Papers
1
Total Citations
4
H-Index
1
About
Yuyang Fang is an emerging scholar in the learning sciences and educational technology, whose work explores how failure—particularly when observed in others—can be leveraged as a powerful tool for classroom learning. Drawing on productive failure (PF) theory, Fang’s most-cited paper, “Observing a robot peer’s failures facilitates students’ classroom learning” (2025, 4 citations), investigates a novel twist on PF: rather than having students experience failure themselves, they watch a robot peer struggle and err. This research demonstrates that vicarious failure can enhance knowledge acquisition without the emotional and cognitive strain of direct problem-solving, offering a scalable, low-stakes alternative for instructional design. Though early in their career, Fang’s work sits at the intersection of human-robot interaction, cognitive load theory, and educational psychology, with implications for AI-assisted classrooms. By reframing failure as a shared, observable experience, Fang is helping to shape more resilient and effective learning environments—one robot misstep at a time.
Research Focus
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Top Papers
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