Publication Date
| In 2025 | 0 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Acoustics | 1 |
| Algorithms | 1 |
| Artificial Intelligence | 1 |
| Attribution Theory | 1 |
| Authentic Learning | 1 |
| Automation | 1 |
| Bayesian Statistics | 1 |
| Computation | 1 |
| Computer Assisted Instruction | 1 |
| Cooperative Learning | 1 |
| Decision Making | 1 |
| More ▼ | |
Source
| Journal of Learning Analytics | 1 |
Author
| Adolfo Ruiz-Calleja | 1 |
| Luis P. Prieto | 1 |
| Maria Jesus Rodriguez-Triana | 1 |
| Pankaj Chejara | 1 |
| Reet Kasepalu | 1 |
| Shashi Kant Shankar | 1 |
| Yannis Dimitriadis | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textPankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence
