Exploring a Real-time Feedback Display of Non-verbal Cues in Online Work Meetings to Support Self-Presentation
Kevin Chow, Roy Rutishauser, André N. Meyer, Joanna McGrenere, Thomas Fritz
Abstract
Expressing oneself appropriately in online meetings through non-verbal cues can be challenging for knowledge workers. Automatic non-verbal cue detection technologies have the potential to support workers' self-presentation efforts through real-time feedback, but little is known about workers' reactions to and the implications of doing so. We designed and implemented Novecs as a technology probe of a real-time feedback display that automatically detects and signals users' own non-verbal cues -smiling, nodding, gaze, and posture. Novecs was deployed in an exploratory field study (n=18) to support knowledge workers' self-presentation in their everyday meetings. Post-study interviews reveal how Novecs' real-time feedback helped increase in-the-moment self-awareness, and how neutrally-framed feedback may help navigate tensions between authentic and in-authentic self-presentation. Participants also emphasized the need for natural timing when adjusting non-verbal cues in-meeting. We discuss design opportunities and challenges of real-time, non-verbal cue feedback systems, such as personalizing feedback based on different meeting types.
CCS Concepts: • Human-centered computing → Empirical studies in HCI; Interactive systems and tools; Field studies.
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