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EyeMeet: A Joint Attention Support System for Remote Meetings

Langner, Moritz ORCID iD icon 1; Toreini, Peyman 1; Maedche, Alexander 1
1 Institut für Wirtschaftsinformatik und Marketing (IISM), Karlsruher Institut für Technologie (KIT)


A major challenge in remote meetings is that awareness cues, such as gaze, become degraded despite playing a crucial role in communication and establishing joint attention. Eye tracking allows overcoming these obstacles by enabling augmentation of remote meetings with gaze information. In this project, we followed a participatory approach by first distributing a scenario-based survey to students (n=79) to uncover their preference of eye-based joint attention support (real-time, retrospective, real-time & retrospective, no) for remote university meetings. Building on these findings, we developed EyeMeet, an eye-based joint attention support system that combines state-of-the-art real-time joint attention support with a retrospective attention feedback for remote meetings. In a four-week study, two student groups worked remotely on course assignments using EyeMeet. Our findings of the study highlight that EyeMeet supports students in staying more focused on the meetings. Complementing real-time joint attention support, retrospective joint attention feedback is recognized to provide valuable support for reflecting and adapting behavior for upcoming meetings.

DOI: 10.1145/3491101.3519792
Zitationen: 6
Zitationen: 4
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 27.04.2022
Sprache Englisch
Identifikator ISBN: 978-1-4503-9156-6
KITopen-ID: 1000145953
Erschienen in CHI Conference on Human Factors in Computing Systems Extended Abstracts, 30th April - 06th May 2022, New Orleans
Veranstaltung Conference on Human Factors in Computing Systems (CHI 2022), New Orleans, LA, USA, 29.04.2022 – 05.05.2022
Verlag Association for Computing Machinery (ACM)
Seiten 1–7
Nachgewiesen in Dimensions
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