Designing AI-Enabled Games to Support Social-Emotional Learning for Children with Autism Spectrum Disorders

TL;DR

The paper tackles the need for scalable, personalized social-emotional interventions for children with autism spectrum disorder by proposing an AI-enabled mobile game that generates individualized social stories. It employs a co-design process with five domain experts and a GPT-based storytelling pipeline to produce and curate stories across seven basic emotions, accompanied by a 56-story dataset evaluated for suitability. Key contributions include design insights for adaptive, familiar, and multimodal storytelling, a fine-tuned AI model approach, and a dataset to support social-emotional learning in ASD contexts. The envisioned system aims to enable caregiver involvement and AI-assisted facial expression feedback, with planned empirical evaluations to establish efficacy in real-world settings. These elements collectively offer a practical pathway toward affordable, personalized, AI-assisted interventions for ASD families.

Abstract

Children with autism spectrum disorder (ASD) experience challenges in grasping social-emotional cues, which can result in difficulties in recognizing emotions and understanding and responding to social interactions. Social-emotional intervention is an effective method to improve emotional understanding and facial expression recognition among individuals with ASD. Existing work emphasizes the importance of personalizing interventions to meet individual needs and motivate engagement for optimal outcomes in daily settings. We design a social-emotional game for ASD children, which generates personalized stories by leveraging the current advancement of artificial intelligence. Via a co-design process with five domain experts, this work offers several design insights into developing future AI-enabled gamified systems for families with autistic children. We also propose a fine-tuned AI model and a dataset of social stories for different basic emotions.