John R. Gallagher

17 articles
  1. When collaborating turns into dishonesty: A data-driven heuristic comparing human and AI collaborators
    Abstract

    With respect to AI writing technologies (AIWT), we pose three foundational questions about academic dishonesty. First, do writing instructors and students perceive differences between AI agents and human agents in classroom scenarios? Second, to what extent are writing instructor and student perceptions are aligned? Third, what types of writing scenarios are perceived as academic dishonesty? Answering these questions provides a baseline of comparison not only for future studies of AIWT collaboration but also contextualizes perceptions of human-to-human collaboration. We report on a large-scale experimental survey study that answers these questions using item response theory (IRT). Our findings demonstrate that while there are differences between AI and human agents of collaborations, writing instructors and students are generally aligned in their perceptions. Using a Rasch model, we find that academic dishonesty operates along a spectrum of textual production. Regardless of whether the collaborating agent is human or AI, the more an agent produces text, the more this collaboration is perceived as academic dishonesty. Conversely, the less text that is produced, the less this scenario is perceived as academically dishonest. In our discussion, we provide a data-driven heuristic to guide instructors and administrators.

    doi:10.1016/j.compcom.2025.102947
  2. Comparing Student and Writing Instructor Perceptions of Academic Dishonesty When Collaborators Are Artificial Intelligence or Human
    Abstract

    It remains unclear if perceptions of academic dishonesty concerning artificial intelligence writing technologies (AIWTs) present new challenges or if they reflect prior, non-AI concerns. To structure this problem, we used a randomized control survey experiment. We compared student ( n = 603) and instructor ( n = 312) attitudes toward dishonesty in collaborations involving humans versus AIWT in 10 writing-related scenarios. Results suggest similar perception patterns among students and instructors, with both populations expressing significant differences in perceived dishonesty between AI and human collaborators in some scenarios. This experiment structures the problem of AI writing and academic dishonesty for future research in this emerging field.

    doi:10.1177/10506519241239937
  3. Emojination Facilitates Inclusive Emoji Design Through Technical Writing: Fitting Tactical Technical Communication Inside Institutional Structures
    Abstract

    Creating new emojis is predicated on a system of technical writing that lobbies for new emojis to the Unicode Consortium. Emojination, an activist collective working for cultural inclusivity, helps everyday people write proposals for inclusive and culturally sensitive emojis. Through a case study of Emojination, this article describes ways that Tactical Technical Communication can work toward cultural inclusivity within regulatory frameworks.

    doi:10.1177/00472816231161062
  4. Analyses of seven writing studies journals, 2000–2019, Part II: Data-driven identification of keywords
    doi:10.1016/j.compcom.2023.102756
  5. Analyses of seven writing studies journals, 2000–2019, Part I: Statistical trends in references cited and lexical diversity
    doi:10.1016/j.compcom.2023.102755
  6. Required Templates: An Assemblage Theory Analysis of How Template Character Limits Influence the Writing of DIY Online Grant Proposals
    Abstract

    Identifying the effects of online templates, such as empty state pages (ESPs), sheds light on the user writing habits and best practices for user design. By using assemblage theory and extending previous studies of ESPs to grant proposal writing on the crowded-funded website Experiment.com, this large-scale study (n = 778) finds that required fields are more likely to be filled to the character limit than optional fields.

    doi:10.1080/10572252.2021.2019318
  7. Project-Oriented Web Scraping in Technical Communication Research
    Abstract

    This article advocates for web scraping as an effective method to augment and enhance technical and professional communication (TPC) research practices. Web scraping is used to create consistently structured and well-sampled data sets about domains, communities, demographics, and topics of interest to TPC scholars. After providing an extended description of web scraping, the authors identify technical considerations of the method and provide practitioner narratives. They then describe an overview of project-oriented web scraping. Finally, they discuss implications for the concept as a sustainable approach to developing web scraping methods for TPC research.

    doi:10.1177/10506519211064619
  8. A Collaborative Longitudinal Design for Supporting Writing Pedagogies of STEM Faculty
    Abstract

    Providing contextualized, effective writing instruction for engineering students is an important and challenging objective. This article presents a needs analysis conducted in a large engineering college and introduces the faculty development program that was created based on that analysis. The authors advocate for sustained interdisciplinary collaboration to promote contextualized adoption and adaptation of best practices and testing of scalable strategies.

    doi:10.1080/10572252.2020.1713405
  9. Machine Time: Unifying<i>Chronos</i>and<i>Kairos</i>in an Era of Ubiquitous Technologies
    Abstract

    Chronos and kairos are often understood as separate from one another in discussions of rhetorical temporality. For online and other highly mediated contexts, however, chronos and kairos can be understood as deeply related and intertwined. Via the concept of transduction, this article introduces machine time, which describes rhetorical time across a broad range of digital contexts, including online discussion forums and computer code.

    doi:10.1080/07350198.2020.1805573
  10. The Ethics of Writing for Algorithmic Audiences
    doi:10.1016/j.compcom.2020.102583
  11. Peering into the Internet Abyss: Using Big Data Audience Analysis to Understand Online Comments
    Abstract

    This article offers a methodology for conducting large-scale audience analysis called “big data audience analysis” (BDAA). BDAA uses distant reading and thin description to examine a large corpus of text data from online audiences. In this article, that corpus is approximately 450,000 online reader comments. We analyze this corpus through sentiment analysis, statistical analysis, and geolocation to identify trends and patterns in large datasets. BDAA can better prepare TPC researchers for large-scale audience studies.

    doi:10.1080/10572252.2019.1634766
  12. A Framework for Internet Case Study Methodology in Writing Studies
    doi:10.1016/j.compcom.2019.102509
  13. Empty Templates: The Ethical Habits of Empty State Pages
    Abstract

    This article examines how empty state pages (ESPs) constrain user-generated communication through the ethical lens of Bourdieu’s habitus. The authors define ESPs as interactive instructional templates that prompt users to input information to participate in an online network. Through a case study analyzing ~450,000 online comments from The New York Times, the authors find a direct connection between ESP elements, such as the character limit for comments, and online writers’ cultivated habitus.

    doi:10.1080/10572252.2018.1564367
  14. Considering the Comments: Theorizing Online Audiences as Emergent Processes
    doi:10.1016/j.compcom.2018.03.002
  15. Writing for Algorithmic Audiences
    doi:10.1016/j.compcom.2017.06.002
  16. Five Strategies Internet Writers Use to “Continue the Conversation”
    Abstract

    This article investigates the strategies web-writers develop when their audiences respond to them via textual participation. Focusing on three web-writers who want to “continue the conversation,” this article identifies five major strategies to accomplish this aim: (a) editing after production, (b) quotation, (c) question posing, (d) naming secondary writers, and (e) textual listening. Using the lens of writer-audience tension, I find that due to these web-writers’ perceptions of audience, one that is partially externalized via the website’s template, the term audience itself may not be a discrete concept, but a fluid, evolving, and recursive one, in other words, ongoing. These perceptions of audience reflect the unending nature of online texts and are exemplified by these five strategies.

    doi:10.1177/0741088315601006
  17. The Rhetorical Template
    doi:10.1016/j.compcom.2014.12.003