Details

Autor(en) / Beteiligte

• Huber, Stephan
• Rathß, Natalie
• Goyal, Tesh
• Peters, Anicia
• Mueller, Stefanie
• Väänänen, Kaisa
• Kristensson, Per Ola
• Schmidt, Albrecht
• Williamson, Julie R.
• Wilson, Max L.

Titel

Empathic Accuracy and Mental Effort During Remote Assessments of Emotions

Ist Teil von

• Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023, p.1-13

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2023

Link zum Volltext

Quelle

ACM Digital Library

Beschreibungen/Notizen

• Observing users in remote settings is unfavorable because it adds filters altering the information that underlie judgement. Still, the COVID pandemic led to an unprecedented popularity of remote user experience tests. In this work, we revisited the question, which information is most important for evaluators to assess users’ emotions successfully and efficiently. In an online study, we asked N=55 participants to assess users’ emotions from short videos of 30 interaction situations. As independent variable, we manipulated the combination of the information channels video of users, video of the interactive technology, and audio within subjects. Our findings indicate that empathic accuracy is highest and mental effort is lowest when all stimuli are present. Surprisingly, empathic accuracy was lowest and mental effort highest, when only video of users was available. We discuss these findings in the light of emotion literature focusing on persons’ facial expressions and derive practical implications for remote observations.