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design com-munity understand that design must convey the essence of a device’s oper- ation; the way it works; the possible actions that can be taken; and, through feedback, just what it is doing at any particular moment. Design is really an act of communication, which means having a deep understanding of the person with whom the designer is communicating.
conceptual models points out that good design is also an act of communication between the designer and the user, except that all the communication has to come about by the appearance of the device itself.
Feedback
Constraints. The surest way to make something easy to use, with few errors, is to make it impossible to do otherwise—to constrain the choices. Affordances. A good designer makes sure that appropriate actions are perceptible and inappropriate ones invisible. DOET introduced the con- cept of “perceived affordances” to the design community, and to my pleas- ure, the concept has become immensely popular. Technology may change rapidly, but people change slowly.
affords (“is for”)
a conceptual model of the device and mentally simulate its operation. You can do the simulation because the parts are visible and the implications clear.
Principles of Design for Understandability and Usability
We have now encountered the fundamental principles of designing for people: (1) provide a good conceptual model and (2) make things visible.
The design model is the designer’s conceptual model. The user’s model is the mental model developed through interaction with the system. The system image results from the physical structure that has been built (including docu- mentation, instructions, and labels).
mental models, the models people have of themselves, others, the environment, and the things with which they interact.When things are visible, they tend to be easier
The Design of Everyday Things
than when they are not. In addition, there must be a close, natural relationship between the control and its function: a natural mapping.
; it is that everyone forms theories (mental models) to explain what they have observed
LEARNED HELPLESSNESS
The phenomenon called learned helplessness may help explain the self-blame. It refers to the situation in which people experience failure at a task, often numerous times. As a result, they decide that the task cannot be done, at least not by them: they are helpless. They stop trying. If this feeling covers a group of tasks, the result can be severe difficulties coping with life. In the extreme case, such learned helpless- ness leads to depression and to a belief that the person cannot cope with everyday life at all. Sometimes all that it takes to get such a feeling of helplessness is a few experiences that accidentally turn out bad. The phenomenon has been most frequently studied as a precursor to the clinical problem of depression, but it might easily arise with a few bad experiences with everyday objects.
TAUGHT HELPLESSNESS
Do the common technology and mathematics phobias result from a kind of learned helplessness? Could a few instances of failure in what appear to be straightforward situations generalize to every technologi- cal object, every mathematics problem? Perhaps. In fact, the design of everyday things (and the design of mathematics courses) seems almost guaranteed to cause this. We could call this phenomenon taught helpless- ness.
With badly designed objects—constructed so as to lead to misunderstanding—faulty mental models, and poor feedback, no wonder people feel guilty when they have trouble using objects, especially when they perceive (even if incorrectly) that nobody else is having the same problems. Or consider the normal mathematics curriculum, which con- tinues relentlessly on its way, each new lesson assuming full knowl-
edge and understanding of all that has passed before. Even though each point may be simple, once you fall behind it is hard to catch up. The result: mathematics phobia. Not because the material is difficult, but because it is taught so that difficulty in one stage hinders further progress. The problem is that once failure starts, it soon generalizes by self-blame to all of mathematics. Similar processes are at work with technology. The vicious cycle starts: if you fail at something, you think it is your fault. Therefore you think you can’t do that task. As a result, next time you have to do the task, you believe you can’t so you don’t even try. The result is that you can’t, just as you thought. You’re trapped in a self-fulfilling prophecy.
There we have it. Seven stages of action: one for goals, three for execution, and three for evaluation.
People function through their use of two kinds of knowledge: knowledge of and knowledge how. Knowledge of—what psychologists call declarative knowledge—includes the knowledge of facts and rules.
Knowledge how—what psychologists call procedural knowledge—is the knowledge that enables a person to perform music, to stop a car smoothly with a flat tire on an icy road, to return a serve in tennis, or to move the tongue properly when saying the phrase “frightening witches.”
The difficulty with LTM is in organization—in getting material in and in figuring out how to retrieve it—not in capacity.
Memory for arbitrary things. The items to be retained seem arbitrary, with no meaning and no particular relationship to one other or to things already known.
Memory for meaningful relationships. The items to be retained form meaningful relationships with themselves or with other things al- ready known.
Memory through explanation. The material does not have to be remem- bered, but rather can be derived from some explanatory mechanism.
Rote learning: memorizing without understanding
But the proper natural mapping requires no diagrams, no labels, and no instructions.
four different classes of constraints—physical, semantic, cultural, and logical.
PHYSICAL CONSTRAINTS
Physical limitations constrain possible operations.
SEMANTIC CONSTRAINTS
Semantic constraints rely upon the meaning of the situation to control the set of possible actions.
CULTURAL CONSTRAINTS
Some constraints rely upon accepted cultural conventions, even if they do not affect the physical or semantic operation of the device.
Logical Contraints
Natural mappings work by providing logical constraints. There are no physical or cultural principles here; rather there is a logical relation- ship between the spatial or functional layout of components and the things that they affect or are affected by.
Errors come in several forms. Two fundamental categories are slips and mistakes. Slips result from automatic behavior, when subconscious actions that are intended to satisfy our goals get waylaid en route. Mistakes result from conscious deliberations. The same processes that make us creative and insightful by allowing us to see relationships between apparently unrelated things, that let us leap to correct conclu- sions on the basis of partial or even faulty evidence, also lead to error.
We can place slips into one of six categories: capture errors, description errors, data-driven errors, associative activation errors, loss-of-activation errors, and mode errors.
What has this to do with everyday thought? A lot. Everyday thought seems to be based upon past experiences, upon our ability to retrieve an event from the past and use it to model the present. This event- based reasoning is powerful, yet fundamentally flawed. Because thought is based on what can be recalled, the rare event can predomi- nate. Think about it. Think of your experiences with computers, or VCRs, or home appliances; what probably come to mind are the unusual experiences, things that are discrepant. It doesn’t matter that you may have used the device a hundred times successfully—it is the
one time you got embarrassed that will come to mind.8
Subconsciously cannot think at level. Just as I’m sure other cannot think at my level. Need to consciously try to think at a different level so much that it becomes unconscious.
Typesetting machines (such as the Linotype machine) use a completely different layout; the Linotype keyboard is called “shrdlu,” after the pattern of keys it follows, and is modeled after the relative frequency of letters in English. This was how hand printers arranged the letters that they would remove from bins and insert manually into the printing forms. Ah, yes, the natural evolution of design.
Why? Because prizes tend to be given for some aspects of a design, to the neglect of all others—usually including usability.
There is no simple solution, no one size fits all. But designing for flexibility helps.
Creeping featurism is the tendency to add to the number of features that a device can do, often extending the number beyond all reason. There is no way that a program can remain usable and understandable by the time it has all of those special-purpose features.
The point of POET is to advocate a user-centered design, a philoso- phy based on the needs and interests of the user, with an emphasis on making products usable and understandable.
Design should:
Make it easy to determine what actions are possible at any moment (make use of constraints).
Make things visible, including the conceptual model of the system, the alternative actions, and the results of actions.
Make it easy to evaluate the current state of the system.
Follow natural mappings between intentions and the required ac- tions; between actions and the resulting effect; and between the information that is visible and the interpretation of the system state.
In other words, make sure that (1) the user can figure out what to do, and (2) the user can tell what is going on.
How does the designer go about the task? As I’ve argued in POET, the principles of design are straightforward.
Use both knowledge in the world and knowledge in the head. 2. Simplify the structure of tasks.
Make things visible: bridge the gulfs of Execution and Evaluation. 4. Get the mappings right.
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Exploit the power of constraints, both natural and artificial. 6. Design for error.
When all else fails, standardize.