Anne Pfeifer

University of Würzburg, University of Minnesota

Papers

Total Citations

H-Index

About

Anne Pfeifer’s research lies at the compelling intersection of social robotics, human-robot interaction, and educational technology. Her most influential work explores how robots can scaffold motivation and enhance learning outcomes, particularly through the nuanced design of robot social characteristics. In her highly cited 2018 study (48 citations), she demonstrated that a social robot’s ability to provide motivational scaffolding significantly improves learner engagement and performance. Expanding this line of inquiry, her work on robot gender and learning materials (17 citations) revealed that a robot’s perceived gender can subtly influence learning success, challenging researchers to consider how robot embodiment shapes educational dynamics. Earlier in her career, Pfeifer contributed foundational insights to multi-robot systems, designing heterogeneous robotic teams with adaptive sensing capabilities (24 citations). Her work bridges technical robotics engineering with cognitive and social psychology, offering practical guidance for creating robots that are not only functional but also pedagogically effective. Pfeifer’s research is essential reading for anyone interested in designing robots that can genuinely support human learning and motivation.