The study of revision has been a topic of interest in writing research over the past decades. Numerous studies have, for instance, shown that learning-to-revise is one of the key competences in writing development. Moreover, several models of revision have been developed, and a variety of taxonomies have been used to measure revision in empirical studies. Current advances in data collection and analysis have made it possible to study revision in increasingly precise detail. The present study aimed to combine previous models and current advances by providing a comprehensive product- and process-oriented tagset of revision. The presented tagset includes properties of external revisions: trigger, orientation, evaluation, action, linguistic domain, spatial location, temporal location, duration, and sequencing. We identified how keystroke logging, screen replays, and eye tracking can be used to extract both manually and automatically extract features related to these properties. As a proof of concept, we demonstrate how this tagset can be used to annotate revisions made by higher education students in various academic tasks. To conclude, we discuss how this tagset forms a scalable basis for studying revision in writing in depth.

在过去的几十年里，修订研究一直是写作研究的一个感兴趣的话题。例如，许多研究表明，学习修改是写作发展的关键能力之一。此外，已经开发了几种修订模型，并且在实证研究中使用了各种分类法来衡量修订。当前在数据收集和分析方面的进步使得研究修订的细节越来越精确成为可能。本研究旨在通过提供一个全面的以产品和过程为导向的修订标签集，将以前的模型和当前的进步结合起来。呈现的标签集包括外部修订的属性：触发、方向、评估、动作、语言域、空间位置、时间位置、持续时间和排序。我们确定了击键记录的方式，屏幕回放和眼动追踪可用于手动和自动提取与这些属性相关的特征。作为概念证明，我们演示了如何使用此标记集来注释高等教育学生在各种学术任务中所做的修订。最后，我们讨论这个标签集如何形成一个可扩展的基础来深入研究书面修订。