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Using Galvanic Skin Response Measures To Identify Areas of Frustration for Older Web 2.0 Users
 

Using Galvanic Skin Response Measures To Identify Areas of Frustration for Older Web 2.0 Users

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The World Wide Web (Web) is changing. The much vaunted Web 2.0 sees once static pages evolving into hybrid applications. Content that was once simple is now becoming increasingly complicated due to ...

The World Wide Web (Web) is changing. The much vaunted Web 2.0 sees once static pages evolving into hybrid applications. Content that was once simple is now becoming increasingly complicated due to the many updating components located throughout the page. The information overload and visual complexity of such components is significant. This increased complexity can produce lower performance and higher levels of stress and frustration which negatively effect the user. In previous work we have shown how galvanic skin response (GSR) measurements, collected in tandem with eye-tracking data, can be used as a method for determining how stressed users become when interacting with content. The results of that study demonstrated that when used appropriately, the presence of Web 2.0 content can reduce GSR measurements and be of benefit to users. In this work, the previous study was repeated with twenty-three older Web users to establish if similar patterns of interaction could be established. The results reveal that while older participants made use of dynamic content, unlike previous participants, they were a non-homogenous group with a large variance in the GSR measurements. We assert that a cause of this is hesitancy and therefore developing techniques to reduce hesitancy will benefit older users when interacting with Web 2.0 content.

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  • Hello <br />
  • This is what we&#x2019;ll try and get out of the talk. Show how the Web has become more complex. Can use Galvanic Skin Response and Eye Tracking to identify areas that cause a reaction from the participant, which we associate with stress. Age was not a determining feature but a combination of factors that are more likely with age. <br />
  • Original Web was linked documents. Online books and magazines that people could passively read. <br />
  • Not very interesting. Taken from 10th May 2000. Just links to other news articles. <br />
  • New Web is more programatic. Pages are composed of multiple information sources mashed together. Have application like features with buttons to click and areas to drag and drop. <br />
  • New yahoo! page taken on 19th April 2010. Areas pop up. Mouse hover has different functionality to mouse click. eg carousel. Roll over changes image and story. Clicking takes you to that stories page. <br />
  • New yahoo! page taken on 19th April 2010. Areas pop up. Mouse hover has different functionality to mouse click. eg carousel. Roll over changes image and story. Clicking takes you to that stories page. <br />
  • How do users react to this change in paradigm. Are they stressed or frustrated. Do users prefer them to be present or absent. Do users ignore such widgets. <br />
  • Used in biofeedback. Place straps on fingers or toes as these are less effected by atmosphere but more responsive to stress. as participants react to events, measurements change. Can learn to adapt behaviour. eg used in hypertension disorder. <br />
  • Used in biofeedback. Place straps on fingers or toes as these are less effected by atmosphere but more responsive to stress. as participants react to events, measurements change. Can learn to adapt behaviour. eg used in hypertension disorder. <br />
  • Used in biofeedback. Place straps on fingers or toes as these are less effected by atmosphere but more responsive to stress. as participants react to events, measurements change. Can learn to adapt behaviour. eg used in hypertension disorder. <br />
  • Not creating a generic model but trying to see what areas cause stress with participants. Can also assume that the more peaks there are in the graph, the more stressful a page was as users reacted to it more. <br />
  • National Rail similar but had multiple ASLs on the page that were enabled / disabled. Also a less popular Website. <br />
  • <br />
  • Checked to see if users used the dynamic content. Would they be distracted by all the other widgets? <br />
  • <br />
  • Two studies but groups shown here for completeness. Younger people run as a pilot to establish usefulness of the method. Get base case. More interesting when you compare the results from the two. <br />
  • Definite difference between the two groups. Younger used looked where the ASL would occur even when it didn&#x2019;t. Expected it to happen. <br />
  • More cautions, more hesitant. Ignored the ASLs on occasions. <br />
  • Older users no significant different. Younger users T-value was p = 0.0004 (significant). With One way ANOVA for all age groups (p = 0.195 for Google Search and p = 0.893 for Google Suggest) no significant difference when taking age into account. MSE = Mean squared error <br /> <br />
  • Definite difference between the two groups. Younger used looked where the ASL would occur even when it didn&#x2019;t. Expected it to happen. <br />
  • More cautions, more hesitant. Ignored the ASLs on occasions. <br />
  • Older users no significant different. Younger users T-value was p = 0.0004 (significant). With One way ANOVA for all age groups (p = 0.195 for Google Search and p = 0.893 for Google Suggest) no significant difference when taking age into account. MSE = Mean squared error <br /> <br />
  • For type 2, peaks occurred when something changed, eg video loaded. <br />
  • <br />
  • <br />
  • <br />
  • This is what we&#x2019;ll try and get out of the talk. Show how the Web has become more complex. Can use Galvanic Skin Response and Eye Tracking to identify areas that cause a reaction from the participant, which we associate with stress. Age was not a determining feature but a combination of factors that are more likely with age. <br />
  • <br />

Using Galvanic Skin Response Measures To Identify Areas of Frustration for Older Web 2.0 Users Using Galvanic Skin Response Measures To Identify Areas of Frustration for Older Web 2.0 Users Presentation Transcript

  • Using Galvanic Skin Response Measures To Identify Areas of Frustration for Older Web 2.0 Users Darren Lunn and Simon Harper
  • Summary • Web is more complex due to the evolution from static to dynamic content. • GSR + Eye Trackingstress for users. of content that cause can identify areas • Age is not how stressed users can become. identifying a determining factor for 2
  • The Web • Collection of documents linked together. • Content is static: - Images. - Tables. - Animations. • Users passively read content. 3
  • Yahoo! (May 2000) 4
  • The Web 2.0 • Collection of documents “mashed” together. • Application type Widgets: - Auto Suggest Lists. - Maps. • Users actively contribute to the content. 5
  • Yahoo! (April 2010) 6
  • Yahoo! (April 2010) 6
  • Yahoo! (April 2010) 6
  • Effect On Users • Establish if automatically updating components effects users. • Are stress levels effected by such components. • Do users know how to use the widgets. 7
  • Galvanic Skin Response • Used in the field of biofeedback. • Measures psychophysical reactions to a given event. 52600 52550 52500 Galvanic Skin Response Value 52450 52400 52350 52300 52250 52200 0 0 0 0 0 20 40 60 80 10 12 14 16 18 8 0 Time (0.1 Seconds)
  • Eye Tracking • Captures users’ eye movements. • Understand how users perceive the Web page or application. 1 3 2 9
  • GSR + Eye Tracking • Use GSR measurements to capture what users react to. • Use Eye Tracking to capture what users look at. 52600 Look at (1) Look at (2) 52550 Typing & Glancing 52500 Galvanic Skin Response Value 52450 Look at (1) Look at (2) 52400 Press Return (3) Typing 52350 Typing & Glancing 52300 Look at (2) 52250 52200 10 0 0 0 0 0 20 40 60 80 10 12 14 16 18 0
  • Comparison of GSR Graphs • Each person’s GSR graph is different. • Not attempting to create a generic GSR model. • Identify if similar graph.consistently cause responses in the areas • More responses can be considered as more stressful. 11
  • Four Directed Tasks • Search for “The University of Manchester” - Google Search / Suggest • Search for a train from “Manchester” to “London” - National Rail Enquiries Search / Suggest • Search version had ASLs disabled. Suggest version had ASLs enabled. 12
  • Directed Task Example Search Suggest 13
  • Two Browsing Tasks • Lookone the news stories on the page and find at that may be of interest. - iGoogle - Yahoo! UK • Wide range of widgets available to use. 14
  • Browsing Task Example 15
  • Participants Sample Size Age Group Male Female Combined Mean Std. Dev. ≤29 18 3 21 17.52 2.66 30 - 49 6 2 8 40.88 7.40 50 - 59 4 4 8 52.00 2.33 60 - 69 4 3 7 62.57 2.57 Total 32 12 44 16
  • Google Results • Youngerpages consistently:with the two Google users interacted - Look at the search box. - Look between search box and auto suggest list area. • Disabling the ASL caused significantly more stress from the GSR readings. 17
  • Google Results • Older users did not interact with the Google pages consistently - Used the “UK Pages” radio button. - Ignored screen and only looked at keyboard. - Avoidance of using ASLs. • No difference in stress between the two Websites. 18
  • Google Results T Test Between Tasks Group T p(T≤t) ≤29 4.29 0.0004 30 - 49 0.55 0.60 50 - 59 0.24 0.82 60 - 69 1.77 0.13 19
  • National Rail Results • Younger userspages in lesswith the two National Rail interacted consistently: - look around the page before typing. - Type in wrong search box. - Look between search boxes and auto suggest list area. • Disabling the ASL caused significantly more stress from the GSR readings. 20
  • National Rail Results • Older users did tend to interact with the National Rail pages consistently - Looking around the page - Type and glance at the search box. • No difference in stress between the two Websites except for 50 - 59s. 21
  • National Rail Results T Test Between Tasks Group T p(T≤t) ≤29 2.32 0.03 30 - 49 0.15 0.86 50 - 59 2.73 0.04 60 - 69 1.93 0.102 22
  • iGoogle and Yahoo! Results • Typically two user types: - Those who fixated on the news story to complete the task. - Those who got distracted by lots of updating regions. • Not all participants made use of the widgets. 23
  • Experience • Youngerdue to being very familiar with expect users typically knew what to certain Web pages. • Older users typically had less experience and so dealt with the page “as is”. • Howevercontent. with the were competent at interacting 24
  • Cautiousness • Younger users typically went wrong the computer when things lay blame on - “That’s not me. It’s the keyboard!” • Some things users lay blame on themselves when older went wrong: - “Oh no! Look at that.” 25
  • Abilities • Younger users typically completed tasks in similar ways: - Little talking / discussion - As fast as possible • Older users had a wider range of skills: - Some completed tasks quickly - Some talked through all the actions 26
  • Summary • Web is more complex due to the evolution from static to dynamic content. • GSR + Eye Trackingstress for users. of content that cause can identify areas • Age is not how stressed users can become. identifying a determining factor for 27
  • Question? http://hcw.cs.manchester.ac.uk/