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Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web

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Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web

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When users struggle on the Web they employ extreme adaptations to tackle problematic situations, namely coping strategies. If we are able to automatically detect such situations we can provide the means to bypass or pre-empt them. However, isolating these coping strategies is a challenging task: coping occurs seldom and when it happens, coping is not always overtly manifested. Therefore, in order to identify the coping strategies employed by users in situ longitudinal observations have to be conducted, which are resource intensive. We propose a more economical method that transfers the coping strategies employed by groups of users that cope frequently and overtly, such as people with disabilities, to broader populations. To do so, we first identify the coping strategies employed by people with disabilities; then we code these strategies and convert them into coping detection algorithms that are injected into web pages. Remote longitudinal studies are run with broader populations to measure the detection rate of the algorithms. Based on participants’ feedback we iteratively modify the algorithms to adjust them to the coping strategies users employ. We illustrate this method with a case study that transfers the strategies employed by visually disabled users to able-bodied users. We discover that different populations do not only face the same problems, but also exhibit similar strategies to tackle them.

When users struggle on the Web they employ extreme adaptations to tackle problematic situations, namely coping strategies. If we are able to automatically detect such situations we can provide the means to bypass or pre-empt them. However, isolating these coping strategies is a challenging task: coping occurs seldom and when it happens, coping is not always overtly manifested. Therefore, in order to identify the coping strategies employed by users in situ longitudinal observations have to be conducted, which are resource intensive. We propose a more economical method that transfers the coping strategies employed by groups of users that cope frequently and overtly, such as people with disabilities, to broader populations. To do so, we first identify the coping strategies employed by people with disabilities; then we code these strategies and convert them into coping detection algorithms that are injected into web pages. Remote longitudinal studies are run with broader populations to measure the detection rate of the algorithms. Based on participants’ feedback we iteratively modify the algorithms to adjust them to the coping strategies users employ. We illustrate this method with a case study that transfers the strategies employed by visually disabled users to able-bodied users. We discover that different populations do not only face the same problems, but also exhibit similar strategies to tackle them.

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Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web

  1. 1. Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web Markel Vigo1 & Simon Harper2 University of Manchester (UK) 1: @markelvigo 2: @sharpic ACM Web Science 2013 markel.vigo@manchester.ac.uk simon.harper@manchester.ac.uk http://dx.doi.org/10.6084/m9.figshare.695072
  2. 2. Coping The cognitive and behavioral efforts to manage demands that exceed the resources of a person. Lazarus & Folkman, 1984 ACM Web Science 20132 May 2013 2
  3. 3. Problem We do not know the coping strategies employed on the Web ACM Web Science 20132 May 2013 3
  4. 4. Why is this important If we are able to automatically detect coping we can provide the means to overcome the situation ACM Web Science 20132 May 2013 4
  5. 5. What do we propose ACM Web Science 20132 May 2013 Transferring the identified strategies from populations who cope more frequent and overtly to general audiences 5
  6. 6. Why is it challenging Coping occurs seldom Once every 75 minutes. Novick et al., 2007 112 minutes for sighted users 95 for visually impaired Vigo and Harper, 2013 ACM Web Science 20132 May 2013 6
  7. 7. Why is it costly Significant amount of observations in the wild are required ACM Web Science 20132 May 2013 7
  8. 8. What do we propose: Step 1. Observation & Identification of Strategies ACM Web Science 20132 May 2013 8 1. Observation
  9. 9. What do we propose: Step 2. Implementation of algorithms to detect strategies ACM Web Science 20132 May 2013 9 1. Observation 2. Algorithms
  10. 10. ACM Web Science 20132 May 2013 What do we propose: Step 3. Deployment in the wild 10 1. Observation 2. Algorithms 3. Deployment
  11. 11. What do we propose: Step 4. Run user studies ACM Web Science 20132 May 2013 11 1. Observation 2. Algorithms 3. Deployment 4. User studies
  12. 12. What do we propose: Refine algorithms go to step 2 ACM Web Science 20132 May 2013 12 1. Observation 2. Algorithms 3. Deployment 4. User studies
  13. 13. 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 ACM Web Science 20132 May 2013 13
  14. 14. Case study Step 2. Implementation - Retracing: users retrace the steps in a sequence of pages. - Re-checking: fast revisitations. ACM Web Science 20132 May 2013 14
  15. 15. Case study Step 3. Deployment • Algorithms deployed in a Firefox add-on ACM Web Science 20132 May 2013 15
  16. 16. Case study Step 4. User study • 18 sighted participants, 10 days • 126 retraces and 67 rechecks • Tabbed browsing was interfering • Feedback on false positives: – “I’m browsing across tabs” – “I’m comparing different web pages” – “I’m navigating through different tabs” ACM Web Science 20132 May 2013 16
  17. 17. Case study Refinement; then iterate. Tab browsing breaks the interaction context re-checking: webpagei  wpj  wpi  wpj ACM Web Science 20132 May 2013 17 NON-TABBED NON-TABBED NON-TABBED
  18. 18. False positive rate (less is better) ACM Web Science 20132 May 2013 study 1 study 20.0 0.2 0.4 0.6 0.8 1.0 study 1 study 20.0 0.2 0.4 0.6 0.8 1.0 Retracing Re-checking 18 • 2nd study: 20 sighted participants, 10 days • 24 retraces, 16 rechecks
  19. 19. Conclusion There is an overlap between the coping strategies of different populations ACM Web Science 20132 May 2013 19
  20. 20. Follow up ACM Web Science 20132 May 2013 20 Contact @markelvigo | markel.vigo@manchester.ac.uk Presentation DOI http://dx.doi.org/10.6084/m9.figshare.695072 Source code https://bitbucket.org/mvigo/cope Datasets http://wel-data.cs.manchester.ac.uk/studies/3

Editor's Notes

  • ethno
  • caption, lower better
  • TransferabilityExtent and magnitude
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