Changhao Liang
Biographic Data
| ID | 8988407 |
|---|---|
| NAME | Changhao Liang |
| GIVEN NAMES | Changhao |
| FAMILY NAME | Liang |
| SIGNATURE | LIANG C |
| AFFILIATIONS | Kyoto University |
| ORCID | 0000-0002-9775-0697 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Enabling data-driven peer help for extracurricular learning
The rapid advancement of educational technologies has reshaped informal and extracurricular learning, particularly in regions like Hokkaido, Japan, where demographic shifts have increased reliance on remote learning. While these settings offer flexibility and accessibility, they often lack structured opportunities for interpersonal interactions, posing challenges to social interactional learning and timely assistance. This study proposes an adapt…
Data-driven peer recommendation in higher education
Collaborative learning in tertiary education faces challenges such as limited teacher intervention and effective student pairing. This study addresses these issues by proposing a data-driven peer recommendation approach enhanced with learner profile visualisation. The system dynamically matches students based on evolving learning profiles, using an open learner model to improve transparency and decision-making. Implemented in a Japanese universit…
Algorithmic group formation and group work evaluation in a learning analytics-enhanced environment
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group formation and group work evaluation systems in a Japanese junior high school context. Data from a seri…
No prominent works on this page.
Algorithmic group formation and group work evaluation in a learning analytics-enhanced environment
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group formation and group work evaluation systems in a Japanese junior high school context. Data from a seri…
Data-driven peer recommendation in higher education
Collaborative learning in tertiary education faces challenges such as limited teacher intervention and effective student pairing. This study addresses these issues by proposing a data-driven peer recommendation approach enhanced with learner profile visualisation. The system dynamically matches students based on evolving learning profiles, using an open learner model to improve transparency and decision-making. Implemented in a Japanese universit…
Enabling data-driven peer help for extracurricular learning
The rapid advancement of educational technologies has reshaped informal and extracurricular learning, particularly in regions like Hokkaido, Japan, where demographic shifts have increased reliance on remote learning. While these settings offer flexibility and accessibility, they often lack structured opportunities for interpersonal interactions, posing challenges to social interactional learning and timely assistance. This study proposes an adapt…
Computer Science (3 works) · Mathematics education (3 works) · Psychology (3 works) · Innovative Teaching and Learning Methods (2 works) · Multimedia (2 works) · Online Learning and Analytics (2 works) · Reflective Practices in Education (2 works) · Analytics (1 works) · Collaborative learning (1 works) · Cooperative learning (1 works)