Affective and Cognitive Feedback from a Robot for Human-attributed Failure Handling

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Authors: Jihwan Kim, Myeongul Jung, Donghyun Kang, Taehyun James Rhee, Dooyong Kim, Kwanguk Kenny Kim
Cited by: 1
References: 48

Abstract

Human–robot collaboration increasingly frames robots as teammates rather than tools, yet there is limited guidance on how robots should respond when failures are attributed to the human collaborator. We investigate how robot collaborators should respond to support collaboration experience after a human-attributed failure. In a 4 × 2 mixed factorial design (N = 60), participants completed a collaborative block-stacking task with either a humanoid robot (NAO) or a human collaborator under four scenarios: success, affective feedback, cognitive feedback, and no feedback. We measured collaboration experience in terms of teamwork quality, perceived copresence, and intimacy. Both affective and cognitive feedback improved these outcomes compared with no feedback: affective cues yielded the strongest socio-relational gains (copresence, intimacy), whereas cognitive cues more strongly enhanced perceived teamwork quality. These patterns were consistent across human–robot and human–human collaboration, indicating shared team-level expectations that extend beyond the individual actor. The results provide empirical evidence for socially adaptive robots that pair brief emotional reassurance with concrete guidance to support collaboration after human-attributed failures.

Fields of Study & Subjects

Social Robot Interaction and HRI Human-Automation Interaction and Safety Action Observation and Synchronization

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–16
Publication date
13 April 2026