Introduction: The technical editing discipline stands in need of additional empirical research—particularly language-level research. However, the time- and resource-intensive nature of data collection and analysis may prevent some scholars from completing the needed research. Therefore, this tutorial introduces TrackEDT, a tool we have developed to ease the process of collecting and analyzing edits and comments from edited documents. Key concepts: TrackEDT extracts editors’ tracked insertions, deletions, moves, and comments from Microsoft (MS) Word documents—all elements of traditional editorial markup. It outputs the extracted data into an MS Excel format that affords easier analysis of the editors’ data than would be possible in the data’s original MS Word format. Key lessons: Researchers can download TrackEDT as an executable file at editingresearch.byu.edu/trackedt. To run the file, they select a folder containing edited MS Word documents that have tracked changes and comments. After TrackEDT processes the documents, the researchers can analyze the extracted tracked changes, comments, and metadata in the resulting Excel reports, which include information such as who made the edit, what type of edit was made, when the edit was made, how long the edit was, and what comments were appended. Implications for practice: Technical editing researchers can use TrackEDT and its reports to ease their collection and analysis of editing data, thereby answering important empirical research questions related to language-level editorial changes and processes.

Scholars have long argued that technical editing should be viewed as a rhetorical practice in which copy editors take “a situational approach to each individual task” (Buehler, 1980/2003, p. 458). Yet many editing pedagogies still treat some language-level editing tasks, like those that involve prescriptive usage rules, as mechanical rather than rhetorical. This article discusses how empirical data from corpora can help copy editors adopt a more rhetorical view of prescriptive usage rules and introduces corpus linguistics as a methodology that can contribute to technical editing pedagogy.

Background: Captions do important communicative work, but little research has investigated their content quantitatively. Literature review: Captions help facilitate learning and make retrieving information from databases easier. Yet, few studies have explored the rhetorical moves found in figure captions to better understand their communicative function. Research questions: 1. How do captions found in psychology, linguistics, biology, and technical and professional communication (TPC) journals differ in terms of length? 2. What are the rhetorical structures of figure captions in psychology, linguistics, biology, and TPC journals? 3. How do the rhetorical structures of captions in journals from these four disciplines differ? 4. To what extent does visual type interact with caption length and rhetorical structure? Research methodology: Using quantitative content analysis, I compared the frequencies of moves in captions across disciplines, determined whether the moves were conventional or optional, and identified patterns in the progression of moves in the captions that I analyzed. A supplementary analysis of the types of visuals that accompanied the captions offered insights into the findings of the caption-content analysis. Results: Results suggest a high degree of variation in the rhetorical structure of captions in academic journals. Biology captions were, on average, the longest and contained the most moves. TPC captions were the shortest and contained the fewest moves. Psychology and linguistics captions fell between the biology and TPC captions. Conclusions: Understanding variation in caption content can encourage a more rhetorical approach to caption writing. Researchers in disciplines where shorter captions are standard might consider writing elaborated captions.

The authors examined a corpus of figure captions from technical and professional communication (TPC)-journal articles to test their sense that TPC captions do not fulfill their communicative potential as well as, they sensed, journals in science often do. The authors performed a content analysis on captions from biology-journal articles and iteratively tested a coding scheme of caption content. The resulting scheme can help in analyzing caption content, developing captions, and imparting a variety of TPC-related skills to students.