VALF: A CLA-Based Reinforcement Learning Framework for Vietnamese Language Learning in Dyslexic Children

Dyslexic children faces many persistent challenges in learningTonal languages such as Vietnamese, Chinese, Koeran where visual, phonetic, and orthographic components interact in complex ways.This paper introduces a new approach VALF (Vietnamese Adaptive Learning Framework), a novel educational AI prototype that uses Cellular Learning Automata (CLA) to generate adaptive multimedia content for Vietnamese language instruction.VALF integrates a reinforcement learning-driven virtual pen for character rendering, tone marker placement, and audio pronunciation to enhance learners' visual, auditory, and motor integration.Designed for primary school children with dyslexia, the system simulates personalized learning through games, quizzes, and pronunciation feedback.The proposed VALF model can also able to produce long texts and sentences using Vietnamese Word Generation algorithm.Main objectives of VALF's efficacy is to promote literacy and self-confidence in dyslexic learners.Future work includes implementing VALF in gaming platform to support and integrate deep learning for natural speech synthesis and feedback.