Dana Rezazadegan, Atie Kia, Phongpadid Nandavong, Dominique Carlon, Jeremy Nguyen (2026) — Artificial Intelligence (cs.AI). 📄 Full text (arXiv)
DysLexLens is a low-resource LLM framework designed to analyze how dyslexic learners experience AI tools by mining online forum discussions. The framework employs dictionary-driven filtering to construct focused corpora from Reddit, integrates LLM-assisted knowledge graph reasoning, and generates verifiable query responses about learners' lived experiences with AI for reading, writing, and study tasks.
The research reveals that while dyslexic learners find value in AI tools for supporting literacy, they face significant accessibility barriers including inconsistent output quality and lack of equitable accommodations. This has direct implications for student-AI interaction design and suggests that inclusive AI education must address language and literacy support across both K-12 and higher education settings.
By grounding analysis in real user discourse rather than controlled experiments, the work complements traditional student modeling approaches and provides an evidence base for designing AI tools that better serve neurodiverse learners.
Related Pages
- ai-literacy — AI literacy concepts and programs
- equity — Equity in AI education
- student-experience — Student-AI interaction experiences
- special-education — Special education and AI
- accessible-learning — Accessible learning with AI
- language-learning — Language learning with AI
- llm-student-modeling-memory — LLM memory for student modeling