User-Centered Design

Finding Out What They Think: A Rough Primer To User Research, Part 1

[In this first article in a new series, college professor and user research Ben Lewis-Evans takes a look at different methods of game user research, offering up a handy guide to different ways you can collect useful information about your game.]

This article, and its forthcoming followup, is intended to give a rough idea to developers of several different methods that can be used in games user research.

However, many, many books have been written on research methodology and I cannot cover everything. Therefore these two articles cannot be taken as completely comprehensive.

In the first of the articles I will be covering a few general points about Games User Research and then discussing three methods, focus groups, heuristic evaluation and questionnaires in some detail.

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Buttons Were An Inspired UI Hack, But Now We’ve Got Better Options

Josh Clark on the future of touch and other types of UI.

If you’ve ever seen a child interact with an iPad, you’ve seen the power of the touch interface in action. Is this a sign of what’s to come — will we be touching and swiping screens rather tapping buttons? I reached out to Josh Clark (@globalmoxie), founder of Global Moxie and author of “Tapworthy,” to get his thoughts on the future of touch and computer interaction, and whether or not buttons face extinction.

Clark says a touch-based UI is more intuitive to the way we think and act in the world. He also says touch is just the beginning — speech, facial expression, and physical gestures are on they way, and we need to start thinking about content in these contexts.

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Are Your Users S.T.U.P.I.D?

How good design can make users effective

dunce-200It is an honest question: how smart are your users? The answer may surprise you: it doesn’t matter. They can be geniuses or morons, but if you don’t engage their intelligence, you can’t depend on their brain power.

Far more important than their IQ (which is a questionable measure in any case) is their Effective Intelligence: the fraction of their intelligence they can (or are motivated to) apply to a task.

Take, for example, a good driver. They are a worse driver when texting or when drunk. (We don’t want to think about the drunk driver who is texting.) An extreme example you say? Perhaps, but only by degree. A person who wins a game of Scrabble one evening may be late for work because they forgot to set their alarm clock. How could the same person make such a dumb mistake? Call it concentration, or focus, we use more of our brain when engaged and need support when we are distracted.

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Next Generation Technology for Full Body Game Controllers

Patent approved for Motion Recognition Clothing(TM)

Medibotics’ U.S. patent 7,980,141 for Motion Recognition Clothing™ (MRC) has been approved. MRC is an innovative technology for translating body motion into computer-readable signals that could power the next generation of full-body game controllers. The market for translating body motion into computer-readable signals is already very large. For example, over 10 million units of an existing camera-based full-body game controller system have been sold. With further development, MRC could be used for a variety of applications including not only computer gaming, but also virtual reality in general, sports training, medical therapy, virtual exercise, weight management, and telerobotics.

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The Future of Gaming: A Portrait of the New Gamers

In the spring of 2011, Latitude Research launched a study to understand the recent explosion in gaming, driven in part by the popularity of mobile phones and tablets. Specifically, the study sought to uncover how the profile of the stereotypical gamer has changed, various motivations for gaming, and the evolving role of games in moving traditionally online experiences into the “offline” world—suggesting new opportunities for game and technology developers, educators, and social innovators.

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Utilize Available Screen Space

Summary: Websites and mobile apps both frequently cram options into too-small parts of the screen, making items harder to understand.

A computer screen’s precious pixels are the world’s most valuable real estate. Amazon’s Add to Cart button is 160×27 pixels, or 0.003 square feet (0.0003 m2) at a typical 100 dpi monitor resolution. You could crowd almost 800,000 Buy buttons onto the floor space of the average American home, which currently sells for $160,000. Even a single Buy button will often bring in more than that — let alone the revenue from 800,000 buttons.

Normally, when something is extremely valuable, you try to conserve it. But screen space shouldn’t be hoarded, it should be spent. I see too many designs that cram highly valuable content or action items into tiny spaces while wasting vast amounts of screen space.

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Kinect Gestural UI: First Impressions

Read the manual before using the interface. (Kinect Adventures)
(Yes, it’s a *cute* manual, but these are still instructions to memorize.)

Summary: Inconsistent gestures, invisible commands, overlooked warnings, awkward dialog confirmations. But fun to play.

Kinect is a new video game system that is fully controlled by bodily movements. It’s vaguely similar to the Wii, but doesn’t use a controller (and doesn’t have the associated risk of banging up your living room if you lose your grip on the Wii wand during an aggressive tennis swing).

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Why You Only Need to Test with 5 Users

Some people think that usability is very costly and complex and that user tests should be reserved for the rare web design project with a huge budget and a lavish time schedule. Not true. Elaborate usability tests are a waste of resources. The best results come from testing no more than 5 users and running as many small tests as you can afford.

In earlier research, Tom Landauer and I showed that the number of usability problems found in a usability test with n users is:

N(1-(1-L)n)

where N is the total number of usability problems in the design and L is the proportion of usability problems discovered while testing a single user. The typical value of L is 31%, averaged across a large number of projects we studied. Plotting the curve for L=31% gives the following result:

The most striking truth of the curve is that zero users give zero insights.

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Ford Ergonomics Lab: Optimized by Gaming Technology

When Glenn Harrington donned a motion capture suit complete with more than 40 reflective spheres he wasn’t being turned into the latest video game character, but helping to design car manufacturing jobs that are less physically stressful on workers.

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