I am an associate professor at the Université Grenoble Alpes
Hello everyone, my name is Alix Goguey,
and today (or tonight depending on which timezone your in)
I’m gonna present you a work that was done
with Carl Gutwin, Zhe Chen, Pang Suwanaposee and Andy Cockburn
With a short presentation I’m starting with the takeaway message…
User preferences for system pace are correlated with user pace
In other words: fast users prefer faster interfaces,
and slow users prefer slow interfaces.
Let’s play a simple game that I’m sure
most of you are familiar with: slots machine.
on your screen and stops on a randomly
selected symbol.
You press a button, a series of symbols flashes up
Ok I lost…
Let’s try again
I lost again…
but about Interaction pace.
But! This paper is not about how lucky I am,
I don’t know if you’ve noticed but the first time I played,
I interacted rather slowly with the system
And as a result the following animation matched
now the second time I played,
my interaction pace
everything happened much quicker
from my pace to the system’s pace
This gambling machine that automatically adapts its pace
was describes by Giacolone in 98
to the user’s pace
automatic interface adaptation to user’s pace of interaction benefit users?
More generally it opens up a question: can
There are plethoras of situations in which the system pace
from timeout before folder expansion,
is contrived by pre-defined parameters:
window reorganisation animations,
mouse pointer transfer functions
to long presses.
And most interfaces use fixed timeouts.
via some preference system menus,
Sometimes system allow users change the values
Consequently, users typically have a 'one size fits all' solution:
but those are often ignored.
too fast for some,
too slow for others.
and while in theory customisation
can account for differences between users,
it will not account for intra-user differences.
For instance,
when focused, when fatigued, when in a hurry, and so on.
Before examining automatic adaptation, we wanted to answer the first question.
Do user preferences for different levels of system pace covary with user pace?
In other words, do fast users prefer fast interfaces and slow users prefer slow interfaces?
To test this hypothesis, we use a common drag and drop task
as like dropping files into a list of folders. A simple version with no folder expansions
(which basically is a Fitts task), allowed us to categorise users.
And a version with folder expansions (in which we controlled the timeout for expansion),
allowed us to have our users test different system pace and ask them which one they preferred.
Our experiment was done online with 208 amazon mechanical turkers.
It followed an A / B testing protocol, with a short timeout and a long timeout for folder
expansion. Details of the protocol and results are in the paper.
We categorized users into 3 quantiles: fast,
medium and slow, based on their mean performance in the Fitts task.
And interestingly when it comes to expansion,
faster users tend to prefer the fast timeout and slower users the slow one.
A similar trend appeared when letting users set their own expansion timeout values.
This overall trend is also reflected in the participants' comments.
Thus, results all support our hypothesis.
We discuss in great length the ins and outs of this study in the paper,
from lessons for expansion interfaces to reasons these results matters for UX designers.
But as I said earlier, the takeaway message is:
User preferences for system pace are correlated with user pace 72 00:04:43,700 --> 1193:07:24,796 Thank you.