Academic Profile : Faculty

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Asst Prof Zhu Gaoxia
Assistant Professor, National Institute of Education - Learning Sciences and Assessment
External Links
Dr. Zhu Gaoxia is an assistant professor in the Learning Sciences and Assessment Academic Group. Before joining NIE, she worked as a postdoctoral associate at the Department of Psychology, Cornell University, researching how adolescents’ psychological factors change during their self-driven learning. Gaoxia received her Ph.D. degree in Curriculum & Pedagogy (specialization in Learning Sciences) from the University of Toronto, doing Knowledge Building, CSCL, learning analytics, emotion, and STEM education research. She supervises research assistants and graduate students. Her mentees have published in top-tier journals, presented at top conferences, and received the Outstanding Student Paper Award Nomination or Undergraduate Poster Award.
Dr. Zhu's research operates at the nexus of Learning Sciences, Emerging Technologies for Education (such as AI for Education), and Motivational Psychology. This interdisciplinary approach allows for a comprehensive exploration of how technology and psychology influence learning. Her work is particularly concentrated on three main areas:
1. Student-Student Collaborative Inquiry Learning: She delves into how students interact with each other in computer-supported learning environments, focusing on social, cognitive, and emotional dynamics. This involves analyzing their knowledge building, collaboration patterns, and emotional responses using learning analytics, discourse analysis, and observational studies.
2. Human-AI and Human-Human-AI Collaboration: She explores the dynamics of student collaboration with peers and AI tools and investigates the effects of various interaction types on creativity, sense of agency, productive knowledge building, and emotional wellbeing.
3. Design of Pedagogical and Technological Supports: This aspect focuses on creating and implementing tools to foster a more engaging and emotionally supportive learning environment for students.
Her research contributes to a deeper understanding of the evolving landscape of education, where technology and collaborative learning play pivotal roles. The findings not only advance academic knowledge in these fields but also provide practical insights for educators aiming to optimize learning environments and prepare future-oriented students in the digital age.
  • Facilitate Students' Knowledge Building and Supportive Emotions through Emotion Analytics and Socially Shared Emotion Regulation
  • Foster Singapore Secondary School Students' Data Science Competencies : A Knowledge Building Approach
  • Designing Group Activities to Enhance Undergraduates' Interdisciplinary Learning
  • Are our children feeling good and functioning well' Examining student well-being us ing a multi-dimensional approach
CSCL 2023 Outstanding Student Paper Award Nomination (by supervised student)
Co-author and mentor, Undergraduate Poster Award, 10th Conference on Emerging Adulthood
Ontario Graduate Scholarship
Doctoral Completion Award, University of Toronto
Chinese Government Award for Outstanding Self-Financed Students Abroad
Outstanding Graduate, Beijing Normal University
Outstanding Master’s Thesis, Beijing Normal University
Fellowships & Other Recognition
Attendee, International Society of the Learning Sciences Early Career Workshop
Courses Taught
MSL903 Learning Analytics for Science of Learning
MID905 Foundations of Learning and Instruction
MLT902 Computer Supported Collaborative Learning and Knowledge Building
QED50G Technologies for Meaningful Learning