Memory-Based Personalization for Fostering a Long-Term Child-Robot Relationship
Mike E.U. Ligthart, Mark A. Neerincx, Koen V. Hindriks
- Year
- 2022
- Citations
- 31
Abstract
After the novelty effect wears off children need a new motivator to keep interacting with a social robot. Enabling children to build a relationship with the robot is the key for facilitating a sustainable long-term interaction. We designed a memory-based personalization strategy that safeguards the continuity between sessions and tailors the interaction to the child's needs and interests to foster the child-robot relationship. A longitudinal (five sessions in two months) user study (N = 46, 8–10 y.o) showed that the strategy kept children interested longer in the robot, fosters more closeness, elicits more positive social cues, and adds continuity between sessions.
Keywords
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