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Optimizing dyslexia intervention through an adaptive sequential recommender system
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DOI：10.1016/j.knosys.2025.114309.png)
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Abstract
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• Personalized recommender system: The paper introduces a system that dynamically adapts word difficulty based on user performance, ensuring that each child remains within their optimal learning zone. • Dynamic word generator: The system features a word generator that phonetically modifies words to adjust the difficulty level of reading tests. • 3D matrix structure: It utilizes a three-dimensional matrix structure ( E, W, and F matrices) to manage word difficulty and user performance effectively. • Advancements in intervention design: The system allows real-time adjustments based on the child’s progress, making the intervention more effective and personalized. • Virtual children evaluation: The system uses “virtual children” models based on Bayesian knowledge tracking to optimize and test the system before real-world implementation.
Keywords:
Recommendation system
Bayesian knowledge tracking
Virtual children
Intervention test
Phonemes
Dyslexia
Word-generator,
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1.2W
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