Qiuju Si
Papers
1
Total Citations
28
H-Index
1
About
Qiuju Si’s research lies at the intersection of educational technology, cognitive science, and STEM pedagogy, with a particular focus on how students learn through hands-on problem-solving. Her most cited work, “Troubleshooting to Learn via Scaffolds: Effect on Students’ Ability and Cognitive Load in a Robotics Course” (2020, 28 citations), makes a significant contribution by empirically examining how structured scaffolds can transform troubleshooting—often a frustrating experience—into a powerful learning mechanism. Si demonstrates that carefully designed support not only improves students’ technical abilities but also manages their cognitive load, preventing the overwhelm that can derail learning in complex robotics environments. This work is notable for bridging a critical gap: while the importance of scaffolding and troubleshooting has been acknowledged, few studies have simultaneously analyzed the learning process and the cognitive demands placed on students. By integrating these dimensions, Si provides actionable insights for educators designing courses that require both conceptual understanding and procedural skill. Her research is especially valuable for instructors in engineering and computer science education, offering evidence-based strategies to help students build resilience and deeper comprehension through guided, reflective problem-solving.
Research Focus
Key Achievements
Top Papers
- 1