wud slovakia 2015: experiment v ux class / prof. ing. mária bieliková, phd
TRANSCRIPT
20 eye-trackers in one room (UXI Labs @ Slovak University of Technology)
20x Tobii X2-60 eye
trackers
Screen recording
Face recording
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Infrastructure for
transferring all the
data to the central
server
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3D depth
camera60Hz
eyetracker
Mass data collection is excellent for
summative studies
• Same conditions for
every participant
• Saving staff time
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Our UX Group Research Software
• Data collection from all UX nodes
• Lifecycle management of user studies projects
• Processing of gathered data
• Annotations
• Cleaning
• Export
• Archivation
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UXI@FIIT = three laboratories
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Tobii
TX300
PC,
EEG,
...
Tobii
X2-60
mobiles,
TV, PC20x Tobii X2-60
gaze tracking
PC
Control
room
Twin-experiment(two experiments taken with the same group of 50 participants, ~2,5GB of
raw csv data)
Experiment #1:
Crowdsourcing study demonstrating the use
of eye-tracking for human computation scenario.Participants had to categorize of documentary movies based on their
descriptions.
Experiment #2:
Questionnaire deception detection using eye-trackingParticipants had to fill out the big five personality trait questionnaire.
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Experiment #1:
Crowdsourcing movie categorizations
Participant’s task:
1. View the description of a documentary movie
2. Pick a primary category for the movie from the list
3. [Optionally] Pick a secondary category
Hypothesis:
We can discover additional classification information,
if we eye-track the workers during the task
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The gaze reveals, what other options
the workers considered
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“Saving rhino phila"
[["animals", 100], ["crime", 50]]
[["traveling", 1150.0], ["geography", 1017.0],
["biography", 500.0], ["health", 400.0], ["animals", 367.0],
Title:
Picked categories:
Viewed categories:
Experiment #1:
Observations
Experiment #2:
Questionnaire deception detection
Participant’s task:
Fill out the big five personality trait questionnaire that matches
1. your personality (respond honestly)
2. an ideal worker for job position (faking good instruction)
Hypothesis:
We can detect deception by analysis of gaze data
Van Hooft, E.A.J. & Born, M.P. (2012). Intentional response distortion on personality
tests: Using eye-tracking to understand response processes when faking. Journal of
Applied Psychology, 97(2), 301–316. doi:10.1037/a0025711
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We were looking for fixation order, response
times, pupil dilation, first fixation…
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Deception cases were characteristic by:
• First fixations at extreme response options
p = 3.538e-14 < 0.001
• Longer reaction times
p = 0.039 < 0.05
• Pupil dilation variance before and after answering
a question
p = 0.022 < 0.05
Experiment #2:
Observations
Have some assistants
There were 3 of us: one experiment conductor and two
assistants. It was enough for 20 people, but barely.
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Do a pilot study with multiple participants,
don’t just do it with individuals
If the study has to be parallel recording, do the pilot likewise
Pilot allowed us to properly update instructions• No browser window resizing, no zooming
• Make the scenario as simple as possible. The more steps there are, the more mistakes the participants make.
Instructions are crucial
• Don’t just use paper instructions, use slides and presentation as well
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Group calibration is best done two-step
First, do a presentation (slide) demonstration.
• Do not allow participants to do anything during the
explanation.
• Make them watch you, or they will screw up.
Second, let everyone follow the remembered
instruction from the first step.
• Watch the calibration status on the dashboard
• Attend everyone that raises any problems
• 3 experiment conductors were enough to handle
calibration problems
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Never let participants to do anything
during the time you speak to them.
Stress to them the necessity of discipline.
Paper instructions won’t always save you.
Participants do not read them properly.
Better communicate important things also
verbally.
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