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Wangda Zhu
PolyU Scholars Hub

Wangda Zhu

Assistant Professor

Biography

Dr Wangda Zhu is a doctoral supervisor in interaction design at The Hong Kong Polytechnic University. He received his Ph.D. in Human-Centered Design and M.Arch. from Cornell University, and his B.Eng. and B.Arch. from Zhejiang University. Before joining PolyU, he worked as a Postdoctoral Research Fellow at the University of Florida, an Adjunct Lecturer at the University of Pittsburgh, and a User Experience Researcher at Google. His research focuses on Human-Centered AI for Learning and Creativity, integrating interdisciplinary approaches from artificial intelligence, human–computer interaction, learning sciences, and learning analytics to create future learning environments. Dr Zhu has published more than 50 peer-reviewed journal articles and conference papers in leading venues, including Computers & Education, BJET, ACM CHI, ACM Multimedia, AIED, and LAK. His work has received Best Paper Awards and Nominations at international conferences, such as LAK and ASEE. He currently serves as an Associate Editor of Behaviour & Information Technology and as a reviewer for leading journals and conferences, including Computers & Education, Design Studies, ACM CHI, and AIED.

Dr Zhu is now actively looking for 1 postdoc and 1 to 2 PhD students in learning system design and development starting in 2027 (e.g., Creative Learning System, Teachable Agent, Social Networking Tool). Please feel free to send your resume to his email if you are interested in the application. Ideally, you need to have experience in application design and development, and statistical analysis. Candidates may have a background in educational technology/computer science/human factors/human-computer interaction/environmental design and a passion for AI-powered learning technologies. Prospective postdoc candidates are encouraged to explore funding opportunities such as PolyU Postgraduate Fellowship and Scholarship Schemes and RGC Postdoctoral Fellowship Scheme.

Education and Academic Qualifications

  • PhD, College of Human Ecology, Cornell University
  • Master, College of Architecture, Art, and Planning, Cornell University
  • Bachelor, College of Computer Science and Technology, Zhejiang University
  • Bachelor, College of Civil Engineering and Architecture, Zhejiang University

Teaching Area

  • Interaction Design
  • UX Research Methods

Research Outputs

Zhu, W., Xing, W., Kim, E., Li, C., Wang, Y., Lee, J., & Liu, Z. (2025) Integrating Image-Generative AI into Conceptual Design in Computer-Aided Design Education: Exploring Student Perceptions, Prompt Behaviors, and Artifact Creativity. Educational Technology & Society 28.3 (2025): 166-183. https://doi.org/10.30191/ETS.202507_28(3).SP11


Li, H., Xing, W., Li, C., Zhu, W., & Oh, H. (2025). Are simpler math stories better? Automatic readability assessment of GAI‐generated multimodal mathematical stories validated by engagement. British Journal of Educational Technology, 56(3), 1092-1117. https://doi.org/10.1111/bjet.13554


Lyu, B., Li, C., Li, H., Oh, H., Song, Y., Zhu, W., & Xing, W. (2025). The role of teachable agents’ personality traits on student-AI interactions and math learning. Computers & Education, 234, 105314. https://doi.org/10.1016/j.compedu.2025.105314


Zhu, W., Xing, W., Lyu, B., Li, C., Zhang, F., & Li, H. (2025, March). Bridging the gender gap: The role of AI-powered math story creation in learning outcomes. In Proceedings of the 15th International Learning Analytics and Knowledge Conference (pp. 918-923). https://doi.org/10.1145/3706468.3706539


Xing, W., Song, Y., Li, C., Liu, Z., Zhu, W., & Oh, H. (2025). Development of a generative AI‐powered teachable agent for middle school mathematics learning: A design‐based research study. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13586


Zhu, W., Zhu, G., & Hua, Y. (2024). Enhancing undergraduates’ engagement in a learning community by including their voices in the technological and instructional design. Computers & Education, 214, 105026. https://doi.org/10.1016/j.compedu.2024.105026


Li, C., Zhu, W., Xing, W., & Guo, R. (2024). Analyzing Student Attention and Acceptance of Conversational AI for Math Learning: Insights from a Randomized Controlled Trial. In Proceedings of 2024 Learning Analytics and Knowledge (LAK 2024). Kyoto, Japan. https://doi.org/10.1145/3636555.3636895


Zhu, W., & Hua, Y. (2023). Enhancing students’ learning experience using social networking applications: evidence from a random experiment. Interactive Learning Environments, 1-25. https://doi.org/10.1080/10494820.2023.2255229


Zhu, W., Hua, Y., Zhu, G., & Wang, L. (2022). Share and embrace demographic and location diversity: Creating an Instagram‐based inclusive online learning community. British Journal of Educational Technology, 53(6), 1530-1548. https://doi.org/10.1111/bjet.13272

 

 

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