Legal researchers were tested to see whether their preferred settings for reading documents online resulted in better perceived visual appeal and performance. Results showed that customized text formatting does not translate into improved reading performance, nor does it sustain its “preferred” status when compared to optimized alternatives.

1. The effects of preferred text formatting on performance and
perceptual appeal
Paul Doncaster
Senior User Experience Designer
Spring 2010

2. Agenda
• Introduction to Research
• Readability Factors
• Our Method & Analysis
• Results & Discussion
• Conclusion

3. Introduction to Research
3

4. Why readability is important
• Readable text stands out AND is recognizable
• A website that can be read can be read again,
and again
• Readable text connects to your reader
• Readable text lowers barriers to other content on
your site
• A readable website puts your readers at
immediate ease
http://ezinearticles.com/?Five-Reasons-Why-Readability-is-Important-For-Your-Website&id=4283444

5. www.cnn.com, 11/3/2010
5

6. Quest for the “ideal” text formatting state
• For the “enlightened” designer
– Rely on style guides and best practices to settle on a
default set of text formatting criteria
– Provide features that allow the user to adjust those
criteria to a personalized "preferred" state

7. Quest for the “ideal” text formatting state
• For the “enlightened” designer
– Rely on style guides and best practices to settle on a
default set of text formatting criteria
– Provide features that allow the user to adjust those
criteria to a personalized "preferred" state
• Implied assumption: the implementation of a
preferred state will
– meet the reader’s immediate needs
– positively affect perceptual appeal of the online reading
environment
– increase task performance (hopefully)
– enhance the overall user experience

8. Readability Literature Review (for Cobalt)
• Recommendations based on review of related
studies and design/UX literature (97 sources)
Criteria Suggestion
Font Type Verdana, Arial
Font Size 12 or 13 point
Line Length 60 characters per line, with a limit of 70 cpl
Interlinear Spacing 1.5 spacing between lines
Whitespace Extra space between paragraphs; indent first line of each new
paragraph
Columns Single column
Justification Left-justify, ragged right edge
Color Black text on very light gray background

9. A Research Opportunity

10. Theory of “Miswanting”
• Just because we say we want something does
not necessarily mean we’ll like it if and when we
get it
Gilbert, D.T. & Wilson, T.D. (2000). Miswanting: Some problems in the forecasting of future affective states.
In Lichtenstein, S. & Slavic, P. (Eds.), The Construction of Preference. Cambridge University Press, 550-
563.

11. Theory of “Miswanting”
• Just because we say we want something does
not necessarily mean we’ll like it if and when we
get it
Gilbert, D.T. & Wilson, T.D. (2000). Miswanting: Some problems in the forecasting of future affective states.
In Lichtenstein, S. & Slavic, P. (Eds.), The Construction of Preference. Cambridge University Press, 550-
563.
• Just because we indicate that we like something does not
necessarily mean it will result in better performance

12. Theory of “Miswanting”
• Just because we say we want something does
not necessarily mean we’ll like it if and when we
get it
Gilbert, D.T. & Wilson, T.D. (2000). Miswanting: Some problems in the forecasting of future affective states.
In Lichtenstein, S. & Slavic, P. (Eds.), The Construction of Preference. Cambridge University Press, 550-
563.
• Just because we indicate that we like something does not
necessarily mean it will result in better performance
• Just because we indicate that we like something does not
necessarily mean we’ll still like it if presented with a better
alternative

13. Our Questions
• For Cobalt design/development
– What should be the default text formatting settings for
online reading?
• For research
– Is performance discernibly better when using a
preferred state than when using optimized alternatives?
– Is the perceptual appeal of the preferred state
maintained after exposure to those alternatives?

14. Readability Factors
14

15. Factors
• Reading performance is
ultimately determined by a
variety of factors that can be
divided into three categories
– Typographic
– Atmospheric
– Contextual

16. Typographic
• Characteristics of the letters
and words as they exist
electronically
– Effectiveness of serif vs.
sans serif fonts
– How font sizes affect
readers of all age groups
– How “optimal” line length
makes a significant
difference for reading

17. Atmospheric
• Delivery of the typographic
factors
• Display size
• Display resolution
• Display illumination
• Display position
• The physical conditions and
environments of online
reading
– How task efficiency and
accuracy can be impacted
by
• Ambient lighting
• Ergonomic factors

18. Contextual
• The uniqueness of users
– The motivations that drive
them
– Various strategies they
employ to maximize
cognitive efficiencies
• Reading
• Skimming
• Scanning

19. Preference
• In research literature, it largely plays a supporting
role in answering practitioner questions
– More often than not, preference measurements are
taken as supporting data in determining an ideal default,
or “best,” text formatting for websites
• The SURL lab (http://www.surl.org/) has done a
fairly good job of including preference into its
many research articles

20. Preference (cont’d)
– Other attempts at
determining “preferred”
font settings for websites
suffer from focusing
strictly on only a few
typographic factors
• no controls on the
atmospheric factors
• critical contextual factors
“What Is Your Text Preference?”
ignored at http://www.message.uk.com/textprefs/

21. Our method & analysis
21

22. Study logistics
• Portland, OR
• 24 participants (10 women, 14 men) ranging in age
from 25 to 62 (M = 42.9 years)
• 50/50 split: over/under age 40
• At least 4 hours of online legal research per week
• Had to pass a Snellen near acuity test in order to
participate

23. Procedures
• Establishment of Preferred Settings
• Performance measurement
– Cases/Statutes = Reading
– Results List = Information Target Detection
• Perception measurement

24. Self-formatting option groups
Criteria Options
Font Type Arial, Verdana, Tahoma, Georgia, Times
Font Size 10px, 11px, 12px, 13px, 14px, 16px
Margin Width 45px, 75px, 105px, 150px, 225px
Interlinear Spacing ** dynamically programmed to be 4, 6, 8 or 10 pixels larger than
the selected font size
Justification indent/align left
no indent/align left
indent/justify
no indent/justify
Font/Background
#000000 on #FFFFFF #000000 on #F7F7F7
Color
#636363on # FFFFFF #363636 on # FFFFFF

25. Performance
• Participants were exposed to content formatted in six different
text formatting “suites”

26. UP: User Preference, established by participant in Procedure 1
?
WL: Westlaw text default settings
LX: Lexis text default settings

27. DT1: Optimized setting combination recommended for testing by the Cobalt Design Team
DT2: Optimized setting combination recommended for testing by the Cobalt Design Team
DT3: Optimized setting combination recommended for testing by the Cobalt Design Team

28. Prototype Demonstration

29. Procedure 3: Perception
• After each performance test, participants were asked to rate
the text-formatting suite they had just used on two 10-point
Likert scales (perceived readability and visual appeal)
• Once all performance tests for a content type were
completed, participants were asked to rank the suites in order
of overall preference for both readability and visual appeal
• Participants were encouraged to toggle between all of the
suites in the prototype to achieve an informed comparison

30. Results & Discussion
30

31. Performance
• Reading (Cases & Statutes)
– Error Detection
• Very little difference in the detection of errors between suites
• All error id averages were between 82.2% and 88.1%

32. Performance
• Reading (Cases & Statutes) Statute Case
– Speed UP
• DT2 had the fastest overall
average DT1
• LX had the slowest overall DT2
average
• There were instances of DT3
significant variance between
WL
the average times within a
suite, most notably for UP LX
170 180 190 200 210 220 230 240
Seconds to complete

33. Performance
• Info Target Detection
(Results Lists) UP
– DT1 was the only suite in
DT1
which there all information
items were correctly DT2
identified by all participants
DT3
– UP and WL performed
equally well, and both WL
performed somewhat
LX
better than the remaining
suites 0 20 40 60 80 100 120 140
Seconds to complete

34. Ratings & Rankings
• Perceptual scores for UP were generally high
• UP had highest ratings for both readability and
visual appeal
Averaged Ratings Averaged Rankings
(9=high, 1=low) (1-6)
Suite Readability Visual Appeal Readability Visual Appeal
UP 7.06 6.82 2.61 3.06
DT1 7.12 6.74 2.11 2.47
DT2 5.17 5.18 4.19 3.84
DT3 5.11 5.10 4.64 4.20
WL 5.55 5.04 4.31 4.59
LX 5.81 5.80 3.14 3.01

35. Discussion: Cobalt defaults
Criteria Lit Review UP/Testing* Doc Display defaults
Font Type Verdana, Arial Verdana Arial, Verdana
Font Size 12 or 13 point (~16-17px) 14-16px 15px
Margins Accommodate ~70 75 px or more (min 70-75 Normal = 40px (~80 cpl
characters per line cpl at 1024x768) at 1024x768)
Justification Left-justify, ragged right Left-justify, ragged right Left-justify, ragged right
edge edge edge
Color #000000 on #DEDEDE #000000 on #FFFFFF #252525 on #FFFFFF
* Accumulated User Preferences, established by participants in Procedure 1;
performance and perception were not factored

37. Discussion: Research
• ASSUMPTION 1: PERFORMANCE
– Reading performance enhancement via the creation of a
“preferred” formatting state was not consistent
– Overall, performance measures (% of errors detected
divided by reading time) showed none of the suites being
statistically significant from each other

38. Discussion
• ASSUMPTION 2: PERCEPTION
– Formatting text to a preferred state did not mean that the
preference fared well when compared to alternatives
– for the 96 instances (48 for readability, 48 for visual appeal) in
which a participant could have given his/her UP a higher rating
than the other options, they did so only 29 times (30.2%)
– Likewise, for the same number of instances in which a participant
could have ranked his/her UP first, it actually was only 40 times
(40.8%).

39. Conclusion
39

40. Conclusion
• The results do not support the implied assumption
that personalized text formatting positively affects
perceptual appeal of the online reading
environment and, consequently, reading
performance
However . . .

41. Conclusion
• Though not a central focus of our study, fodder for
future research may be found in the differences
seen between those under and over age 40
– Larger variances in both performance and rankings in the
over-40 group, who were more likely to rank their own
preferences higher in both readability and visual appeal
– The 40+ set may be affected far more by decisions made
for default formatting
– Websites targeting that profile must be flexible enough to
accommodate personalization of text formatting
• Supported by the drive to make websites compliant with
web accessibility guidelines

42. Conclusion
Doncaster, P. and Samnee, N. (2010). The effects of preferred
text formatting on performance and perceptual appeal. In
Proceedings of the Usability Professionals Association
(UPA 2010) Conference, Munich, Germany.

43. Questions?
43

44. Appendix
44

45. Bibliography
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states. In Lichtenstein, S. & Slavic, P. (Eds.), The Construction of Preference. Cambridge University
Press, 550-563.

46. APPENDIX I: Bibliography
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