An adaptive robot teacher boosts a human partner’s learning performance in joint action

Citation

Vignolo A, Powell H, McEllin L, Rea F, Sciutti A & Michael J (2019) An adaptive robot teacher boosts a human partner’s learning performance in joint action. In: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN 2019), New Delhi, India, 14.10.2019-18.10.2019. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/ro-man46459.2019.8956455

Abstract
One important challenge for roboticists in the coming years will be to design robots to teach humans new skills or to lead humans in activities which require sustained motivation (e.g. physiotherapy, skills training). In the current study, we tested the hypothesis that if a robot teacher invests physical effort in adapting to a human learner in a context in which the robot is teaching the human a new skill, this would facilitate the human's learning. We also hypothesized that the robot teacher's effortful adaptation would lead the human learner to experience greater rapport in the interaction. To this end, we devised a scenario in which the iCub and a human participant alternated in teaching each other new skills. In the high effort condition, the iCub slowed down his movements when repeating a demonstration for the human learner, whereas in the low effort condition he sped the movements up when repeating the demonstration. The results indicate that participants indeed learned more effectively when the iCub adapted its demonstrations, and that the iCub's apparently effortful adaptation led participants to experience him as more helpful.

• Accepted manuscript