Robot Assisted Learning and Rehabilitation
Social robots have a real potential as learning or teaching companions for children in classrooms or at home, for elderly people to help maintain their cognitive and physical abilities, and for learners with deficiencies by adapting content to their capabilities. Robots show the potential to improve individual adaptation by learning from and with the user. Several research projects have aimed to apply HRI to education and learning to teach disciplines other than STEM, such as languages or handwriting. Robots also have the potential to enhance learning via kinaesthetic interaction, as well as enabling users to improve their self-esteem and providing adaptive empathic feedback. Robots can thus be a means to engage the learner and to motivate him in the learning task.
While robots for learning is quite an applied topic of HRI, we found that the context of learner-robot interaction is one of the most challenging and interesting for research, while having the potential to be very impactful. In an effort to go beyond individual interfaces or projects, this project aims to investigate and generate principles for the design of the learner-robot interaction.
This research is conducted in collaboration with EPFL.
- N. Rakhymbayeva, Z. Balgabekova, M. Nurmukhamed, K. Burunchina, W. Johal and A. Sandygulova, "To Transfer or Not To Transfer: Engagement Recognition within Robot-assisted Autism Therapy," 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022, pp. 1002-1006, doi: 10.1109/HRI53351.2022.9889577.
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- Jennifer K. Olsen, Arzu Guneysu Ozgur, Kshitij Sharma, Wafa Johal. Leveraging eye tracking to understand children’s attention during game-based, tangible robotics activities, International Journal of Child-Computer Interaction, Volume 31, 2022, https://doi.org/10.1016/j.ijcci.2021.100447
- Amirova, A., Rakhymbayeva, N., Yadollahi, E., Sandygulova, A., & Johal, W. (2021). 10 years of Human-Nao Interaction Research: A Scoping Review. Frontiers in Robotics and AI, 8.
- Ozgur, A. G., Wessel, M. J., Olsen, J. K., Cadic-Melchior, A. G., Zufferey, V., Johal, W., ... & Hummel, F. C. (2022). The effect of gamified robot-enhanced training on motor performance in chronic stroke survivors. Heliyon, 8(11), e11764.