Matthew Dooner
Papers
1
Total Citations
7
H-Index
1
About
Matthew Dooner is a pioneering researcher at the intersection of robotics, education, and developmental psychology, whose work explores how robotic agents can serve as tools for learning and human-robot interaction. His most influential contribution, the 2006 paper "Educational Robots: Three Models for the Research of Learning Theories and Human-Robot Interaction" (7 citations), emerged from a unique collaboration between Tulane University’s Electrical Engineering and Computer Science department and graduate students in education and developmental psychology from the University of New Orleans. This interdisciplinary study, conducted with students from the "AI Robotics" class using Sony robots, established foundational frameworks for using robots to investigate learning theories in young children. Though modest in citation count, Dooner’s work is notable for its early, integrative approach—bridging technical robotics with empirical education research at a time when the field was nascent. His research remains a touchstone for scholars examining how embodied AI can shape cognitive development and pedagogical strategies, highlighting the potential of human-robot interaction to transform early childhood education.
Research Focus
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Top Papers
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