Name
Abstract | ||
|---|---|---|
The interest in developing Learning Analytics tools that can be integrated into the well-known Moodle course management systems is increasing nowadays. These tools generally provide some type of basic analytics and graphs about usersu0027 interaction in the course. However, they do not enable a varied set of Data Mining techniques to be applied, such as approaches for classification, clustering, or association. To address this issue, a new and freely available Moodle Data Mining tool, named MDM, has been proposed in this paper. The proposed tool eases the whole knowledge discovery process, including tasks such as selection, data pre-processing, and data mining from Moodle courses. The proposed MDM tool has been developed in PHP programming language, so it can be easily integrated into Moodle as a module for a specific course. Its main features and architecture are described in depth, and a tutorial is also provided as a practical way of using the MDM interface. Finally, some experimental results using a real-life sample dataset of mechanical engineering students are analyzed. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1002/cae.21782 | Comp. Applic. in Engineering Education |
Keywords | Field | DocType |
data Mining,clustering,classification,association,moodle | Data mining,Graph,Architecture,Learning analytics,Computer science,Knowledge extraction,Analytics,Cluster analysis,Management system | Journal |
Volume | Issue | ISSN |
25 | 1 | 1061-3773 |
Citations | PageRank | References |
7 | 0.47 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José M. Luna | 1 | 366 | 23.59 |
| Cristobal Castro | 2 | 7 | 0.81 |
| Cristóbal Romero | 3 | 2226 | 148.97 |