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Assessment of Engagement and Learning During Child-Robot Interaction Using EEG Signals

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Social Robotics (ICSR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13086))

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Abstract

Social robots are being increasingly employed for educational purposes, such as second language tutoring. Past studies in Child-Robot Interaction (CRI) have demonstrated the positive effect of an embodied agent on engagement and consequently learning of the children. However, these studies commonly use subjective or behavioral metrics of engagement that are measured after the interaction is over. In order to gain better understanding of children’s engagement with a robot during the learning phase, this study employed objective measures of EEG. Two groups of Japanese children participated in a language learning task; one group learned French vocabulary from a storytelling robot while seeing pictures of the target words on a computer screen and the other group listened to the same story with only pictures on the screen and without the robot. The engagement level and learning outcome of the children were measured using EEG signals and a post-interaction word recognition test. While no significant difference was observed between the two groups in their test performance, the EEG Engagement Index (\(\frac{\beta }{\theta + \alpha }\)) showed a higher power in central brain regions of the children that learned from the robot. Our findings provide evidence for the role of social presence and engagement in CRI and further shed light on cognitive mechanisms of language learning in children. Additionally, our study introduces EEG Engagement Index as a potential metric for future brain-computer interfaces that monitor engagement level of children in educational settings in order to adapt the robot behavior accordingly.

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Correspondence to Maryam Alimardani .

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Alimardani, M., van den Braak, S., Jouen, AL., Matsunaka, R., Hiraki, K. (2021). Assessment of Engagement and Learning During Child-Robot Interaction Using EEG Signals. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_59

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  • DOI: https://doi.org/10.1007/978-3-030-90525-5_59

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  • Print ISBN: 978-3-030-90524-8

  • Online ISBN: 978-3-030-90525-5

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