Name
Abstract | ||
|---|---|---|
Some learning theories emphasize the benefits of group work and shared knowledge acquisition in the learning processes. The
Computer-Supported Collaborative Learning (CSCL) systems are used to supportcollaborative learning and knowledge building,
making communication tools, shared workspaces, and automatic analysis tools available to users. In this article we describe
a Bayesian network automatically built from a database of analysis indicators qualifying the individual work, the group work,
and the solutions built in a CSCL environment that supports a problem solving approach. This network models the relationships
between the indicators that represent both the collaborative workprocess and the problem solution.
|
Year | DOI | Keywords |
|---|---|---|
2006 | 10.1007/978-1-84628-666-7_3 | machine learning,bayesian networks,. cscl,collaboration and interaction analysis,solution analysis,learning theory,bayesian network,network model |
Field | DocType | Citations |
Data science,Algorithmic learning theory,Instance-based learning,Collaborative learning,Inductive transfer,Computer science,Learning theory,Group work,Bayesian network,Artificial intelligence,Computational learning theory,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Duque | 1 | 86 | 11.51 |
| Crescencio Bravo | 2 | 366 | 35.31 |
| Carmen Lacave | 3 | 154 | 12.81 |