This case study examines how a multilingual graduate student in a U.S. pathway program negotiates epistemic authority across concurrent academic writing and disciplinary courses. Drawing on metadiscourse and positioning theory, it introduces “suspended authority” to explain why professional expertise may be strategically withheld in a transitional institutional space.
This presentation shares findings from a case study that examines how L2 writing teacher (L2WT) expertise is conceptualized and developed at a training practicum for teaching L2 writing at the college level. It discusses the context-dependent nature of L2WT expertise and its implications for L2WT preparation.
This study examines extramural L2 writing practices of third-age (60+) EFL learners in community-based lifelong learning contexts in Istanbul, Türkiye. Using interview data from a purposeful subsample of 30 learners drawn from a larger profiling study (N=535), it explores multilingual genre repertories, modalities, and literacy trajectories, advancing a lifespan and socially situated perspective on L2 learning and L2 writing.
The study examined whether online resources differentially advantaged 60 intermediate L2 learners’ writing processes or products by motivation or anxiety. While motivation and anxiety influenced pausing behaviors, they did not moderate the effect of resource use on writing quality, suggesting resources do not introduce bias based on these learner profiles.
This presentation examines the impact of Generative AI (GenAI) on the Journal of Second Language Writing based on the observations and experiences of an outgoing editor-in-chief (EIC). The outgoing EIC will discuss influences of GenAI on this journal, including both the benefits and challenges in managing the publication process.
This presentation examines a multimodal, project-based “Manga” creation task to support Japanese EFL novices’ source-based writing. It shows students paraphrased, summarized, and transformed academic texts into colloquial dialogue while experiencing challenges in maintaining rhetorical consistency. Results indicate the potential of this approach to develop discourse synthesis skills in L2 writing.
This paper reconceptualizes AI in second language writing beyond surveillance and punishment. It argues that AI shapes L2 learners’ authorship, agency, and identity, and proposes a reflective AI literacy framework that positions AI as a collaborative pedagogical tool and calls for aligned pedagogical and assessment practices in L2 writing.
This autoethnography explores the conflict between Generative Ais’ standardized feedback and an L2 writer’s intentional stylistic rhetorical design. By analyzing negotiation logs, I illustrate how AIs prioritize pseudo-authoritative, opaque norms over strategic style choices. The findings suggest that AI-driven corrections risk colonizing the writer’s voice and stripping away authorial ownership.
This paper presentation argues that Cicero’s Five Canons equip L2 teachers to assess what AI cannot: rhetorical nuance. Drawing on over 1,400 peer feedback instances from 700+ students, we demonstrate how classical rhetoric validates teacher expertise and provides practical strategies for maintaining pedagogical authority in an increasingly automated world.
The present study investigated 104 English language learners’ longitudinal development of syntactic complexity over five CEFR levels. They first improved their use of subordination clauses but eventually improved their use of complex nominals. Some learners exhibited unpredictable developmental trajectories, which were closely examined by qualitatively examining their language use.
This study examines how a writing teacher’s feedback role evolves when AI tools are integrated into the revision process in a Technical Writing classroom, with the aim of finding out areas where human guidance remains essential.
This study examines how pre-service teachers in South Korea used generative AI while writing English lesson plans. Drawing on a cognitive writing model, it analyzes AI use across stages and perceptions of its usefulness. Finding show reliance on AI for translation and idea generation, highlighting implications for ESP writing instruction and AI literacy.
This study examines teacher–student rubric co-construction as metacognitive instruction in ESL academic writing. Using mixed-methods data from two first-year ESL classes, findings show that collaborative rubric development supports L2 students’ metacognitive knowledge and regulation, enhances reflection on writing expectations, and highlights the role of assessment literacy in formative assessment practices.
This mixed-methods study examines a 14-week Padlet blogging program for 90 Taiwanese high schoolers. Integrating AI-scaffolded conversation and multimodal journals, the intervention significantly boosted writing self-efficacy and reduced anxiety across proficiency levels. Findings position blogging as an "affective equalizer" while fostering authentic human voices and touch in the AI era.
This longitudinal study seeks to extend writing teacher feedback literacy (WTFL) and provide developmental patterns for EFL teachers in AI-mediated classrooms. Adopting a human-centered approach, the researcher attempts to challenge current skepticism about EFL writing teachers’ roles and redefine our positionality in the age of GenAI.
EFL essay quality correlated with meaning complexity (argument depth, nominal groups), not clausal form. Challenging traditional views, this highlights meaning complexity’s critical role in L2 writing development and assessment.
This study examines sentence structure in multilingual writing among Polish L1, English L2, and Swedish L3 university students. Findings reveal that sentence patterns result from interactions of language-specific norms, cross-linguistic transfer, individual writing style, and proficiency. Higher L3 proficiency promotes target-language conformity, while personal stylistic traits persist across languages.
This study examined how annotation training affected Taiwanese undergrad students’ annotation quality and their perceptions toward such training. In English Composition II, students completed two self-annotated assignments for reviewer (instructor and peer) feedback. Preliminary findings showed that student held overall positive attitudes toward annotation training. Annotation quality improvement, however, varied individually.
This paper argues that AI-mediated L2 writing creates an “uncanny” tension between fluency and authorship, challenging traditional notions of competence. Drawing on poststructuralist theory, it reframes writing as a distributed process and calls for pedagogical shifts toward process, interpretation, and uncertainty rather than correctness and individual authorship
This study examines how narrative ownership is negotiated in an EFL picture book writing project integrating hand-drawn, digital, and AI-generated illustrations. Grounded in task-based writing pedagogy, it explores how students navigate authorship, creative agency, and technological mediation, highlighting the teacher’s role in preserving human storytelling in AI-augmented writing environments.
This mixed-methods study explores how integrating critical AI literacy into process-based EAP writing influences student engagement, rhetorical quality, and strategy recall. Findings indicate that structured AI use enhances revision practices, argumentation, and metacognitive awareness, positioning learners as reflective collaborators and informing AI-integrated writing pedagogy in second language contexts.
This paper presents the application of the AcOnHE e-tivity framework to an online L2 academic writing course at a Ukrainian university. Through qualitative case study analysis, it maps the course design onto Salmon’s five-stage model, identifying implications for writing teachers and course designers working in online and disrupted learning environments.
This study examines Japanese EFL students’ causal reasoning in argumentative writing by analyzing because-clauses and connective use across two prompts. Results show strong reliance on generalization and because, with rare use of inferential markers like therefore, indicating difficulty constructing advanced argumentative relations and sensitivity to prompt effects.
This systematic review brings together empirical findings on cohesion, showing the relationships between cohesion features, L2 proficiency, and contextual factors. It also warns that growing reliance on automated analytical tools risks reductionism, potentially oversimplifying complex cohesion phenomena in written texts.
This proposal explores L2 writing teachers’ identity dilemma and humanistic reconstruction in the AI era. It adopts a mixed-methods design, analyzes internal/external causes of role conflicts, and aims to propose a human-centered framework to balance AI application and humanistic teaching for teachers’ professional development.
This session examines how AI shapes linguistic diversity, access, and standards in writing. Drawing on literacy and L2 writing scholarship, it explores human dimensions of language, identity, and pedagogy, highlighting AI’s impact on reinforcing dominant linguistic norms.
This paper explores how editorial mentorship can humanize scholarly publishing for multilingual scholars in the age of AI. Drawing on the co-editing of a Writing Center Journal special issue, our presentation examines how transparent editorial infrastructures, mentorship-oriented review practices, and collaborative feedback can expand equitable participation in academic knowledge-making.
This study examines affective and interactional dynamics during young learners’ L2 writing assessment. Using multimodal interaction analysis from test administrations with 57 children aged 5–6, we show how student interruptions and test administrator responses shape agency and engagement. Results demonstrate writing assessment as a relational and interactionally mediated process.
Engaging the concept of emotion labor (Benesch & Prior, 2023; Miller & Gknonou, 2023) we examine how university-based EAP writing instructors negotiate ‘feeling rules’, that is, external expectations that can shape internal emotions in highly regulated institutional contexts, drawing insights from data generated at three Canadian post-secondary institutions.
This study examines how AI integration influences IELTS writing teachers’ professional identity negotiation. Using collaborative reflection panels and narrative frames, findings suggest that AI reshapes teachers’ identities by expanding their role as critical mediators, reaffirming human values, transforming anxiety as a catalyst for professional growth, and reinforcing authoritative human expertise.
To illuminate the correlation between self-reported AI usage and writing self-efficacy in L2 writers, research findings will be presented from a two-year study conducted at the UNC Charlotte Writing Resources Center. Additionally, a methodology will be presented for other writing centers to implement collection of similar data at their institution.
This paper presentation situates generative AI in a conversational pedagogy for the L2 composition classroom in a way that de-emphasizes the mere linguistic production of the written text, but which preserves the dialogic practices of writing between writer, community, and discourse to encourage writerly development.
Mixed-methods study examines how screen immersion and AI use shape Gen Z L2 learners’ reading–writing behaviors and self-regulation, proposing an adaptive pedagogy to support their reading–writing development, motivational regulation, and agency in digitally saturated learning environments.
This presentation examines how AI-mediated feedback influences syntactic complexity development in L2 writing and what these effects reveal about the continuing role of writing teachers. Findings suggest AI supports micro-level elaboration, while teachers remain essential for guiding higher-order syntactic development, pedagogical judgment, and meaningful instructional design.
This presentation examines the use of myProse, an AI-supported analytic writing environment, in two first-year writing courses at a multilingual U.S. branch campus. Analysis of student reflections shows that analytic AI can support diagnostic awareness, authorial control, and critical AI literacy when instructor-mediated and embedded within process-oriented writing pedagogy.
This study explores Japanese first-year university students’ perspectives on ethical AI use in L2 writing, emphasizing the key qualities of the teacher-student relationship. Through a ChatGPT-4 classroom activity, findings highlight transparency, critical engagement with AI feedback, and collaboration, which reinforce teachers’ roles as real human beings in writing education.
This presentation introduces a Quantum Dialogic framework for L2 writing that centers human agency in AI-mediated classrooms. Drawing on agential realism, it shows how dialogic peer review, narrative grounding, and reflective metacognition help teachers guide ethical decision-making, preserve student voice, and sustain meaningful human interaction in the age of AI.
This study explores how multilingual TESOL graduate students negotiate authorial voice in AI-assisted academic writing. Using Kong and Zhang’s (2021) cognitive, affective, and sociocultural AI literacy framework, it examines strategies, emotions, and contextual influences, highlighting how writers critically engage with AI while preserving voice and identity, offering pedagogical insights.
This qualitative study of 52 international graduate students examines how multilingual writers negotiate voice through AI collaboration. Drawing on Bakhtin’s dialogism and the APSE model (Wang & Wang, 2025), findings reveal a monologic-to-dialogic continuum shaped by positionality. Authenticity emerges not despite AI engagement, but through intentional, agentive negotiation with it.
This study examines how pre-service EFL teachers learn to compose in AI-mediated multimodal environments within a technology-enhanced language teaching course. Using social semiotic and New Literacies perspectives, it analyzes students’ artifacts and reflections to explore shifts in authorship, design practices, and pedagogical understanding, highlighting implications for preparing future writing teachers in the age of AI.
Examining GPT-4o as an EFL writing tutor in Japan, this longitudinal study finds that while student writing showed gains in lexical and syntactic complexity, it increasingly resembled the tone of AI-generated text. This suggests a potential trade-off between complexity gains and the loss of a student’s unique authorial voice.
This document-based historical analysis explores how writing instruction and activities have been articulated in Japan’s national curriculum guidelines for English education, and reconsiders the writing abilities required in the age of generative artificial intelligence (GenAI). Presenters highlight the importance of a process-genre approach to writing instruction that incorporates GenAI technology.
