A interesting theory:
I think this “like English but not quite” aspect of AppleScript is the Uncanny Valley of programming languages. Because AppleScript looks like English it is easy to fall into the trap of believing it has the flexibility of English. When that mental model fails its more unsettling than when you screw up the syntax in a regular programming language because your mental model isn’t making unwarranted assumptions.
Mac OS X can run on systems with a screen size as small as 800 x 600 … Unless you know that your users will be using a specific display size, it is best to optimize your applications for display at 1024 x 768 pixels. … Design your user interface for a resolution of at least 800 x 600.
According to Apple’s Human Interface Guidelines (retrieved 2010-04-21).
…
Also, in every color combination surveyed, the darker text on a lighter background was rated more readable than its inverse (e.g. blue text on white background ranked higher then white text on blue background).
I wish Columbia Blue and Red were tested in the survey. They were my high school’s colors; and they were terrible. The worst permutation was blue text on a red background.
Question for all you who prefer light source-code on a dark background: why do you like it?
Bruce Schneier has a new essay, How to Sell Security. As usual, it’s well worth reading.
The most interesting tidbit, to me, is that people have a bias to choose a small certain gain over an uncertain but possibly larger gain. But with loss, it’s the opposite. People avoid certain losses; preferring to “play double or nothing” — risking a larger loss for the chance of not sustaining a loss.
Here’s an experiment that illustrates Prospect Theory. Take a roomful of subjects and divide them into two groups. Ask one group to choose between these two alternatives: a sure gain of $500 and 50 percent chance of gaining $1,000. Ask the other group to choose between these two alternatives: a sure loss of $500 and a 50 percent chance of losing $1,000.
These two trade-offs are very similar, and traditional economics predicts that the whether you’re contemplating a gain or a loss doesn’t make a difference: People make trade-offs based on a straightforward calculation of the relative outcome. Some people prefer sure things and others prefer to take chances. Whether the outcome is a gain or a loss doesn’t affect the mathematics and therefore shouldn’t affect the results. This is traditional economics, and it’s called Utility Theory.
But Kahneman’s and Tversky’s experiments contradicted Utility Theory. When faced with a gain, about 85 percent of people chose the sure smaller gain over the risky larger gain. But when faced with a loss, about 70 percent chose the risky larger loss over the sure smaller loss.
This experiment, repeated again and again by many researchers, across ages, genders, cultures and even species, rocked economics, yielded the same result. Directly contradicting the traditional idea of “economic man,” Prospect Theory recognizes that people have subjective values for gains and losses. We have evolved a cognitive bias: a pair of heuristics. One, a sure gain is better than a chance at a greater gain, or “A bird in the hand is worth two in the bush.” And two, a sure loss is worse than a chance at a greater loss, or “Run away and live to fight another day.” Of course, these are not rigid rules. Only a fool would take a sure $100 over a 50 percent chance at $1,000,000. But all things being equal, we tend to be risk-adverse when it comes to gains and risk-seeking when it comes to losses.
This cognitive bias is so powerful that it can lead to logically inconsistent results. Google the “Asian Disease Experiment” for an almost surreal example. Describing the same policy choice in different ways–either as “200 lives saved out of 600” or “400 lives lost out of 600”– yields wildly different risk reactions.
Evolutionarily, the bias makes sense. It’s a better survival strategy to accept small gains rather than risk them for larger ones, and to risk larger losses rather than accept smaller losses. Lions, for example, chase young or wounded wildebeests because the investment needed to kill them is lower. Mature and healthy prey would probably be more nutritious, but there’s a risk of missing lunch entirely if it gets away. And a small meal will tide the lion over until another day. Getting through today is more important than the possibility of having food tomorrow. Similarly, it is better to risk a larger loss than to accept a smaller loss. Because animals tend to live on the razor’s edge between starvation and reproduction, any loss of food — whether small or large — can be equally bad. Because both can result in death, and the best option is to risk everything for the chance at no loss at all.
intuition
noun
the ability to understand something immediately, without the need for conscious reasoning.
“Intuitive” sounds like a great property for an interface to have, but in The Humane Interface
Many interface requirements specify that the resulting product be intuitive, or natural. However, there is no human faculty of intuition…When an expert uses what we commonly call his intuition to make a judgment … we find that he has based his judgment on his experience and knowledge. Often, experts have learned to use methods and techniques that non-experts do not know… Expertise, unlike intuition, is real.
When users say that in interface is intuitive, they mean that it operates just like some other software or method with which they are familiar.…
Another word that I try to avoid in discussing interfaces is ‘natural’. Like ‘intuitive’, it is usually not defined. An interface feature is natural, in common parlance, if it operates in such a way that a human needs no instruction. This typically means that there is some common human activity that is similar to the way the feature works. However, it is difficult to pin down what is meant by ‘similar’. … the term ‘natural’ (can also equate) to ‘very easily learned’. Although it may be impossible to quantify naturalness, it is not to difficult to quantify learning time.
…
The belief that interfaces can be intuitive and natural is often detrimental to improved interface design. As a consultant, I am frequently asked to design a “better” interface to a product. Usually, an interface can be designed such that, in terms of learning time, eventual speed of operation (productivity), decreased error rates, and ease of implementation, it is superior to both the client’s existing products and competing products. Nonetheless, even when my proposals are seen as significant improvements, they are often rejected on the grounds that they are not intuitive. It is a classic Catch-22: The client wants something that is sigificantly superior to the competition. But if it is to be superior, it must be different. (Typically, the greater the improvement, the greater the difference.) Therefore, it cannot be intuitive, that is, familiar. What the client wants is an interface with at most marginal differences from current practice — which almost inevitably is Microsoft Windows — that, somehow, makes a major improvement.
There are situations where familiarity is the most important concern, but they are rare. One example is a kiosk at a tourist attraction. Millions of people will use it only once, and they must be able to use it as soon as they touch it (because they will walk away rather then spend their vacation reading a manual). And in such cases, mimicking the most promiscuously used interface you can find, warts and all, makes sense — if that means more people will already know how to use it.
Outside of rare exceptions, software that people use enough to justify buying is used repeatedly. The value of the product is what people make with it, not what they can do with it the moment they open the box. Designing for the illusion of “intuitiveness” is clearly the wrong choice when it harms the long-term usefulness of the product.
This is not an excuse for a crappy first-run experience! The first impression is still the most important impression. By definition, the less familiar something is, the more exceptional it is. And an exceptionally good first impression is what you are after — so unfamiliarity can work to your advantage here. It is more work to design an exceptional first-run experience, but good design is always more work.
This is not a rational for being different just to be different. It is a rational for being different, when different is measurably better. For something to be measurably better, it first needs to be measurable. That means using precise terms, like “familiar” instead of “intuitive”, and “quick to learn” not “natural”.
For personal reasons, I do not browse the web from my computer. (I also have not[sic] net connection much of the time.) To look at page[sic] I send mail to a demon which runs wget and mails the page back to me. It is very efficient use of my time[sic], but it is slow in real time.
—Richard Stallman, 15 Dec 2007
How in touch with regular people do you think that guy is? How well do you think a system he designed would server their needs? How well do you think it would serve your needs? (I mean I think it’s pretty fair to say you use the internet a bit more … shall we say … functionally.)
Apparently GNU/Linux can’t even meet a hardcore nerd’s needs.
Among other things, (this study) found that the Back button is now only the 3rd most-used feature on the Web. Clicking hypertext links remains the most-used feature, but clicking buttons (on the page) has now overtaken Back to become the second-most used feature. The reason for this change is the increased prevalence of applications and feature-rich Web pages that require users to click page buttons to access their functionality.
Here’s Jakob Nielsen’s economic justification for giving employees large screens,
Big monitors are the easiest way to increase white-collar productivity, and anyone who makes at least $50,000 per year ought to have at least 1600×1200 screen resolution. A flat-panel display with this resolution currently costs less than $500. So, as long as the bigger display increases productivity by at least 0.5%, you’ll recover the investment in less than a year. (The typical corporate overhead doubles the company’s per-employee cost; always remember to use loaded cost, not take-home salary, in any productivity calculation.)
Jeff Atwood has written a “one-stop-shop for research data supporting the idea that, yes, having more display space would in fact make you more productive”. But he warns us that “Having all that space can make you less productive due to all the window manipulation excise you have to deal with to make effective use of it.”He calls this the Large Display Paradox. But, there are solutions to this problem. Using software to divide the large single-display into a “grid” of virtual “monitors” is the one he proposes.
A recent and widely publicized University of Utah study concluded that people were less productive on a 26″ screen then an 18″ screen. (Unfortunately I haven’t found a better link to their actual data then this crappy PDF brochure.) However, they also found that people were more productive with two 20″ screens. Their 26″ monitor was 1920×1200 pixels = 2.3 MP, their 20″ was 1600×1200 pixels = 1.92MP, so two 20″ screens = 3.84 MP, quite a bit bigger then the 26″ screen, and with greater productivity. This supports the theory with the right windowing system, productivity increases as the number of usable pixels increases.
I’ve only found one exception to the “bigger is better” rule of workspaces. Portability (Availability) can be worth more then pure productivity. There’s an old gunslinger saying that “The best gun in the world is the the one I’ve got in my hand right now”. Similarly, having a “big iron” on your office isn’t much use if you are flying somewhere over the atlantic. There’s no substitute for having a computer in-hand. Even if you would be more productive using a 17″ laptop, it’s better to get a 13″ ultra-portable, if it means you are more likely to actually have it around when you need it.
Business travelers, and creative professionals who work better in eclectic settings, are examples of people who are better served by the smallest sufficiently-powerful laptop they can find. But for most people bigger is better. Fortunately, small laptops can be connected to large displays.
…Judy Olson and Erik Nilsen wrote a classic paper comparing two user interfaces for large data tables. One interface offered many more features for table manipulation and each feature decreased task-performance time in specific circumstances. The other design lacked these optimized features and was thus slower to operate under the specific conditions addressed by the first design’s special features.
So, which of these two designs was faster to use? The one with the fewest features. For each operation, the planning time was 2.9 seconds in the stripped-down design and 4.6 seconds in the feature-rich design. With more choices, it takes more time to make a decision on which one to use. The extra 1.7 seconds required to consider the richer feature set consumed more time than users saved by executing faster operations.
—Jakob Nielsen, the day before my birthday, 2006.
Just a curiosity, but it happens that in a yes-no binary response test, the reaction time to select “no” is longer than for “yes.”
I haven’t taken the time to verify this, or see if anyone has quantified the difference in response times.
UPDATE 2009-12-18: The technical term for this is Acquiescence Response Bias — the tendency to agree with any assertion, regardless of its content.
Powered by WordPress