It is no secret that the user interface of most computer systems could be improved. Systems are often intimidating, prone to error, and require a high investment in effort before productive work can be undertaken. A desire to make systems easier to use is a good starting point, but we can't get very far without some theory of how to do so. Underlying this formulation is an assumption that there is a qualitative difference between how experts and novices achieve particular goals. Experts and novices differ in the coarseness of granularity with which they view the constituent elements of a particular problem or task.
Novices are attentive to low-level details.
For example, operational details such as finding a particular character on the keyboard or remembering the name of a command involve problem solving . The result is that valuable cognitive resources are diverted from the central problem at hand. With experts, these low-level details can be performed automatically . Hence, the size of the chunks of the problem to which they are attentive are much larger. The acquisition of skills, therefore, can be characterized by developing an ability to perform ever-larger chunks of a problem automatically.