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Cited by 279

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Evaluations of an artificial intelligence instructor's voice: Social Identity Theory in human-robot interactions

Edwards, Chad, Edwards, Autumn, Stoll, Brett, Lin, Xialing, Massey, Noelle·2019·Computers in Human Behavior

Abstract

Abstract This study employs the Computers are Social Actors (CASA) paradigm to extend the predictions of Social Identity Theory (SIT) to human-robot interaction (HRI) in the context of instructional communication. SIT posits that individuals gain a sense of personal worth from the groups with which they identify. Previous research has demonstrated that age group identification is meaningful to individuals’ self-concepts. Results demonstrated that higher age identified students rated the older A.I. voice instructor (representing an out-group member) higher for credibility and social presence and reported more motivation to learn than those students with low age identification. Implications are discussed for SIT and design features of computerized voices.

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Crossref · 10.1016/j.chb.2018.08.027

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Metadata

Authors
Edwards, C., Edwards, A., Stoll, B., Lin, X., & Massey, N.
Venue
Computers in Human Behavior
Publisher
Elsevier BV
Published
2019-01
Volume
90
Pages
357-362
ISSN
0747-5632 (ISSN-L)
OpenAlex
W2887919024
Cited by
279
References
8
FWCI
20.62
Type
journal article
Language
en
Open access
closed

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