Here should be introductions.
I got my Ph.D. in Informatics at the Graduate School of Informatics, Kyoto University in Sep. 2023.
I am a program-specific researcher at Ogata Laboratory, Academic Center for Computing and Media Studies, Kyoto University.
Currently, my research focuses on algorithmic group formation and group learning support in data-driven environments with Learning Analytics.
Please take a look at my publications.
Contact me: liang.changhao.8h [at] kyoto-u.ac.jp
Ph.D. in Informatics, Department of Informatics, Kyoto University (September 2023)
Dissertation: GLOBE: Data-Driven Support for Group Learning
Proposed a data-driven educational framework GLOBE for collaborative learning.
Master's Degree in Informatics, Department of Informatics, Kyoto University (2020)
Dissertation: Learning Log-based Automatic Group Formation: System Design and Classroom Implementation Study
Bachelor's Degrees, Peking University (2018)
- Information management and information system, Department of Information Management (main degree)
- Psychology, Department of Psychology (double degree)
JSPS early-career grant (2025/4 -)
Transforming Collaborative Learning: A Data-Driven System for Group Formation and Intervention (25K21357)
Kyoto University Graduate Division Fellow (2021/12 - 2023/9)
Kyoto University and Support for Pioneering Research Initiated by the Next Generation program operated by the Japan Science and Technology Agency (JST) (JPMJSP2110)
Group Formation System
- A system to create student groups based on diverse data sources, including learning logs, e-book annotations, and previous performance metrics.
- Implemented algorithms to support group formation in various educational contexts (e.g., primary school math, junior high English, and university-level courses).
- Exploring optimal grouping strategies and input attributes in different scenarios.
Peer Evaluation System
- Integrated peer evaluation results to refine group dynamics in classrooms.
- Analyze peer feedback reliability and detect unserious rater behaviors.
Peer Recommendation and Peer Help System
- Recommending peer tutors based on knowledge proficiency from learning logs.
- Online platform for peer tutoring and communication, with behavior sensors for learning analytics.
APSCE ICLEA 2026 Program co-chair
APSCE ICCE 2025 C4: Technology Enhanced Learning for Mobility of Learners and Learning Experiences (TEML), co-chair
APSCE ICLEA 2025 PC-member
AIED 2025 Late Breaking Results (LBR) Track PC-member
APSCE ICCE 2024 C4: Technology Enhanced Learning for Mobility of Learners and Learning Experiences (TEML), co-chair
SOLAR LAK24 PC-member
Yiming Zhou (Master student, 2025.4 - )
Yu Yan (PhD student, 2025.4 - )
Yu-tung Chen (Master student, 2024.10 - )
Yudai Okayama (Master student, 2024.4 - )
Kensuke Takii (PhD candidate, 2024.3 - ) Dissertation: OKLM: Open Knowledge and Learner Model for Learning Analytics
Peixuan Jiang (Master student, 2023.9 - 2025.3) Dissertation: Data-driven Peer Recommendation and Its Implementation