Professor LEE, Min

Learner Agency

Feedback

Learning Designs

Learning Theories and Perspectives

Technology Enhanced Learning

2025 Dean's Commendation Award 2025 (Ph.D.), Nanyang Technological University, National Institute of Education (Research study: Multiple-case study on Learner-ChatGPT interactions from a Learner Agency Perspective)

2025 Dean's Commendation Award 2025 (Ph.D.), Nanyang Technological University, National Institute of Education (Research study: A Review of Conceptualisations on Learner Agency in Feedback.)

2025 AERA International Travel Award 

2024 Dean's Commendation Award 2024 (Ph.D.), Nanyang Technological University, National Institute of Education (Research study: Reconceptualising Learner Feedback Agency)

Journal Article 

Lee, M., Tan, R. J. Y., Chen, D. T., Huang, J. S., & Hung, W. L. D. (2025). Exploring interactions between learners and ChatGPT from a learner agency perspective: A multiple case study on historical Inquiry. Education and Information Technologies, 30, 7167–7189. https://doi.org/10.1007/s10639-024-13114-y
(Q1 journal with impact factor: 4.8 (2023))

Lee, M., & Chen, D. T. (2025). Knowledge Framing: Is Taiwan's Bilingual Education an Enhancement or a Hindrance? 教育學誌, (53), 85-99. https://www.airitilibrary.com/Article/Detail?DocID=20713126-N202506260008-00004

Lee, M., Chen, D. T., Tan, R. J. Y., & Hung, W. L. D. (2024). Re-conceptualising learner feedback agency: a situational, deliberative and entangled perspective. Assessment & Evaluation in Higher Education, 49(5), 680–692. https://doi.org/10.1080/02602938.2024.2318281
(Q1 journal with impact factor: 4.1 (2023))

Lee, M. (2024). Learner Agency in Feedback: A Review of Conceptualisations and Related Constructs. Cambridge Educational Research e-Journal, 11, 144–158. https://doi.org/10.17863/CAM.114527 

Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445-8501. https://doi.org/10.1007/s10639-022-11491-w [F5]
(Q1 journal with impact factor: 4.8 (2023))

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 [F6]
(Q1 journal with impact factor: 8.9 (2023))

Tan, S. C., Lee, A. V. Y., & Lee, M. (2022). A systematic review of artificial intelligence techniques for collaborative learning over the past two decades. Computers and Education: Artificial Intelligence, 3, 100097. https://doi.org/10.1016/j.caeai.2022.100097 [F7]
(Q1 journal with citescore: 16.8 (2023))

Keynote 

Lee, M., & Chen, D. T. (2024, November 22). Knowledge Forensics: Is Bilingual Education an Enhancement or a Hindrance? [Keynote Speech]. The 2024 Conference on Education, Tainan, Taiwan). [F8]

Conference Paper

Lee, M., & Chen, D. T. (2025). Enacticipation Graph: A Tool for Visualizing Learner Agency [Paper presentation]. 2025 American Educational Research Association (AERA) Annual Meeting, Colorado, United States. [F9]

Lee, M. (2024). A Systematic Review of Student-facing Learning Analytics: Competencies and Designs [Paper presentation]. Redesigning Pedagogy International Conference (RPIC) 2024, Singapore. [F10]

Huang, J. S., Radhakrishnan, A., Lee, T., Lee, M., Lum, J., Liu, G., & Kim, J. J. (2024, June). Unveiling the dynamics of learning behaviors in learning K-12 math: An exploration of an ASSISTments Dataset. In 2024 IEEE Conference on Artificial Intelligence (CAI) (pp. 1474-1480). IEEE. https://doi.org/10.1109/CAI59869.2024.00265 [F11]

Lee, M., & Lee, A. V. Y. (2022). Cultivating and supporting learning analytics literacy using 3M analytical framework. In Sridhar Iyer, J.-L. Shih, W. Chen, & Mas Nida Md Khambari (Eds.), Proceedings of the 30th International Conference on Computers in Education Conference (Vol. 2, pp. 74-78). Asia-Pacific Society for Computers in Education. https://icce2022.apsce.net/proceedings/volume2 [F12]

Lee, M., & Tan, S. C. (2022). Developing student agency through feedback seeking practices in a CSCL environment. In Sridhar Iyer, J.-L. Shih, W. Chen, & Mas Nida Md Khambari (Eds.), Proceedings of the 30th International Conference on Computers in Education Conference (Vol. 2, pp. 729-732). Asia-Pacific Society for Computers in Education. https://icce2022.apsce.net/proceedings/volume2 [F13]

Tan, S. C., Lee, A. V. Y., & Lee, M. (2022). Ideations for AI-supported Knowledge Building. 2022 Hybrid Knowledge Building Institute “Knowledge building for the public good: Education for a world in transition”, Wageningen, The Netherlands. [F14]

Teo, C.L., Lee, M., & Ong, A. (2021). Redesigning Curriculum to Support Knowledge Building Analytics. 25th Annual Knowledge Building Virtual Institute “Building Knowledge for Public Good: Meeting New People and New Ideas in Knowledge Building’s Metaspace”, Toronto, Ontario, Canada (pp. 165-171). https://ikit.org/summerinstitute2021/wp-content/uploads/2022/03/KBSI2021-Proceedings.pdf [F15]

Lee, M., Tan, R. J. Y, & Chu, S. K. W. (2021) Rescue Mission: A Gamified Online Learning Platform for Sex Education amongst Young Adolescents. Redesigning Pedagogy International Conference 2021, Singapore. [F16]

Lee, M., Yu, Y., & Chan, C. K. (2020). Characterising Shared Epistemic Agency in a Knowledge Building Learning Environment. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 2 (pp. 919-920). Nashville, Tennessee: International Society of the Learning Sciences. https://doi.dx.org/10.22318/icls2020.919 [F17]

Lee, M., & Chan, C. K. (2018). Engaging students in Authentic Science through Knowledge Building using Virtual World [Poster session]. In 2018 Knowledge Building Summer Institute (KBSI) (pp. 233), Toronto, Ontario, Canada. https://ikit.org/KBSI2018/KBSI2018-Proceedings.pdf [F19]

Book Chapter

Lee, M., & Tan, R. J. Y (2025). Reclaiming Control: Empowering Learner Agency in Generative AI Literacy. In Ng, D. T. K., Chu, S. K. W., O’Dea, X., Leung, J. K. L. (Eds.), From AI Literacy to Generative AI Literacy Theory, Policy and Practice. Springer. [F20]

Huang, J. S., Lee, M., Wu, J. (in press, 2025). Conjecture Mapping as a framework to Design for Change in Learning. In Jamaludin, A., Hung, W. L. D., Huang, J. S., Scaling System-Wide Education Change in Learning. [F21]

Lee, M. (2024). Designing for Learning amidst a Pandemic: Challenges and Silver Lining. In Quek, C. L. & Yap, C. F. (Eds.), Engaging in Home-Based Learning. Pearson. [F22]

Accepting PhD and EdD students