Businesses increasingly use Artificial Intelligence (AI) Applicant Tracking Systems (ATS) to screen job applicants’ résumés. A summative content analysis auditing how 18 business communication, business English, and technical communication textbooks cover résumés and AI ATS found a lack of consensus. The study identified the challenge of offering specific advice on emerging AI technology in textbooks. The article recommends writing and teaching practice changes when discussing emerging technology and creating or using textbook content.

This article examines how artificial intelligence is transforming instructor-student communication and student evaluation in higher education. By comparing traditional and AI-mediated communication practices, the study synthesizes current literature on opportunities, challenges, and ethical considerations. The analysis highlights the need for digital literacy, emotionally intelligent AI tools, and balanced pedagogical strategies. Practical and theoretical propositions are provided to guide educators in leveraging AI while preserving human-centered teaching values.

As noted in my previous editorial, this semester I've been adjusting to my new role as CDQ 's Editor-in-Chief. It has been rewarding working with Associate Editor Casey McArdle on our first issue together. In keeping with CDQ 's roots, Casey has been spearheading a comprehensive review of our in-house and public-facing documentation and streamlining our production processes. He also helped to shoulder the load associated with copyediting and producing the articles for this exciting issue. Later in this editorial, you'll hear more from Casey about generative artificial intelligence (GenAI), pedagogical trust, bridges between academia and industry, and accessibility as a core design competency. Meanwhile, I've been settling into my new role as Associate Professor and Chair of Professional and Public Writing at the University of Rhode Island, reconnecting with old friends, and making trips to the shore where I've observed firsthand how the coastline has changed. On clear days, it is now possible to identify windmills on the horizon offshore.

Taking stock of the diminishing material conditions faced by contemporary writers broadly conceived, this article (re)frames writing as a site and a practice of exploited labor. Arguing that writing scholars have often avoided interrogating writing’s links to labor, particularly with respect to declining working conditions and the appropriation of value from workers, I draw attention to the pervasive crisis of writing’s devaluation under late capitalism. To evidence this assessment, I apply political economist Harry Braverman’s conception of the “progressive alienation of the process of production”—the notion that labor is increasingly eroded through capitalism’s advancement—to the scene of contemporary gig writing, specifically Amazon’s microtask platform Mechanical Turk (MTurk). MTurk, I maintain, offers a paradigmatic illustration of contemporary writers’ material exploitation, both for its efforts to de-skill writers and for its conscription of writers to advance their own exploitation by employing them to train generative AI.

This study investigated the impact of using ChatGPT 3.5 as a prewriting brainstorming tool on the overall quality of persuasive writing among five gifted seniors majoring in Arabic at the College of Education, Kuwait University. Giftedness, in this study, was not defined by innate advantages such as intelligence quotient (IQ) but was instead viewed from a multidimensional perspective, focusing on academic performance, writing skills, and personal traits that reflect intellectual engagement. Four participants were typically developing gifted students, while one participant was twice exceptional, both gifted and autistic. An integrated single-subject design with multiple probes across multiple baselines was used, with each participant serving as their own control. Repeated measures were used throughout the baseline, intervention, and maintenance phases to monitor intraindividual variability and examine the effectiveness of the intervention. The results indicated a significant increase in mean scores for persuasive essays from baseline to intervention for all participants, with continued improvement during maintenance for all but the twice-exceptional student, whose mean maintenance score remained unchanged from the intervention. While promoting ChatGPT 3.5 as a valuable brainstorming tool for persuasive writing, this study emphasizes its complementary role and recommends that writers engage in brainstorming using multiple resources before writing.

Jennifer L. Bay is professor of English at Purdue University, where she teaches undergraduate courses in the professional and technical writing major and graduate courses in technical and professional writing, community engagement, experiential learning, and rhetorical theory. Her work has appeared in journals such as the Journal of Business and Technical Communication, Journal of Technical Writing and Communication, IEEE Transactions on Professional Communication, and Technical Communication Quarterly.Felisa Baynes-Ross is an assistant course director of English 1014 (writing seminars) and senior lecturer in English at Yale University where she teaches courses in expository writing, creative nonfiction, and pedagogy. Both in her teaching and writing, she is interested in aesthetics of dissent, which she explores in medieval polemical treatises and poetry and historical narratives on the Caribbean. Her published work appears in the Journal of Medieval and Early Modern Studies, Caribbean Quarterly, and The Caribbean Writer.Caitlin Cawley is the assistant director of the writing program and an advanced lecturer of English at Fordham University. She teaches courses in twentieth and twenty-first-century American literature, composition and rhetoric, critical theory, and film studies. Her scholarship has appeared in the Journal of the History of Ideas, Journal of American Studies, The Faulkner Journal, and The Oakland Review and has received generous support from the US Army Heritage Center and the National Endowment for the Humanities.Tracy Clark is a senior lecturer in the Professional Writing program at Purdue University. Research interests include accessibility and usability, public health communication, multimodal content development, and the intersection of gender identity and neurodiversity in technology use.Garrett I. Colón is a doctoral candidate in the Rhetoric and Composition program at Purdue University and the assistant director of content development for the Purdue OWL. His research interests include technical and professional communication, user experience design, community engagement, and writing across the curriculum.Adrianna Deptula is a current doctoral student in the Rhetoric and Composition program at Purdue University. Her research interests include science, technology, and medicine (STM); patient advocacy; and new materialism.Shelley Garcia is associate professor of English at Biola University where she teaches courses on race, gender, and culture in American literature, as well as composition and rhetoric. She has published on Chicana feminist authors who write across genre, focusing on the intersections of form, identity, and resistance. Additional research interests that have emerged from her teaching include the role of literary studies in developing intercultural competence, the theme of abjection in Toni Morrison's novels, and representations of the femme fatale in American modernist fiction.Eliza Gellis is a recent graduate of the Rhetoric and Composition doctoral program at Purdue University. Her research interests include comparative rhetorics, public and cultural rhetorics, rhetorical theory, and pop culture.Caroline Hagood is an assistant professor of literature, writing, and publishing and director of Undergraduate Writing at St. Francis College in Brooklyn. Her scholarship has appeared in journals including Resources for American Literary Study, Texas Studies in Literature and Language, Pennsylvania Literary Journal, and Caribbean Literature, Language, and Culture.Emily Rónay Johnston is an assistant teaching professor in writing studies at the University of California, Merced, and a New Directions Fellow through the Andrew W. Mellon Foundation. She holds a PhD in English studies from Illinois State University, an MFA in creative writing from the University of Alaska, Fairbanks, and a BA in women's studies from the University of California, Davis. Prior to academia, she worked in a domestic violence shelter and an addiction recovery center for women. She has published articles on the relationship between writing and adversity, as well as the restorative promises of writing pedagogy in the face of adversity, in College Composition and Communication (2023), Writers: Craft & Context (2022), Rhetoric of Health and Medicine (2020), and elsewhere.Pamela B. June is associate professor of English at Ohio University Eastern, where she teaches women's literature, American literature, literature and social justice, and writing courses. She is the author of two books, Solidarity with the Other Beings on the Planet: Alice Walker, Ecofeminism, and Animals in Literature (2020) and The Fragmented Female Body and Identity: The Postmodern, Feminist, and Multiethnic Writings of Toni Morrison, Theresa Hak Kyung Cha, Phyllis Alesia Perry, Gayl Jones, Emma Pérez, Paula Gunn Allen, and Kathy Acker (2010). In 2021, she earned the Ohio University Outstanding Professor Award in Regional Higher Education.Nate Mickelson is clinical associate professor and director of faculty development in the Expository Writing Program at New York University. He is author of City Poems and American Urban Crisis, 1945 – Present (2018) and editor of Writing as a Way of Staying Human in a Time That Isn't (2018). Nate's scholarly writing has appeared in Criticism; Journal of Modern Literature; Journal of Urban Cultural Studies; Learning Communities Research and Practice; and Journal of College Literacy and Learning.Ryan Michael Murphy is an assistant professor of business communication in the department of business information systems at Central Michigan University. He completed his PhD in rhetoric and composition at Purdue University in 2022. His current research focuses on the transfer of knowledge and skills between academic and nonacademic settings with a special interest in the ways business communication pedagogy can better recognize the experiences and knowledge students bring into the university.Jenni Quilter is executive director of the Expository Writing Program and assistant vice dean of general education in the College of Arts and Sciences at New York University (NYU). She is author of Hatching: Experiments in Motherhood and Technology (2022) and Painters and Poets of the New York School: Neon in Daylight (2014). She's currently writing and publishing about silent cinema, bodybuilding, Zeno's paradoxes, Afro-futurism, North African piracy, Norway, and animal migration. Quilter won NYU's Golden Dozen Teaching Award in 2014.Sahar Romani is a clinical assistant professor in the Expository Writing Program at New York University (NYU), where she teaches in the College of Arts and Sciences. She has published poems and essays in Guernica, Poetry Society of America, Entropy, The Offing, The Margins and elsewhere. She's received fellowships from Poets House, Asian American Writers’ Workshop, and NYU's Creative Writing Program.Megan Shea is a clinical professor and faculty mentor in the Expository Writing Program at New York University, where she teaches in the Tisch School of the Arts. Shea is the author of Tragic Resistance: Feminist Agency in Performance (2025). Her articles have been published in Theatre Journal, Theatre Topics, and the Journal of Dramatic Theory and Criticism. Shea is also an actor, director, and playwright. Her gender-bending play Penelope and Those Dang Suitors was selected as a 2018 winner in Hudson Valley Shakespeare's ten-minute play contest.Christina Van Houten is a clinical associate professor in the Expository Writing Program at New York University, where she teaches in the Tandon School of Engineering. She is completing her first book Home Fronts: Modernism and the Regional Framework of the American Century. Her articles have been published in Comparative Literature Studies, Women's Studies, Politics and Culture, and Workplace: A Journal of Academic Labor.Bethany Williamson is associate professor of English at Biola University, where she teaches courses in British and global literatures, literary theory, and academic writing. Her current interests include ecocritical approaches to the long eighteenth century and articulating the humanities’ value in the age of artificial intelligence. She is the author of Orienting Virtue: Civic Identity and Orientalism in Britain's Global Eighteenth Century (2022), as well as articles in journals such as Eighteenth-Century Fiction, the Journal for Early Modern Cultural Studies, South Atlantic Review, and ABO: Interactive Journal for Women in the Arts, 1640–1830.Elisabeth Windle is senior lecturer of English and women, gender, and sexuality studies at Washington University in St. Louis, where she teaches advanced writing courses and introductory courses in gender and sexuality studies, as well as courses on queer US literature, true crime, and contemporary fiction. She formerly taught in the College Writing Program. Her work has been published in MELUS and Camera Obscura.Mira Zaman is an associate professor of English at Borough of Manhattan Community College, City University of New York. Her research centers on representations of the devil in eighteenth-century British literature, and she is also passionate about teaching composition and rhetoric. Her scholarship has appeared in Persuasions, ANQ, Marvell Studies, and Eighteenth-Century Life.

Mainstream artificial intelligence (AI) is an extractive industry that exploits both humans and nonhumans. The extractive underpinning of mainstream AI systems means that technical communicators must be careful when advocating for accessibility and inclusivity in AI because those efforts may expose marginalized groups to further exploitation. Extractive AI also necessitates that technical communicators reconsider how their own discipline may be complicit in the damaging logics and practices of extraction.

Generative artificial intelligence (GenAI) has brought into question how much ownership college students feel for “their” writing when it is AI-generated. This study recruited 88 college writers at one midwestern state university in the United States. In a within-subjects design, participants composed poems about a meaningful, challenging life experience, then prompted GenAI to compose a poem about that same event. Results showed significantly greater ownership for human-made poems; additionally, human-made poems were rated as more accurately reflective of selected lived experiences. Aesthetic merit, however, was rated higher for AI-generated poems for imagery, language, and form—but not for originality. Half the students preferred GenAI poems, mainly because of their textual features, while less than half preferred human poems, mainly for personal connections to the events presented. Implications for GenAI as a tool to support creative writing and meaningful literacy are explored.

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.

The integration of generative artificial intelligence (AI) into academic writing has raised questions about the syntactic complexity of AI-generated texts compared to human-authored essays. While studies have explored syntactic complexity in human writing, limited research has compared AI-generated argumentative and narrative texts, particularly in isolating cognitive overload and proficiency factors. This study addressed this gap by examining genre-specific syntactic patterns in AI-generated essays. Using the L2 Syntactic Complexity Analyzer, the study analyzed four hundred AI-generated essays (two hundred argumentative and two hundred narrative) and employed paired T-tests and Pearson correlation coefficients to identify differences and relationships among syntactic measures. Results showed that argumentative essays demonstrated higher syntactic complexity than narrative essays, especially in production unit length, coordination, and phrasal sophistication, while subordination measures remained similar. Correlation analysis revealed that argumentative essays compartmentalized ideas through coordinated and nominally complex structures, while narrative essays integrated descriptive richness through longer sentences and embedded clauses. The findings suggest that genre-specific rhetorical demands shape syntactic complexity in AI-generated writing. Implications for teaching and learning writing and future studies are discussed.

In response to disruptions introduced to the job market by AI resume screeners, this article introduces a novel theoretical framework for the life cycle of artificial intelligence systems to help unblackbox resume screening AI systems. It then applies the AI life cycle framework to a digital case study of RChilli’s job-resume matching algorithm. The article introduces an eleven-step computational job-resume matching assignment that writing instructors can use in their classrooms to explore the pedagogical implications offered by the AI life cycle framework. The assignment helps students simulate important phases in AI production and development while highlighting biases and ethical concerns in AI screening of resumes. By exploring job-resume analytics, this study helps to teach critical AI and data literacy, make job-resume matching algorithms more explainable, and transform how professional writing can be taught in the age of automated hiring.

From an unsettled, ambivalent middle between discourses of generative AI integration and refusal, we offer a critical-ethical stance for AI-engaged writing assignments. We apply a critical thinking framework to these assignments, assert critical AI literacy as a kind of critical thinking, and discuss how critical thinking and critical AI literacy can facilitate ethical discernment about generative AI use. This unsettled, critical-ethical stance positions scholars in our field to support context-sensitive pedagogical responses to generative AI across first-year writing, Writing Across the Curriculum, writing centers, and beyond.

In a relatively short time, market and political forces have intensified the reach of artificial intelligence (AI). AI has become, in a word, climatic—not only a discrete technological system but also a creeping assemblage of ideological, material, and political forces. This article tracks these forces by developing rhetorical climates of AI as a conceptual framework. In doing so, I aim to (1) link the harms of climate change with the rapid buildout of AI infrastructure and (2) shift the frame of the conversation by emphasizing the extractive, exploitative, enclosed, and knotted supremacist conditions that have been prerequisites for building AI systems at scale. While these pervading rhetorical climates may seem unchangeable, I track how microclimates of resistance have developed, in the past and in the present. In particular, I emphasize the importance of bodily intelligence in navigating asymmetrical conditions of power felt in the AI industry. The article concludes by discussing how rhetoric and writing studies can weather the unfolding rhetorical climates of AI by diagnosing conditions, seizing moments, and plotting futures to imagine a less extractive and less harmful world.

In gaming, cheat codes change how players engage a system by inviting exploration and reducing the fear of failure. Drawing on writing center pedagogy, this article proposes a similar framework for navigating generative AI in writing instruction and positions play as a method for developing critical AI literacy. Writing centers have long served as spaces where students engage collaboratively with new technologies and construct meaning through dialogue. This article extends that tradition by positioning writing center pedagogy as a framework for helping students examine AI’s ethical implications through treating it as a rhetorical situation to be unpacked, which demands principled, human-centered engagement rooted in values such as collaborative exploration. By weaving together writing center praxis and game-informed pedagogy, this article contributes to ongoing conversations in writing studies about how to integrate AI in ways that support critical thinking and ethical reflection. It demonstrates how playful, classroom-tested activities can animate discussions of bias and representation while helping students build rhetorical discernment through experience. Ultimately, the article argues that ethical literacy must be practiced through relational, iterative work. As writing classrooms become one of the few remaining spaces where students encounter generative AI with support and critical context, writing instructors have a vital opportunity to help students learn to write with, against, and around powerful technologies.

Over the past year, Antonio Byrd, Ira Allen, Sherry Rankins-Robertson, and John Gallagher developed researched recommendations for a Generative AI policy for CCC . From these recommendations, the CCC editorial team wrote an official policy, which is available on our website at https://cccc.ncte.org/cccc/ccc-generative-ai-policy/ . We, the editorial team, are grateful for the thoughtful, generous work of these scholars on this project, which is the foundation of the following symposium.

I argue that composition studies must build critical awareness about how humans from the Global South train AI with their writing embodiments. To draw our attention to how those working in the Global South train AI in harmful conditions, even though AI companies use algorithms and terms of service to smooth away these embodiments, I adapt the concept of humans-in-the-loop. Critical awareness of humans-in-the-loop moves scholarship in writing studies from a focus on AI-human collaboration that begins after an AI produces a text to one that requires us to see how AI products are always already human authored. Through a case study of Google Translate, I demonstrate how a critical awareness of how AI can erase the writing embodiment of humans-in-the-loop affords me opportunities to ask generative questions: How does language translation play a role in the erasure of embodied writing? Why does AI produce with bias toward marginalized populations when marginalized populations are those that moderate AI? Overall, I ask compositionists to see AI products as already human authored so that writing studies can consider the invisible labor of humans-in-the-loop as the field moves forward in researching AI.

This Research Brief discusses transformers—the core engine for most artificial intelligence applications. The brief situates transformer technology within the field of rhetoric and composition by surveying recent studies; highlights the innovative aspects of transformers; and, finally, thinks through (Majdik and Graham) the operations of transformers and generative AI through Miller’s theory of topoi, illustrating one way in which rhetoric and composition scholars and teachers can critically engage with generative AI in instruction and research.

Writing centers in Brazil emerge from an internationalization initiative that combines tutoring students on academic assignments and translating Portuguese articles written by faculty and graduate students into English. Thus, they arise from local needs and contexts. Three articles about writing centers in Brazil have been published, and only one mentioned student tutors’ views. This research aims to understand their views on being part of a Brazilian writing center while pursuing their majors and graduate courses. Through narratives, four participants have voiced challenges regarding dealing with texts from a diversity of fields, handling technical terms, and expressed varying degrees of self-confidence when working with a text written by an individual in a scholarly higher position. Regarding growth opportunities, the student tutors mentioned the development of soft skills and teamwork, improvement in performing reading and writing tasks in their undergraduate programs, and opportunities to increase their knowledge in other fields. The discussions presented in this paper contribute to tutors’ training and to other research on student tutors, as well as to the landscape of what writing centers do in the domain of international publishing. In the U.S., writing centers emerged from labs and clinics (Carino, 1995) and were a resource for college writing assistance for undergraduate students from the 1970s on. However, this is not a common scenario in Brazilian high schools or higher education institutions. Universities in Brazil originated in the 1900s, meaning that higher education is a relatively recent phenomenon. The Brazilian educational system was established based on a “banking model of education” (Freire, 1970/2007), a metaphor used to describe students as containers into which educators must deposit knowledge, reinforcing that knowledge came from outside. Students were not encouraged as creators of new ideas and little was done to develop students’ critical thinking and writing skills, bearing resemblance to the observations made by Mora (2022) on her Mexican context. In this regard, writing centers are not a national reality and are not found in high schools or universities, as most of the writing practice is devoted to the essay students need to write to be accepted in the university entrance exam (Cons & Rezende, 2024; Martinez, 2023). Brazilian undergraduate and graduate students struggle to meet the demands of higher education, accomplishing academic tasks such as an undergraduate thesis and writing for publication without the help or the culture of pursuing the assistance of a writing center. Additionally, the pressure to publish internationally is an obstacle that faculty and graduate students must face, especially since high-impact journals publish in English and the Brazilian population is not bilingual. English language schools are profitable businesses in Brazil as compulsory education does not provide proper conditions for learning foreign languages. Thus, to cope with this demand, most graduate departments are applying part of their budgets to pay for translation and editing services (Martinez & Graf, 2016). Prof. Ron Martinez observed this scenario at the Federal University of Paraná (UFPR) and proposed the creation of the first Brazilian writing center – CAPA – Centro de Assessoria de Publicação Acadêmica (Academic Publishing Advisory Center) in 2016 to offer both translation and tutoring services (Martinez, 2023). Through this action, he aimed to apply resources inside the institution and provide academic and professional development to the students and faculty. Following the creation of CAPA, seven other writing centers were established in the state universities of Paraná, Brazil in the second semester of 2021. The writing center at our university is one of them. Since its creation, our center has offered tutoring and translation services, with its staff comprised of a university lecturer as a coordinator and graduate and undergraduate students as tutors and translators. These student tutors use English as a second language and are majoring mainly in English Language and Literature; however, students from other areas are welcome and have been part of the center. The increasing popularity of paid editorial services (Hartwood, 2019; Martinez, 2023) underscores the importance of writing centers offering sophisticated machine learning (ML) editing assistance, ensuring that all individuals may benefit from these services irrespective of financial circumstances. These two realities demonstrate that globalization and internationalization initiatives have influenced the tasks performed by some writing centers. In Brazil, student tutors are mainly involved in translation services from Portuguese to English, editing manuscripts in Portuguese and English, and tutoring undergraduate students in their academic tasks in Portuguese or in English. Performing these responsibilities involves challenges, and as a result, we want to explore the challenges and benefits of working as a tutor. Though inspired by aspects of American models, writing centers in Brazil arise from local needs and contexts that display their distinct histories (Martinez, 2023). They emerge from an internationalization initiative that combines tutoring students on academic assignments and translating Portuguese articles written by faculty and graduate students into English (Cons & Rezende, 2024). There are only three international publications about Brazilian writing centers: Martinez (2023), Cons and Rezende (2024), and Cons et al. (2025). Martinez (2023) explores the emergence and development of writing centers in Brazil, using the author’s experience as the founder of the Academic Publishing Advisory Center (CAPA) at the Federal University of Paraná. Cons and Rezende (2024) conducted their research at CAPA and focused on one particular consultation as a case study. Cons et al. (2025) discuss preliminary tutor impressions about Generative AI and evaluate how formal training on the use of Generative AI has impacted the translation and tutoring practices at CAPA. Even though these three articles present the Brazilian reality, none of them look at student tutors’ perspectives on working at a writing center in Brazil. International publications that focus on tutors (Thompson et al., 2009; Thonus, 2001, for example) have centered their research on the North American context. The current research presents the tutors’ voices on being part of a Brazilian writing center and advances the discussion about how writing centers in Brazil create situated practices with transnational applications (Mora, 2022). To contribute to the landscape of what writing centers do (Jackson & McKinney, 2012), this article addresses the following questions: What are the challenges faced by these student tutors? To what extent do student tutors at one Brazilian writing center perceive their work at the center as beneficial for their individual growth?

This piece explores a recent change in pedagogy for a professional communication program at a U.S. university. The Covid-19 pandemic prompted a reevaluation of the program’s service-learning curricula. Students’ pre-pandemic challenges are described and compared to their exacerbated struggles post-Covid, especially the impact of misinformation and artificial intelligence upon critical thinking skills. Service- learning clients’ struggles too are analyzed. Intersecting service-learning pedagogy with thought from public pedagogy scholarship can address these challenges by enhancing reciprocity in service-learning relationships. A nuanced understanding of reciprocity in service-learning roles can address power dynamics and break free from restrictive academic conventions, fostering a more equitable learning environment. The piece includes an example of how a revised service-learning curriculum in grant writing affected students’ critical thinking skills and enabled client partners to advocate for their organizations’ constituents.

This study assesses the potential use of artificial intelligence-programmed managers in the workplace through two experiments that manipulated source cues and time cues. Data were collected before the Novel Coronavirus pandemic and then 3 years after the pandemic’s outbreak when many businesses had returned to normal operations and ChatGPT had been released. Results held across the two experiments. Neither time nor source automation cues had an impact on the affective impressions participants formed of the simulated email exchange. Attention check data further suggests time cues may no longer be a relevant predictor of impression formation in workplace communication.

The emergence of artificial intelligence (AI) technologies is significantly impacting public relations (PR) practices, especially in the area of organization-public dialogues. This study explores how Kenyan PR practitioners perceive AI’s influence on their ability to achieve mutuality and openness, which are core principles of effective communication. Through in-depth interviews, the findings reveal that AI is regarded as a valuable tool for transforming dialogues across both online and offline channels, indicating a paradigm shift in how practitioners facilitate communication. However, concerns surrounding AI-generated content, data security transparency, and the responsible application of AI technology also arose, potentially affecting trust between organizations and their publics. The implications of these findings are discussed.

ChatGPT has created considerable anxiety among teachers concerned that students might turn to large language models (LLMs) to write their assignments. Many of these models are able to create grammatically accurate and coherent texts, thus potentially enabling cheating and undermining literacy and critical thinking skills. This study seeks to explore the extent LLMs can mimic human-produced texts by comparing essays by ChatGPT and student writers. By analyzing 145 essays from each group, we focus on the way writers relate to their readers with respect to the positions they advance in their texts by examining the frequency and types of engagement markers. The findings reveal that student essays are significantly richer in the quantity and variety of engagement features, producing a more interactive and persuasive discourse. The ChatGPT-generated essays exhibited fewer engagement markers, particularly questions and personal asides, indicating its limitations in building interactional arguments. We attribute the patterns in ChatGPT’s output to the language data used to train the model and its underlying statistical algorithms. The study suggests a number of pedagogical implications for incorporating ChatGPT in writing instruction.

The research combines explanatory and predictive modeling to examine the impact of annual report tone in predicting publicly traded companies’ profitability in Vietnam, an emerging Southeast Asian market. SGMM regression shows that this year’s narrative tone affects next year’s profitability. The study also used Scikit-learn Python machine learning algorithms to forecast profitability. The tone-based forecasting model that incorporates the company’s general and financial features predicts profitability is the most effective model. This study provides stakeholders such as investors and creditors with an approach to predict future profitability based on the narrative tone and expands theoretical understanding of its predictive power. JEL codes: D21, G33, M40, M41

Generative AI has the potential to transform writing in schools and universities. This makes it necessary to develop training programmes for writing with AI, especially for students in teacher training. So far, however, little is known about the students' initial preconditions on which the trainings can be based upon. Evidence so far has come mainly from observational studies and questionnaire studies examining the frequency and type of AI use. However, the students themselves were not considered, nor the extent to which they can be categorised into groups. In other words, the focus has been on the writing rather than on the writers. To address this gap, the present article analyses data from a survey of N=505 students. To identify writer profiles, i.e. groups of students with comparable characteristics, we apply two-step cluster analysis. The students are clustered based on their use of AI for writing, as well as their level of awareness of AI applications, AI literacy, digital media literacy and writing-related self-concept. The results reveal four clusters, the two largest of which are characterised by the fact that students tend not to use AI, sometimes because they apparently have no awareness of AI, sometimes despite having such awareness. Merely one cluster, which describes 20% of the students, is characterised by regular use of AI for writing. The results therefore provide a useful insight for planning training in the context of university teaching.

Artificial intelligence-based Language Tools (AILTs) are being increasingly used in essay writing in higher education. Its application promotes global and multicultural perspectives in education and plays a critical role in advancing scholarly communication and research dissemination. However, these benefits cannot be measured without also considering student perspectives. This study analyzes the positive and negative aspects identified by students regarding the use of AILTs in their written texts at university. A total of 314 undergraduate and graduate education students were surveyed, and results were analyzed using the Reinert method. The results show that positive aspects are linked to the three pillars of text construction (planning, textualization, and revision). The negative aspects highlight concerns about academic integrity and student competencies. These findings can help guide teachers on how they can promote the responsible and beneficial use of AILTs.

As businesses begin utilizing generative AI to assist with written communications, professionals will need to have the skills to get the results employers demand. A working strategy to assist students on how to best collaborate with generative AI to create traditional business writing pieces is essential as we move to this new integrated workplace.

This case study investigates how two ESL graduate students, Ian and Sam, use ChatGPT in their research writing after receiving a comprehensive tutorial based on Warschauer et al.’s (2023) AI literacy framework. We analyzed their engagement with ChatGPT across prompt categories including genre, content, language use, documentation, coherence, and clarity. Data were collected from research paper drafts, ChatGPT chat histories, and interviews. Data analyses included coding ChatGPT prompts, textual analysis of drafts, and thematic analysis of interview transcripts . Results show that while both participants utilized ChatGPT for understanding genre conventions and content development, they developed distinct approaches reflecting their individual backgrounds. Ian selectively used ChatGPT for specific assistance needs, while Sam engaged more systematically, particularly for APA style and coherence checks. Both approaches maintained academic integrity and scholarly voice, demonstrating that Generative AI tools can be effectively tailored to individual needs without compromising ethical standards. This study highlights how advanced ESL writers can adapt GenAI tools to their unique writing processes, offering insights into the diverse ways AI can enhance academic writing while preserving individual agency. The findings suggest that AI integration in academic writing can be customized to support diverse writing goals and backgrounds.

This article presents “The Cure for Talking,” a pioneering conceptual framework that blends Transactional Analysis (TA) with Artificial Intelligence (AI), to produce a TA-AI Bot designed to optimize executive communication. Here, the medium of interest is written emails. The TA-AI Bot aims to change behavior through the reinforcement mechanism of repetition. The feedback system of the TA-AI Bot is designed to enhance users’ self-awareness and communication quality, that is, identification and shifting of ego states to approximate better communication; and recognition of rhetorical appeals that typify their exchanges with others. Validation of “The Cure for Talking” will require iterative research.

Emerging consensus suggests faculty should teach students to use large language models (LLMs) rather than ban them, but it is not clear that students need detailed AI-related instruction. To investigate, we conducted two studies: Study 1 used survey and focus group methods to assess how such instruction influenced students’ perceptions, while Study 2 used rater evaluation to examine how AI use affected message quality. Study 1 found no meaningful impact on perceptions. Study 2 found that instruction did not affect ratings, but genAI use did—messages composed with LLM assistance received higher evaluations than those without it. We conclude with recommendations for genAI-focused classroom instruction.

Teachers, students, and professionals widely use ChatGPT for business communication. Recent studies have explored predictors driving its adoption, predominantly from a general education perspective. To address this gap, this study examines predictors and barriers encountered by English for Specific Purposes (ESP) learners in India, a developing market with a significant number of ChatGPT users enrolled in business communication (BC) courses. A model based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) was proposed, incorporating seven predictors to assess their influence on the intention to use ChatGPT. Structural equation modeling (SEM) was performed on 526 students’ responses from two reputed Indian private universities, yielding a good model fit (minimum discrepancy by degree of freedom = 2.95, goodness of fit index [GFI] = 0.945, root mean square error of approximation [RMSEA] = 0.043). Further, the results identified five significant predictors: perceived usefulness (β = 0.234, p < 0.001), academic integrity (β = 0.291, p = 0.003), perceived ease of participation (β = 0.174, p = 0.013), privacy concerns (β = 0.224, p = 0.004), and perceived ease of participation’s effect on perceived usefulness (β = 0.354, p < 0.001). However, peer behavior (β = −0.032, p = 0.769) and security concerns (β = −0.059, p = 0.434) were found to be insignificant predictors. The findings suggest that ChatGPT adoption is shaped by perceived functionality, ethical confidence, ease of use, and privacy assurance, while peer behavior and security concerns play a limited role, likely due to the tool’s early-stage adoption and individualistic usage patterns. This study highlights the importance of addressing barriers through targeted training, transparent policies, and AI literacy initiatives to ensure responsible and effective integration of ChatGPT in academic and professional contexts.