Xiaoqing Yang
Papers
1
Total Citations
3
H-Index
1
About
Xiaoqing Yang is a pioneering researcher at the intersection of artificial intelligence and early childhood education, with a primary focus on robot-assisted teaching methodologies. Her most-cited work, "Evaluation of the effectiveness of robot-assisted teaching in the training room in preschool education" (2024), has garnered 3 citations and represents a significant contribution to understanding how AI technologies can be integrated into preschool learning environments. In this study, Yang proposed a novel robot-assisted teaching model that incorporates coordinate transformation and velocity modeling to enhance interactive learning experiences. Her research directly responds to national policy initiatives promoting AI integration in education, making her work both timely and policy-relevant. Yang's major contribution lies in developing practical frameworks that bridge theoretical AI concepts with real-world classroom applications, particularly in training room settings. Her findings offer valuable insights for educators and technologists seeking to implement robotic systems in early childhood education, demonstrating measurable improvements in teaching effectiveness. As a researcher, Yang continues to explore how intelligent systems can transform traditional pedagogical approaches, positioning her at the forefront of educational technology innovation.
Research Focus
Key Achievements
Top Papers
- 1