research-article

Not Your Cup of Tea?: How Interacting With a Robot Can Increase Perceived Self-efficacy in HRI and Evaluation

Authors:

Astrid Marieke Rosenthal-von der P�tten,

Katharina BrockmannAuthors Info & Claims

HRI '17: Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

Pages 483 - 492

https://doi.org/10.1145/2909824.3020251

Published: 06 March 2017 Publication History

Abstract

The goal of this work is to explore the influence of do-it-yourself customization of a robot on technologically experienced students and unexperienced elderly users' perceived self-efficacy in HRI, uncertainty, and evaluation of the robot and interaction. We introduce the Self-Efficacy in HRI Scale and present two experimental studies. In study 1 (students, n=60) we found that any interaction with the robot increased self-efficacy, regardless of whether this interaction involves customization or not. Moreover, individual increases in self-efficacy predict more positive evaluations. In a second study with elderly users (n=60) we could not replicate the general positive effect of the interaction on self-efficacy. Again, we did not find the hypothesized stronger effect of customization on self-efficacy, nor did we find that relationship between self-efficacy increase and evaluation. We discuss limitations of the setting and for questionnaire design for elderly participants.

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Index Terms

Not Your Cup of Tea?: How Interacting With a Robot Can Increase Perceived Self-efficacy in HRI and Evaluation
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. HCI design and evaluation methods
      1. Laboratory experiments
2. Social and professional topics
  1. User characteristics
    1. Age
      1. Seniors

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cover image ACM Conferences

HRI '17: Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

March 2017

510 pages

ISBN:9781450343367

DOI:10.1145/2909824

General Chairs:
Bilge Mutlu
University of Wisconsin-Madison, USA
,
Manfred Tscheligi
University of Salzburg, Austria
,
Program Chairs:
Astrid Weiss
Vienna University of Technology, Austria
,
James E. Young
University of Manitoba, Canada

Copyright � 2017 ACM.

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SIGAI: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
IEEE-RAS: Robotics and Automation

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New York, NY, United States

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Published: 06 March 2017

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Science Support Center of the University of Duisburg-Essen

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HRI '17: ACM/IEEE International Conference on Human-Robot Interaction

March 6 - 9, 2017

Vienna, Austria

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HRI '17 Paper Acceptance Rate 51 of 211 submissions, 24%;

Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

Ayub ADe Francesco ZMehta JYaakoub Agha KHolthaus PNehaniv CDautenhahn K(2024)A Human-Centered View of Continual Learning: Understanding Interactions, Teaching Patterns, and Perceptions of Human Users Toward a Continual Learning Robot in Repeated InteractionsACM Transactions on Human-Robot Interaction10.1145/365911013:4(1-39)Online publication date: 23-Oct-2024
https://dl.acm.org/doi/10.1145/3659110
Meah MQin H(2024)ChatGPT: Advocacy or Opposition Through Mixed MethodsJournal of Computer Information Systems10.1080/08874417.2024.2372036(1-16)Online publication date: 9-Jul-2024
https://doi.org/10.1080/08874417.2024.2372036
Pasparakis ADe Vries JDe Koster R(2023)Assessing the impact of human–robot collaborative order picking systems on warehouse workersInternational Journal of Production Research10.1080/00207543.2023.218334361:22(7776-7790)Online publication date: 2-Mar-2023
https://doi.org/10.1080/00207543.2023.2183343
Seaborn KBarbareschi GChandra S(2023)Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction ResearchInternational Journal of Social Robotics10.1007/s12369-023-00968-415:11(1841-1870)Online publication date: 8-Mar-2023
https://doi.org/10.1007/s12369-023-00968-4
Xavier Macedo de Azevedo FHeimgärtner RNebe K(2022)Development of a Metric to Evaluate the Ergonomic Principles of Assistive Systems, based on the DIN 92419Ergonomics10.1080/00140139.2022.2127920(1-70)Online publication date: 22-Sep-2022
https://doi.org/10.1080/00140139.2022.2127920
Förster FAlthoefer K(2021)Attribution of autonomy and its role in robotic language acquisitionAI & SOCIETY10.1007/s00146-020-01114-837:2(605-617)Online publication date: 16-Jan-2021
https://doi.org/10.1007/s00146-020-01114-8
Straßmann CKrämer NBuschmeier HKopp S(2020)Age-Related Differences in the Evaluation of a Virtual Health Agent’s Appearance and Embodiment in a Health-Related Interaction: Experimental Lab StudyJournal of Medical Internet Research10.2196/1372622:4(e13726)Online publication date: 23-Apr-2020
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Lugrin BRosenthal-von der Pütten AHahn S(2019)Identifying Social Context Factors Relevant for a Robotic Elderly AssistantSocial Robotics10.1007/978-3-030-35888-4_52(558-567)Online publication date: 17-Nov-2019
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Caleb-Solly PDogramadzi SHuijnen CHeuvel H(2018)Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptanceThe Information Society10.1080/01972243.2018.144425534:3(153-165)Online publication date: 26-Apr-2018
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