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Aegis

Gaining 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 questions

1. To which extent do older people indeed
navigate websites differently from younger
people?

2. Which kind of differences can be
distinguished?

3. What are the implications for
organisations wanting to ‘design for
dynamic diversity’ ?
Data

Literature review of eye-tracking studies

Dutch explorative eye-tracking
case study which I conducted in 2009
Literature reviews about studies related to the ways
younger and older people use websites to find
information

Pernice & Nielsen (2002)
Chisnell & Redish (2004, 2005)
Andrew (2008)

Most studies are based on observations and interviews
but they don’t give us insight into differences related to
the navigation behaviour of younger and older users.
Eye-tracking studies giving us insight into
the navigation behaviour by older and
younger people using websites

According to Tullis (2007) and Houtepen
(2007) older users read more text (broader
reading pattern) than younger ones.
But: These eye-tracking studies were
based on a low number of participants and
paid no attention to factors other than age.
Dutch explorative eye-tracking case study
(Loos & Mante-Meijer, 2009)

29 younger and 29 older users
respectively about 21 years old
and 65 years and older
The users performed a search task on the
website of Maarssen, a Dutch municipality.

The users had to find information about
parking facilities for people with disabilities
in their municipality which could be found
on a specific web page of the website.
Heatmaps and gaze plots are used to show
the output of the eye-tracking instrument
which measures the eye-movements of the
different user groups.
Heatmaps use different colours to show
how intensely navigation areas are visited
based on the number of fixations by
individual users or groups of users (red for
high, yellow for moderate and green for low
intensity). Red-white demarcations show
where users have clicked.
Gaze plots provide insight into the eye
movements, or saccades, of individual
users by presenting the order (numbers in
circles) and duration of gaze fixations (the
longer the gaze fixations the bigger the
circle). Red-white demarcations show
where users have clicked.
Eye-tracking
Results
Heatmap (1): all older users   Heatmap (2): all younger users
●The heatmaps showed that navigation
patterns of senior citizens differ from
those of younger people to a certain
extent.

Older users read more text than
younger users. The eye-tracking
studies conducted by Tullis (2007) and
Houtepen (2007) showed a similar
result.
● 79.3 % of all older users
accomplished the search task
successfully versus 100% of all
younger users.

● Younger users were found to be
faster than older users, averaging 81
versus 104 seconds.
This confirms the result of the studies
conducted by Tullis (2007) and
Houtepen (2007).
‘Intra-age variability’

Although differences in navigation
behaviour in this eye-tracking study are
to some extent age-related,
there are also differences within the group
of senior citizens (‘intra-age variability’ –
Dannefer, 1988) due to gender, educational
background and frequency of internet use.
● Gender differences

Only 26.7% of the older male users made
use of the search box versus 50% of the
older female users.

86.7% of all older male users succeeded in
accomplishing the search task successfully
versus 71.4% of all older female users.

Older male users were faster than female
users, averaging 94 versus 116 seconds.
● Educational differences

Older users with a higher level of
education were more successful than
less educated older users: 89.5% versus
60%.

Older users with higher education
were much faster than older users
without higher education, respectively
averaging 94 seconds and 131 seconds.
● Differences related to frequency of
internet use

Older users who did not make daily use
of the internet were slower than older
users who make daily use of the
internet, respectively averaging 113
seconds and 98 seconds.
Conclusion

The black-and-white distinction
between 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 designers

1) ‘Age-restricted users’ are at
considerable risk from age-related
functional limitations, making it
difficult and more time-consuming
for them to search information on
websites.
Solution: ‘multimodality’ – the use of
images, text and sound.
The fear that this might irritate younger
and more experienced users is
unfounded.

A study carried out by Johnson & Kent
(2007) showed that, rather than having
an adverse effect on a site’s user
friendliness, it tended to enhance it for
all users.
2) If you wish to enhance the accessibility
of your organisation’s website then follow
the principle of ‘designing for dynamic
diversity’ (Gregor et al. 2002):
‘the premise of which is that older people
are much more diverse in terms of life
experience and levels of capability and
disability than their younger counterparts.’
Chisnell & Redish (2004: 48)
3) Ask various users to participate in
usability testing and to proceed in
different rounds (Krug, 2006)

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

  • 1. Aegis Gaining acess to information at a municipality website: A question of age? Prof. Dr. Eugène Loos University of Amsterdam e.f.loos@uva.nl
  • 2. ‘Digital Immigrants’ versus ‘Digital Natives’? Prensky (2001)
  • 3. Research questions 1. To which extent do older people indeed navigate websites differently from younger people? 2. Which kind of differences can be distinguished? 3. What are the implications for organisations wanting to ‘design for dynamic diversity’ ?
  • 4. Data Literature review of eye-tracking studies Dutch explorative eye-tracking case study which I conducted in 2009
  • 5. Literature reviews about studies related to the ways younger and older people use websites to find information Pernice & Nielsen (2002) Chisnell & Redish (2004, 2005) Andrew (2008) Most studies are based on observations and interviews but they don’t give us insight into differences related to the navigation behaviour of younger and older users.
  • 6. Eye-tracking studies giving us insight into the navigation behaviour by older and younger people using websites According to Tullis (2007) and Houtepen (2007) older users read more text (broader reading pattern) than younger ones. But: These eye-tracking studies were based on a low number of participants and paid no attention to factors other than age.
  • 7. Dutch explorative eye-tracking case study (Loos & Mante-Meijer, 2009) 29 younger and 29 older users respectively about 21 years old and 65 years and older
  • 8. The users performed a search task on the website of Maarssen, a Dutch municipality. The users had to find information about parking facilities for people with disabilities in their municipality which could be found on a specific web page of the website.
  • 9. Heatmaps and gaze plots are used to show the output of the eye-tracking instrument which measures the eye-movements of the different user groups.
  • 10. Heatmaps use different colours to show how intensely navigation areas are visited based on the number of fixations by individual users or groups of users (red for high, yellow for moderate and green for low intensity). Red-white demarcations show where users have clicked.
  • 11. Gaze plots provide insight into the eye movements, or saccades, of individual users by presenting the order (numbers in circles) and duration of gaze fixations (the longer the gaze fixations the bigger the circle). Red-white demarcations show where users have clicked.
  • 14. Heatmap (1): all older users Heatmap (2): all younger users
  • 15. ●The heatmaps showed that navigation patterns of senior citizens differ from those of younger people to a certain extent. Older users read more text than younger users. The eye-tracking studies conducted by Tullis (2007) and Houtepen (2007) showed a similar result.
  • 16. ● 79.3 % of all older users accomplished the search task successfully versus 100% of all younger users. ● Younger users were found to be faster than older users, averaging 81 versus 104 seconds. This confirms the result of the studies conducted by Tullis (2007) and Houtepen (2007).
  • 17. ‘Intra-age variability’ Although differences in navigation behaviour in this eye-tracking study are to some extent age-related, there are also differences within the group of senior citizens (‘intra-age variability’ – Dannefer, 1988) due to gender, educational background and frequency of internet use.
  • 18. ● Gender differences Only 26.7% of the older male users made use of the search box versus 50% of the older female users. 86.7% of all older male users succeeded in accomplishing the search task successfully versus 71.4% of all older female users. Older male users were faster than female users, averaging 94 versus 116 seconds.
  • 19. ● Educational differences Older users with a higher level of education were more successful than less educated older users: 89.5% versus 60%. Older users with higher education were much faster than older users without higher education, respectively averaging 94 seconds and 131 seconds.
  • 20. ● Differences related to frequency of internet use Older users who did not make daily use of the internet were slower than older users who make daily use of the internet, respectively averaging 113 seconds and 98 seconds.
  • 21. Conclusion The black-and-white distinction between 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’.
  • 22. Implications for website designers 1) ‘Age-restricted users’ are at considerable risk from age-related functional limitations, making it difficult and more time-consuming for them to search information on websites. Solution: ‘multimodality’ – the use of images, text and sound.
  • 23. The fear that this might irritate younger and more experienced users is unfounded. A study carried out by Johnson & Kent (2007) showed that, rather than having an adverse effect on a site’s user friendliness, it tended to enhance it for all users.
  • 24. 2) If you wish to enhance the accessibility of your organisation’s website then follow the principle of ‘designing for dynamic diversity’ (Gregor et al. 2002): ‘the premise of which is that older people are much more diverse in terms of life experience and levels of capability and disability than their younger counterparts.’ Chisnell & Redish (2004: 48)
  • 25. 3) Ask various users to participate in usability testing and to proceed in different rounds (Krug, 2006)