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About

Daniel Davison is a pioneering researcher in child-robot interaction and educational robotics, whose work sits at the crossroads of human-robot interaction, learning technology, and inclusive design. With over 240 citations across his most influential publications, Davison has made substantial contributions to understanding how social robots can meaningfully support children's learning in real-world classroom environments. His landmark 2020 study, "Working with a Social Robot in School" (46 citations), demonstrated the viability of long-term, unsupervised robot deployments in educational settings, while complementary work explored how robot-delivered praise shapes children's growth mindsets. Davison has been equally influential in shaping the field's methodology, with his 2016 review of user-centered evaluation approaches for child-robot interaction becoming an essential reference for researchers designing rigorous studies. A particularly notable thread of Davison's research addresses the needs of autistic children, including minimally verbal learners — developing accessible, teacher-teleoperated systems and examining how robot predictability supports engagement in this community. His involvement in the EASEL Project further reflects his commitment to building symbiotic, adaptive educational human-robot systems. Across his career, Davison's work consistently champions child-centered design, making him an important voice in shaping the responsible and effective integration of robots into education.