The Limits of Robot Moderators: Evidence Against Robot Personalization and Participation Equalization in a Building Task
Hayley Owens, Reuben M. Aronson, Elaine Schaertl Short · 2024
Prior research has suggested that equalizing participation may benefit group performance and group cohesion. Robot-moderated groups have largely focused on improving member participation by focusing on the least performing member and do not consider the frequency of interaction or type of interaction. We introduce a robot moderator that varies its frequency and interaction types to observe the impact on groups in terms of performance and group cohesion. We investigate this in user studies across four conditions for equalizing participation. Leveraging Bayesian statistical methods that can evaluate evidence both for and against the null hypothesis, we find evidence that neither personalizing robot actions nor balancing the target of the robot’s assistance affected user experience in the group (as measured by performance, group cohesion, and variance of participation). We find a lack of evidence for equalization of participation impacting performance and group cohesion. Additionally, we also find positive evidence against the correlation of equalized participation and group cohesion in our task and weak evidence against equalized participation correlating with performance. In addition to guiding future researchers regarding robot behaviors that may not be effective in affecting groups, this work is an important negative result suggesting that equalizing participation may not be adequate to improve group performance and cohesion in all tasks.