This dialog box, which appeared in a program that prints custom award certificates, presents the task of selecting a template for the certificate. This interface is clearly graphical. It’s mouse-driven–no memorizing or typing complicated commands. It’s even what-you-see-is-what-you-get (WYSIWYG)–the user gets a preview of the award that will be created.

So why isn’t it usable?

The first clue that there might be a problem here is the long help message on the left side. Why so much help for a simple selection task? Because the interface is bizarre! The scrollbar is used to select an award template.

Each position on the scrollbar represents a template, and moving the scrollbar back and forth changes the template shown.

This is a cute but poor use of a scrollbar. Notice that the scrollbar doesn’t have any marks on it. How many templates are there? How are they sorted? How far do you have to move the scrollbar to select the next one? You can’t even guess from this interface.

Normally, a horizontal scrollbar underneath an image (or document, or some other content) is designed for scrolling the content horizontally. A new or infrequent user looking at the window sees the scrollbar, assumes it serves that function, and ignores it. Inconsistency with prior experience and other applications tends to trip up new or infrequent users.

Another way to put it is that the horizontal scrollbar is an affordance for continuous scrolling, not for discrete selection. We see affordances out in the real world, too; a door knob says “turn me”, a handle says “pull me”.

We’ve all seen those apparently-pullable door handles with a little sign that says “Push”; and many of us have had the embarrassing experience of trying to pull on the door before we notice the sign. The help text on this dialog box is filling the same role here.

But the dialog doesn’t get any better for frequent users, either. If a frequent user wants a template they’ve used before, how can they find it? Surely they’ll remember that it’s 56% of the way along the scrollbar? This interface provides no shortcuts for frequent users. In fact, this interface takes what should be a random access process and transforms it into a linear process. Every user has to look through all the choices, even if they already know which one they want. The computer scientist in you should cringe at that algorithm.

Even the help text has usability problems. “Press OKAY”? Where is that? And why does the message have a ragged left margin? You don’t see ragged left too often in newspapers and magazine layout, and there’s a good reason.

On the plus side, the designer of this dialog box at least recognized that there was a problem–hence the help message. But the help message is indicative of a flawed approach to usability.

Usability can’t be left until the end of software development, like package artwork or an installer. It can’t be patched here and there with extra messages or more documentation. It must be part of the process, so that usability bugs can be fixed, instead of merely patched.

How could this dialog box be redesigned to solve some of these problems?

Here’s one way it might be redesigned. The templates now fill a list box on the left; selecting a template shows its preview on the right. This interface suffers from none of the problems of its predecessor: list boxes clearly afford selection to new or infrequent users; random access is trivial for frequent users. And no help message is needed.

The fact that users are learning our interfaces by actually using them has some implications for how we should design them.

First, we should know something about what the users’ goals actually are – collecting information about that is a critical feature of the user-centered design process that we’ll talk about in a few lectures. If we’re designing for the wrong goals, users are going to struggle to figure out how to do what they want in our system.

Second, the UI should be the primary teacher of how to use it. The UI itself must communicate as clearly as possible how it’s supposed to be used, so that users can match their goals with appropriate actions in the system. Later, we’ll talk about a few specific techniques for doing this–affordances, feedback, and information scent.

Third, when the user does have to resort to help, that help should be searchable and goal-directed. Providing a 30-minute video tutorial probably won’t help people who learn by doing.

Users depend on visible cues to figure out how to achieve their goals with the least effort. For information gathering tasks, like searching for information on the web, it turns out that this behavior can be modeled much like animals foraging for food. An animal feeding in a natural environment asks questions like: Where should I feed? What should I try to eat (the big rabbit that’s hard to catch, or the little rabbit that’s less filling)? Has this location been exhausted of food that’s easy to obtain, and should I try to move on to a more profitable location? Information foraging theory claims that we ask similar questions when we’re collecting information: Where should I search? Which articles or paragraphs are worth reading? Have I exhausted this source, should I move on to the next search result or a different search? (Pirolli & Card, “Information Foraging in Information Access Environments,” CHI ‘95.)

An important part of information foraging is the decision about whether a hyperlink is worth following – i.e., does this smell good enough to eat? Users make this decision with relatively little information – sometimes only the words in the hyperlink itself, sometimes with some context around it (e.g., a Google search result also includes a snippet of text from the page, the site’s domain name, the length of the page, etc.) These cues are information scent – the visible properties of a link that indicate how profitable it will be to follow the link. (Chi et al, “Using Information Scent to Model User Information Needs and Actions on the Web”, CHI 2001.)

For the user, collecting information scent cues is done progressively, with steadily increasing cost.

Some properties can be observed very quickly, with a glance over the interface: detecting affordances (like buttons or hyperlinks, if they’re well designed), recognizing icons (like a magnifying glass), or short and very visible words (like Search in big bold text).

With more effort, the user can read: long labels, help text, or search result snippets. Reading is clearly more expensive than glancing, because it requires focusing and thinking.

Still more time and effort is required to hover the mouse or press down, because your hands have to move, not just your eyes. We inspect menubars and tooltips this way. Note that tooltips are even more costly, because you often have to wait a time for the tooltip to appear.

Clicking through a link or bringing up a dialog box is next, and actually invoking a command to see its effect is the costliest way to explore.

Exploration is important to learning. But much of this reading has been about techniques for reducing the costs of exploration, and making the right feature more obvious right away. An interface with very poor affordances will be very expensive to explore. Imagine a webpage whose links aren’t distinguished by underlining or color – you’ve just taken away the Glance, and forced the user to Read or Hover to discover what’s likely to be clickable. Now imagine it in a foreign language – you’ve just taken away Read. Now get rid of the mouse cursor feedback – no more Hover, and the user is forced to Click all over the place to explore. Your job as a designer is to make the user’s goal as easy to recognize in your user interface as possible.

Hyperlinks in your interface – or in general, any kind of feature, including menu commands and toolbar buttons – should provide good, appropriate information scent.

Examples of bad scent include misleading terms, incomprehensible jargon (like “Set Program Access and Defaults” on the Windows XP Start menu), too-general labels (“Tools”), and overlapping categories (“Customize” and “Options” found in old versions of Microsoft Word).

Examples of good scent can be seen in the (XP-style) Windows Control Panel on the left, which was carefully designed. Look, for example, at “Printers and Other Hardware.” Why do you think printers were singled out?

Presumably because task analysis (and collected data) indicated that printer configuration was a very common reason for visiting the Control Panel. Including it in the label improves the scent of that link for users looking for printers. (Look also at the icon – what does that add to the scent of Printers & Other Hardware?)

Date, Time, Language, and Regional Options is another example. It might be tempting to find a single word to describe this category – say, Localization – but its scent for a user trying to reset the time would be much worse.

Here’s an example of going overboard with information scent. There is so much text in the main links of this page (Search listings…, Advertise…, See…, Browse…) that it interferes with your ability to Glance over the page. A better approach would be to make the links themselves short and simple, and use the smaller text below each link to provide supporting scent.

IBM’s RealCD is CD player software, which allows you to play an audio CD in your CD-ROM drive.

Why is it called “Real”? Because its designers based it on a real-world object: a plastic CD case. This interface has a metaphor, an analog in the real world.

Metaphors are one way to make an interface more learnable, since users can make guesses about how it will work based on what they already know about the interface’s metaphor.

Unfortunately, the designers’ careful adherence to this metaphor produced some remarkable effects, none of them good.

Here’s how RealCD looks when it first starts up. Notice that the UI is dominated by artwork, just like the outside of a CD case is dominated by the cover art. That big RealCD logo is just that–static artwork. Clicking on it does nothing.

There’s an obvious problem with the choice of metaphor, of course: a CD case doesn’t actually play CDs. The designers had to find a place for the player controls–which, remember, serve the primary task of the interface–so they arrayed them vertically along the case hinge. The metaphor is dictating control layout, against all other considerations.

Slavish adherence to the metaphor also drove the designers to disregard all consistency with other desktop applications. Where is this window’s close box? How do I shut it down? You might be able to guess, but is it obvious? Learnability comes from more than just metaphor.

But it gets worse. It turns out, like a CD case, this interface can also be opened. Oddly, the designers failed to sensibly implement their metaphor here. Clicking on the cover art would be a perfectly sensible way to open the case, and not hard to discover once you get frustrated and start clicking everywhere. Instead, it turns out the only way to open the case is by a toggle button control (the button with two little gray squares on it). Opening the case reveals some important controls, including the list of tracks on the CD, a volume control, and buttons for random or looping play. Evidently the metaphor dictated that the track list belongs on the “back” of the case. But why is the cover art more important than these controls? A task analysis would clearly show that adjusting the volume or picking a particular track matters more than viewing the cover art.

And again, the designers ignore consistency with other desktop applications. It turns out that not all the tracks on the CD are visible in the list. Could you tell right away? Where is its scrollbar?

We’re not done yet. Where is the online help for this interface?

First, the CD case must be open. You had to figure out how to do that yourself, without help. With the case open, if you move the mouse over the lower right corner of the cover art, around the IBM logo, you’ll see some feedback. The corner of the page will seem to peel back. Clicking on that corner will open the Help Browser.

The aspect of the metaphor in play here is the liner notes included in a CD case. Removing the liner notes booklet from a physical CD case is indeed a fiddly operation, and alas, the designers of RealCD have managed to replicate that part of the experience pretty accurately. But in a physical CD case, the liner notes usually contain lyrics or credits or goofy pictures of the band, which aren’t at all important to the primary task of playing the music. RealCD puts the help in this invisible, nearly unreachable, and probably undiscoverable booklet.

This example has several lessons: first, that interface metaphors can be horribly misused; and second, that the presence of a metaphor does not at all guarantee an “intuitive”, or easy-to-learn, user interface. (There’s a third lesson too, unrelated to metaphor–that beautiful graphic design doesn’t equal usability, and that graphic designers can be just as blind to usability problems as programmers can.)

Fortunately, metaphor is not the only way to achieve learnability. In fact, it’s probably the hardest way, fraught with the most pitfalls for the designer. In this lecture, we’ll look at some other ways to achieve learnability.

It’s important to make a distinction between recognition (remembering with the help of a visible cue, also known as knowledge in the world) and recall (remembering something with no help from the outside world–purely knowledge in the head). Recognition is far, far easier than uncued recall.

Psychology experiments have shown that the human memory system is almost unbelievably good at recognition. In one study, people looked at 540 words for a brief time each, then took a test in which they had to determine which of a pair of words they had seen on that 540-word list. The result? 88% accuracy on average! Similarly, in a study with 612 short sentences, people achieved 89% correct recognition on average.

Note that since these recognition studies involve so many items, they are clearly going beyond working memory, despite the absence of elaborative rehearsal. Other studies have demonstrated that by extending the interval between the viewing and the testing. In one study, people looked briefly at 2,560 pictures, and then were tested a year later–and they were still 63% accurate in judging which of two pictures they had seen before, significantly better than chance. One more: people were asked to study an artificial language for 15 min, then tested on it two years later–and their performance in the test was better than chance.

A menu/form interface presents a series of menus or forms to the user. Traditional (Web 1.0) web sites behave this way. Most graphical user interfaces have some kind of menu/forms interaction, such as a menubar (which is essentially a tree of menus) and dialog boxes (which are essentially forms).

Next we have direct manipulation: the preeminent interface style for graphical user interfaces. Direct manipulation is defined by three principles [Shneiderman, Designing the User Interface, 2004]

1. A continuous visual representation of the system’s data objects. Examples of this visual representation include: icons representing files and folders on your desktop; graphical objects in a drawing editor; text in a word processor; email messages in your inbox. The representation may be verbal (words) or iconic (pictures), but it’s continuously displayed, not displayed on demand. Contrast that with the behavior of ed, a command language- style text editor: ed only displayed the text file you were editing when you gave it an explicit command to do so.
2. The user interacts with the visual representation using physical actions or labeled button presses. Physical actions might include clicking on an object to select it, dragging it to move it, or dragging a selection handle to resize it. Physical actions are the most direct kind of actions in direct manipulation–you’re interacting with the virtual objects in a way that feels like you’re pushing them around directly. But not every interface function can be easily mapped to a physical action (e.g., converting text to boldface), so we also allow for “command” actions triggered by pressing a button–but the button should be visually rendered in the interface, so that pressing it is analogous to pressing a physical button.
3. The effects of actions should be rapid (visible as quickly as possible), incremental (you can drag the scrollbar thumb a little or a lot, and you see each incremental change), reversible* (you can undo your operation–with physical actions this is usually as easy as moving your hand back to the original place, but with labeled buttons you typically need an Undo command), and immediately visible (the user doesn’t have to do anything to see the effects; by contrast, a command like “cp a.txt b.txt” has no immediately visible effect).

Why is direct manipulation so powerful? It exploits perceptual and motor skills of the human machine–and depends less on linguistic skills than command or menu/form interfaces. So it’s more “natural” in a sense, because we learned how to manipulate the physical world long before we learned how to talk, read, and write.

Let’s look at Twitter’s interface–specifically, let’s focus on the interface for creating a new tweet. What aspects of this interface are knowledge-in-the-world, and what aspects require knowledge in the head? In what way is Twitter a hybrid of a command language and a menu/form interface?

Twitter is actually an unusual kind of command interface in that examples of “commands” (formatted tweets generated by other users) are constantly flowing at the user. So the user can do a lot of learning by watching on Twitter. On the other hand, learning by doing is somewhat more embarrassing, because your followers can all see your mistakes (the incorrect tweets you send out while you’re still figuring out how to use it).

Self-disclosure is a technique for making a command language more visible, helping the user learn the available commands and syntax. Self-disclosure is useful for interfaces that have both a traditional GUI (with menus and forms and possibly direct manipulation) as well as a command language (for scripting). When the user issues a command in the GUI part, the interface also displays the command in the command language that corresponds to what they did. A primitive form of self-disclosure is the address bar in a web browser–when you click on a hyperlink, the system displays to you the URL that you could have typed in order to visit the page. A more sophisticated kind of self-disclosure happens in Excel: when you choose the sum function from the toolbar, and drag out a range of cells to be summed, Excel shows you how you could have typed the formula instead. (Notice that Excel also uses a tooltip, to make the syntax of the formula more visible.)

On the bottom is another example of self-disclosure: Google’s Advanced Search form, which allows the user to specify search options by selecting them from menus, the results of which are also displayed as a commandbased query (“microsoft windows” “operating system” OR OS -glass -washing site:microsoft.com) which can be entered on the main search page. (example suggested by Geza Kovacs)

Regardless of interaction style, learning a new system requires the user to build a mental model of how the system works. Learnability can be strongly affected by difficulties in building that model.

A model of a system is a way of describing how the system works. A model specifies what the parts of the system are, and how those parts interact to make the system do what it’s supposed to do.

For example, at a high level, the model of Twitter is that there are other users in the system, you have a list of people that you follow and a list of people that follow you, and each user generates a stream of tweets that are seen by their followers, mixed together into a feed. These are all the parts of the system. At a more detailed level, tweets and people have attributes and data, and there are actions that you can do in the system (viewing tweets, creating tweets, following or unfollowing, etc.). These data items and actions are also parts of the model.

There are actually several models you have to worry about in UI design:

• The system model (sometimes called implementation model) is how the system actually works.
• The interface model (or manifest model) is the model that the system presents to the user through its user interface.
• The user model (or conceptual model) is how the user thinks the system works.

A cell phone presents the same simple interface model as a conventional wired phone, even though its system model is quite a bit more complex. A cell phone conversation may be handed off from one cell tower to another as the user moves around. This detail of the system model is hidden from the user.

As a software engineer, you should be quite familiar with this notion. A module interface offers a certain model of operation to clients of the module, but its implementation may be significantly different.

In software engineering, this divergence between interface and implementation is valued as a way to manage complexity and plan for change. In user interface design, we value it primarily for other reasons: the interface model should be simpler and more closely reflect the user’s model of the actual task.

Note that we’re using model in a more general and abstract sense here than when we talk about the model-view-controller pattern (which you may have heard of previously, and which we’ll discuss more in a future lecture). In MVC, the model is a software component (like a class or group of classes) that stores application data and implements the application behavior behind an interface. Here, a model is an abstracted description of how a system works. The system model on this slide might describe the way an MVC model class behaves (for example, storing text as a list of lines). The interface model might describe the way an MVC view class presents that system model (e.g., allowing end-of-lines to be “deleted” just as if they were characters). Finally, the user model isn’t software at all; it’s all in the user’s mind.

Here’s an example drawn directly from graphical user interfaces: the Back button in a web browser. What is the model for the behavior of Back? Specifically: how does the user think it behaves (the mental model), and how does it actually behave (the system model)?

The system model is that Back goes back to the last page the user was viewing, in a temporal history sequence.

But on a web site that has pages in some kind of linear sequence of their own–such as the result pages of a search engine (shown here) or multiple pages of a news article–then the user’s mental model might easily confuse these two sequences, thinking that Back will go to the previous page in the web site’s sequence. In other words, that Back is the same as Previous! (The fact that the “back” and “previous” are close synonyms, and that the arrow icons are almost identical, strongly encourages this belief.)

Most of the time, this erroneous mental model of Back will behave just the same as the true system model. But it will deviate if the user mixes the Previous link with the Back button–after pressing Previous, the Back button will behave like Next!

A nice article with other examples of tricky mental model/system model mismatch problems is “Mental and conceptual models, and the problem of contingency” by Charles Hannon, interactions, November 2008.

Consider image editing software. Programs like Photoshop and Gimp use a pixel editing model, in which an image is represented by an array of pixels (plus a stack of layers). Programs like PowerPoint and Illustrator, on the other hand, use a structured graphics model, in which an image is represented by a collection of graphical objects, like lines, rectangles, circles, and text. In this case, the choice of model strongly constrains the kinds of operations available to a user. You can easily tweak individual pixels in Microsoft Paint, but you can’t easily move an object once you’ve drawn it into the picture.

Similarly, most modern text editors model a text file as a single string, in which line endings are just like other characters. But it doesn’t have to be this way. Some editors represent a text file as a list of lines instead.

When this implementation model is exposed in the user interface, as in old Unix text editors like ed, line endings can’t be deleted in the same way as other characters. ed has a special join command for deleting line endings.

The user’s model may be totally wrong without affecting the user’s ability to use the system. A popular misconception about electricity holds that plugging in a power cable is like plugging in a water hose, with electrons traveling from the power company through the cable into the appliance. The actual system model of household AC current is of course completely different: the current changes direction many times a second, and the actual electrons don’t move far, and there’s really a circuit in that cable, not just a one-way tube. But the user model is simple, and the interface model supports it: plug in this tube, and power flows to the appliance.

But a wrong user model can also lead to problems. Consider a household thermostat, which controls the temperature of a room. If the room is too cold, what’s the fastest way to bring it up to the desired temperature?

Some people would say the room will heat faster if the thermostat is turned all the way up to maximum temperature. This response is triggered by an incorrect mental model about how a thermostat works: either the timer model, in which the thermostat controls the duty cycle of the furnace, i.e. what fraction of time the furnace is running and what fraction it is off; or the valve model, in which the thermostat affects the amount of heat coming from the furnace. In fact, a thermostat is just an on-off switch at the set temperature. When the room is colder than the set temperature, the furnace runs full blast until the room warms up. A higher thermostat setting will not make the room warm up any faster. (Norman, Design of Everyday Things, 1988)

These incorrect models shouldn’t simply be dismissed as “ignorant users.” (Remember, the user is always right! If there’s a consistent problem in the interface, it’s probably the interface’s fault.) These user models for heating are perfectly correct for other systems: a car heater and a stove burner both use the valve model. And users have no problem understanding the model of a dimmer switch, which performs the analogous function for light that a thermostat does for heat. When a room needs to be brighter, the user model says to set the dimmer switch right at the desired brightness.

The problem here is that the thermostat isn’t effectively communicating its model to the user. In particular, there isn’t enough feedback about what the furnace is doing for the user to form the right model.

There’s a general principle of learnability: consistency. This rule is often given the hifalutin’ name the Principle of Least Surprise, which basically means that you shouldn’t surprise the user with the way a command or interface object works.

Similar things should look, and act, in similar ways. Conversely, different things should be visibly different.

There are three kinds of consistency you need to worry about:

1. Internal consistency within your application
2. External consistency with other applications on the same platform
3. Metaphorical consistency with your interface metaphor or similar real-world objects

The RealCD interface discussed before has problems with both metaphorical consistency (CD jewel cases don’t play; you don’t open them by pressing a button on the spine; and they don’t open as shown), and with external consistency (the player controls aren’t arranged horizontally as they’re usually seen; and the track list doesn’t use the same scrollbar that other applications do).

Metaphors are one way you can bring the real world into your interface. RealCD is an example of an interface that uses a strong metaphor in its interface.

A well-chosen, well-executed metaphor can be quite effective and appealing, but be aware that metaphors can also mislead.

The advantage of metaphor is that you’re borrowing a conceptual model that the user already has experience with. A metaphor can convey a lot of knowledge about the interface model all at once. It’s a notebook. It’s a CD case. It’s a desktop. It’s a trashcan.

Each of these metaphors carries along with it a lot of knowledge about the parts, their purposes, and their interactions, which the user can draw on to make guesses about how the interface will work.

Some interface metaphors are famous and largely successful. The desktop metaphor – documents, folders, and overlapping paperlike windows on a desk-like surface – is widely used and copied. The trashcan, a place for discarding things but also for digging around and bringing them back, is another effective metaphor – so much so that Apple defended its trashcan with a lawsuit, and imitators are forced to use a different look. (Recycle Bin, anyone?)

But a computer interface must deviate from the metaphor at some point – otherwise, why aren’t you just using the physical object instead? At those deviation points, the metaphor may do more harm than good. For example, it’s easy to say “a word processor is like a typewriter,” but you shouldn’t really use it like a old-fashioned manual typewriter. Pressing Enter every time the cursor gets close to the right margin, as a typewriter demands, would wreak havoc with the word processor’s automatic word-wrapping.

The basic rule for metaphors is: use it if you have one, but don’t stretch for one if you don’t.

Appropriate metaphors can be very hard to find, particularly with real-world objects. The designers of RealCD stretched hard to use their CD-case metaphor (since in the real world, CD cases don’t even play CDs), and it didn’t work well.

Metaphors can also be deceptive, leading users to infer behavior that your interface doesn’t provide. Sure, it looks like a book, but can I write in the margin? Can I rip out a page?

Metaphors can also be constraining. Strict adherence to the desktop metaphor wouldn’t scale, because documents would always be full-size like they are in the real world, and folders wouldn’t be able to have arbitrarily deep nesting.

The biggest problem with metaphorical design is that your interface is presumably more capable than the real-world object, so at some point you have to break the metaphor. Nobody would use a word processor if really behaved like a typewriter. Features like automatic word-wrapping break the typewriter metaphor, by creating a distinction between hard carriage returns and soft returns.

Most of all, using a metaphor doesn’t save an interface that does a bad job communicating itself to the user. Although RealCD’s model was metaphorical – it opened like a CD case, and it had a liner notes booklet inside the cover – these features had such poor visibility and perceived affordances that they were ineffective.

Another important principle of learnability is good mapping of functions to controls.

Consider the spatial arrangement of a light switch panel. How does each switch correspond to the light it controls? If the switches are arranged in the same fashion as the lights themselves, it is much easier to learn which switch controls which light.

A direct mapping means that the physical layout of the controls matches the physical arrangement of their functions. In a direct mapping, control A is to the left of control B if and only if function A (e.g. the light that’s turned on or off) is to the left of function B.

Direct mappings are not always easy to achieve, since a control may be oriented differently from the function it controls. Light switches are mounted vertically, on a wall; the lights themselves are mounted horizontally, on a ceiling. So the switch arrangement may not correspond directly to a light arrangement.

So sometimes the best that can be done is a natural mapping: the physical layouts are not identical, but a simple mental model can transform the controls to the functions and vice versa. The turn signal switch in most cars is a stalk that moves up and down (vertically), but the function it controls is a signal for turning left or right, horizontally. But the mapping is natural, because the turn signal stalk sits on the steering column, and the user can mentally map it to moving the stalk in the direction that the steering wheel will be turned, rather than the direction the car will move.

Other good examples of mapping include:

• Stove burners. Many stoves have four burners arranged in a square, and four control knobs arranged in a row. Which knobs control which burners? Most stoves don’t make any attempt to provide even a natural mapping.
• An audio mixer for DJs (proposed by Max Van Kleek for the Hall of Fame) has two sets of identical controls, one for each turntable being mixed. The mixer is designed to sit in between the turntables, so that the left controls affect the turntable to the left of the mixer, and the right controls affect the turntable to the right. The mapping here is direct.
• The controls on the RealCD interface don’t have a natural mapping. Why not?
• The Segway’s controls have a direct mapping. Why?
• Here’s a meta question. What’s wrong with the mapping of this bulleted list with respect to the slide above?

Another important kind of consistency, often overlooked, is in wording. Use the same terms throughout your user interface. If your interface says “share price” in one place, “stock price” in another, and “stock quote” in a third, users will wonder whether these are three different things you’re talking about.

Don’t get creative when you’re writing text for a user interface; keep it simple and uniform, just like all technical writing.

Here are some examples from the Course VI Underground Guide web site – confusion about what’s a “review” and what’s an “evaluation”.