This paper reframes findings from two prior case studies on Zoom Fatigue in avatar-based virtual learning environments through the lens of Mori’s Uncanny Valley (UV) theory. The two studies, conducted within a master’s program at a German university, compared six desktop-based learning environments varying in avatar realism: face-to-face teaching, Zoom with camera, Zoom with stylized 2D avatars, Gather Town (2D pixel avatars), and Frame with both a non-humanoid “Android” avatar and a humanoid avatar. Using a 9-item questionnaire derived from the Zoom Exhaustion & Fatigue (ZEF) scale (5-point Likert, N=17–20 per condition), results show that the Android avatar—which combines a human body form with a non-humanoid appearance—produced the highest general fatigue (M=3.67) across all six conditions, even exceeding face-to-face teaching (M=3.60). The stylized Zoom avatar produced the lowest fatigue (M=2.72). Mapping these six conditions onto a realism continuum reveals a pattern consistent with the UV hypothesis: fatigue does not decrease linearly with increasing realism but peaks at the point of maximal perceptual mismatch. These findings suggest that avatar design for virtual learning environments should either remain clearly stylized or achieve sufficiently high realism to avoid the UV effect, and that intermediate, near-human representations may inadvertently increase student exhaustion.

Authors:
Gerhard Hube, Technical University of Applied Sciences Würzburg-Schweinfurt, Germany
Hakan Arda, University of Applied Sciences Wuerzburg-Schweinfurt, Germany
Nicholas Mueller, University of Applied Sciences Wuerzburg-Schweinfurt, Germany
Christian Moellmann, University of Applied Sciences Wurzburg-Schweinfurt, Germany

About the Presenter(s)
Gerhard Hube is Professor of Innovation Management and Future Technologies at THWS Würzburg-Schweinfurt. Within the long-term research study "Avatar Campus," he is evaluating and comparing the use of digital avatar based learning environments.

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