Are Robots More Engaging When They Respond to Joint Attention? Findings from a Turn-Taking Game with a Social Robot Articles uri icon

publication date

  • August 2025

start page

  • 1

end page

  • 30

issue

  • 15

volume

  • 15

Electronic International Standard Serial Number (EISSN)

  • 2076-3417

abstract

  • Joint attention, the capacity of two or more individuals to focus on a common event simultaneously, is fundamental to human¿uman interaction, enabling effective communication. When considering the field of social robotics, emulating this capability might be necessary for promoting natural interactions and thus improving user engagement. Responding to joint attention (RJA), defined as the ability to react to external attentional cues by aligning focus with another individual, plays a critical role in promoting mutual understanding. This study examines how RJA impacts user engagement during human-robot interaction. The participants play a turn-taking game against a social robot under two conditions: with our RJA system active and with the system inactive. Auditory and visual stimuli are introduced to simulate real-world dynamics, testing the robot's ability to detect and follow the user's focus of attention. We use a twofold approach to evaluate the system's impact on the user's experience during the interaction. On the one hand, we use head pose telemetry to quantify attentional aspects of engagement, including measures of distraction and focus during the interaction. On the other hand, we use a post-experimental questionnaire incorporating the User Engagement Scale Short Form to assess engagement. The results regarding telemetry data reveal reduced distraction and improved attentional consistency, highlighting the system's ability to maintain attention on the current task effectively. Furthermore, the questionnaire responses show that RJA significantly enhances self-reported engagement when the system is active. We believe these findings confirm the value of attentional mechanisms in promoting engaging human¿obot interactions.

subjects

  • Robotics and Industrial Informatics

keywords

  • distractions; engagement; human-robot interaction; joint attention; responding to joint attention; social robots; user experience