Effects of Perceived Agency and Message Tone in Responding to a Virtual Personal Trainer (bibtex)
by Gale M Lucas, Nicole Kramer, Clara Peters, Lisa-Sophie Taesch, Johnathan Mell, Jonathan Gratch
Abstract:
Research has demonstrated promising benefits of applying virtual trainers to promote physical fitness. The current study investigated the value of virtual agents in the context of personal fitness, compared to trainers with greater levels of perceived agency (avatar or live human). We also explored the possibility that the effectiveness of the virtual trainer might depend on the affective tone it uses when trying to motivate users. Accordingly, participants received either positively or negatively valenced motivational messages from a virtual human they believed to be either an agent or an avatar, or they received the messages from a human instructor via skype. Both self-report and physiological data were collected. Like in-person coaches, the live human trainer who used negatively valenced messages were well-regarded; however, when the agent or avatar used negatively valenced messages, participants responded more poorly than when they used positively valenced ones. Perceived agency also affected rapport: compared to the agent, users felt more rapport with the live human trainer or the avatar. Regardless of trainer type, they also felt more rapport - and said they put in more effort - with trainers that used positively valenced messages than those that used negatively valenced ones. However, in reality, they put in more physical effort (as measured by heart rate) when trainers employed the more negatively valenced affective tone. We discuss implications for human--computer interaction.
Reference:
Effects of Perceived Agency and Message Tone in Responding to a Virtual Personal Trainer (Gale M Lucas, Nicole Kramer, Clara Peters, Lisa-Sophie Taesch, Johnathan Mell, Jonathan Gratch), In Proceedings of the 18th International Conference on Intelligent Virtual Agents, ACM, 2018.
Bibtex Entry:
@inproceedings{lucas_effects_2018,
	address = {Sydney, Australia},
	title = {Effects of {Perceived} {Agency} and {Message} {Tone} in {Responding} to a {Virtual} {Personal} {Trainer}},
	isbn = {978-1-4503-6013-5},
	url = {https://dl.acm.org/citation.cfm?id=3267855},
	doi = {10.1145/3267851.3267855},
	abstract = {Research has demonstrated promising benefits of applying virtual trainers to promote physical fitness. The current study investigated the value of virtual agents in the context of personal fitness, compared to trainers with greater levels of perceived agency (avatar or live human). We also explored the possibility that the effectiveness of the virtual trainer might depend on the affective tone it uses when trying to motivate users. Accordingly, participants received either positively or negatively valenced motivational messages from a virtual human they believed to be either an agent or an avatar, or they received the messages from a human instructor via skype. Both self-report and physiological data were collected. Like in-person coaches, the live human trainer who used negatively valenced messages were well-regarded; however, when the agent or avatar used negatively valenced messages, participants responded more poorly than when they used positively valenced ones. Perceived agency also affected rapport: compared to the agent, users felt more rapport with the live human trainer or the avatar. Regardless of trainer type, they also felt more rapport - and said they put in more effort - with trainers that used positively valenced messages than those that used negatively valenced ones. However, in reality, they put in more physical effort (as measured by heart rate) when trainers employed the more negatively valenced affective tone. We discuss implications for human--computer interaction.},
	booktitle = {Proceedings of the 18th {International} {Conference} on {Intelligent} {Virtual} {Agents}},
	publisher = {ACM},
	author = {Lucas, Gale M and Kramer, Nicole and Peters, Clara and Taesch, Lisa-Sophie and Mell, Johnathan and Gratch, Jonathan},
	month = nov,
	year = {2018},
	keywords = {Virtual Humans, UARC},
	pages = {247--254}
}
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