Prof. DAI Yun

B.A. (PKU), M.A. (PKU), M.Ed. (UCSB), Ph.D. (UCSB)

Assistant Professor
Prof. DAI Yun

Prof. DAI Yun

Assistant Professor

HTB Rm. 405
3943 6719


Introduction
Dr. Dai is an Assistant Professor of Curriculum and Instruction at the Chinese University of Hong Kong (CUHK). Before joining the CUHK in the fall of 2019, she worked as Postdoc Fellow in engineering education at the University of Southern California. She is committed to developing new theoretical perspectives and methodological approaches to meet the emerging challenges that AI brings to the forefront of education, humanity, and society. Her current research focuses on: (1) teaching and learning AI literacy in the K-12 context, (2) generative AI in higher education, and (3) personal epistemology of STEM teachers. Her commitment to research extends to community service. She has developed and led an annual summer camp of AI literacy since 2022, where her research team provides inclusive AI education to under-privileged students in upper primary and junior high schools (Grade 5 – 8). She is also the expert reviewer of AI curriculum development in Beijing, Shenzhen, and other major cities.
Research Areas
AI literacy, STEM education, education technology, digital humanity
Courses
PEDU 6126: Special Topics in STEAM Education and Research
PEDU 6052: Curriculum Evaluation: Theory & Practice
PEDU 6004: Ethnographic Study in Education Research
Grants and Funding
  • PI. Early Career Scheme, Research Grant Council. Fostering quality online academic help seeking through an analytics-enhanced course forum in large college classes. 2021-2023.
  • Co-I. Knowledge Transfer Project Fund, Chinese University of Hong Kong. Empowering Youth from Underprivileged Community: Enhancing Programming Skills and Mathematical Knowledge for STEM Teaching and Learning. 2024-2025.
  • PI. Direct Grant at the Chinese University of Hong Kong. Investigating upper primary students’ misconceptions and learning trajectories in an introductory artificial intelligence course. 2023.
  • Co-I. Quality Education Fund, HK Education Bureau. The curriculum development of artificial intelligence and education in Hong Kong schools. 2021-2022.
  • PI. Direct Grant at the Chinese University of Hong Kong. Design-based research on student-facing learning analytics and pedagogical supports for self-regulated learning in online education. 2019-2021.
  • PI. Women in Engineering Visiting Funding Scheme, University of New South Wales, Australia, 2019.
Selected Publications
  1. Dai, Y. (2024). Dual-contrast pedagogy for AI literacy in upper elementary schools. Learning and Instruction, 91 (2024), 101899. https://doi.org/10.1016/j.learninstruc.2024.101899
  2. Dai, Y., Lin, Z.Y., Liu, A., Dai, D., & Wang, W.L. (2024). Effect of an analogy-based approach of artificial intelligence pedagogy in upper primary schools. Journal of Educational Computing Research, 61(8), 159-186. https://doi.org/10.1177/07356331231201342
  3. Dai, Y., Lin, Z.Y., Liu, A., & Wang, W.L. (2024). An embodied, analogical and disruptive approach of AI pedagogy in upper elementary education: An experimental study. British Journal of Education Technology, 55, 417-434. https://doi.org/10.1111/bjet.13371
  4. Tian, Y., Liu, A., Dai, Y., Nagato, K., & Nakao, M. (2024). Systematic synthesis of design prompts for large language models in conceptual design. CIRP Annals. https://doi.org/10.1016/j.cirp.2024.04.062
  5. Dai, Y., Lai, S., Lim, C. P., & Liu, A. (In press). A scoping review of university policies on generative AI in Asia: Promising practices, gaps, and future directions. Journal of Asian Public Policy. DOI: 10.13140/RG.2.2.21783.38563
  6. Dai, Y., Lin, Z.Y., & Liu, A. (In press). Facilitating Students’ Help-seeking and Peer Interactions in Undergraduate Design Education through an Analytics-enhanced forum. Procedia CIRP.
  7. Cha, Y.Y., Dai, Y., Lin, Z.Y., Liu, A., & Lim, C.P. (In press). Empowering engineering educators to support GenAI-enabled learning: proposing a competency framework. Procedia CIRP.
  8. Wen, X.J., Ye, H.Y., Dai, Y., & Ng, O.L. (In press). Integrating artificial intelligence and computational thinking in educational contexts: A systematic review of instructional design and student learning outcomes. Journal of Educational Computing Research.
  9. Dai, Y., Lai, S., Lim, C. P., & Liu, A. (2023). ChatGPT and its impact on research supervision: Insights from Australian postgraduate research students. Australasian Journal of Educational Technology, 39(4), 74–88. https://doi.org/10.14742/ajet.8843
  10. Hu, X., Liu, A., Li, X., Dai, Y., & Nakao, M. (2023). Explainable AI for customer segmentation in product development. CIRP Annals. https://doi.org/10.1016/j.cirp.2023.03.004
  11. Dai, Y., Liu, A., & Lim, C.P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 119, 84-90. https://doi.org/10.1016/j.procir.2023.05.002
  12. Wang, X.Z., Anwer N., Dai, Y. & Liu, A. (2023). ChatGPT for design, manufacturing, and education. Procedia CIRP, 119, 7-14. https://doi.org/10.1016/j.procir.2023.04.001
  13. Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S. Y., Chai, C. S., & Lin, Z. (2023). Collaborative construction of artificial intelligence curriculum in primary schools. Journal of Engineering Education, 112 (1), 23-42. https://doi.org/10.1002/jee.20503
  14. Dai, Y. (2023). Negotiation of epistemological understandings and teaching practices between primary teachers and scientists about artificial intelligence in professional development. Research in Science Education, 53(3), 577-591. https://doi.org/10.1007/s11165-022-10072-8
  15. Xia, Q., Chiu, T. K., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers & Education, 189, 104582. https://doi.org/10.1016/j.compedu.2022.104582
  16. Yue, M., Jong, M. S. Y., & Dai, Y. (2022). Pedagogical design of K-12 artificial intelligence education: A systematic review. Sustainability, 14(23), 15620. https://doi.org/10.3390/su142315620
  17. Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89-101.
  18. Lin, P. Y., Chai, C. S., Jong, M. S. Y., Dai, Y., Guo, Y., & Qin, J. (2021). Modeling the structural relationship among primary students’ motivation to learn artificial intelligence. Computers and Education: Artificial Intelligence, 2, 100006.
  19. Dai, Y., Chai, C. S., Lin, P. Y., Jong, M. S. Y., Guo, Y., & Qin, J. (2020). Promoting students’ well-being by developing their readiness for the artificial intelligence age. Sustainability, 12(16), 6597.
  20. Dai, Y., Liu, A. (2019). Understanding student variances in learning outcomes and task interpretations from multimedia presentations. British Journal of Education Technology, 50(5), 2685-2702.
  21. Dai, Y. (2019). Situating videoconferencing in a connected class toward intercultural knowledge development: A comparative reflection approach. The Internet and Higher Education, 41, 1-10.
  22. Dai, Y., Lu, S., & Liu, A. (2019). Student pathways to understanding the global virtual teams: An ethnographic study. Interactive Learning Environments, 27(1), 3-14.
  23. Dai, Y., Liu, A., Morrison, J., & Lu, S. (2016). Systemic design of interactive learning environment for global engineering courses. International Journal of Engineering Education, 32(6), 2597-2611.
  24. Green, J. L., Joo, J., Dai, Y. Hirsch, T., Chian, M., & David, P. B. (2016). Challenges in understanding different epistemologies for studying learning: A telling case of constructing a new research agenda. International Journal of Educational Research. 84, 119-126.
  25. Liu, A., Dai, Y., & Lu, S. (2015). Effectiveness of E-learning 2.0 tools and services to support learner-learner interactions in a global engineering class. International Journal of Engineering Education, (31)2, 553-566.
  26. Green, J.L., Dai, Y., Joo, J., Williams, E., Liu, A., & Lu, S. (2015). Interdisciplinary dialogues as a site for reflexive exploration of conceptual understandings of teaching–learning relationships. Pedagogies: An International Journal, 10(1), 86-103.