Affiliation:
1. RWTH Aachen University, Aachen, Germany
Abstract
This methodological article discusses the influence of individuals’ beliefs about their abilities to use and control robotic technologies on their evaluation of human-robot-interaction (HRI). We conducted three surveys to develop and validate a new measure of Self-Efficacy in HRI. Exploratory factor analysis revealed a two-factorial (factors perceived self-efficacy and loss of control) solution with good reliability (Study 1, n = 201). Confirmatory factor analysis did not confirm the two-factorial structure. Instead, it revealed a better model fit for a one-factorial solution for a German (Study 2, n = 450) and an English version (Study 3, n = 209) of the scale with good indices for convergent and divergent validity. The final questionnaire with 18 items was used in two experimental studies (Study 4, n = 120). We found that interacting with a robot increased self-efficacy and that individual changes in self-efficacy predict more positive evaluations within a student sample, but not a sample of seniors. Interviews with seniors from this study suggested shortening the scale, and revising the instructions and answering scheme. The revised scale was again subject to confirmatory factor analysis (Study 5, n = 198), confirming the one-factorial solution for the German and the English version of the scale. We discuss potential use cases for the scale in HRI research.
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Human-Computer Interaction
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3. pages = 123--456 publisher = ACM isbn = 9781450343367 editor = Mutlu Bilge booktitle = Proceedings of the 2017 ACMIEEE International Conference on Human-Robot Interaction year = 2017 address = {S.l.} doi = 123-456 anonymized title = anonymized paper. {n. d.}. pages = 123--456 publisher = ACM isbn = 9781450343367 editor = Mutlu Bilge booktitle = Proceedings of the 2017 ACMIEEE International Conference on Human-Robot Interaction year = 2017 address = {S.l.} doi = 123-456 anonymized title = anonymized paper. {n. d.}.
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