Prof WANG, Minjuan    王敏娟 教授
Chair Professor
Department of Mathematics and Information Technology
Contact
ORCiD
0000-0003-2561-3420
Phone
(852) 2948 7355
Email
mwangcp@eduhk.hk
Address
10 Lo Ping Road, Tai Po, New Territories, Hong Kong
Website
https://pappl.eduhk.hk/rich/web/person.xhtml?pid=312408&name=WANG, Minjuan
Scopus ID
8941545200
SDGs
3 - Good Health and Well-Being
4 - Quality Education
9 - Industry, Innovation and Infrastructure
17 - Partnerships for the Goals
Research Interests
  • Emerging technologies such as AI and XR (Extended Reality) for teaching and training in various disciplines
  • AI-assisted language learning
  • AI-assisted creative arts
  • Futuristic mindset and workforce development

External Appointments

Editor-in-Chief, IEEE Transactions on Learning Technologies

(High-Impact, Q1 journal in Computer Science, Education and Educational Research)


Associate Editor, Nature-HSSC (Humanities and Social Sciences Communications)


Co-Chair, IEEE Technical Committee on interactive learning environments

Personal Profile

Assistant Vice President (Interdisciplinary Studies and Partnership)

Chair Professor, Emerging Technologies and Future Education


Associate Co-Director, Academy for Applied Policy Studies and Education Futures (AAPSEF)

Co-Director, Global Institute for Emerging Technologies (GIET)


Research Interests
  • Emerging technologies such as AI and XR (Extended Reality) for teaching and training in various disciplines
  • AI-assisted language learning
  • AI-assisted creative arts
  • Futuristic mindset and workforce development

External Appointments

Editor-in-Chief, IEEE Transactions on Learning Technologies

(High-Impact, Q1 journal in Computer Science, Education and Educational Research)


Associate Editor, Nature-HSSC (Humanities and Social Sciences Communications)


Co-Chair, IEEE Technical Committee on interactive learning environments

Research Outputs
Scholarly Books, Monographs and Chapters
Andreas Dengel, Alexander Steinmaurer, Lea Marie Müller, Melanie Platz, Minjuan Wang, Christian Gütl, Andreas Pester & Leonel Morgado (2024). Research agenda 2030: The great questions of immersive learning research. Marie-Luce BOURGUET, Jule M. KRÜGER, Daniela PEDROSA, Andreas DENGEL, Anasol PEÑA-RIOS, Jonathon RICHTER, Immersive learning research network: 9th International Conference, iLRN 2023, San Luis Obispo, USA, June 26–29, 2023, revised selected papers (161-172). Springer. https://doi.org/10.1007/978-3-031-47328-9_12
SDGs infomation: 4 - Quality Education

Journal Publications
Dai, Z., Liu, H., & Wang, M. (2025). Conceptualizing the Edu-Metaverse ecosystem based on an analysis of the Edu-Metaverse development in China. Interactive Learning Environments, 1- 20. https://doi.org/10.1080/10494820.2025.2476005
SDGs infomation: 4 - Quality Education
Chu, X., Wang, M., Spector, J. M., Chen, N.-S., Chai, C. S., Hwang, G.-J., & Zhai, X. (2025). Enhancing the flipped classroom model with generative AI and Metaverse technologies: Insights from lag sequential and epistemic network analysis. Educational Technology Research and Development, Article 101453. https://doi.org/10.1007/s11423-025-10457-2
SDGs infomation: 4 - Quality Education
Lang, Q., Wang, M., Yin M., Liang, S. & Song, W. (2025). Transforming education with Generative AI (GAI): Key insights and future prospects. IEEE Transactions on Learning Technologies, 18, 230-242. https://doi.org/10.1109/TLT.2025.3537618
SDGs infomation: 4 - Quality Education
Li, X., Li, T., Wang, M., Tao, S., Zhou, X., Wei, X., & Guan, N. (2025). Navigating the textual maze: Enhancing textual analytical skills through an innovative GAI prompt framework. IEEE Transactions on Learning Technologies, 18, 206-215. https://doi.org/10.1109/TLT.2025.3539104
SDGs infomation: 4 - Quality Education
Wang, M.J. & Lee, J.C.K. (2025). Editorial: Journey to the future: Extended reality and intelligence augmentation. IEEE Transactions on Learning Technologies, 18, 53-55. https://doi.org/10.1109/TLT.2024.3513373
SDGs infomation: 4 - Quality Education
Wu, J. G., Zou, D., Colpaert, J., & Wang, M. (2025). Guest editorial: Virtual reality in teacher education: Innovations, opportunities, and challenges. Educational Technology and Society, 28(1), 335-337. https://doi.org/10.30191/ETS.202501_28(1).SP01
SDGs infomation: 3 - Good Health and Well-Being, 4 - Quality Education
Zheng R., Xu H., Wang, M. and Lu J. (2024). The impact of artificial general intelligence-assisted project-based learning on students’ higher order thinking and self-efficacy. IEEE Transactions on Learning Technologies, 17, 2207-2214. https://doi.org/10.1109/TLT.2024.3488086
SDGs infomation: 4 - Quality Education
Sheng, SH., Liu, Q., Huang, ZY., Chen, EH., & Wang, M.J. (2024). A survey of knowledge tracing: Models, variants, and applications. IEEE Transactions on Learning Technologies, 17, 1898-1919. https://doi.org/10.1109/TLT.2024.3383325
SDGs infomation: 4 - Quality Education
Xu, L., Wang, Z., Zhang, S., Yuan, X., Wang, M., & Chen, E. (2024). Modeling student performance using feature crosses information for knowledge tracing. IEEE Transactions on Learning Technologies, 17, 1390-1403. https://doi.org/10.1109/TLT.2024.3381045
SDGs infomation: 4 - Quality Education
Bobko, T., Corsette, M., Wang, M.J., & Springer, E. (2024). Exploring the possibilities of Edu-Metaverse: A new 3-D ecosystem model for innovative learning. IEEE Transactions on Learning Technologies, 17, 1290-1301. https://doi.org/10.1109/TLT.2024.3364908
SDGs infomation: 4 - Quality Education
楚肖燕，沈书生，王敏娟，王会军，李晓文，翟雪松 (2024)。 世界一流高校探索生成式人工智能應用規範的經驗及對我國的啟示：基於 LDA 主題模型分析的文本挖掘。 現代遠距離教育，2024(3)，38-47。 https://tra-oversea-cnki-net.ezproxy.eduhk.hk/KCMS/detail/detail.aspx?dbcode=CJFD&dbname=CJFDAUTO&filename=YUAN202403005&uniplatform=OVERSEA&v=MqFpHyhRYU4aSgTjWpdRnuClFaIoHoNjKpc5n72eN7ZyRoMGOxmdhcdRruL4tViOpublished version (EdUHK Users only)
SDGs infomation: 4 - Quality Education
Zhai, XS, Chu, XY, Wang, M.J. et al. (2024). A systematic review of Stimulated Recall (SR) in educational research from 2012 to 2022. Humanities and Social Sciences Communications, 11, Article 489. https://doi.org/10.1057/s41599-024-02987-6
SDGs infomation: 4 - Quality Education
M. Wang, M. Wang, X. Xu, L. Yang, D. Cai and M. Yin (2024). Unleashing ChatGPT's power: A case study on optimizing information retrieval in flipped classrooms via prompt engineering. IEEE Transactions on Learning Technologies, 17, 629-641. https://doi.org/10.1109/TLT.2023.3324714
SDGs infomation: 4 - Quality Education

Projects
Three-Year Strategic Plan for Global Institute for Emerging Technologies (GIET), AAPSEF
The Global Institute for Emerging Technologies (GIET) aims to build the capacity of the education/professional development and training workforce (policymakers, leaders, teachers, and professional development and training staff) for learning innovations and emerging technologies to enhance education and professional learning equity, quality, and efficiency locally (Greater Bay Area), nationally, regionally, and internationally.The key objectives of GIET are as follows:
Objective 1 build the capacity of the future workforce for learning innovations and emerging technologies in various disciplines (e.g., STEAM, healthcare, environmental science, management, public policy);
Objective 2 enhance education and professional learning equity, quality, and efficiency;
Objective 3 strengthen internationalisation efforts by conducting work locally (Greater Bay Area), nationally, regionally, and internationally;
Objective 4 strengthen the research-professional learning nexus for learning innovations and emerging technologies
Project Start Year: 2025, Principal Investigator(s): WANG, Minjuan
SDGs Information: 3 - Good Health and Well-Being, 4 - Quality Education, 9 - Industry, Innovation and Infrastructure, 17 - Partnerships for the Goals
 
MuseAI: Transforming K-12 Science Education with AI-Driven Innovations
This research explores how combining neuroscience, innovative learning strategies, and behavioral evaluation in AI-infused science education can transform teaching and learning, especially for students of regions with limited educational resources. Project team will use principles from cognitive neuroscience to design MuseAI and its curriculum, aiming to adapt to the unique cognitive profiles of students and optimize their learning processes. This project aims to greatly enhance the teaching and research of science education by fostering deeper understanding, critical thinking, and sustained motivation among K-12 students, preparing them for a future shaped by scientific and technological advancements.Expected Outputs / Achieved Outputs:
1) the development of an advanced AI tool (MuseAI) that may lead to patents,
2) the dissemination of findings through teacher workshops and publication in peer-reviewed journals, and
3) the establishment of best practices for integrating AI in educational contexts.
Project Start Year: 2025, Principal Investigator(s): WANG, Minjuan
SDGs Information: 3 - Good Health and Well-Being, 4 - Quality Education, 11 - Sustainable Cities and Communities
 
Developing and Evaluating MuseAIWrite: An AI-Assisted Platform to Support English Creative Writing for Senior Primary Students
This proposal is aimed to develop and evaluate an AI-driven platform, MuseAIWrite, designed to enhance self-regulated English creative writing among senior primary school students. The ultimate goal of the proposal is to integrate MuseAIWrite into the primary classrooms to aid teachers to guide students smartly harness AI for self-regulated learning (SRL). Furthermore, the platform is designed to empower students to take charge of their own creative and effective learning processes.
Project Start Year: 2025, Principal Investigator(s): YANG, Yin, Nicole (WANG, Minjuan as Collaborator)
SDGs Information: 4 - Quality Education, 17 - Partnerships for the Goals
 
Design and Implementation of AI Curriculum from the Perspective of CDIO (Conceive, Design, Implement, Operate)
The team of EdUHK will mainly work with primary schools in three regions, Hong Kong, Zhejiang and Western China. This three-year project will apply the (Conceive, Design, Implement, Operate) CDIO model (Crawley et al., 2007) (refer to Figure 1) to develop AI courses for primary school students in three representative regions of China.
The primary objectives are to: 1) construct a design framework for AI courses in primary schools from the perspective of CDIO; 2) Identify relevant tools and resources for teaching AI courses, such as state-of-art AI and conduct teaching training for developing teachers’ AI literacy. 3) Evaluate the implementation of AI courses in selected schools from the perspective of student learning and teacher AI literacy.This proposed project will use design-based research (DBR), a commonly used method in learning sciences (Reeves, 2005). DBR is an iterative methodology that focuses on the continuous refinement of educational interventions. These refinements are grounded in theoretical principles that have emerged from empirical research within authentic settings by multiple iterations where each cycle encompasses phases of design, implementation, analysis and redesign. In DBR, researchers will develop the interventions first and then to test how well they work. In this case, the interventions will be AI courses. The testing of the new and innovative courses will be conducted through action research and multiple case studies, using mixed-method design to collect both qualitative and quantitative data. The study will further select typical school cases to Each school will be treated as an individual case then compared with other schools in AI teaching and effectiveness. The research team will collect data through in-field course observation, follow-up interviews and surveys with teachers, and students. The analyses will focus on the influencing factors of AI course design and implementation, and their perceptions on the AI courses.
Project Start Year: 2024, Principal Investigator(s): WANG, Minjuan
SDGs Information: 3 - Good Health and Well-Being, 4 - Quality Education, 17 - Partnerships for the Goals
 
Prizes and awards
Best Paper Award
Unleashing ChatGPT's Power: A case study on optimizing information retrieval in flipped classrooms via prompt engineering
Date of receipt: 15/1/2025, Conferred by: IEEE Education Society: Transactions on Learning Technologies