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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

ClosenessNoveltyPersonalizationRobotTerm (time)Key (lock)PsychologySocial robotComputer scienceHuman–computer interaction

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