Name
Abstract | ||
|---|---|---|
In this study we analyzed the curricula of 65 university students to investigate the impact of activities progression on student performances. Clustering curricula based on activity order and type we discovered a significant incidence on performance, validating the predictive power of curricula. Nevertheless, we discovered that the characterization of clusters is mainly due to non mandatory activities, selected by a student to personalize his curriculum, while activity order is very less relevant. This observation rejects the idea that activities progression has impact on performance, resulting rather as a consequence of student choices. |
Year | Venue | Keywords |
|---|---|---|
2016 | IEEE Global Engineering Education Conference | educational data mining,experimental study,university curricula,students performances |
Field | DocType | ISSN |
Predictive power,Knowledge management,Curriculum,Engineering,Cluster analysis | Conference | 2165-9567 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonia Azzini | 1 | 119 | 20.38 |
| Paolo Ceravolo | 2 | 252 | 44.89 |
| Nello Scarabottolo | 3 | 25 | 7.99 |
| Ernesto Damiani | 4 | 3911 | 416.18 |