Year: 2015
Editor: Christian Weber, Stephan Husung, Gaetano Cascini, Marco Cantamessa, Dorian Marjanovic, Monica Bordegoni
Author: Nguyen, Philon; Nguyen, Thanh An; Zeng, Yong
Series: ICED
Institution: Concordia University, Canada
Section: Human Behaviour in Design, Design Education
Page(s): 061-070
ISBN: 978-1-904670-74-2
ISSN: 2220-4334


The measure of a design problem s hardness is a window into human intelligence. We propose a new measure of problem hardness based on the transient microstate percentage of EEG signals. Based on the heuristic that different segments of design protocol data have different perceived hardness, we use this transient microstate percentage to segment design protocol data into domain-valid segments. Currently, two main techniques exist to analyze design protocol data: simultaneous thinking aloud and retrospective protocol analysis. Our method based on physiological measurements (EEG) mitigates the strengths and weaknesses of both methods. It was able to classify some segments as expected and discover new segments. Using EEG to solve this problem is a typical inverse problem where a thought process is reconstructed from potential-valued signals of the brain. We discuss limitations and challenges of such an approach.

Keywords: Design Cognition, Protocol Data Analysis, Eeg Based Segmentation, Problem Hardness

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