CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
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id acadia18_118
authors Kalantari, Saleh; Contreras-Vidal, Jose Luis; Smith, Joshua Stanton; Cruz-Garza, Jesus; Banner, Pamela
year 2018
title Evaluating Educational Settings through Biometric Data and Virtual Response Testing
source ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 118-125
summary The physical design of the learning environment has been shown to contribute significantly to student performance and educational outcomes. However, the existing literature on this topic relies primarily on generalized observations rather than on rigorous empirical testing. Broad trends in environmental impacts have been noted, but there is a lack of detailed evidence about how specific design variables can affect learning performance. The goal of this study was to apply a new approach in examining classroom design innovations. We developed a protocol to evaluate the effectiveness of classroom designs by measuring the physical responses of study participants as they interacted with different designs using a virtual reality platform. Our hypothesis was that virtual “test runs” can help designers to identify potential problems and successes in their work prior to its being physically constructed. The results of our initial pilot study indicated that this approach could yield important results about human responses to classroom design, and that the virtual environment seemed to be a reliable testing substitute when compared against real classroom environments. In addition to leading toward practical conclusions about specific classroom design variables, this project provides a new kind of research method and toolset to test the potential human impacts of a wide variety of architectural innovations.
keywords work in progress, signal processing, eeg, virtual reality, big data, learning performance
series ACADIA
type paper
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