Designing AI-Enabled Games to Support Social-Emotional Learning for Children with Autism Spectrum Disorders
Yue Lyu, Pengcheng An, Huan Zhang, Keiko Katsuragawa, Jian Zhao

TL;DR
This paper presents the design of an AI-enabled social-emotional game tailored for children with autism spectrum disorder, aiming to improve emotional understanding through personalized stories generated by AI.
Contribution
It introduces a novel AI-driven game with personalized social stories for ASD children, developed through expert co-design and a new emotion dataset.
Findings
Successful integration of AI for personalized social stories
Expert-driven design insights for future AI gamified systems
A new dataset of social stories for basic emotions
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…
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Taxonomy
TopicsAutism Spectrum Disorder Research
