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Evaluating Accessibility-in-Use
Markel Vigo1 & Simon Harper2 University of Manchester (UK)
1: @markelvigo
2: @sharpic
W4A 2013
markel.vigo@manchester.ac.uk
simon.harper@manchester.ac.uk
http://dx.doi.org/10.6084/m9.figshare.701482
Evidence
Guidelines cover around 53% of the problems
encountered by users
Power et al. 2012
Guidelines are only half of the story: accessibility problems encountered by blind users on the web
CHI 2012, 433-442
W4A 201313 May 2013 2
Problem
The perception of users about accessibility
barriers is difficultly measurable and
generalisable
W4A 201313 May 2013 3
Paradox
– Some barriers are not perceived
– Some barriers are encountered but overcome
– Barrier free pages can cause a great hindrance
W4A 201313 May 2013 4
Accessibility-in-use
“the effects that real accessibility problems have
on the quality of interaction as perceived by real
users when interacting with real pages for
achieving real goals”
Vigo and Brajnik, 2011
Automatic web accessibility metrics: where we are and where we can go
Interacting with Computers 23 (2), 137-155
W4A 201313 May 2013 5
What do we propose:
Step 1. Observation & Identification
of Coping Strategies
6
1. Observation
W4A 201313 May 2013
Cognitive markers that indicate
problematic situations
What do we propose:
Step 2. Development of algorithms
to detect strategies
7
1. Observation 2. Algorithms
W4A 201313 May 2013
What do we propose:
Step 3. Deployment in the wild
8
1. Observation 2. Algorithms 3. Deployment
W4A 201313 May 2013
Case study
Step 1. Observation and analysis
• 2 independent studies/datasets generated
from ethnographic studies and user tests
• 24 screen reader and screen magnifier
users
• 17 coping strategies were identified
9 W4A 201313 May 2013
Case study
Step 2. Implement algorithms
– Asking for assistance
– Impulsive clicking
– Exploration tactics
– Narrowing down search
– Gaining orientation
– Re-doing
– Not operating
– Giving up
10 W4A 201313 May 2013
11
WebTactics
t1(){
..
}
DB
User Website Manager
/Researcher
1.1 Detection
algorithms are
injected onto web
pages.
1.2 Each algorithm keeps track of determined
sequences of events and actions.
3. This event is
asynchronously sent
to a remote location.
2. When the use of a
tactic is detected a
notification is triggered.
4. Reports from users are
viewed by interested parties.
ti(){
..
}
tn(){
..
}
id timestamp URL tactic
ccgu1331569030153 1333922552190 http://www.bbc.co.uk/sport/ t5
ccgu1331569030153 1333922556391 http://www.bbc.co.uk/sport/ t1
W4A 201313 May 2013
Case study
Step 3. Deployment: WebTactics
Contributions
• A method to observe accessibility-in-use
• Our approach allows to capture the
problems that emerge in the wild
• WebTactics
W4A 201313 May 2013 12
Follow up
13
Contact
@markelvigo | markel.vigo@manchester.ac.uk
Presentation DOI
http://dx.doi.org/10.6084/m9.figshare.701482
Source code
https://bitbucket.org/mvigo/cope
W4A 201313 May 2013

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Evaluating Accessibility-in-Use

  • 1. Evaluating Accessibility-in-Use Markel Vigo1 & Simon Harper2 University of Manchester (UK) 1: @markelvigo 2: @sharpic W4A 2013 markel.vigo@manchester.ac.uk simon.harper@manchester.ac.uk http://dx.doi.org/10.6084/m9.figshare.701482
  • 2. Evidence Guidelines cover around 53% of the problems encountered by users Power et al. 2012 Guidelines are only half of the story: accessibility problems encountered by blind users on the web CHI 2012, 433-442 W4A 201313 May 2013 2
  • 3. Problem The perception of users about accessibility barriers is difficultly measurable and generalisable W4A 201313 May 2013 3
  • 4. Paradox – Some barriers are not perceived – Some barriers are encountered but overcome – Barrier free pages can cause a great hindrance W4A 201313 May 2013 4
  • 5. Accessibility-in-use “the effects that real accessibility problems have on the quality of interaction as perceived by real users when interacting with real pages for achieving real goals” Vigo and Brajnik, 2011 Automatic web accessibility metrics: where we are and where we can go Interacting with Computers 23 (2), 137-155 W4A 201313 May 2013 5
  • 6. What do we propose: Step 1. Observation & Identification of Coping Strategies 6 1. Observation W4A 201313 May 2013 Cognitive markers that indicate problematic situations
  • 7. What do we propose: Step 2. Development of algorithms to detect strategies 7 1. Observation 2. Algorithms W4A 201313 May 2013
  • 8. What do we propose: Step 3. Deployment in the wild 8 1. Observation 2. Algorithms 3. Deployment W4A 201313 May 2013
  • 9. Case study Step 1. Observation and analysis • 2 independent studies/datasets generated from ethnographic studies and user tests • 24 screen reader and screen magnifier users • 17 coping strategies were identified 9 W4A 201313 May 2013
  • 10. Case study Step 2. Implement algorithms – Asking for assistance – Impulsive clicking – Exploration tactics – Narrowing down search – Gaining orientation – Re-doing – Not operating – Giving up 10 W4A 201313 May 2013
  • 11. 11 WebTactics t1(){ .. } DB User Website Manager /Researcher 1.1 Detection algorithms are injected onto web pages. 1.2 Each algorithm keeps track of determined sequences of events and actions. 3. This event is asynchronously sent to a remote location. 2. When the use of a tactic is detected a notification is triggered. 4. Reports from users are viewed by interested parties. ti(){ .. } tn(){ .. } id timestamp URL tactic ccgu1331569030153 1333922552190 http://www.bbc.co.uk/sport/ t5 ccgu1331569030153 1333922556391 http://www.bbc.co.uk/sport/ t1 W4A 201313 May 2013 Case study Step 3. Deployment: WebTactics
  • 12. Contributions • A method to observe accessibility-in-use • Our approach allows to capture the problems that emerge in the wild • WebTactics W4A 201313 May 2013 12
  • 13. Follow up 13 Contact @markelvigo | markel.vigo@manchester.ac.uk Presentation DOI http://dx.doi.org/10.6084/m9.figshare.701482 Source code https://bitbucket.org/mvigo/cope W4A 201313 May 2013

Editor's Notes

  1. ethno
  2. ethno