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File:Computer keyboard.gif

Typing is the process of inputting text into a device, such as a typewriter, cell phone, computer, or a calculator, by pressing keys on a keyboard. It can be distinguished from other means of input, such as the use of pointing devices like the computer mouse, and text input via speech recognition.

It is a clerical secretarial skill that has been developed in everyday use in other contexts.


Motor skills perspectiveEdit

TechniqueEdit

Touch typingEdit

File:Touch typing.svg
Main article: Touch typing

The basic technique stands in contrast to search and peck typing as the typist keeps their eyes on the source copy at all times. Touch typing also involves the use of the home row method, where typists keep their wrists up, rather than resting them on a desk or keyboard as this can cause carpal tunnel syndrome. To avoid this, typists using this method should sit up tall leaning slightly forward from the waist, place their feet flat on the floor in front of them with one foot slightly in front of the other, keeping their elbows close to their sides with their forearms slanted slightly upward to the keyboard, fingers should be curved slightly resting on the home row (asdfjkl;).

Many touch typists also use keyboard shortcuts or hotkeys when typing on a computer. This allows them to edit their document without having to take their hands off the keyboard to use a mouse. An example of a keyboard shortcut is touching the Control key plus the S key to save your copy as you type or the Control key plus the Z key to undo a mistake. Many experienced typists can feel or sense when they've made an error and can hit the backspace key and make the correction without missing a beat.

A highly trained touch-typist on a Dvorak keyboard is the second-fastest method of English text entry available as of 2007Template:Dated maintenance category.[How to reference and link to summary or text] (The fastest text entry method involves a highly trained typist on a stenotype keyboard.)

Search and peckEdit

Search and peck (two-fingered typing) is a common form of typing, in which the typist must find and press each key individually. This is almost always considerably slower than touch typing. Instead of relying on the memorized position of keys, the typist must find each key by sight. Use of this method may also prevent the typist from being able to see what has been typed without glancing away from the keys. Although good accuracy may be achieved, any typing errors that are made may not be noticed immediately, if at all. There is also the disadvantage that because fewer fingers are used, they are forced to move a much greater distance.

File:CCC typing class.gif

There are many idiosyncratic typing styles in between "search and peck" and touch typing; for example, many people will type blindly, but use only two to five fingers, and not always in a systematic fashion. Some people have developed advanced forms of search and peck that don't require looking at keys, or losing too much speed.

BufferingEdit

Some people use a combination of touch typing and Search and peck by using a buffering method. In the buffer method, the typist looks at the source copy, stores one or many sentences in his or her head, then looks at the keyboard and types out the buffer of sentences. Doing this allows the typist to eliminate frequent up and down motions with the head. It is particularly used in typing competitions, where the typist is not well versed in touch typing. It is not normally used in day-to-day contact with keyboards, only when time is of the essence.

ThumbingEdit

A rather new trend in typing, primarily used with devices such as PDAs with built-in keyboards, is thumbing or thumb typing.[How to reference and link to summary or text] This can be accomplished using one or both thumbs. Similar to desktop keyboards and input devices, if a user overuses keys which need hard presses or/and have small and unergonomic layouts, it could cause thumb tendinitis or other repetitive strain injury.

Words per minuteEdit

Words per minute (WPM) is a measure of typing speed, commonly used in recruitment. For the purposes of WPM measurement a word is standardized to five characters or keystrokes. Therefore, "fifth" counts as one word, but "fifteenth" counts as two.

The benefits of a standardized measurement of input speed are that it enables comparison across language and hardware boundaries. The speed of an Afrikaans-speaking operator in Cape Town can be compared with a French-speaking operator in Paris.

Alphanumeric entryEdit

In one study of average computer users, the average rate for transcription was 33 words per minute, and only 19 words per minute for composition.[1] In the same study, when the group was divided into "fast", "moderate" and "slow" groups, the average speeds were 40wpm, 35wpm, and 23wpm respectively. Two-finger typists, sometimes also referred to as "Search-and-Peck" typists can reach speeds of about 37wpm for memorized text, and 27wpm when copying text.[2]

An average typist reaches 50 to 70wpm, while some positions can require 80 to 95 (usually the minimum required for dispatch positions and other typing jobs), and some advanced typists work at speeds above 120. As of 2005, Barbara Blackburn is the fastest typist in the world, according to The Guinness Book of World Records. Using the Dvorak Simplified Keyboard, she has maintained 150 wpm for 50 minutes, 170 wpm for shorter periods of time, and has been clocked at a peak speed of 212 wpm. Blackburn failed her typing class in high school, first encountered the Dvorak keyboard in 1938, quickly learned to achieve very high speeds and occasionally toured giving speed-typing demonstrations during her secretarial career.

Using a personalized interface, physicist Stephen Hawking, who suffers from Lou Gehrig's disease, managed to type 15 wpm with a switch and adapted software created by Walt Woltosz. Due to a slowdown of his motor skills, his interface was upgraded with an infrared camera that detects eye blinks. Actual wpm are unknown.

A less common form of finding the speed of a typist, the acronym CPM is used to identify the number of characters typed per minute. This is a common measurement for typing programs, or typing tutors, as it can give a more accurate measure of a person's typing speed without having to type for a really prolonged period of time. It is also used occasionally for associating the speed of a reader with the amount they have read.

The CPM (characters per minute) measurement can be associated with older models of printers, but this is often not the case. The most common term associated with the speed of printers today is PPM (pages per minute).

Numeric entryEdit

The Numeric Entry or 10 key speed is a measure of one's ability to manipulate the numeric keypad found on most keyboards. It is used to measure speed for jobs such as data entry of number information on items such as bills and checks. It is measured in 'Keystrokes per hour', or KPH.

Much like alphanumeric keyboards, people start using a numeric keyboard with 1-finger search-and-peck, but the fastest data entry professionals use a kind of touch-typing using 3, 4 or 5 fingers. [How to reference and link to summary or text]

Text-Entry ResearchEdit

Error AnalysisEdit

With the introduction of computers and word-processors, there has been a change in how text-entry is performed. In the past, using a typewriter, speed was measured with a stopwatch and errors were tallied by hand. With the current technology, document preparation is more about using word-processors as a composition aid, changing the meaning or error rate and how it is measured. Research performed by R. William Soukoreff and I. Scott MacKenzie, has led to a discovery of the application of a well-know algorithm. Through the use of this algorithm and accompanying analysis technique, two statistics were used, minimum string distance error rate (MSD error rate) and keystrokes per character (KSPC). The two advantages of this technique include:

1. Participants are allowed to enter text naturally, since they may commit error and correct them.
2. The identification of errors and generation of error rate statistics is easy to automate.

Deconstructing the Text Input ProcessEdit

Through analysis of keystrokes, the keystrokes of the input stream were divided into four classes: Correct (C), and Incorrect Fixed (IF), Fixes (F), Incorrect Not Fixed (INF). These key stroke classification are broken down into the following

1. The two classes Correct and Incorrect Not Fixed comprise all of the characters in transcribed text.
2. Fixes (F) keystrokes are easy to identify, and include keystrokes such as backspace, delete, cursor movements, and modifier keys.
3. Incorrect Fixed (IF) keystrokes are found in the input stream, but not the transcribed text, and are not editing keys.

Using these classes, the Minimum String Distance Error Rate and the Key Strokes per Character statistics can both be calculated.

Minimum String Distance Error RateEdit

The minimum string distance (MSD)is the number of "primitives" which is the number of insertions, deletions, or substitutions to transform one string into another. The following equation was found for the MSD Error Rate

MSD Error Rate = (INF/(C + INF)) * 100%

Key Strokes per Character (KSPC)Edit

With the minimum string distance error, errors that are corrected do not appear in the transcribed text. The following example will show you why this is an important class of errors to consider:

Presented Text: the quick brown
Input Stream: the quix<-ck brown
Transcribed Text: the quick brown

in the above example, the incorrect character ('x') that was deleted with a backspace ('<-'). Since these errors to do appear in the transcribed text, the MSD error rate is 0%. This is why there is the key strokes per character (KSPC)statistic.

KSPC = (C+INF+IF+F)/(C+INF)

The three shortcommings of the KSPC statistic are listed below:

1. High KSPC values can be related to either many errors which were corrected, or few errors which were not corrected, however there is no way to distinguish the two.
2. KSPC depend on the text input method, and cannot be used to meaningfully compare two different input methods, such as Qwerty-keyboard and a multi-tap input.
3. There is no obvious way to combine KSPC and MSD into an over-all error rate, even though they have an inverse relationship.

Example of MSD and KSPCEdit

Presented Text: the quick brown
Input Stream: th quix<-ck brpown
Transcribed Text: th quick brpown

In the above example, there are three errors: an 'e' is omitted, there is an extra 'x' that is corrected, and there is an extra 'p' which was not corrected. The key strokes are mapped out below:

Input Stream: |the qui| |x| |<-| |ck br||p| |own|
C: |the qui|, |ck br|, |own| = 14 characters
F: |<-| = 1 character
IF: |x| =1 character
INF:|b| = 2 characters(since the 'e' is missing)

using these numbers the following statistics were calculated

MSD = (2 / 16)*100% = 12.5%
KSPC = (18 / 16) = 1.125

Further MetricsEdit

Using the classes described above, further metrics were defined by R. William Soukoreff and I.Scott MacKenzie:

1. Error correction efficiency refers to the ease with which the participant performed error correction.
Correction Efficiency = IF/F

2. Participant conscientiousness is the ratio of corrected errors to the total number of error, which helps distinguish perfectionists from apathetic participants.
Participant Conscientiousness = IF / (IF + INF)

3. If C represents the amount of useful information transferred, INF, IF, and F represent the proportion of bandwidth wasted.
Utilized Bandwidth = C / (C + INF + IF + F)
Wasted Bandwidth = (INF + IF + F)/ (C + INF + IF + F)

Total Error RateEdit

The classes described also provide an intuitive definition of total error rate:

Total Error Rate = ((INF + IF)/ (C + INF + IF)) * 100%
Not Corrected Error Rate = (IF/ (C + INF + IF)) * 100%
Corrected Error Rate = (IF/ (C + INF + IF)) * 100%

Since these three error rates are ratios, they are comparable between different devices, something that cannot be done with the KSPC statistic, which is device dependent.[3]


See alsoEdit

ReferencesEdit

  1. Karat, C.M., Halverson, C., Horn, D. and Karat, J. (1999), Patterns of entry and correction in large vocabulary continuous speech recognition systems, CHI 99 Conference Proceedings, 568-575.
  2. Brown, C. M. (1988). Human-computer interface design guidelines. Norwood, NJ: Ablex Publishing.
  3. Soukoreff, R. W., & MacKenzie, I. S. (2003). Metrics for text entry research: An evaluation of MSD and KSPC, and a new unified error metric. Proceedings of the ACM Conference on Human Factors in Computing Systems - CHI 2003, pp. 113-120. New York: ACM.
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