Learning Analytics Model for Smart Toys using Edge Computing

Abstract

In this study, learning information of learners when using diverse smart toys is analyzed. A learning analytics model using edge computing to support intelligent tutoring system is studied. This study configures the following: an open learning management system, which is provided to learners; a learning analytics edge node that broadcasts learning activity information received from the open learning management system and learning content received from learning analysis cloud server; and a learning analytics cloud server that saves learning activity information received from the edge node into the learning record store and then analyzes and visualizes the information. A scenario is configured for each step. All these steps reduce the latency of situation recognition and learning activities, allowing for efficient distributed computing by enabling edge interactions based on edge computing, in which processing occurs away from the conventional cloud server system where all the processing would otherwise occur.