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The majority of research on infants’ and children’s understanding of emotional expressions has focused on their abilities to use emotional expressions to infer how other people feel. However, an emerging body of work suggests that emotional expressions support rich, powerful inferences not just about emotional states but also about other unobserved states, such as hidden events in the physical world and mental states of other people (e.g., beliefs and desires). Here we argue that infants and children harness others’ emotional expressions as a source of information for learning about the physical and social world broadly. This “emotion as information” framework integrates affective, developmental, and computational cognitive sciences, extending the scope of signals that count as “information” in early learning.
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Designing Emotionally Expressive Social Commentary to Facilitate Child-Robot Interaction
Emotion expression in human-robot interaction has been widely explored, however little is known about how such expressions should be coupled with feelings and opinions expressed by a social robot. We explored how 12 children experienced emotionally expressive social commentaries from a reading companion robot across five interaction styles that differed in their non-verbal emotional expressiveness and opinionated conversational styles (neutral, divergent, or convergent opinions). We found that, while the robot’s opinions and non-verbal emotion expressions affected children’s experiences with the robot, the speech content of the commentaries was the more prominent factor in their experience. Additionally, children differed in their perceptions of social commentary: while some expressed a sense of connection-making with the robot’s self-disclosure commentaries, others felt distracted by them or felt like the robot was off-topic. We recommend designers pay particular attention to the robot’s speech content and consider children’s individual differences in designing emotional and opinionated speech.
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- Award ID(s):
- 1906854
- PAR ID:
- 10293591
- Date Published:
- Journal Name:
- IDC '21: Interaction Design and Children
- Page Range / eLocation ID:
- 314 to 325
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3459990.3460714
