Identification of Significant Variables for the Parameterization of Structures Learning in Architecture Students

  • Carles Campanyà
  • David Fonseca
  • Núria Martí
  • Enric Peña
  • Alvaro Ferrer
  • Josep Llorca
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 747)


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.


Learning analytics Structures for architecture students Architecture studies Learning indicators 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.La Salle, Universitat Ramon LlullBarcelonaSpain
  2. 2.AR&M, Barcelona School of Architecture, BarcelonaTechCatalonia Polithecnic UniversityBarcelonaSpain

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