338
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

How to Provide Feedback? The Role of Robot’s Language and Feedback Framework

&
Pages 1856-1872 | Received 27 Oct 2022, Accepted 06 Jun 2023, Published online: 04 Jul 2023
 

Abstract

Approximately half of the world’s population are bilingual or multilingual. The foreign language effect has been a part of the academic study of people’s decision-making. The Computers are Social Actors (CASA) paradigm posited that people will respond differently when the robot used different social cues. The robot’s language might be an important social cue that makes people have different behavior and experience in the interaction. A limited amount of work has examined the effect of the robot’s language. Thus, this study investigated the effects of the robot’s language (native, foreign) and feedback framework (positive, neutral, negative) on users’ interaction with robots in cognitive tasks. This study further used fNIRS to investigate the effects of these factors on users’ brain activations. The results indicated that: (i) participants had marginally significantly higher performance, and felt significantly higher social presence when the robot used a foreign language; (ii) participants had significantly lower performance when the robot used a neutral feedback framework; (iii) participants had worse experience when the robot used a negative feedback framework; (iv) the use of a foreign language could reduce the effects of the robot’s feedback framework on participants’ performance and brain activations. These findings enrich the research on the foreign language effect, CASA paradigm and the feedback intervention. The findings also have implications for the design and development of robots and conversational agents.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China (No. 71942005) and the Natural Science Foundation of Fujian Province, China (No. 2022J05018).

Notes on contributors

Hanjing Huang

Hanjing Huang is an associate professor in the School of Economics and Management, Fuzhou University. She received her Ph.D. in Management Science and Engineering from Tsinghua University. Her research interests include human factors engineering, human–robot interaction, cross-cultural research, design for older people.

Pei-Luen Patrick Rau

Pei-Luen Patrick Rau is a professor in the Department of Industrial Engineering, Tsinghua University. He received his Ph.D. in Industrial Engineering from Purdue University. His research areas include human factors engineering, human–computer interaction, cross-cultural design, design for older people, human–robot interaction, and service design and evaluation.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.