Learning from robotic artefacts: A quest for strong concepts in Human-Robot Interaction

Описание: Learning from robotic artefacts: A quest for strong concepts in Human-Robot Interaction
Nazli Cila, Cristina Zaga, Maria Luce Lupetti

DIS '21: ACM Designing Interactive Systems Conference 2021
Session: Social Robots

Abstract
This paper is a methodological replication of Barendregt et al. [11], who urged Child-Computer Interaction field to embrace Intermediate-Level Knowledge as a meaningful and valid way of generating knowledge. We extend this epistemological gap to the Human-Robot Interaction (HRI). Currently, artefact-centered papers—papers that present the development of an artefact—seem to be one of the primary ways that the HRI field generates knowledge. In this paper, we made an analysis of all papers presented at the HRI Conference from 2006 to 2020. Our results indicate that the 41,2% of the papers were artefact-centered; and the impact of them, measured in the number of citations, was significantly lower than other kinds of papers. We used 23 artefact-centered papers to formulate two strong concepts and investigate how the foundational design epistemology about intermediate-level knowledge and RtD can contribute to other design-related disciplines to produce useful and valuable knowledge.

DOI:: https://doi.org/10.1145/3461778.3462095
WEB:: https://dis.acm.org/2021

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