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Although keystroke logging promises to provide a valuable tool for writing research, it can often be difficult to relate logs to underlying processes. This article describes the procedures and measures that the authors developed to analyze a sample of 80 keystroke logs, with a view to achieving a better alignment between keystroke-logging measures and underlying cognitive processes. They used these measures to analyze pauses, bursts, and revisions and found that (a) burst lengths vary depending on their initiation type as well as their termination type, suggesting that the classification system used in previous research should be elaborated; (b) mixture models fit pause duration data better than unimodal central tendency statistics; and (c) individuals who pause for longer at sentence boundaries produce shorter but more well-formed bursts. A principal components analysis identified three underlying dimensions in these data: planned text production, within-sentence revision, and revision of global text structure.
Baaijen et al. (Sun,) studied this question.