Correcting Text Production Errors: Isolating the Effects of Writing Mode From Error Span, Input Mode, and Lexicality

Abstract

Error analysis involves detecting, diagnosing, and correcting discrepancies between the text produced so far (TPSF) and the writers mental representation of what the text should be. The use of different writing modes, like keyboard-based word processing and speech recognition, causes different type of errors during text production. While many factors determine the choice of error-correction strategy, cognitive effort is a major contributor to this choice. This research shows how cognitive effort during error analysis affects strategy choice and success as measured by a series of online text production measures. Text production is shown to be influenced most by error span, that is, whether the error spans more or less than two characters. Next, it is influenced by input mode, that is, whether the error has been generated by speech recognition or keyboard, and finally by lexicality, that is, whether the error comprises an existing word. Correction of larger error spans is more successful than that of smaller errors. Writers impose a wise speed accuracy trade-off during large error spans since correction is better, but preparation times (time to first action) and production times take longer, and interference reaction times are slower. During large error spans, there is a tendency to opt for error correction first, especially when errors occurred in the condition in which the TPSF is not preceded by an auditory prompt. In general, the addition of speech frees the cognitive demands of writing. Writers also opt more often to continue text production when the TPSF is presented auditorially first.