Information Technology Reference
In-Depth Information
10.5 MEASURING USABILITY THROUGH BIOMETRICS
By Amanda Davis, Elizabeth Rosenzweig, and Fiona Tranquada, Design and
Usability Center, Bentley University
A group of Bentley University researchers from the Design and Usability
Center (DUC) wanted to understand how the emotional experience of using a
digital textbook compared to a printed textbook. In 2011, our team of graduate
students (Amanda Davis, Vignesh Krubai, and Diego Mendes), supervised by
DUC principal consultant Elizabeth Rosenzweig, explored this question using
a unique combination of affective biometric measurement and qualitative user
feedback. This case study describes how these techniques were combined to
measure emotional stimulation and cognitive load.
10.5.1
Background
As user experience research achieves greater prominence in business organiza-
tions, we are often asked to help gauge the emotional experience of a product,
as well as its usability. Usability professionals have a variety of tools and tech-
niques available to understanding human behavior. However, the tools used
commonly to measure the emotion of participants while attempting to com-
plete tasks rely on either an observer's interpretation of how the participant is
feeling or the participants' description of their reactions (e.g., through think-
aloud, protocolor post-task ratings). These interpretations are subject to phe-
nomena such as the observer effect, the participants' inclination to please, and
the time passed since they had the reaction. Other tools, such as the Microsoft
Product Reaction Cards, show the direction of a participant's response (positive
or negative) to a product, but not the magnitude of that emotion (
Benedek &
Miner, 2002
).
Adding biometric measures to user research provides a way to measure users'
arousal as they use a product. Arousal describes the overall activation (emo-
tional stimulation and cognitive load) experienced by a user, as measured by
biometric measures such as electrodermal activity (EDA). These measures cap-
ture physiological changes that co-occur with emotional states (
Picard, 2010
).
Because biometric measures are collected in real time during a user's interaction
with a product, they provide a direct measurement of arousal that is not affected
by observer or participant interpretation.
This case study describes initial research to gauge the effectiveness of a new
technique that assigns meaning to biometric measures. We hypothesized that
by combining biometric measures with feedback from the Microsoft Product
Reaction Cards, we could gain a detailed description of a user's arousal, the
interaction that activated a change in arousal, and assignment of emotion (posi-
tive or negative) to that interaction. For example, if we saw a user's arousal level
increase sharply while attempting a search task, the Microsoft Product Reaction
Cards selected would indicate whether the arousal increased due to frustration
or pleasure. This combination would let practitioners quickly identify areas of a
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