Personalized Socially Assistive Robot Tutor of Teaching Number Concepts to Preschool Children
Robot tutors can provide effective supplemental support in the education of young children through delivering and engaging them in developmental materials and drills. However, no two children learn in exactly the same way. Personalization of instruction is a necessary component to reach a child’s full learning potential. It is an important and significant challenge to enable a robot tutor to customize its interaction and material to an individual child’s learning style. This work applies machine learning and statistical methods to learn personalized models of number concepts learning in preschool children, and leverage those models to personalize the robot tutor over multiple, repeated interactions.