Name
Title | ||
|---|---|---|
Identification of Significant Variables for the Parameterization of Structures Learning in Architecture Students. |
Abstract | ||
|---|---|---|
The present work can be included in a much broader research related to an improvement on the learning of structural concepts and their practical application for architecture students, and consists in identifying significant variables to predict the effect of different teaching practices using an academic analytics approach. This work gathers data from surveys answered by architecture students – from La Salle Architecture School in Barcelona - to confirm the hypothesis that motivation is a key aspect to focus on. The results confirm it, and configure the working basis to check the efficiency of the teaching practices to be analyzed next academic years and for defining a predictive model on structural learning for architectural students. |
Year | Venue | Field |
|---|---|---|
2018 | WorldCIST | Data science,Architecture,Learning analytics,Structural learning,Computer science,Academic analytics |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carles Campanyà | 1 | 0 | 0.34 |
| David Fonseca | 2 | 152 | 28.70 |
| Núria Martí | 3 | 0 | 0.34 |
| Enric Peña | 4 | 0 | 0.68 |
| Álvaro Ferrer | 5 | 2 | 1.08 |
| Josep Llorca | 6 | 3 | 1.77 |