33 gaining acess to information at a municipality website  a question of age
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33 gaining acess to information at a municipality website a question of age






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33 gaining acess to information at a municipality website  a question of age 33 gaining acess to information at a municipality website a question of age Presentation Transcript

  • AegisGaining acess to information at a municipality website: A question of age? Prof. Dr. Eugène Loos University of Amsterdam e.f.loos@uva.nl
  • ‘Digital Immigrants’ versus ‘Digital Natives’? Prensky (2001)
  • Research questions1. To which extent do older people indeednavigate websites differently from youngerpeople?2. Which kind of differences can bedistinguished?3. What are the implications fororganisations wanting to ‘design fordynamic diversity’ ?
  • DataLiterature review of eye-tracking studiesDutch explorative eye-trackingcase study which I conducted in 2009
  • Literature reviews about studies related to the waysyounger and older people use websites to findinformationPernice & Nielsen (2002)Chisnell & Redish (2004, 2005)Andrew (2008)Most studies are based on observations and interviewsbut they don’t give us insight into differences related tothe navigation behaviour of younger and older users.
  • Eye-tracking studies giving us insight intothe navigation behaviour by older andyounger people using websitesAccording to Tullis (2007) and Houtepen(2007) older users read more text (broaderreading pattern) than younger ones.But: These eye-tracking studies werebased on a low number of participants andpaid no attention to factors other than age.
  • Dutch explorative eye-tracking case study(Loos & Mante-Meijer, 2009)29 younger and 29 older usersrespectively about 21 years oldand 65 years and older
  • The users performed a search task on thewebsite of Maarssen, a Dutch municipality.The users had to find information aboutparking facilities for people with disabilitiesin their municipality which could be foundon a specific web page of the website.
  • Heatmaps and gaze plots are used to showthe output of the eye-tracking instrumentwhich measures the eye-movements of thedifferent user groups.
  • Heatmaps use different colours to showhow intensely navigation areas are visitedbased on the number of fixations byindividual users or groups of users (red forhigh, yellow for moderate and green for lowintensity). Red-white demarcations showwhere users have clicked.
  • Gaze plots provide insight into the eyemovements, or saccades, of individualusers by presenting the order (numbers incircles) and duration of gaze fixations (thelonger the gaze fixations the bigger thecircle). Red-white demarcations showwhere users have clicked.
  • Eye-tracking
  • Results
  • Heatmap (1): all older users Heatmap (2): all younger users
  • ●The heatmaps showed that navigationpatterns of senior citizens differ fromthose of younger people to a certainextent.Older users read more text thanyounger users. The eye-trackingstudies conducted by Tullis (2007) andHoutepen (2007) showed a similarresult.
  • ● 79.3 % of all older usersaccomplished the search tasksuccessfully versus 100% of allyounger users.● Younger users were found to befaster than older users, averaging 81versus 104 seconds.This confirms the result of the studiesconducted by Tullis (2007) andHoutepen (2007).
  • ‘Intra-age variability’Although differences in navigationbehaviour in this eye-tracking study areto some extent age-related,there are also differences within the groupof senior citizens (‘intra-age variability’ –Dannefer, 1988) due to gender, educationalbackground and frequency of internet use.
  • ● Gender differencesOnly 26.7% of the older male users madeuse of the search box versus 50% of theolder female users.86.7% of all older male users succeeded inaccomplishing the search task successfullyversus 71.4% of all older female users.Older male users were faster than femaleusers, averaging 94 versus 116 seconds.
  • ● Educational differencesOlder users with a higher level ofeducation were more successful thanless educated older users: 89.5% versus60%.Older users with higher educationwere much faster than older userswithout higher education, respectivelyaveraging 94 seconds and 131 seconds.
  • ● Differences related to frequency ofinternet useOlder users who did not make daily useof the internet were slower than olderusers who make daily use of theinternet, respectively averaging 113seconds and 98 seconds.
  • ConclusionThe black-and-white distinctionbetween Prensky’s ‘digital natives’ and‘digital immigrants’ was absent.Instead, what emerged was far more a‘digital spectrum’ (Lenhart & Horrigan,2003) rather than a ‘digital divide’.
  • Implications for website designers1) ‘Age-restricted users’ are atconsiderable risk from age-relatedfunctional limitations, making itdifficult and more time-consumingfor them to search information onwebsites.Solution: ‘multimodality’ – the use ofimages, text and sound.
  • The fear that this might irritate youngerand more experienced users isunfounded.A study carried out by Johnson & Kent(2007) showed that, rather than havingan adverse effect on a site’s userfriendliness, it tended to enhance it forall users.
  • 2) If you wish to enhance the accessibilityof your organisation’s website then followthe principle of ‘designing for dynamicdiversity’ (Gregor et al. 2002):‘the premise of which is that older peopleare much more diverse in terms of lifeexperience and levels of capability anddisability than their younger counterparts.’Chisnell & Redish (2004: 48)
  • 3) Ask various users to participate inusability testing and to proceed indifferent rounds (Krug, 2006)