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Exploring Users’ Mental Models for Anthropomorphized Voice Assistants through Psychological Approaches

Authors :
Dasom Park
Kiechan Namkung
Source :
Applied Sciences, Vol 11, Iss 23, p 11147 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Various perspectives are being studied to increase the usability and persistence of voice assistants (VA) as the use is rapidly expanding to various domains. Particularly, many studies note that users personify VA. Systems designed to suit users differing mental models while using specific systems can provide a positive user experience, increasing usability and persistence. Therefore, we tried to structure the mental model of users using personified VA and proposed these results as an important factor to consider in personifying VA. To determine important factors to consider in personifying VA, this research structures the mental model of users using personified VA. Furthermore, we used two types of psychological approaches that were not applied in previous studies to analyze users’ mental models. Using two types of psychological approaches that were not applied in previous studies, this research analyzed users’ mental models. In Study 1, each user’s thinking process is derived through ZMET (Zaltman metaphor elicitation techniques) as a consensus map. Afterward, in Study 2, correlations between the key components analyzed in Study 1 are validated through RG (repertory grid technique). As a result, the research found that there are three different psychological structures. The first structure is of users who feel human-like empathy and warmth in the use of VA. Meanwhile, the second structure is of users who seek help with problem-solving. The last is the psychological structure of users who regarded anthropomorphic VA as just a machine. Users with this mental model expect the potential for development as a machine rather than the personification of VA. Ultimately, this research is meaningful in that it analyzes each user’s psychological mechanism for personified VA through a psychological approach and derives three new mental models in detail.

Details

Language :
English
ISSN :
11231114 and 20763417
Volume :
11
Issue :
23
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.8d4652f70c91424ba6a8e750972230df
Document Type :
article
Full Text :
https://doi.org/10.3390/app112311147