Tag Archives: information design

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The importance of design – Can you read this at 60 MPH?

The New York Times had a great article a few months ago about redesigning the font used on highway signs.  You’ve probably seen the current font, Highway Gothic, a million times without ever thinking about it – it’s been in use for more than 50 years.

Granphic from the New York TimesWorrying about the font on the signs seems pretty silly compared to all the engineering and resources that go into a single bridge, let alone the entire highway system.  Why does this merit an article in the Times and what does this have to do with programing, web development, social software, or any of the topics many visitors to this blog are interested in?

Programmers and analysts sometimes doubt the value of design.  It’s hard work gathering all the requirements and writing all the code – we don’t have time to worry about how pretty it looks.  A lot of projects we work on, though, involve creating user interfaces, often web applications.  That means that, when it comes down to it, your job is to support the user’s tasks.

Now if someone wanted to add 10% to your hours to pick just the right shade of chartruse, you would be justifiably miffed.  But good interface designers will have good, empirically-tested reasons for their work and the guidelines they live by.  Highway signs are a great example of this kind of empirical benefit:

Intrigued by the early positive results, the researchers took the prototype out onto the test track. Drivers recruited from the nearby town of State College drove around the mock highway. From the back seat, Pietrucha and Garvey recorded at what distance the subjects could read a pair of highway signs, one printed in Highway Gothic and the other in Clearview. Researchers from 3M came up with the text, made-up names like Dorset and Conyer ? words that were easy to read. In nighttime tests, Clearview showed a 16 percent improvement in recognition over Highway Gothic, meaning drivers traveling at 60 miles per hour would have an extra one to two seconds to make a decision.

A one or two second gain in legibility matters a lot when your life depends on it.  Few web applications present the same kind of physical danger, but multiply a small gain over an application with 10,000 users, operating 24 hours a day for a year, and you can see how this can impact the business.  Good design is part of the larger concept of usability.  As anyone who’s done any usability testing can tell you, most applications have many small, easy-to-change pitfalls that can quickly add up to huge wastes of time and effort.

Data Visualization with Maps

One of the best ways to show relationships in data is also one of the oldest: maps. There are lots of cool, fun visualizations out there like topic maps and tag clouds, but sometimes they emphasize form over function (and usability). Maps can be a great choice, even if your data is not directly geographical.

Here’s one example: a map of the United States showing where people use the terms “soda,” “pop,” or “coke.”

You might think this one was a pretty obvious choice, but you could definitely imagine someone using a pie chart to show the total percentages instead, throwing out a ton of information in the process.

Here’s one that’s a little more clever: a map of the United States, which each state labeled by a country with the same GDP. from strange maps.

states-gdp.png

Now, you could argue with the precision of presentation since most people don’t know the exact GDP of Algeria off the top of their heads. But show them a table of figures and ten minutes later they still won’t know. This is a much more interesting and memorable presentation of the data.

Formal usability testing with eye tracking – Mealographer

Usability Testing

Usability tests can be seen to fall into two general categories, based on their aim: tests which aim to find usability problems with a specific site, and tests which aim to prove or disprove a hypothesis. This test would fall into the former category. A search of the literature will reveal that tests looking to uncover specific usability problems often use a very small number of participants, coming from Nielsen’s (2000) conclusion that five users is enough to find 85 percent of all usability problems. Nielsen derived this formula from earlier work (Nielsen and Landauer, 1993). Although there is much disagreement (Spool and Schroeder, 2001), this rule of thumb has the advantage of fitting the time and money budget of many projects.

Use of Eye-Tracking Data

In terms of raw data, eye tracking produces an embarrassment of riches. A text export of one test of Mealographer yielded roughly 25 megabytes of data. There are a number of different ways eye tracking data can be interpreted, and the measures can be grouped into measures of search and measures of processing or concentration (Goldberg and Kotval, 1999):

Measures of search:

  • Scan path length and duration
  • Convex hull area, for example the size of a circle enclosing the scan path
  • Spatial density of the scan path.
  • Transition matrix, or the number of movements between two areas of interest
  • Number of saccades, or sizable eye movements between fixations
  • Saccadic amplitude

Measures of processing:

  • Number of Fixations
  • Fixation duration
  • Fixation/saccade ratio

In general, longer, less direct scan paths indicate poor representation (such as bad label text) and confusing layout, and a higher number of fixations and longer fixation duration may indicate that users are having a hard time extracting the information they need (Renshaw, Finlay, Tyfa, and Ward, 2004). Usability studies employing eye tracking data may employ measures that are context-independent such as fixations, fixation durations, total dwell times, and saccadic amplitudes as well as screen position-dependent measures such as dwell time within areas of interest (Goldberg, Stimson, Lewenstein, Scott, and Wichansky, 2002).

Because of the time frame of this investigation, the nature of the study tasks, and the researcher’s inexperience with eye tracking hardware and software, eye tracking data was compiled into “heat maps” based on the number and distribution of fixations. These heat maps are interpreted as a qualitative measure.

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