One of the numerous approaches that increases the interaction quality between two people is having a proper understanding of the other person's perspective. In this doctoral thesis, we aim to understand children's perspective taking behavior, create a perspective taking framework for social robots, and evaluate the framework in educational scenarios and real-life interactions. The research started by designing tasks that allow us to analyze and decompose children's decision-making mechanisms in terms of their perspective taking choices. We collect data from series of studies that capture the dynamic between the child and the robot using different perspective taking tasks and develop a complementary adaptive model for the robot. This article summarizes the perspective taking tasks, experimental studies, and future works for developing a comprehensive model of perspective taking for social robots.