Name
Abstract | ||
|---|---|---|
One of the most important challenges of collaborative learning systems is to offer mechanisms to facilitate the study of the relationships between the collaboration process and the characteristics of the solution (product) built by the learners in this work process. In this article, a machine learning algorithm that generates a set of rules to classify the different forms of collaboration within a group of learners with respect to the quality of the solution built is presented. The algorithm, based on a fuzzy model, is put into practice using data registered in a collaborative learning environment. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-71618-1_72 | ICANNGA (1) |
Keywords | Field | DocType |
fuzzy model,cscl systems,important challenge,collaboration process,different form,classify collaboration,work process,collaborative learning environment,machine learning,collaborative learning | Robot learning,Educational technology,Fuzzy model,Instance-based learning,Collaborative learning,Active learning (machine learning),Computer science,Artificial intelligence,Error-driven learning,Machine learning | Conference |
Volume | ISSN | Citations |
4431 | 0302-9743 | 10 |
PageRank | References | Authors |
0.60 | 11 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rafael Duque | 1 | 86 | 11.51 |
| Crescencio Bravo | 2 | 366 | 35.31 |