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Conformity and Trust in Multi-party vs. Individual Human-Robot Interaction
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0001-7890-936X
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0003-4532-014X
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Speech, Music and Hearing, TMH.ORCID iD: 0000-0002-8579-1790
2024 (English)In: Proceedings of the 24th ACM International Conference on Intelligent Virtual Agents / [ed] Rachael Jack, Mathieu Chollet, Ruth Aylett, Timothy Bickmore, Stacy Marsella, Gale Lucas, New York, NY United States: Association for Computing Machinery (ACM) , 2024, article id 4Conference paper, Published paper (Refereed)
Abstract [en]

In this study, we explored how conformity and trust vary in adolescent students’ interactions with a social robot. Specifically, we compared how this was influenced by whether the participants had individual or multi-party interaction with robot and whether the robot was portrayed as an adult or a child through appearance and voice. Our experiment involved 75 Swedish middle school students participating in a card sorting game with the Furhat robot, where the objective was to discuss and reach an agreement on the card sequence. The data analysis focused firstly on the participants’ willingness to rearrange cards following the robot’s suggestions and secondly their post-session subjective trust in the robot’s advice. Results indicated that individuals interacting with the robot individually were more likely to conform to its suggestions than those interacting with it together with a peer. Individuals interacting alone with the robot also showed higher post-session trust levels than those in multi-party settings, indicating group size impacts robot trustworthiness perceptions. However, the robot’s perceived age did not affect the level of conformity. Exploratory analyses also showed that mutual understanding was lower in the multi-party setting, while the child robot condition improved user experience, highlighting the complex influence of group dynamics and robot portrayal on human-robot interactions in education.

Place, publisher, year, edition, pages
New York, NY United States: Association for Computing Machinery (ACM) , 2024. article id 4
Keywords [en]
Human-Robot Interaction, Conformity, Influential Agent, Multiparty Interaction, Child-robot Interaction, Education, Trust
National Category
Computer Sciences Human Computer Interaction Languages and Literature Sociology (Excluding Social Work, Social Anthropology, Demography and Criminology)
Research subject
Computer Science; Education and Communication in the Technological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-358521DOI: 10.1145/3652988.3673954ISI: 001441957400004Scopus ID: 2-s2.0-85215536524OAI: oai:DiVA.org:kth-358521DiVA, id: diva2:1928995
Conference
IVA '24: ACM International Conference on Intelligent Virtual Agents, GLASGOW United Kingdom, September 16-19, 2024
Projects
tmh_rall_convRALLe-laddaEarly Language Development in the Digital Age (e-LADDA)
Funder
EU, Horizon 2020, 857897
Note

Part of ISBN 9798400706257

QC 20250120

Available from: 2025-01-18 Created: 2025-01-18 Last updated: 2025-04-30Bibliographically approved

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fulltext(3506 kB)99 downloads
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Kamelabad, Alireza M.Engwall, OlovSkantze, Gabriel

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