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Insights from Human Factors International
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In This Issue:
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Do y'see what I'm saying? Using visual hierarchy
to support your message
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Kath Straub, Ph.D., CUA, Chief Scientist of HFI, looks at the effect
of visual hierarchy on user comprehension.
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The Pragmatic Ergonomist
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Dr. Eric Schaffer, Ph.D., CPE, founder and CEO of HFI offers practical
advice.
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Have you ever tried to read a paper that someone else highlighted? If
you have, you know that it is not an easy thing to do. Different people
read (and highlight) toward different goals. Even so, it is hard to resist
being drawn toward text that has – for better or worse – already
been rendered bright yellow.
In their 1997 paper, Silvers and Kreiner documented the pernicious effects
of inappropriate highlighting. They compared comprehension scores for
students reading un-highlighted and inappropriately highlighted text.
Not surprisingly, they found that working through inappropriately highlighted
text resulted in lower reading comprehension scores. In addition, they
found that prior knowledge didn't help. Students who were warned to ignore
the highlighting scored no better than those who were not warned. This
has serious implications for used textbook buyers. It also has implications
for Web page designers.
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The message received also depends on the receiver
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Web pages are designed to convey a message. Message receivers face a
fairly complicated task. They must filter out the meaningless content
in the visual presentation, identify the meaningful content, recognize
its patterns, interpret and encode it. The effectiveness of this process
can be influenced by receiver characteristics such as age and familiarity
with the content. It may also be affected by information processing constraints
such as attentional focus and memory limitations.
On the Web, as in other presentation channels, there are two components
to a message:
- the message itself, and
- how it is presented.
Seemingly mundane points of content presentation can have influence on
how effectively a document (online or otherwise) conveys its message.
For instance, using typographic details (such as San Serif fonts for headings
and Serif fonts in the body) to help readers recognize the organizational
elements of a document, reportedly correlates positively with overall
funding scores for peer-reviewed grant proposals (Berlant, 2000). Interestingly,
these effects can arise well before any content actually needs interpreting.
Legibility effects actually begin at the physiological/ transductive level
in the eye: work by Rubinstein and Ulichney suggests that the type faces
Helvetica and Times are easier to read than Courier because the frequency
of the vertical strokes in those fonts matches the sensitivity of the
visual system. (Rubinstein, 1988)
The idea that well-crafted content facilitates message transfer should
not be surprising. Presenting well-labeled headings offers readers a roadmap
with which to navigate your content. Offering organized, meaningful chunks
helps them to map your content with what they already know, facilitating
both the interpretation and encoding of your message.
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| Optimizing presentation in search
and compare environments |
Wu and Yuan (2003) present a study designed to demonstrate
that presentation details can facilitate message transmission in data rich
environments. Specifically, they evaluated the effectiveness of various
table presentations when participants are tasked with identifying and comparing
information within a table. Their study explored both the utility of gridlines
in table presentation, and the effectiveness of different approaches to
highlighting critical information within the table.
Within the gridline condition, they compared:
- tables with column gridlines,
- tables with row gridlines,
- tables with both column and row gridlines, and
- tables with no grid lines.
These different presentation styles are shown in the following figure.

Within the highlighting condition, they compared various approaches to
highlighting key data, including:
- blinking key data,
- reverse video,
- colored (red) text, and
- single colored displays (no highlight control).
Participants in this study were asked to scan the tables to identify
cases in which there was a discrepancy between data presented across two
columns in the same row.
Within the gridline comparison, they found participants were roughly
25% faster in comparing target data pairs in tables that had either no
gridlines or had both row and column grids. In contrast, participants
were slowed when they were examining data in tables with just row or just
column gridlines.
Highlighting had an even greater impact. Participants were significantly
faster at identifying exceptional cases when they were highlighted compared
with when the same case were presented without highlighting. In some comparisons
this improvement was greater than 50%. Blinking and reverse text helped
participants focus in on the critical data. Participants proved numerically
(but not significantly) fastest at identifying exceptional cases when
they were simply highlighted with a different text color – in this
case red.
Though not presented in the paper, one explanation I see for the reported
differences could be that the participants' task fundamentally changes
between the no highlight (control) condition to the highlight conditions.
Think about the functional allocation of the sub-tasks that make up the
task. In each trial, the basic process is:
1. Read the value in column A (and remember it)
2. Read the value in column B of the same row (and remember it)
3. Decide if Value A = Value B
4a. If yes, go to next row
4b. If no, record the value
In the control condition the human has to execute each of those steps.
In the highlight condition, the computer (by way of the designer's highlights)
executes steps 1-4a. The participants task flow changes to:
- Scan for the exception
- Record the value
The simple step of using type face appropriately removes steps 1-3 from
the human's sub-task set.
So, by providing visually guiding highlights, the designer essentially
shifts the functional allocation of the task. The part of the task that
is harder for the human (find and compare) is shifted from the human to
the computer. By allocating the functions appropriately, the task becomes
easier for the participant. It is completed more quickly. It is also likely
to be executed with fewer errors – although this is not discussed
in the results section of the paper.
Independent of the analysis, Wu and Yuan (2003) demonstrate that the
visual presentation level can influence the speed with which users can
scan and interpret tabular data.
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The ROI of attention to detail
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Have you ever stared at a Web page that was just tiring to look at (much
less to read)? Unfortunately, Web and information designers often underestimate
the impact of "background" visual details, such as gridlines
in tables. As a result, they fail to exploit the visual hierarchy created
by detailed design. Or worse, they create visual chaos with it. The cost
of this failure to guide their receiver's attention through the message
space can add up quickly.
Consider the differences reported by Wu and Yuan. Effective tabular presentation
saved slightly over two seconds per table. Appropriate functional allocation
saved roughly five seconds per screen. Tullis (1983) reported that employees
at a single insurance company view over 4.8 million screens per year.
Galitz (1980) reported that Bell system employees, using only one software
package, extract information from over 344 million displays within the
same period. Given these numbers, a savings of only a few seconds in processing
time per display could lead to enormous time and cost savings over the
long run.
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| More on basic typography |
Kahn, P. and Lenk, K. (1998). Principles of Typography for
User Interface Design. Interactions, November-December.
pp 15-29.
Rubinstein, R. (1988) Digital Typography: An Introduction to Type and
Composition for Computer System Design, Addison-Wesley.
Savio, N., Web Typography
Tutorial, WebMonkey.
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Good usability engineers look at the high-level structure of a page.
They shape the user's understanding with cues about the hierarchy, relationship,
and criticality of data. To this end we add headers, highlighting, font
changes, and other powerful cues. These can be very effective. But this
newsletter gives us a caution. Sloppy or poorly chosen cues are WORSE
than no cues at all. So we have convincing evidence that poorly conceived
and gratuitous cues will impair the user's performance.
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References
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Berlant, W. (2002) Does typography affect overall proposal
assessment. Communications of the ACM, 43(8),
pp. 24-25.
Galitz, W. (1980) in: Proceedings of the Life Office Management Association
on Human Factors in Office Automation, Atlanta,
1980.
Rubinstein, R. (1988) Digital Typography: An Introduction to Type and
Composition for Computer System Design, Addison-Wesley.
Silvers, V.L. and Kreiner, D.S. (1997). The Effects of Pre-Existing Inappropriate
Highlighting on Reading Comprehension. Reading Research
and Instruction, 36(3), pp. 217-23.
Tullis, T. (1983) The formatting of alphanumeric displays: a review and
analysis, Human Factors 25, pp. 657-682.
Wu, J. and Yuan, Y. (2003) Improving searching and reading performance:
the effect of highlighting and text color coding Information
& Management, 40, pp. 617–637.
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Past Issues
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