Learning Language Skills with a Social Robot
Children’s oral language skills in preschool can predict their academic success later in life. Helping children improve their language and vocabulary skills early on could help them succeed later, in middle and high school. Learning language is also a very social, interactive activity. Social robots could have great impact in this area, since they can leverage the same kinds of social cues and presence that people use. Learning language also takes time.
In this work, we asked whether a sociable robotic learning/teaching companion could supplement children’s early long-term language education. Children played with the robot for two months.
The robot was designed as a social character, engaging children as a peer, not as a teacher, within a relational, dialogic context. The robot targeted the social, interactive nature of language learning through a storytelling game that the robot and child played together. The game was on a tablet – the tablet showed a couple characters that the robot or child could move around while telling their story. During the game, the robot introduced new vocabulary words and modeled good story narration skills.
Furthermore, because children may learn better when appropriately challenged, we asked whether a robot that matched the “level” or complexity of the language it used to the general language ability of the child might help children improve more. The robot told easier or harder stories based on an assessment of the child’s general ability.
This work is supported by the NSF Expeditions in Computing award in Socially Assistive Robots.
In a microgenetic study, 17 children played the storytelling game with the robot eight times each over a two month period. With half the children, the robot adapted its level of language to the child’s level – so that, as children improved their storytelling skills, so did the robot. The other half played with a robot that did not adapt.
We evaluated whether this adaptation influenced (i) whether children learned new words from the robot, (ii) the complexity and style of stories children told, and (iii) the similarity of children’s stories to the robot’s stories. We expected that children would learn more from a robot that adapted, and that they would copy its stories and narration style more than they would with a robot that did not adapt. Children’s language use was tracked across sessions.
We found that all children learned new vocabulary words, created new stories during the game, and enjoyed playing with the robot. In addition, children in the adaptive condition maintained or increased the amount and diversity of the language they used during interactions with the robot more than children who played with the non-adaptive robot.
Understanding how the robot influences children’s language, and how a robot could support language development will inform the design of future learning/teaching companions that engage children as peers in educational play.
- Kory Westlund, J., & Breazeal, C. (2015). The interplay of robot language level with children’s language learning during storytelling. In Adams, J. A., & Smart, W. (Eds.), Proceedings of the 2015 ACM/IEEE international conference on Human-Robot Interaction (Extended Abstracts). ACM: New York, NY. [PDF]
- Kory Westlund, J. (2015). Telling Stories with Green the DragonBot: A Showcase of Children’s Interactions Over Two Months. In J. A. Adams, W. Smart, B. Mutlu, & L. Takayama (Eds.), Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction: Extended Abstracts (p. 263). *Best Video Award* [PDF] [Video link]
- Kory, J., & Breazeal, C. (2014). Storytelling with Robots: Learning Companions for Preschool Children’s Language Development. In P. A. Vargas & R. Aylett (Eds.), Proceedings of the 23rd IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE: Washington, DC. [PDF]
- Kory, J. (2014). Storytelling with robots: Effects of robot language level on children’s language learning. Master’s Thesis, Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, MA. [PDF]