This study explores the relation between writing quality and contextualization and elaboration moves, two kinds of textual expansion devices crucial for building common ground between writers and readers. We ask whether elaboration and contextualization features differentially predict writing quality and whether their quality contributions differ between genres. We also ask to what extent elaboration and contextualization are tied to individual writers, and can be explained by writer characteristics. To examine these issues, we annotated descriptive and argumentative texts of Dutch adolescents. Text quality was rated holistically, using benchmark scales.     As regards elaboration, depth affects quality more than breadth does. It also contributes across genres, whereas breadth only contributes in argumentations. Depth shows a large individual consistency across tasks, which is substantially related to students’ school type, grade and gender. Breadth shows weaker links to individual writers and their characteristics.     With regard to contextualization, opening and closing moves play a modest role in text quality. Initial support moves contribute to quality across tasks; concluding moves contribute more in argumentations. Concluding moves are most consistent within writers; however, for all contextualization moves, the writer variance is substantially explained by writer characteristics. This study opens up new avenues for explicating writing quality and writing skill.

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.