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How to train your DragonBot: Socially assistive robots for teaching children about nutrition through play

Elaine Schaertl Short, Katelyn Swift-Spong, Jillian Greczek, Aditi Ramachandran, Alexandru Litoiu, Elena Corina Grigore, David Feil-Seifer, Samuel Shuster, Jin Joo Lee, Shaobo Huang, Svetlana Levonisova, Sarah Litz, Jamy Li, Gisele Ragusa, Donna Spruijt‐Metz, Maja J. Matarić, Brian Scassellati

Year
2014
Citations
124

Abstract

This paper describes an extended (6-session) interaction between an ethnically and geographically diverse group of 26 first-grade children and the DragonBot robot in the context of learning about healthy food choices. We find that children demonstrate a high level of enjoyment when interacting with the robot, and a statistically significant increase in engagement with the system over the duration of the interaction. We also find evidence of relationship-building between the child and robot, and encouraging trends towards child learning. These results are promising for the use of socially assistive robotic technologies for long-term one-on-one educational interventions for younger children.

Keywords

RobotContext (archaeology)Psychological interventionSession (web analytics)Educational roboticsHuman–computer interactionEthnically diversePsychologyComputer scienceDuration (music)

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