tool use allows us to assess text entry in terms of its utility—how well it supports users in thatpursuit—and its usability—how easy it is to enter text and learn how to enter text.

For example, word predictionusage may not be beneficial if the word suggestions are poorly suited to the individual’s language orif the user can type words faster than the time required to scan and select among word suggestions.

One example is autocorrect, which automatically corrects typing errors while the user is typing. Another example is the use of word predictions, which allow the user to select a word from a set of word suggestions instead of typing out the word in full.

For example, text entry methods such as eye typing are designed to allow nonspeaking users with motor disabilities to enter text using their eye movements only.

Thinking about text entry as

Text entry can also be carried out via spoken dialogue.

When you enter a letter (a turn), a small pop-up appearsfor you to confirm your press (a turn). A word prediction list may show possible completions of theword. At every press, these are updated, over time forming a graphical dialogue between the userand the system.

Text entry can also be seen as dialogue (Chapter 18).

Viewing text entry as a control problem can providea more in-depth understanding of the human perceptual and motor control aspects of text entry,such as a user’s ability to touch individual letter keys on a touchscreen keyboard or a user’s abilityto perform a touchscreen gesture.

In text entry, the theory provides us with concepts andmetrics that aid our understanding of typing performance.

For example, the information rate ofa text entry method can be quantified using the concept of throughput from information theory.

As another example, text entry often relies on language models, and such modeling is based oninformation theory.

First, text entry can be seen as the transmission of typed information to a computer.