Building creativity in a remote group is challenging, and various methods to improve it have been investigated. However, the effect of a real-time feedback system on computer-mediated group creativity outcome remains undetermined. In this study, we studied the creativity performance of 20 two-person groups (dyads) while they engaged in a group alternative uses task via video-mediated communication and received real-time feedback cues based on turn-taking. The study included three conditions: turn-taking encouragement feedback (TTF), random time feedback (RF), and no feedback (NF). To probe the underlying mechanism, we assessed creativity outcomes, participants' mood, and the temporal characteristics of the feedback effect type (i.e., slow gradual or instantaneous). The performance results revealed that TTF can enhance creativity outcome in the three dimensions of fluency, originality, and index of convergence. Comparing the self-reported moods indicated that the TTF cues heightened negative valence with high emotional arousal. While the results did not show any slow gradual changes in idea generation and idea quality differences between conditions, the results showed that the feedback cue impact was instantaneous. The results also indicated a significant instantaneous effect of immediate turn-taking on idea generation. Our findings suggest that the TTF condition enhanced cognitive persistence rather than cognitive flexibility during the remote group creativity session. The results of this study can be useful not only in remote human-tohuman communications, but also in designing social robots and agents.
INDEX TERMSGroup creativity, Real-time feedback, Remote group, Turn-taking, Video-mediated communication. S. Hosseini et al.: Real-Time Feedback Impacts on Remote Group Creativity SARINASADAT HOSSEINI was born in Rasht, Iran in 1994. She received the B.S. degree in electrical Engineering from the Shahid Beheshti University, Tehran, Iran, in 2016 and the M.S degree in computer science from the Tokyo Institute of Technology, Japan in 2019. Her main areas of research are human-computer interaction, multimodal affective computing, learning analytics, and educational technologies.