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

Abstract

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.