A sudoku puzzle consists of nine 3×3 squares, sprinkled with a few starter numbers. The player must fill in all the blanks by referring to the numbers that are already filled. A number can only occur once in each row of 9, each column of 9, and each 3×3 square.

I regularly complete difficult sudoku puzzles, but this easy one—more starter numbers makes the puzzle easier—was taking much longer than I expected.

I soon realised that my slow performance was due to a design decision by the graphic artist!

In the original puzzle, shown at left, the graphic designer used  shading  for all the starter numbers. In my reformatted version, on the right, I used shading to separate the 3×3 squares. Both puzzles also use thicker lines to separate the 3×3 squares.

The shading for starter numbers, on the left, is unfortunate because it interferes with the player’s perception of the nine 3×3 squares. Instead, players perceive groups of numbers (in diagonals, in sets of two, and sets of five).

I assume the designer’s intention was to help identify the starter numbers. Regardless of the designer’s intention, the human brain processes the shading just as it processes all visual information: according to rules that cognitive psychologists call gestalt principles. A sudoku player’s brain—any human brain—will first perceive the shaded boxes as groups or sets.

In sudoku, the grouping on the left is actually meaningless—and counterproductive. However, since the brain applies gestalt principles rather involuntarily and at a low level, the grouping cannot easily be ignored. The player must make a deliberate cognitive effort to ignore the disruptive visual signal of the original shading. This extra effort slows the player’s time-on-task performance.

You can check your own perception by comparing how readily you see diagonals and groups in both puzzles above. On the left, are you more likely to see two diagonals, two groups of five, and many groups of two? If you are a sudoku player, you’ll recognise that these groupings in the puzzle are irrelevant to the game.

If you like, you can print the puzzles at the top, and give them to different sudoku players. Which puzzle is faster to complete?

Interested in gestalt principles? I’ve blogged about the use of gestalt principles before.

One thing I’ve noticed is that about ¼ of seatback touch screens are poorly registered. By registration I mean that the system and the user agree on where the user is tapping or touching the screen:

I recorded a video of two common tasks for a seatback entertainment system: selecting the language and adjusting the volume. As you can see, the registration is off, so I initially get the French interface instead of the English, and I must press an unrelated button to adjust the sound:

Get the latest Flash Player to see this player.

The registration error is significant. My fingertip tapped about 2 cm left of the centre of the EN button. The larger the registration error, the harder to tap a small target—as was the case with the volume controls in the video, above, where I appear to be tapping the Fast-Forward button. On more than one flight I have unintentionally increased the sound to painful levels while attempting to lower the volume!

A system such as this could be made to detect and auto-correct poor registration. If we assume that repeat taps on a blank location indicates poor registration, the software could:

1. After several repeat taps, select the nearest target—a reasonable guess—even if it is a centimetre or two away from the user’s tap.
2. Ask the user to confirm the guess. “Did you mean [this one]?”
3. If the user confirms, calculate the amount by which to correct the registration, and then fix the registration error.

This solution requires a screen—perhaps the start screen—whose choices are spaced far apart, so the system can detect when the user appears to be tapping a blank space:

If user testing were to show that auto-correction needs human involvement, after calculating the registration error, the system could ask the user to check the corrected registration. For example:

Are you there? Please tap the green circle.

I haven’t done any testing of this idea, nor have I given this much thought, so I’m certain there are many more and better ways to auto-correct a registration problem on a touch screen. I merely wanted to identify one possible solution in order to get to the next point: the need to consider the business drivers when deciding to address (or deciding not to address) a usability problem.

Everything costs money

Fixing this problem—it’s a real problem, you’ve seen the video—would cost money. If the following can be quantified and evaluated within a framework of passenger-experience goals, there may be a convincing business case:

• Not every passenger can work around a registration problem. Those who cannot would be unable to use the entertainment system. When everyone else gets a movie, how does the passenger with a failing system feel?
• If a failed entertainment system is perceived as a negative experience, will passengers blame the touch-screen/software manufacturer or blame the airline? I’m sure you can imagine the complaint: “I sat there for hours without a movie! It’s the airline’s fault.” What’s the likelihood that this will cause churn (passenger switches to another brand next time)?
• Based on the screens I’ve seen, some frustrated passengers must use hard objects that scratch and even gouge the touch screen. Are they trying to force the screen to understand what they want? Are they vandalising the screen? What’s the cost of replacing a damaged or vandalised screen?
• A scratched screen is like graffiti. It affects every subsequent passenger in that seat. Do vandalised screens affect the airline’s goal of attaining a particular passenger rating for perceived quality or aesthetic experience?
• The in-flight entertainment system was implicated in a catastrophic Swiss Air crash near Peggy’s Cove about a decade ago. Would a fix to the touch-screen registration problem incur prohibitive safety-testing costs?

My first exposure to agile was in Desiree Sy’s 2005 presentation, Strategy and Tactics for Agile Design: A design case study, to the Usability Professionals Association (UPA) annual conference in Montreal, Canada. It was a popular presentation then, and UPA-conference attendees continue to be interested in agile methods now. This year, at the UPA conference in Portland, USA, a roomful of usability analysts and user-experience practitioners discussed the challenges that agile methods present to their practice. One of the panellists told the room: “Agile is a response to the classic development problem: delivering the wrong product, too late.” There was lots of uncomfortable laugher at this. Then came the second, thought-provoking sentence: “Agile shines a light on the rest of us, since we are now on the critical path.” Wow! So it’s no longer developers, but designers, usability analysts, etc, who are holding up the schedule?

During this week’s training, I’m learning lots while looking for one thing in particular: how to ensure agile methods accommodate non-developer activities, from market-facing product management activities, to generative product design, to early prototype testing, to usability testing, and so on.

I’m starting to suspect that when agile methods “don’t work” for non-developers, it’s because the process is wagging the dog (or that its “rules” are being applied dogmatically). I think I’m hearing that agile isn’t a set of fixed rules—so not a religion—but a sensible and flexible method that team members can adapt to their specific project and product.

The person I was observing was visually impaired and had his GUI enlarged by about 1000% or more. As he attempted to troubleshoot his wireless connection, he was very rapidly scrolling horizontally and vertically in order to read the text and view the icons in the Wireless Connection Status dialog box. The hugely enlarged GUI flew around the screen. His screen displayed only a small portion of the total GUI, but he never lost his place.

In contrast, I lost my place repeatedly. I couldn’t relate the different pieces of information, so what I saw was effectively meaningless to me much of the time. His spatial awareness—his ability to navigate quickly around a relatively large area—was clearly more developed than mine.

I could not keep up with all of the text, either, even when he was reading it to me out loud: ”It says ‘Signal Strength” is 4 bars, but it won’t connect. See?” (Well, actually, I didn’t see.) Though I’m very familiar with this dialog box, I could only read the shorter words as they flew by on screen. The larger words were illegible to me. His ability to read rapidly-moving whole words when only parts of them were visible at any given instant was much more developed than mine. I felt sheepish about being functionally illiterate under these conditions.

It was interesting to see how my own user performance depends on such a narrow range of conditions. I need to see the whole word and its context. I need to see at least half the dialog box at once. And, if the image is moving, it must be moving slowly.

The water only flows while you press the lever—one lever for cold water and one lever for warm water. It takes one hand continuously pressing to make the water flow. Rinsing one hand without the help of the other hand is difficult. Rinsing soap off is much easier when two hands do it together.

Some of the newer Boeing aircraft—like the 787 Dreamliner—may have better taps, but I’ve never been on one. An aircraft lasts decades, so passengers will be using those old sinks and taps for years to come, on Boeing planes. Airbus planes, on the other hand, have had ergonomic taps for years: one press starts the water flow, leaving both hands free for soaping and rinsing. After a fixed duration, the water stops flowing, but you can always press again to restart the water.

While I’m pointing out usability problems in the airline industry, Airbus doesn’t have clean hands. On the Airbus web site,  type a word in the Search box—the word bathroom, for example—and then press ENTER. Nothing happens. The ENTER key doesn’t start the search, but a mouse click does.

It’s ironic. A design that requires me to move a hand from the keyboard to the mouse is a lot like design that requires me to move a hand from the sink basin to the lever.

Here’s a photo of impromptu research, conducted by Betsy Weber, TechSmith’s product evangelist. I was her research subject. Betsy recorded me pushing sugar packets around a table as I explained how I’d like Camtasia to behave.

Betsy takes information like this from the field back to the Camtasia team. There’s no guarantee that my idea will influence future product development, but what this photo shows is that TechSmith listens to its users and customers.

The ongoing stream of research and information that Betsy provides ensures better design of products that will be relevant and satisfying for TechSmith customers down the line.

• Is this a meaningful win? The leader only barely beat the next three designs, and 82% voted for other designs.

I don’t know about the 18% versus 82%. I do wonder whether some of the entries triggered a cognitive process in voters that caused them to pay less attention to the other designs, which may bring the leading design’s razor-thin lead into question. This cognitive process—known as the “ugly option”—is used successfully by designers as they deliberately apply cognitive psychology to entice users to act. I’ll explain why, below, but I first want to explain my motivation for this blog post.

I’m using this WordPress poll as a jumping-off point to discuss the difficulty of survey design. I’m not commenting on the merit of the designs. (I never saw the designs up close.) And I’m certainly not claiming that people involved in the poll used cognitive psych to affect the poll’s outcome. Instead, in this blog, I’m discussing what I know about cognitive psychology as it applies to the design of surveys such as this recent WordPress.org poll.

Survey design affects user responses

If you’ve heard of the controversial Florida butterfly ballot in the USA’s presidential election in 2000, then you know ballot design—survey design—can affect the outcome. I live outside the USA, but as a certified usability analyst I regularly come across this topic in industry publications; since that infamous election, usability analysts in the USA have been promoting more research and usability testing to ensure good ballot design. I imagine that the Florida butterfly ballot would have tested poorly in a formative usability study.

The recent WordPress poll, however, would likely have tested well in a usability study to determine whether WordPress users could successfully vote for their choice. The question I have is whether the entries themselves caused a cognitive bias in favour of some entries at the expense of others.

It seems that one entry was entered multiple times, as dark, medium, and light variations. This seems like a good idea: “Let’s ask voters which one is better.” Interestingly, the visual repetition—the similar images—may have an unintended effect if you add other designs into the mix. Cognitive science tells us people are more likely to select one of the similar ones. Consider this illustration:

More people choose the leftmost image. The brain’s tendency to look for patterns keeps it more interested in the two similar images. The brain’s tendency to avoid the “ugly option” means it’ll prefer the more beautiful one of the two. Research shows that symmetry correlates with beauty across cultures, so I manipulated the centre image in Photoshop to make it asymmetrical, or “uglier”.

The ugly-option rule applies to a choice between different bundles of goods (like magazine subscriptions with different perks), different prices (like the bottles on a restaurant wine list), and different appearances (like the photos, above). It may have applied to the design images in the WordPress poll. The poll results published by WordPress.org lists the intentional variations in the table of results:

• DR1: Fluency style, dark
• DR2: Fluency style, medium
• DR3: Fluency style, light

In addition to these three, which placed 1st, 4th, and 6th overall, it’s possible there were other sets of variations, because other entries may have resembled each other, too.

As a usability analyst and user researcher, I find this fascinating. Does the ugly-option rule hold true when there are 11 options? Was the dark-medium-light variation sufficient to qualify one of the three as ugly? Did the leading design win because it was part of a set that included an ugly option? And, among the 11 entries, how many sets were there?

There are ways to test this.

Test whether the poll results differ in teh absence of an ugly-option set. A|B testing is useful for this. It involves giving half the users poll A with only one of the dark-medium-light variants, and the other half poll B with all three variants included. You can then can compare the two result sets. If there is a significant difference, then some further combinations can be tested to see if other possible explanations can be ruled out.

For more about the ugly option and other ways to make your designs persuasive, I recommend watching Kath Straub and Spencer Gerrol in the HFI webcast, The Science of Persuasive Design: Convincing is converting, with video and slides. There’s also an audio-only podcast and an accompanying white paper.

There are different ways to display the results. You can see the data as a “video” that shows a sequence of dots, everywhere you looked. Larger dots are longer fixations. You can also see the data as a cumulative heat map, similar to this:

Here’s something interesting I learned about myself. When I participate in an eye-tracking study that studies a photograph—such as a full-page magazine ad—I look at all the same places for about the same duration as other participants in the study. I know this because the composite heat map, which combines the eye-tracking data of all the participants into one heat map, looks indistinguishable from my individual heat map. It turns out I’m normal, after all.

Eye tracking has helped researchers answer questions such as these:

• How to people typically scan a web page (in the F pattern), and what are the implications for layout?
• How much attention do people give to ads that look like dialog boxes, or to text that has fancy formatting (so may be perceived to be an ad), and what are the implications for advertisers and ad revenue?

If you’re interested in eye tracking and usability and want to read more, try Eye Tracking as Silver Bullet for Usability Evaluations?  by Markus Weber.

After Œ informing and defining the problem  without judgement  and  generating and sketching lots of ideas  without judgment , it’s often a relief for the team to start Ž  analysing and judging  the potential solutions by taking into account the project’s business goals, development goals, and usability goals).

But what are the usability goals? How can a team quickly assess whether potential designs meet those usability goals? One easy answer is to provide the team with an project-appropriate checklist.

Make your own checklist. You can make your own or find one on the Internet. To make your own, start with a textbook that you’ve found helpful and inspiring. For me, that’s About Face by Alan Cooper. To this, I add things that my experience tells me will help the team—my “favourites” or my pet peeves. In this last category I might consult the Ribbon section of the Vista UX Guide, the User Interface section of the  iPhone human-interface guidelines, and so on.

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“Usability goals are business goals. Web sites that are hard to use frustrate customers, forfeit revenue, and erode brands.

Executives can apply a disciplined approach to improve all aspects of ease-of-use. Start with usability reviews to assess specific flaws and understand their causes. Then fix the right problems through action-driven design practices. Finally, maintain usability with changes in business processes.”

—McCarthy & Souza, Forrester Research, September 1998