Social Skills Scenarios and Emotional Affect Training Via Chatbot for Secondary Students with Autism Spectrum Disorder

Abstract

Chatbots show promise in making conversational support therapy more accessible while providing a safe environment for developing social skills without judgment. This research aims to create a chatbot that generates social scenarios, ranked by difficulty customized for each user. Unlike previous approaches that relied solely on rules-based decision trees, this system incorporates natural language processing (NLP) techniques, including a two-layer neural network for word vector space creation. This advanced NLP approach enables more sophisticated feedback and unprecedented customization in social skills training. The system continuously adapts to challenge users appropriately, addressing a common limitation of existing platforms that often provide overly simplistic training scenarios. In future work, the social scenarios and trainings would be adapted to more successfully address end user accessibility