AI-based adaptive note-taking, concept mapping and paraphrasing for accessibility and inclusivity for learners with SLD

Abstract: The rapid digital transformation of education has redefined how knowledge is produced, shared, and experienced, but it has also revealed persistent gaps in accessibility and personalization. Many existing digital learning platforms remain content-centered rather than learner-centered, offering limited adaptability to individual cognitive differences or diverse learning needs. This concept proposes an innovative, AI-driven web platform for adaptive note-taking and conceptual mapping, designed to support inclusivity and personalization in digital education. The idea aims to enhance accessibility and comprehension through a system that employs artificial intelligence, natural language processing, and knowledge graph technologies to analyze written notes and automatically generate interactive concept maps in real time. The envisioned platform would link user-generated content to open knowledge bases such as Wikipedia and Wikidata, providing contextual expansion and semantic understanding. A data-informed framework is proposed, combining behavioral analytics and linguistic modeling to explore how cognitive and interactional patterns might inform adaptive learning support. By analyzing writing rhythm, lexical variety, and error frequency, the system could identify potential indicators of specific learning disorders (SLD) such as dyslexia or dyscalculia and adapt visual layouts, map complexity, and language presentation accordingly. In parallel, the platform would integrate Open Educational Resources (OER) to recommend supplementary materials aligned with the learner’s abilities and interests, while AI-based paraphrasing tools would simplify complex ideas into accessible language without compromising conceptual richness. This proposal outlines a new model for inclusive and adaptive digital learning environments, where artificial intelligence functions as a cognitive partner rather than a passive content provider. The concept is expected to enhance comprehension and knowledge retention through personalized visualizations, promote inclusion by responding to cognitive diversity, and create semantically enriched, interconnected learning experiences that bridge individual and global knowledge. Ultimately, this idea aims to explore how AI-enhanced adaptive systems could reshape digital education by uniting personalization, accessibility, and open knowledge integration, contributing to the development of more equitable and human-centered learning ecosystems.