Analyzing the input stream for character- level errors in unconstrained text entry evaluations

Abstract

Recent improvements in text entry error rate measurement have enabled the running of text entry experiments in which subjects are free to correct errors (or not) as they transcribe a presented string. In these "unconstrained" experiments, it is no longer necessary to force subjects to unnaturally maintain synchronicity with presented text for the sake of performing overall error rate calculations. However, the calculation of character-level error rates, which can be trivial in artificially constrained evaluations, is far more complicated in unconstrained text entry evaluations because it is difficult to infer a subject's intention at every character. For this reason, prior characterlevel error analyses for unconstrained experiments have only compared presented and transcribed strings, not input streams. But input streams are rich sources of character-level error information, since they contain all of the text entered (and erased) by a subject. The current work presents an algorithm for the automated analysis of character-level errors in input streams for unconstrained text entry evaluations. It also presents new character-level metrics that can aid method designers in refining text entry methods. To exercise these metrics, we perform two analyses on data from an actual text entry experiment. One analysis, available from the prior work, uses only presented and transcribed strings. The other analysis uses input streams, as described in the current work. The results confirm that input stream error analysis yields richer information for the same empirical data. To facilitate the use of these new analyses, we offer pseudocode and downloadable software for performing unconstrained text entry experiments and analyzing data.

Analyzing performance with computer access technology using unconstrained text entry protocol

“…A limitation of the methods used in this article was the failure to distinguish between characters that were erased because they were erroneous (i.e., truly incorrect but fixed) and characters that were actually correct but erased in the process of fixing errors [11][12]. Wobbrock and Myers have recently demonstrated how the input stream can be decomposed into [12]-…”

“…Another common approach is to reject incorrect keystrokes, forcing the transcribed text (T) to match the presented text (P) exactly [8][9][10][11][12]. A common side effect of this approach is that users will often not notice their first incorrect keystroke and produce a string of subsequent "incorrect" keystrokes.…”

“…As an alternative, investigators within the field of human factors have recently begun employing "unconstrained" text entry protocols [8][9][10][11][12], in which the user is allowed to make errors and decide whether or not to correct the errors that occur. The primary advantage of this approach is that it allows users to enter text under more natural, realistic conditions [8][9][10][11][12].…”

“…The primary advantage of this approach is that it allows users to enter text under more natural, realistic conditions [8][9][10][11][12]. This approach also allows investigators to analyze the entire input (I) stream, including errors and error corrections [12], thus providing a more detailed picture of text entry.…”

Haptic Feedback Intensity Affects Touch Typing Performance on a Flat Keyboard

“…For the typing task, we asked the participants to type each given phrase displayed on the computer monitor using the typing test program called TextTest [8]. Twenty five phrases were randomly selected from the MacKenzie phrase set [9] for each condition.…”