Danqing Li

Wenzhou University

Papers

1

Total Citations

32

H-Index

1

About

Danqing Li is a leading researcher in K-12 STEM education, with a particular focus on robotics learning, computational thinking, and embodied cognition. Her most-cited work, “Engaging Young Students in Effective Robotics Education: An Embodied Learning-Based Computer Programming Approach” (2023, 32 citations), addresses a critical challenge in modern education: helping young learners overcome the abstract difficulties of robot construction and programming. Li’s research demonstrates how embodied learning—using physical movement and hands-on interaction—can make complex robotics concepts more accessible and engaging for students. By bridging the gap between theoretical programming knowledge and tangible robot behavior, she has provided educators with practical, evidence-based strategies for integrating robotics into K-12 classrooms. Her work not only advances pedagogical theory but also offers actionable frameworks for curriculum design, making her a key voice in the movement to democratize STEM education. With growing citation impact and a clear focus on solving real-world classroom problems, Danqing Li’s contributions are shaping how the next generation learns to build, code, and think computationally.

Research Focus

Key Achievements

1
H-Index
1
Papers
32
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Engaging Young Students in Effective Robotics Education: An Embodied Learning-Based Computer Programming Approach
32 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Wenzhou University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago