Background: This study adopted a corpus-linguistics approach to investigate the gender effects in students' technical and scientific writing. Specifically, we analyzed whether gender influenced how males and females used adverbs (e.g., very, really, and definitely) and passive voice (e.g., the article was published in the journal). The overuse of both adverbs and passive voice has been associated with poor writing clarity and concision. Literature review: Previous research works on gender effects in language have been mixed. Since these are all the essential elements of effective technical communication, teachers need to know what gender effects might exist. Research questions are as follows: 1. Does gender influence the student writers' use of adverbs? 2. Does gender influence the student writers' use of passive voice? Methodology: The sample included 87 writers (46 females and 41 males) who contributed to a 757,533-word corpus. Researchers analyzed 12,111 instances of adverbs and 4,732 instances of passive voice within a variety of technical texts. Results/discussion: Female writers used significantly more adverbs as well as more additive/restrictive, degree, and stance adverbs than expected. Male writers used more linking and manner adverbs than expected. Female writers also used significantly more passives, particularly passive verbs associated with reporting findings and interpretation. In contrast, male writers associated with passive verbs used to describe methods and analyses. Overall, the results suggested that females and males used the same style markers to fulfill different rhetorical functions.

The quest to understand the nuances of professional communication using computational tools have continued since, and many researchers in our field have embraced the new interdisciplinary approach now known as data science. Our quick metadata search on the journals and conference proceedings in technical and professional communication (TPC) revealed an increasing number of articles associated with terms commonly used in data science (e.g., big data, content analysis, text mining, sentiment analysis, topic modeling, network analysis) originating from numerous disciplines (e.g., corpus linguistics, computational linguistics, artificial intelligence, statistics, business analytics). Yet, the field of TPC is just beginning to embrace the power of data-driven approaches. This special issue extends Orr’s work by taking a snapshot of current work in data-driven approaches to the study of TPC.

We investigated the perception and recognition of errors in a population of practitioners and academics in professional and technical communication. Specifically, we measured 303 participants’ botheration levels of 24 usage errors and then correlated those results against their ability to recognize the errors. Results indicated that practitioners were often more bothered by errors than academics and that participants’ overall botheration level might have fluctuated over the past 40 years. Participants’ botheration level also appeared to associate with their ability to identify error. Finally, we found that participants’ gender, job type, and years working in the field influence their error perception.

This article presents a case history on integrating corpora in a graduate-level technical editing course to teach students about writing variation.

The decision to follow the demonstrative this with a noun phrase is important to students’ writing development. Previous research has emphasized when students should not attend this rather than studying why students make the choice. Using a corpus-linguistic approach, we investigated 1,999 instances of (un)attended this in student technical and academic writing. High shares of unattended this were found in both text types as well as in original and revised drafts.

This study explores a comprehensive sample of experimental and quasi-experimental research within five leading technical communication journals over a 20-year period. Exploratory studies can overview how a method has evolved within a field, highlighting how it has advanced understanding of communication and identifying areas for further inquiry. Research questions: (1) How has experimental research in technical communication journals developed over the 20-year period? Specifically, how much is being published, which journals publish experiments, what topics are being explored, and what fields are informing this research? (2) What content characterizes experimental research in technical communication? Specifically, how explicit are the research questions/hypotheses, are the results of pilot studies reported, what are the sample sizes and populations used, and what measures do researchers use? (3) Who publishes experimental research in technical communication? Specifically, which authors and affiliates are most associated with experimental research, and how does the sample's gender and authorship distribution compare to existing research? Literature review: We first address how scholars have assessed research in technical communication and how these findings implicate experimental research. We then review features of other exploratory studies that inform this study's design. Methodology: We conducted a quantitative and qualitative analysis of 137 experiments, a comprehensive sample identified from a corpus of 2,118 refereed papers published from 1992 to 2011. We coded 14 variables related to the causal relationships that the experiments addressed and who produced the research. We subjected the data to multiple statistical measures, including contingency table analysis and correspondence analysis. Results and conclusions: Over the 20 years, the journals published experimental research at a consistent rate. This could indicate that these methods have a stable presence in the field, or a discouraging sign that output is not on the rise despite calls from leading scholars. IEEE Transactions on Professional Communication (TPC) emerged as a strong producer of experiments, publishing 45% of the sample. TPC was also associated with most recent experiments, assuming this role from Journal of Technical Writing and Communication, which was associated with early experiments. In addition, TPC, Journal of Business and Technical Communication, and Technical Communication correlated with experiments on collaboration, pedagogy, and intercultural communication, respectively. The results also revealed that recent experiments reported significantly more explicit research question/hypotheses and pilot studies, an encouraging sign for the quality of future experiments. Finally, Spyridakis published the most experiments over the past 20 years, and researchers at the University of Washington and the University of Twente were the top affiliates associated with output. The configuration of both of these institutions' programs, which seem to align with a traditional science model, might suggest how the evolution of technical communication programs impacts the type of research that its affiliates produce. Our results are limited by the small, though comprehensive, sample and the exploratory natures of measures like correspondence analysis. Future research could use the proposed framework to investigate the evolution of other research methods in technical communication, strengthening our body of knowledge.

Quantitative content analysis can enrich research in technical communication by identifying the frequency of thematic or rhetorical patterns and then exploring their relationship through inferential statistics. Over the last decade, the field has published few content analyses, and several of these applications have been qualitative, diluting the method's inherent rigor. This paper describes the versatility of quantitative content analysis and offers a broader application for its use in the field. This discussion frames two original case studies that illustrate the design variability that content analysis offers researchers.

Assessing the quality of student efforts and products is a continual necessity for academics and practitioners in technical communication; however, the process of constructing valid and reliable rubrics remains an underexplored topic in the field. This paper first addresses some of the assessment concerns and then describes a case study that documents the development and implementation of one holistic and five analytic rubrics to evaluate undergraduate projects. The discussion focuses on identifying site-specific criteria and training effective raters and is intended to help academics respond to their required accreditation mandates and offer practitioners alternatives for evaluating products and services.