Robocamp at home: Exploring families' co-learning with a social robot: Findings from a one-month study in the wild

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Abstract

Social robots are becoming important agents in several sectors of people's lives. They can act in diferent contexts, e.g., public spaces, schools, and homes. Operating, programming and interacting with these robots will be an essential skill in the future. We present a qualitative and explorative study on how family members collaboratively learn (co-learn) about social robots at their homes. Our one-month in the wild study took place at homes of eight families (N=32) in Finland. We defned a novel model for co-learning about and with a social robot at home, Robocamp. In Robocamp, Alpha Mini robot was introduced and left within the families, who were then provided with weekly robotic challenges to be conducted with the robot. The research data was collected by semi-structured interviews and online diaries. This study provides novel insights about family-based co-learning with social robots in the home context. It also ofers recommendations for implementing family-based co-learning with social robots at homes.

Original languageEnglish
Title of host publicationHRI 2023 - Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
PublisherACM
Pages331-340
Number of pages10
ISBN (Electronic)9781450399647
DOIs
Publication statusPublished - 13 Mar 2023
Publication typeA4 Article in conference proceedings
EventAnnual ACM/IEEE International Conference on Human-Robot Interaction - Stockholm, Sweden
Duration: 13 Mar 202316 Mar 2023

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

ConferenceAnnual ACM/IEEE International Conference on Human-Robot Interaction
Country/TerritorySweden
CityStockholm
Period13/03/2316/03/23

Keywords

  • Co-learning
  • Educational robots
  • Families
  • Homes
  • Social robots
  • User experience

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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