Artificial Intelligence and Machine Learning Based Approach to Motivate and Assist Primary School ADHD Children

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder among primary school children that significantly impacts their academic performance and social interactions. Traditional interventions for ADHD children often lack personalization and struggle to engage and motivate them effectively. This research paper proposes an innovative approach that leverages Artificial Intelligence (AI) and Machine Learning (ML) techniques to develop a personalized intervention system for motivating and assisting primary school children with ADHD. This study includes designing and developing an AI and ML-based intervention system tailored to the unique characteristics and preferences of ADHD children. The system will incorporate adaptive features to customize the intervention content, difficulty level, and feedback mechanism based on individual needs. Furthermore, the effectiveness of the intervention will be evaluated through standardized ADHD assessments, focusing on improvements in attention, impulsivity, and hyperactivity levels. Ethical considerations regarding privacy, data security, and potential risks associated with AI and ML interventions will be addressed to ensure the responsible and ethical deployment of these technologies. Practical recommendations will be provided for parents, and professionals to facilitate the implementation of AI and ML interventions in primary school settings.