper Overview
Field: NLP
Author: Soufiane Jhilal
Published: 2026-03-25
arXiv: 2603.24536
Abstract
Reading comprehension presents a significant challenge for children with Special Educational Needs and Disabilities (SEND), often requiring intensive one-on-one reading support. To assist therapists in scaling this support, the authors developed a multilingual, AI-powered interface that automatically enhances text with visual scaffolding.
The goal of this work is to help therapists scale personalized reading support by automatically augmenting texts with pictogram-based visual aids, improving accessibility for SEND learners across multiple languages.
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