AI is making education more accessible and personalized for dyslexic, at-risk and multilingual learners. Adaptive tools, speech recognition and writing support can boost engagement, speed feedback and help teachers track progress. Schools still must address privacy, access, bias and overreliance on AI, but these tools should supplement, not take away from, educators’ work as they prepare students for school and careers.
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As part of the Ministry of Social Policy’s nationwide initiative to ensure digital accessibility, we invite you to review informational materials about available free screen-access technologies (screen readers).
These technologies enable people with visual impairments or dyslexia to fully and freely use computers, study, work, and independently access government services and online services.
Find a list of these tools HERE
Adaptive learning systems are a significant area of research in personalized education, especially for students with dyslexia, as structured and responsive instructional support can greatly enhance learning outcomes. Many conventional rule-based methodologies are not readily adaptable for personalized instruction or real-time modification. To overcome this limitation, this paper introduces a lightweight adaptive learning system that utilizes a machine learning model to produce instructional recommendations. The system employs a Decision Tree Classifier trained on structured quiz-response features to assess a learner’s proficiency and recommend the most appropriate learning stages. The platform is not meant to be a diagnostic tool; instead, it is meant to be a post-identification instructional support system.
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