Using a multiple case-study approach, this study investigated the dynamics of peer interactions that took place through Microsoft Copilot among six pairs ( n = 12) of ESL learners, focusing on their interaction patterns, use of semiotic and multimodal resources, and functions of languaging. Our analyses illustrated that four pairs displayed collaborative orientation, one pair demonstrated an expert-novice pattern, and one pair exhibited a dominant-passive pattern. It was also found that while the collaborative group students focused more on text search and revision, the expert-novice group and the dominant-passive group allocated more time to image generation. Furthermore, in terms of languaging functions, our results revealed that all six pairs of students spent most of their time negotiating writing content. Our study has implications for technology-enhanced multimodal writing pedagogy in a generative artificial intelligence machine-in-the-loop setting.
This study has analysed and compared Chinese learners’ use of 17 types of complex noun phrases (NPs) in English writing from beginner to advanced levels to explore the learners’ development in NP complexity. The findings reveal a correlation between learners’ proficiency levels and noun modification, which progresses from a reliance on pre-modifying adjectives and possessives at beginner levels, through more use of noun+noun and noun+ of phrases as postmodifiers at intermediate levels, to finally incorporating coordinated structures (noun+multiple prepositional phrases as post-modifiers and noun+ to -clauses as postmodifiers) and nominalized NPs (noun+complement clauses) at advanced levels. These learners’ preference for pre-modifiers in writing, irrespective of proficiency levels, highlights a potential impact from their L1 Mandarin. Qualitative analyses demonstrate beginner-level learners’ reliance on repeated identical NPs from essay topics and prompts in contrast to upper-intermediate learners’ deployment of varied vocabulary to create more complex NPs in writing. The discovery of distinct NP features at various developmental stages confirms L2 learners’ phrasal complexity development from early stages of learning, and the appropriate timing for instruction of specific NP structures is discussed accordingly.
This article tells a story about two methodologies, one used to examine the workings of the other. The examined methodology, the build-measure-learn loop used in Lean Startup, is a design methodology: It involves developing a series of design objects and using them to elicit feedback from huddles of stakeholders in a series of dialogical encounters. But unlike most design methodologies used in technical and professional communication, which assume that both stakeholders and propositions constitute stable categories, this one tests different propositions with different compositions of stakeholders during each cycle. Thus, it disrupts the incrementalist assumptions that underpin conventional design methodologies. To examine the build-measure-loop in action, we require an examining methodology that guides our conceptual decision about what to study. In this article, I use a compositional methodology to offer one such conceptual decision: the fractional object , which is made to cohere across diverse dialogic cycles, with different huddles, evaluating different claims. I apply this examining methodology to a 7-year study of a device developed by an early-stage technology startup. The study has implications for both design methodology and case study methodology.
In primary education, children frequently combine drawings with alphabetic writing in their compositions, and research has shown that drawing can support early writing development. Building on existing research on multimodality and intermodality in early writing, this study examines how drawing and writing function together in children’s multimodal compositions produced for diverse social purposes. The study analyses multimodal texts written by Swedish learners aged 7–8 years and explores intermodal relations between writing and drawing using a systemic functional, transitivity-based analytical approach. The findings indicate a predominance of word-led and combinatory intermodality, with alphabetic writing generally assuming a dominant role. At the same time, children strategically integrate drawing and writing in ways that vary according to social purpose, task theme, and the specific affordances of each mode. In several cases, drawing enables the expression of meanings that are less readily conveyed through writing alone, underscoring its distinct representational potential. The study contributes to ongoing work on intermodality in early school writing by demonstrating the analytical affordances of transitivity for examining multimodal meaning-making, and it highlights the need for pedagogical practices and teacher metalanguage that support flexible movement across semiotic modes in early literacy education.
This qualitative study investigates the biographical factors that influence the professional identities and teaching practices of second language (L2) writing instructors. Previous L2 writing studies have tended to rely on teacher interviews to examine such identities and practices and have failed to include the important perspective of classroom observations. This study conducted teacher interviews and classroom observations with three graduate teaching assistants (GTAs) of a first-year writing course at a U.S. university. The findings suggest that although teachers’ disciplinary backgrounds, teaching philosophies, and prior experiences shape their professional identities and instructional approaches, their classroom practices in language instruction do not always align with their beliefs and stated values. Teacher education programs should integrate language pedagogy and grammar instruction into writing pedagogy, while encouraging teachers to engage in consistent self-evaluation and reflection on their practices.
Studies on the writing process through the analysis of pauses, highlight a link between content formulation and linguistic units. From a text linguistics perspective, particularly Systemic Functional Linguistics (SFL), this relationship becomes even more apparent. This study investigates the location and duration of pauses in relation to syntagmatic units and their functional roles using an SFL-based framework, answering: (1) In what syntagmatic and functional contexts do pauses occur during the process of writing? (2) How does the length of pauses vary in different syntagmatic and functional contexts during the process of writing? (3) How do the frequency and length of pauses during writing vary because of interactions between their syntagmatic and functional contexts? Using keystroke logging, the writing process of 20 adult native English speakers composing argumentative essays was recorded. Findings suggest key syntagmatic and functional units prompt pauses, signaling decision-making moments and cognitive effort in generating a coherent text.
As ChatGPT is increasingly used in second language (L2) writing practice and research, its potential to provide feedback and revision has attracted much scholarly attention. However, it remains largely unknown whether and how ChatGPT revision can influence rhetorical move-steps. This study investigates the effects of ChatGPT revision on rhetorical move-steps in English personal statements (PSs) written by L2 English undergraduate students, using a combination of corpus data and stimulated recall interviews. Based on an unstructured prompt, our analysis revealed significant reductions in the rhetorical efforts devoted to five rhetorical steps. Students’ responses highlighted both benefits and concerns regarding these revisions, illustrating how AI-generated changes can alter textual features and affect writer-reader communication from the writers’ perspective. The findings highlight the importance of students’ critical evaluation of AI-generated revisions and iterative engagement with them.
The problem of data extraction to feed LLMs impacts all digital archives and open-sourced initiatives. Though the practice of data-scraping bots used to create the LLMs that feed algorithms is recent, extractivist models of language documentation are nothing new. To redress the challenges presented by extractivist methods, Indigenous language scholars and linguists as well as digital archivists and librarians have innovated methodologies to provide for a mutually sustaining relationship between language documentation efforts and indigenous language practices with the goal of enhancing language persistence practices and recuperating dormant practices. The Digital Archive of Indigenous Language Persistence (DAILP) at Northeastern University provides one effort to redress extractivist methods using Indigenous Data Sovereignty methodological frameworks. In this essay, I describe the CARE heuristic in relation to DAILP’s goals and methods to support the decision making required to meet the challenges of language extractivism. Though data scraping for LLMs presents ongoing challenges, Indigenous data-sovereignty methodologies allow language persistence with Indigenous communities and digital archives.
Finding a research problem is the first and most consequential choice a researcher can make, but making this choice about what is not yet known can leave the researcher in a hazy world of uncertainty until the project takes shape. While each person needs to find their own path through the haze, I have found that four kinds of questions help me locate and design a useful research project: what is in front of me; how I add up what I and others have learned previously; how the project fits in various perspectives in and outside the field of writing studies; and how the study advances knowledge and/or aids with practical problems. Only when the answers to these four different questions come together, am I confident of the value of a particular study. Often it takes, however, some kind of unexpected catalyst to bring the project into focus.
Approaches like participatory translation expand methods for researching multilingual writing, enabling writing studies researchers to further interrogate the connections among positionality, power, and identity in multilingual writing. Using examples of community-based multilingual writing projects, the author proposes participatory translation as an avenue for centralizing multilingual student and community goals in writing research. This approach can help researchers expand from traditional classroom studies of writing to further consider how language shapes participation in all communication contexts.
In technical and professional communication (TPC) there have been calls to locate the field in transnational contexts. Aligned with the social justice turn in TPC is an emergent body of critical and decolonial scholarship attending to power, privilege, and positionality. The following study extends this scholarship through attention to these issues in an emergent startup ecosystem in the occupied Palestinian territory (oPt). Grounded in mobility studies, this telling case attends to the strategic manner in which a female entrepreneur navigates this system through a process of networking, or knotworking, as she navigates both patriarchal and colonial systems of oppression. Central to this process is the complex way she mobilizes a multimodal and spatial repertoire—conceptualized as repertoires of resistance. These moves shape not only the ways that she traverses the social, semiotic, and geographic landscape, but also the shifting nature of the landscape itself. Methodologically such moves entail a conceptual shift from a focus on activity systems to mobility systems.
This study explores how a human-centered design (HCD) approach encourages written communication researchers to rethink methodologies when studying wicked problems, particularly in healthcare communication contexts. We argue for “methodological mutability” as a strategy to address complex and evolving challenges in rural healthcare communication. Using design thinking principles, we investigated how generative AI (GenAI) and machine learning can enhance medical communication, streamline documentation, and improve telemedicine usability. Our research revealed that rural healthcare providers view effective patient-provider communication as their primary challenge. This finding led us to pivot toward exploring how AI applications can structure and enhance patient narratives. We advocate for researchers to adopt a designer mindset, integrating methodological flexibility to move beyond problem analysis and instead develop solutions. By embedding HCD, design thinking, and methodological mutability into research design, researchers can prioritize practical interventions when working in spaces beset by wicked problems.
Traditional assessments of technical writing privilege final products or task outcomes and provide limited warrant for predicting writing competence across task types and workplace contexts. This article proposes a methodological shift toward process-based assessment, which evaluates the effectiveness of writers’ strategic actions during text production using observable process indicators and translates that evaluation into individualized, strategy-focused feedback benchmarked against group norms. To address alphabetic bias and genre/context blindness in keystroke logging, the article develops an integrated logging method for analyzing technical writing processes. To demonstrate feasibility and analytic affordances, it presents a case study adapting Perrin’s progression analysis for professional writing: Processes from 24 technical writers were captured and analyzed to generate performance feedback, strategy instruction, and process-based competence measures. By specifying analytic procedures, key process indicators, and principles for inferring writing competence from writing processes, this article advances process-oriented professional writing research and offers a transferable, scalable framework for workplace evaluation.
As generative artificial intelligence (GenAI) tools become embedded in writing practices, researchers must refine methodologies for studying self-regulation in AI-assisted composition. While sociocognitive and co-regulation frameworks have effectively captured self-regulatory processes in human collaboration, they are insufficient for understanding how writers manage the dynamic and probabilistic nature of AI-generated text. This article introduces interplay as a methodological framework to analyze the recursive process of initiating, responding, adapting, and revising in human-AI writing interactions. Unlike co-regulation, where collaborators share communicative intent, interplay highlights the writer's active role in interpreting and steering AI-generated content. Drawing on self-regulation theory, we propose an analytical framework that integrates traditional self-regulation categories (goal-setting, monitoring, and reflection) with interplay-specific coding (initiation, evaluation, acceptance, and adaptation). Through case analyses of human-AI writing exchanges, we demonstrate how interplay provides a systematic approach to studying agency, decision making, and regulatory strategies in AI-assisted writing. We argue that recognizing interplay as a distinct dimension of self-regulation advances both empirical research and pedagogical approaches to AI-mediated composition.
This article makes the case for studying community writing using sociohistorical writing ethnography, an approach that combines ethnographic and historical research methods to produce “deep theorizing” about present writing activities grounded in felt senses of history. Drawing from a study of a community writing group, the author demonstrates how individuals’ writing practices become entangled with a community’s literacies throughout time, highlighting how this methodology provides deeper insight into this research context.
While methods associated with community-engaged research have traditionally included surveys, interviews, workshops, and stakeholder feedback, this article argues that the affordances of eye tracking make it a strong candidate for use in community research contexts. Because eye tracking is grounded in experiential metrics that describe—rather than prescribe—how participants engage with multimodal work, the method encourages genuine engagement with written and visual materials, inviting the experience of a broad range of participants. Using examples of eye tracking data collected as part of three previous community research initiatives, I argue that eye tracking can bolster community-engaged research by (a) reflecting a multiplicity of reader experiences, (b) revealing how design choices impact cognitive load, and (c) fostering reflection on strengthening community engagement. While eye tracking has often been used in educational and academic settings, community-engaged research projects offer an opportunity to expand the impact of the method, benefiting the work of researchers, writers, and designers as well as the communities they serve.
This article develops the concept and procedures of a large-scale, autoethnographic research process termed Community Inter-Autoethnography . This is a research methodology in which multiple individuals conduct autoethnographies and collaboratively synthesize their positionings to produce negotiated, community-level understandings. The methodical argument is that there is a need for a research process that allows multiple voices across large social groupings to be heard in order to capture and understand diverse and shared positionings within that setting. As argued, this increase in scale answers historical questions concerning the representativeness and applicability of autoethnographic research. Building upon the expansion of single-person autoethnographies to collaborative studies (Chang, Ngunjiri, & Hernandez) and developments in science education toward the inclusive Research and Education Community (Hanauer et al.), the current article explicates how autoethnographic research can be used with a large number of participants across a community. In Hanauer et al. this approach is exemplified in a study that included 106 participants co-authoring a study of the professional identity of Course-Based Research lab instructors. Community inter-autoethnographic research provides a way of reaching community conclusions based on both diverse individual experiences and negotiated collective understandings.
Transnational and multilingual writing data are characterized by mobile practices that rarely hold still for study. As individuals form and re-form communities in the process of migration, their language and literacy paths increasingly diversify forms of language sociality, goals, or expectations. In such cases, a priori community knowledge around genre use becomes tenuous or nonexistent. Yet, many default methodological orientations in Rhetorical Genre Studies (RGS) have tended to emphasize agreement, recognizability, and community cohesion, focusing analysis especially on textual typicality. This article attends to this methodological issue by resurfacing and extending a discussion of the centrifugal nature of genre. To demonstrate this shift, the article enacts a genre analysis of a multilingual community-based writing workshop, showing how centripetal and centrifugal forces run through workshop participants’ creation of a language portrait. Ultimately, the article shows that tracking genre’s stabilizing and destabilizing forces, particularly from a human perspective, provides an analytic guide to writing practices as they fragment and re-coalesce. It further demonstrates how centering the human handling of genre can orient writing researchers to the instability that is often the reality of transnational and multilingual writing.
This article illustrates the affordances of a four-part interview protocol that combines elements of phenomenology with traditional discourse-based interviews. On the basis of two case studies with Black and Latinx writers, I demonstrate how this protocol affords a richer understanding of tacit writing competencies developed to push back against and mitigate the harm of marginalization.
