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

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.