Papers
10
Total Citations
229
H-Index
7
About
Fan Ouyang is a researcher whose work bridges robotics engineering and educational technology, with a particular focus on the integration of robots into learning environments and the technical foundations that make such systems possible. Early in his career, Ouyang made contributions to industrial robotics, tackling challenges in dual-robot welding coordination, collision detection using octree-based hierarchical models, and motion planning for redundant manipulators — work that laid a strong technical foundation for his later educational applications. His research trajectory has increasingly shifted toward how robotic technologies can transform teaching and learning, particularly within STEM education and collaborative programming contexts. His most celebrated work, a 2024 multilevel meta-analysis on educational robotics in STEM education, has already amassed 132 citations, signaling its significance as a landmark synthesis in the field. Ouyang has also examined scaffolding strategies in robot-assisted collaborative programming in higher education and proposed frameworks for understanding learner-robot relationships. Collectively, his scholarship addresses both the "how" of building effective robotic systems and the "why" of deploying them pedagogically — making him a valuable voice at the intersection of engineering, cognitive science, and educational innovation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Offline motion planning and simulation of two-robot welding coordination22 citations · 2012
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- 8Octree-based Spherical hierarchical model for Collision detection5 citations · 2012
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- 10Task planning and simulation of two-robot welding coordination2 citations · 2012