Yizhou Fan (Ph.D.)

Assistant Professor, Research fellow  Graduate School of Education, Peking University

Adjunct Research Fellow  Faculty of Information Technology, Monash University

Tel：+86 15210167528   Email：fyz@pku.edu.cn

Address：Room 419 Graduate School of Education, No.5 Yiheyuan Road, Beijing, 100871, China

 

Professional Preparation and Work Experience:

           Peking University, Beijing    Assistant Professor, Research fellow   2023-present

           Monash University, Melbourne    Adjunct Research Fellow     2022-present

           The University of Edinburgh, Edinburgh  Post-doc Research Associate     2019-2023

           Peking University, Beijing       Educational Technology Ph.D.         2013- 2019

           University of Minnesota, Twin Cities  LTmedia Lab (Visiting Scholar)         2017

           Student’ Federation of Beijing, Beijing  Executive Chairman                  2012-2013

           China Agricultural University, Beijing  Vehicle Engineering  B.S.              2009-2013

Research Interests：

           AI in Education and AI for Science, AI Literacy, Learning Analytics, Self-regulated Learning, Learning Design

Selected Honors and Awards：

           NG Teng Fong/ Sino Scholarship for Outstanding Young Researcher (2024)

           QS Reimagine Education Award (E-Learning project - FLoRA) Silver Winner (2024)

           Emerging Scholar Award (2023), Society for Learning Analytics Research (The only recipient from Asia so far)

           National Excellent MOOC Award (2017, 2019) (Highest course design award in China)

           Excellent Dissertation Award for Educational Research (2019) (Highest educational dissertation award in China)

           National scholarship for graduate students (2014) (Highest scholarship for students in China)

           Beijing Public Welfare Pioneer (2013) (lead public welfare work to serve disadvantaged groups in China)

Selected Funded Grants

           2025-2027, PI, National Natural Science Foundation of China (NSFC), Research on Key Technologies and Empirical Applications of Metacognitive Scaffolding Based on Generative Artificial Intelligence

           2024-2026, PI, Peking University, AI for Science: How Artificial Intelligence Facilitates World-class Scientific Research and Talent Cultivation at Peking University

           2023-2025, PI, Alibaba Foundation, Research on Using Cloud Computing Technology to Facilitate STEM Education and Improve the AI Literacy of Rural Left-behind Children (conducted in 263 rural schools)

           2023-2024, PI, SoLAR Early Career Research grant (Canada), Measuring and Scaffolding Hybrid Human-AI Regulation: Comparing Learning Processes Facilitated by ChatGPT and Human Experts

           2020-2022, PI, Peking University, Learning Analytics to Reveal Learning Tactics and Strategies in Teacher Professional Development MOOC Settings

           2019-2022, Post-doc Researcher, Open Research Area (ORA), Facilitating Self-Regulated Learning with Personalized Scaffolds on Student’s own Regulation Activities

           2016-2020, Researcher, National Natural Science Foundation of China (NSFC), Organization and Continuous Optimization of Course-Oriented Large Scale Online Educational Resources for underdeveloped regions

           2016-2017, Researcher, Digital Learning for Development (DL4D), MOOCs for Teacher Professional Development in Underserved Regions: Examining Persistent Teacher-learners in a Chinese MOOC

Selected Publication - Books

           Fan, Y. (2025). Learning with Generative Artificial Intelligence: What Empirical Studies Tell Us. Routledge (in press)

           Fan, Y., Juelich, T., Mao, J. (2024). English Academic Writing in Practice (in Chinese). Tsinghua University Press

Selected Publication - Journals

           Fan, Y.*, Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., ... & Gašević, D. (2024). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology.

           Fan, Y. *, Rakovic, M., van Der Graaf, J., Lim, L., Singh, S., Moore, J., ... & Gašević, D. (2023). Towards a fuller picture: Triangulation and integration of the measurement of self‐regulated learning based on trace and think aloud data. Journal of Computer Assisted Learning, 39(4), 1303-1324.

           Fan, Y. *, Tan, Y., Raković, M., Wang, Y., Cai, Z., Shaffer, D. W., & Gašević, D. (2023). Dissecting learning tactics in MOOC using ordered network analysis. Journal of Computer Assisted Learning, 39(1), 154-166.

           Fan, Y. *, van der Graaf, J., Lim, L., Raković, M., Singh, S., Kilgour, J., ... & Gašević, D. (2022). Towards investigating the validity of measurement of self-regulated learning based on trace data. Metacognition and Learning, 17(3), 949-987.

           Fan, Y. *, Lim, L., Van der Graaf, J., Kilgour, J., Raković, M., Moore, J., ... & Gašević, D. (2022). Improving the measurement of self-regulated learning using multi-channel data. Metacognition and Learning, 17(3), 1025-1055.

           Fan, Y. *, Jovanović, J., Saint, J., Jiang, Y., Wang, Q., & Gašević, D. (2022). Revealing the regulation of learning strategies of MOOC retakers: A learning analytic study. Computers & Education, 178, 104404.

           Fan, Y., Matcha, W., Uzir, N. A. A., Wang, Q. *, & Gašević, D. (2021). Learning analytics to reveal links between learning design and self-regulated learning. International Journal of Artificial Intelligence in Education, 31(4), 980-1021.

           Fan, Y. *, Li, T., Tan, Y., Wang, Y., Singh, S., Li, X., ... & Gašević, D. (2023). Analytics of self-regulated learning scaffolding: effects on learning processes. Frontiers in psychology, 14, 1206696. (co-first author)

           Li, X., Fan, Y. *, Li, T., Rakovic, M., Singh, S., van der Graaf, J., ... & Gasevic, D. (2024). The FLoRA Engine: Using Analytics to Measure and Facilitate Learners' own Regulation Activities. Journal of Learning Analytics.

           Shen, Y., Tang, L., Le, H., Tan, S., Zhao, Y., Shen, K.,... & Fan, Y. * (2025). Aligning and Comparing Values of ChatGPT and Human as Learning Facilitators: a Value-Sensitive Design Approach. British Journal of Educational Technology.

           Chen, A., Xiang, M., Zhou, J., Jia, J., Shang, J., Li, X., ... & Fan, Y. * (2025). Unpacking help-seeking process through multimodal learning analytics: A comparative study of ChatGPT vs Human expert. Computers & Education, 226, 105198.

           Tang, L., Shen, K., Le, H., Shen, Y., Tan, S., Zhao, Y., ... & Fan, Y. * (2024). Facilitating learners' self‐assessment during formative writing tasks using writing analytics toolkit. Journal of Computer Assisted Learning, 40(6).

           Zhang, X., Zhang, P., Shen, Y., Liu, M., Wang, Q., Gašević, D., & Fan, Y. * (2024). A Systematic Literature Review of Empirical Research on Applying Generative Artificial Intelligence in Education. Frontiers of Digital Education, 1(3), 223-245.

           Lim, L., Bannert, M., van der Graaf, J., Fan, Y., Rakovic, M., Singh, S., ... & Gašević, D. (2024). How do students learn with real‐time personalized scaffolds?. British Journal of Educational Technology, 55(4), 1309-1327.

           Osakwe, I., Chen, G., Fan, Y., Rakovic, M., Singh, S., Lim, L., ... & Gašević, D. (2024). Towards prescriptive analytics of self‐regulated learning strategies: A reinforcement learning approach. British Journal of Educational Technology.

           van der Graaf, J., Raković, M., Fan, Y., Lim, L., Singh, S., Bannert, M., ... & Molenaar, I. (2023). How to design and evaluate personalized scaffolds for self-regulated learning. Metacognition and Learning, 18(3), 783-810.

           Saint, J., Fan, Y., Gašević, D., & Pardo, A. (2022). Temporally-focused analytics of self-regulated learning: A systematic review of literature. Computers and education: Artificial intelligence, 3, 100060.

           van der Graaf, J., Lim, L., Fan, Y., Kilgour, J., Moore, J., Gašević, D., ... & Molenaar, I. (2022). The dynamics between self-regulated learning and learning outcomes: An exploratory approach and implications. Metacognition and Learning, 17(3), 745-771.

           Raković, M., Iqbal, S., Li, T., Fan, Y., Singh, S., Surendrannair, S., ... & Gašević, D. (2023). Harnessing the potential of trace data and linguistic analysis to predict learner performance in a multi‐text writing task. Journal of Computer Assisted Learning, 39(3), 703-718.

           Chen, B., Fan, Y., Zhang, G., Liu, M., & Wang, Q. (2020). Teachers’ networked professional learning with MOOCs. PloS one, 15(7), e0235170.

Selected Publication - Conference Proceedings

           Fan, Y. *, Srivastava, N., Rakovic, M., Singh, S., Jovanovic, J., Van Der Graaf, J., ... & Gasevic, D. (2022, March). Effects of internal and external conditions on strategies of self-regulated learning: A learning analytics study. In LAK22: 12th international learning analytics and knowledge conference (pp. 392-403). (joint first author)

           Fan, Y. *, Saint, J., Singh, S., Jovanovic, J., & Gašević, D. (2021, April). A learning analytic approach to unveiling self-regulatory processes in learning tactics. In LAK21: 11th international learning analytics and knowledge conference (pp. 184-195).

           Fan, Y. *, Lim, L., Van der Graaf, J., Kilgour, J., Engelmann, K., Bannert, M., ... & Gasevic, D. (2020, March). Measuring micro-level self-regulated learning processes with enhanced log data and eye tracking data. In Proc. Companion 10th Int. Conf. Learn. Anal. Knowl. (pp. 433-436).

           Saint, J., Fan, Y., & Gasevic, D. (2024, March). Analytics of scaffold compliance for self-regulated learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 326-337).

           Li, T., Fan, Y., Srivastava, N., Zeng, Z., Li, X., Khosravi, H., ... & Gašević, D. (2024, March). Analytics of Planning Behaviours in Self-Regulated Learning: Links with Strategy Use and Prior Knowledge. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 438-449).

           Nath, D., Gasevic, D., Fan, Y., & Rajendran, R. (2024, March). CTAM4SRL: A Consolidated Temporal Analytic Method for Analysis of Self-Regulated Learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 645-655).

           Osakwe, I., Chen, G., Fan, Y., Rakovic, M., Singh, S., Molenaar, I., & Gašević, D. (2024, March). Measurement of Self-regulated Learning: Strategies for mapping trace data to learning processes and downstream analysis implications. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 563-575).

           Rakovic, M., Fan, Y., Van Der Graaf, J., Singh, S., Kilgour, J., Lim, L., ... & Gasevic, D. (2022, March). Using learner trace data to understand metacognitive processes in writing from multiple sources. In LAK22: 12th International Learning Analytics and Knowledge Conference (pp. 130-141).

           Saint, J., Fan, Y., Singh, S., Gasevic, D., & Pardo, A. (2021, April). Using process mining to analyse self-regulated learning: a systematic analysis of four algorithms. In LAK21: 11th international learning analytics and knowledge conference (pp. 333-343).

           Chen, B., Fan, Y., Zhang, G., & Wang, Q. (2017, March). Examining motivations and self-regulated learning strategies of returning MOOCs learners. In Proceedings of the seventh international learning analytics & knowledge conference (pp. 542-543).

PhD/Master supervision

           Mingxue Xu (Ph.D.), Luzhen Tang (Master), Zijian Li (Master), Mengyu Xia (Master). Graduate School of Education, Peking University (adviser)

           John Saint (Ph.D.), School of Informatics, The University of Edinburgh (co-adviser)

           Saleh Alghamdi (Ph.D.). Faculty of Information Technology, Monash University (co-adviser)

Services to the Research Community and leadership

           Editorial Board member, British Journal of Educational Technology and Journal of Learning Analytics, 2024 till now

           Guest Editor for Special Issue on SRL and Scaffolding, Metacognition and learning, 2022-2023

           Funding Chair, Idea Marathon of Future Digital and Intelligence Education, Peking University, 2024 and 2025

           Workshop Chair, The 15th International Learning Analytics and Knowledge Conference, 2024-2025

           Leader or coordinator of more than 10 workshops or symposiums for top conferences (LAK, ECTEL, AERA, EARLI)

           Dissemination Chair, Seventeenth European Conference on Technology Enhanced Learning, 2022

           Publicity Chair, The 12th International Learning Analytics and Knowledge Conference, 2022 and 2023

           Member, Communications Working Group, The Society for Learning Analytics Research (SoLAR), 2020-present

           General Chair/Program Chair, MOOC Research Doctoral Forum at Peking University, 2016-2018

List of courses taught

           Learning Analytics in Practice (both as a postgraduate course, as a workshop or as a mini programme)

           Building AI literary for Future (postgraduate course, another beginner's edition as popular science course for schools)

           English Academic Writing in the Age of AI (Hybrid teaching, undergraduate course, MOOC and workshops)

           Human-computer interaction design in digital education (Hybrid teaching, postgraduate course)

           Peer Instruction (MOOC), How do Teachers do Research (MOOC), Flipped Classroom Pedagogy (MOOC)