Design of a personalized r-learning system for children

Abstract

This paper introduces the r-learning (robot-learning) system that utilizes robotic interactions to personalize instructions for individual children. A child who is not familiar with using an educational tool to study could learn readily from educational contents through various interactions with a robot which is based on the behavior control. The contents which are chosen according to a child's learning data extracted by analysis from human-robot interaction data could lift the educational effectiveness. An r-learning scenario is designed by using Petri net to handle exception occurred in a learning process. The robot contents maker and the Open API for operating a robot are described as management utilities for a personalized r-learning system.