EmoLand: Utilizing narrative animations, multilevel games, and affective computing to foster emotional development in children with autism spectrum disorder

• We designed an interactive system that utilizes narrative animations, multilevel games, and affective computing to support children with autism spectrum disorder (ASD) learning neurotypical emotions and facial expressions in social contexts. • Children with ASD achieved generalized learning gains in recognizing and producing neurotypical facial expressions. • The three-step design approach is feasible for developing interactive AI systems for children with ASD. • Narrative animations provide value social contexts, while multilevel games and interactivity help children to stay focused. • Blending AI and human support enables children's personalized, engaging, and effective learning. Emotional skills are crucial for a child's success, though children with autism spectrum disorder (ASD) face challenges in understanding social contexts, as well as recognizing and expressing facial expressions. We present EmoLand, a web-based interactive system that utilizes narrative animations, multilevel games, and artificial intelligence (AI) affective computing to instruct children with ASD about neurotypical emotions and facial expressions in social contexts. The paper sets out the iterative design process used, which was informed by ASD intervention theories, empirical studies focused on children with ASD and their educators (tutors, therapists, parents), and multiple discipline expert inputs. A preliminary evaluation involving twelve children with ASD (aged 4 to 7 years) and five tutors suggests that EmoLand is a viable teaching aid for ASD educators and effectively assists children in learning and applying generalized knowledge about emotions and facial expressions. In this paper, we discuss the design approach and key lessons learned for creating interactive AI systems for children with ASD and explore beneficial considerations for enhancing emotional development.