Understanding users in the Wild

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http://www.cs.man.ac.uk/~apaolaza/research.html

Abstract:
Laboratory studies are a well established practice that present disadvantages in terms of data collection. One of these disadvantages is that laboratories are controlled environments that do not account for unpredicted factors from the real world. Laboratory studies are also obtrusive and therefore possibly biased. The Human-Computer Interaction (HCI) community has acknowledged these problems and has started exploring in-situ observation techniques. These observation techniques allow for bigger participant pools and their environments can conform to the real world. Such real-world observations are particularly important to the accessibility community who has coined the concept accessibility-in-use to differentiate real world from laboratory studies. Real-world observations provide low-level interaction data therefore making a bottom-up analysis possible. This way behaviours emerge from the obtained data instead of looking for predefined models. Some in-situ techniques employ Web logs in which the data is too coarse to infer meaningful user interaction. In some other cases an exhaustive manual modification is required to capture interaction data from a Web application. We describe a tool which is easily deployable in any Web application and captures longitudinal interaction data unobtrusively. It enables the observation of accessibility-in-use and guides the detection of emerging tasks.

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Understanding users in the Wild

  1. 1. Understanding Users inthe WildAitor Apaolaza, Simon Harper, Caroline JayUniversity of ManchesterW4A 13th May 2013
  2. 2. ● Real users in the real world trying toachieve real goals● Differentiates real world and laboratorystudies● In situ and unobtrusive● Low-levelAccessibility-in-useUnderstanding Users in the WildW4A 13th May 2013 1
  3. 3. ● Laboratory studies○ Controlled environments○ Obtrusive○ Short term○ Use of predefined tasksObservation methodsUnderstanding Users in the WildW4A 13th May 2013 2● Our proposal○ Remote observation○ Ecological and naturalistic○ Longitudinal○ Low-level, tasks emerge
  4. 4. Our ApproachUnderstanding Users in the WildW4A 13th May 2013 3VisualizationtoolDataProcessingBehaviourmodel libraryCapture moduleDataQuery andupdateExploreinformation
  5. 5. ● Requires identifying unique users● Enables learnability studies● Study the effect of changes to the interfaceLongitudinalUnderstanding Users in the WildW4A 13th May 2013 4
  6. 6. ● In the Mood to Click? Q. Guo et al.■ Single purpose website study● WebInSitu Bigham et al.■ Differences between blind and sighted users usage● Support for remote usability evaluation ofweb mobile applications Carta et al.■ Comparison of single sessionsSimilar workUnderstanding Users in the WildW4A 13th May 2013 5
  7. 7. Our ApproachUnderstanding Users in the WildW4A 13th May 2013 6InteractioneventsHTML+ JSClientVisualizationtoolDataProcessingBehaviourmodel libraryCapture moduleCapture serverDataWeb ServerQuery andupdateExploreinformation
  8. 8. Our ApproachUnderstanding Users in the WildW4A 13th May 2013 7InteractioneventsHTML+ JSClientVisualizationtoolDataProcessingBehaviourmodel libraryCapture moduleCapture serverDataWeb ServerQuery andupdateExploreinformation
  9. 9. Our ApproachClient Capture serverWeb ServerUnderstanding Users in the WildW4A 13th May 2013 8
  10. 10. Our ApproachHTML+ JS<script type="text/javascript">//Configure and import capture solution</script>+● JavaScript is added to all Web pagesWeb Server Client Capture serverUnderstanding Users in the WildW4A 13th May 2013 9
  11. 11. Understanding Users in the WildW4A 13th May 2013 10Our ApproachHTML+ JSWeb Server Client Capture server● Listeners for events are registered● Mouse● Keyboard● Form input● WindowInteractionevents
  12. 12. Web Server ClientOur ApproachInteractioneventsHTML+ JS● Events get processed and storedUnderstanding Users in the WildW4A 13th May 2013 11Capture server
  13. 13. Our Approach (examples)"nodeInfo" : {"nodeDom" : "id("selectquicklinks")","nodeType" : "SELECT",},"value" : "http://manc.ac.uk/software/","selected" : "8","event" : "change",What user sees What we seeUnderstanding Users in the WildW4A 13th May 2013 12
  14. 14. ● Extendible and easy to deploy in the wild● Provide low-level interaction data● Longitudinal in-situ studies are possible● Allows the recreation of the interaction● Sensitive elements can be blacklistedAdvantagesUnderstanding Users in the WildW4A 13th May 2013 13
  15. 15. Emerging behaviours● Users tasks emerge from low-levelinteraction data● Ecologically valid behaviour models● Accessibility problems arise● Similar users have similar problemsUnderstanding Users in the WildW4A 13th May 2013 14
  16. 16. Understanding Users in the WildAitor Apaolaza, Simon Harper and Caroline Jayhttp://www.cs.man.ac.uk/~apaolaza/Thank you!Understanding Users in the WildW4A 13th May 2013 15

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