Resumo (PT):
Abstract (EN):
Human-computer interactions in the AECO sector may be improved through alternative approaches such as the implementation of immersive applications (Me¸a, Turk, and Dolenc 2015; Paes, Arantes, and Irizarry 2017; de Klerk et al. 2019). However, there is a lack of common frameworks and procedures to assess the usability issues that may arise from the application of such immersive systems (e.g., Virtual Reality (VR), Augmented Reality (AR)). Thus, the present work proposes a methodology and guidelines to conduct usability assessments for Civil
Engineering Education.
Principal Component Analysis (PCA), a multivariate data analysis methodology, was used to ascertain the possibility of reducing the dimensionality of the problem (usability attributes), i.e., to find a few set of new variables, denominated principal components, able to well explain the correlations between the original observed variables in terms of their correlations with a smaller set of new variables.
Results confirm that the initial set of variables is hardly replaced by a smaller number of principal components, hence lacking a sufficiently strong relation. Furthermore, the authors suggest presenting univariate and bivariate measures to be able to establish future comparisons relating these attributes and other immersive systems.
Language:
English
Type (Professor's evaluation):
Educational
No. of pages:
1