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

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 747)

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.

Keywords

Learning analytics Structures for architecture students Architecture studies Learning indicators 

References

  1. 1.
    Learning and Knowledge Analytics course blog. http://www.learninganalytics.net
  2. 2.
    Vitruvius, P., Morgan, M.H.: Vitruvius: The Ten Books on Architecture. Dover Publications, New York (1960)Google Scholar
  3. 3.
    Alberti, L.B., Tory, G.: Leonis Baptistae Alberti … Libri De re aedificatoria decẽ. Opus integrũ et absolutũ: diligenter q recognitum. Distinctum est autẽ nuper opus ipsum totum. B. Rembolt, Parrhisijs (1512)Google Scholar
  4. 4.
    Viollet-le-Duc, E.: Entretiens sur l’architecture. A. Morel, Paris (1863)Google Scholar
  5. 5.
    Encyclopedia Britannica: “Architecture”. https://www.britannica.com/topic/architecture
  6. 6.
    «BOE» núm. 266, 06/11/1999. Ley 38/1999. Ley de Ordenación de la Edificación. Departamento: Jefatura de Estado (1999)Google Scholar
  7. 7.
    Official Journal of the European Union: Directive 2005/36/EC of the European Parliament and of the Council (2005)Google Scholar
  8. 8.
    ANECA: Libro blanco de grado en Arquitectura. Agencia nacional de evaluación de la calidad y acreditación. http://www.aneca.es/media/326200/libroblanco_arquitectura_def.pdf
  9. 9.
    «BOE» núm. 184, 30/06/2010. Acuerdo de Consejo de Ministros por el que se establecen las condiciones a las que deberán adecuarse los planes de estudios conducentes a la obtención de títulos que habiliten para el ejercicio de la profesión regulada de Arquitecto. Departamento: Ministerio de Educación (2010)Google Scholar
  10. 10.
    La Salle Academic Guide: Syllabus of the degree in Architecture Studies. http://www.salleurl.edu/en/education/degree-architecture-studies/syllabus
  11. 11.
    Fonseca, D., Climent, A., Vicent, L., Canaleta, X.: Learning4Work. designing a new evaluation system based on scenario centered curriculum. Methodology: the pre-test, vol. 9753. Lecture Notes in Computer Science, July 2016, pp. 1–11 (2016).  https://doi.org/10.1007/978-3-319-39483-1_1
  12. 12.
    Fonseca, D., Redondo, E., Villagrasa, S.: Mixed-methods research: a new approach to evaluating the motivation and satisfaction of university students using advanced visual technologies. Univers. Access Inf. Soc. 14(3), 311–332 (2015).  https://doi.org/10.1007/s10209-014-0361-4 CrossRefGoogle Scholar
  13. 13.
    Redondo, E., Giménez, L., Valls, F., Navarro, I., Fonseca, D., Villagrasa, S.: High vs. low intensity courses: student technological behavior. In: Proceedings of the 3rd International Conference on Technological Ecosystems for Enhancing Multiculturality, pp. 77–82 (2015).  https://doi.org/10.1145/2808580.2808593
  14. 14.
    Long, P., Siemens, G.: Penetrating the fog: analytics in learning and education. EDUCAUSE Rev. 46, 31–40 (2011)Google Scholar
  15. 15.
    Conde, M.A., Hernández-García, A.: A promised land for educational decision-making?: present and future of learning analytics. In: García-Peñalvo, F.J. (ed.) Proceedings of the First International Conference on Technological Ecosystem for Enhancing Multiculturality (TEEM 2013), pp. 239–243. ACM, New York (2013). http://dx.doi.org/10.1145/2536536.2536573
  16. 16.
    Johnson, L., Adams, S., Cummins, M.: The NMC Horizon Report: 2012 Higher, Education edn. The New Media Consortium, Austin (2012)Google Scholar
  17. 17.
    Ferguson, R.: The state of learning analytics in 2012: a review and future challenges. Technical report KMI-12–01, Knowledge Media Institute, The Open University, UK (2012)Google Scholar
  18. 18.
    Goldstein, P.J., Katz, R. N.: Academic analytics: the uses of management information and technology in higher education. EDUCASE, vol. 8 (2005)Google Scholar
  19. 19.
    Peña, E., Fonseca, D., Martí, N.: Relationship between learning indicators in the development and result of the building engineering degree final project. In: Proceedings of the 4th International Conference on Technological Ecosystems for Enhancing Multiculturality, pp. 335–340 (2016)Google Scholar
  20. 20.
    Bain, K.: What the Best College Teachers Do. Harvard University Press, Cambridge (2004)Google Scholar

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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