Studies on reformulation in L2 writing vary in how they are defined, operationalized, and reported, making comparisons across studies difficult. This study presents a methodological synthesis of reformulation research in L2 writing. The paper concludes by discussing key considerations in the use of reformulation for educational and research purposes.
This study examines how Chinese, Japanese, and Korean learners use a corpus-informed GenAI (Google Gemini) chatbot to develop informal internet writing in a DDL framework. Analysis of chatlogs, journals, and surveys shows that learners benefited from authentic language exposure but needed further training to use the tool effectively and strategically.
This is a corpus-based study to compare stance features in excellent L2 engineering writing rated by English teachers and a GenAI tool. From the lens of stance features, the findings reveal the limitations of using GenAI to assess second language writing.
This presentation explores the evolving identity of L2 writing teachers in AI-mediated English for Specific Purposes (ESP) contexts. Utilizing an AI-enhanced Multimodalities-Entextualization Cycle (MEC), I demonstrate how teachers transition into "discourse mentors." While AI scaffolds disciplinary genres, teachers maintain essential human agency through critical oversight, ethical responsibility, and relational pedagogy.
This study examines how Chinese scholars promote their research in English research articles by integrating corpus-based analysis and author interviews. It explores promotional practices across textual, socio-cognitive, and socio-cultural dimensions, offering insights into how Chinese scholars negotiate promotional demands in English academic publishing.
This colloquium examines SLW program administration in the time of generative artificial intelligence (GenAI). Addressing policy development, curriculum design, pedagogy, faculty support, and assessment, presenters explore challenges, opportunities, innovations, and principled responses for ethically integrating (or resisting) GenAI in SLW programs across diverse national contexts.
Assistant Teaching Professor, Iowa State University
Angela Hakim is an Assistant Teaching Professor in the Department of English. She teaches courses in Academic English, ISU Foundation Communication, Advanced Communication, and the B.A. in Linguistics, including a course in sociolinguistics. Angela serves as the Director of Academic... Read More →
This study examines how AI-supported peer review reshapes feedback practices and revision processes in first-year EFL writing. Using a mixed-methods classroom intervention, the study explores changes in feedback quality, revision uptake, and learner engagement, highlighting the role of AI in developing feedback literacy and academic writing.
This paper reports on the development of a new rubric used to score two assessments for English learners in K-12 U.S. public schools. During development, researchers sought input from multiple groups, including educators and experienced trained raters, and concluded with an empirical validation study of the new rubric.
Large language models are transforming scholarly writing. In ERPP, debates on generative AI often emphasize compliance and individual responsibility. This presentation reconceptualizes AI ethics as distributed across scholars, institutions, and infrastructures within a global knowledge economy. It examines how AI reshapes academic legitimacy, multilingual scholars’ positioning, and the sociolinguistic ecology of knowledge production.
This study proposes a unified L2 model of rhetorical moves for IMRaD-style papers of novice writers. Previous studies addressed specific sections by expert writers. Our model is based on a Swalesian genre-based analysis of student-authored IMRaD papers, providing an accessible scaffolding for novice writers with teaching implications for EFL contexts.
This classroom-based study examines whether comprehensive written corrective feedback improves accuracy in beginning adolescent EFL writing and whether cognitive and affective reactions predict improvement. Results show short-term gains and suggest that deeper cognitive engagement, especially reconstruction and transfer-oriented processing, is more strongly associated with progress than affective response.
Associate Professor, Miyagi University of Education
Wataru Suzuki is an associate professor at Miyagi University of Education in Sendai, Japan. His research interests include cognitive and sociocultural second language (L2) acquisition, in particular, input, output, interaction, feedback and languaging. He publishes these topics widely... Read More →
This study compares AI-assisted and corpus-based revision in a first-year Japanese university writing course. Using engagement and uptake frameworks, it analyzes revision depth, metacognitive reflection, and longitudinal writing development. The study examines how different feedback modes shape the quality and durability of learner engagement in L2 writing.
This abstract examines tensions in EFL freshmen writing classes as generative AI reshapes ideas of effort, authorship, and integrity. It proposes simple, participatory classroom structures that keep teacher humanity central, support students’ critical engagement with AI, and foster shared agency, dialogue, and ethical decision-making in academic writing.
Senior Instructor II, American University in Cairo
Yasmine Salah El-Din has an MA in TEFL and a Ph. D. in Applied Linguistics. Her research interest include error corrective feedback, sociolinguistics, pragmatics and critical discourse analysis.
Updating Hyon’s (1996) three traditions map, this scoping review synthesizes empirical genre based writing research from 1996 to 2025. Using layered coding of tradition and educational level, this study cross analyses disciplines, teaching designs, and datasets. Findings show tertiary dominance, RGS largely postsecondary, ESP strongly text analytic, and SFL primarily classroom based across K–12 and higher education.
Associate Professor / PhD candidate, Ryukoku Uviversity
Dr Akiko Nagao is a lecturer at the Department of Global Studies at Ryukoku University, Japan. Current research interests include L2 academic writing community, systemic functional linguistics (SFL), genre-based approach (GBA) classroom teaching, and effective writing assessment... Read More →
This qualitative case study examines four L2 writing feedback teacher-researchers, exploring how research shapes their feedback beliefs/practices, noting alignments/misalignments, and highlighting their role as research-practice bridges.
This presentation reports on a first-semester graduate L2 writing course in Japan, using survey and interview data to support a more flexible, student-centered approach that includes AI literacy. It addresses learner needs, anxiety, and agency, evaluates outcomes, and reflects on implications for context-sensitive, AI-supported graduate writing instruction.
This study examines Arabic-speaking learners’ trust in AI versus human corrective feedback in L2 Hebrew writing. Findings reveal a functional–relational divide: while AI offers speed and psychological safety, human teachers provide essential relational scaffolding and semantic nuance, supporting a hybrid, human-centered model of AI-mediated writing instruction.
This study investigates if ChatGPT 5.2 surpasses earlier AI limitations in offering formative feedback on source-based argumentation. Comparing human and AI feedback on 350 student essays, we evaluate the model’s accuracy and formative utility regarding thesis development to explore whether GenAI can provide actionable directions for academic revision.
This classroom-based study examines how intermediate L2 Chinese learners use ChatGPT feedback in writing revision and what this reveals about teachers’ roles in AI-supported writing. Preliminary findings show limited learner engagement, pedagogical limitations in AI feedback, and Chinese-specific constraints, highlighting teachers as essential mediators of AI use and writing development.
This presentation aims to identify issues and challenges of teaching L2 creative writing in the age of AI. Two practitioners will reflect on their teaching practices in Japan and the United States and discuss multilingual students’ perspectives on the use of AI in creative writing tasks.
This design study traces a three-year, iterative implementation of critical GenAI literacy in second language writing programs. Moving from a short unit to an integrated curricular model, the study highlights evolving frameworks, instructor and student tensions, and the complex negotiations required to incorporate GenAI ethically and effectively at program level.
This session presents Peer & AI Review + Reflection (PAIRR), a multi-institutional model integrating peer review and AI-assisted feedback grounded in linguistic justice. Presenters share PAIRR’s tested AI feedback prompts, common rubric, AI literacy curriculum, and strategies for building linguistic justice while honoring multilingual students’ voices across.
DE Faculty Development Coordinator, Glendale College
Julie Gamberg is a full-time faculty member at Glendale College. She teaches English composition and humanities fully online. Julie is interested in all things pedagogy, OER, equity, and collaboration. At GCC, as the Distance Education Faculty Development Coordinator, she instituted... Read More →
Using an exploratory case study, this presentation examines how a bilingual adult engages in AI-mediated creative writing after reading a novel and discussing it with generative AI.
This longitudinal study traces how a research writing course for doctoral students at a Hong Kong university responded to AI over three semesters. Drawing on teaching materials and student reflections, it explores the instructor’s evolving pedagogical practices grounded in academic literacies and genre-based approaches, and students’ experiences of AI-influenced research writing.
Using genre analysis and the three subsystems of appraisal theory, this presentation compares how 20 ESL graduate students and 20 scholars incorporate and evaluate sources across different moves of the CARS model in research article introductions. The findings can help ESL writers develop a stronger authorial voice when writing introductions.
This study reports on low-proficiency L2 writers’ collaborative processing of their teacher’s written corrective feedback. Preliminary results suggested a complex interplay among the cognitive, affective, and social dimensions of these learners’ collaborative engagement and the dynamic nature of their social engagement due to their different knowledge levels about the feedback.
This study compares human and AI-generated reformulations as written feedback in L2 writing. Using corpus-based lexical analyses, it examines text length, lexical coverage, diversity, vocabulary novelty, and multiword unit usage. Results show that Bing reformulations most closely resemble human feedback, while ChatGPT and Claude produce more lexically complex outputs.
Critical AI literacy (CAIL), extending beyond AI literacy, empowers L2 writers to navigate ethical, cultural, and linguistic tensions inherent in human-AI interaction. This qualitative study of 12 Chinese EFL learners using ChatGPT explores CAIL enactment, influenced by proficiency and context, highlighting varied patterns and implications in AI-mediated writing.
This year-long collaborative autoethnography explores how two EFL writing teachers develops adaptive expertise in GenAI-mediated writing. Data analysis shows that expertise emerges through harmonizing epistemological-ethical orientations with the adaptive, situated pedagogical innovation. Its development is shaped by teachers’ open-mindedness toward GenAI, teacher resilience, social interactions, and institutional support.
Dynamic Written Corrective Feedback (DWCF) remains underexplored in foreign language contexts. This quasi-experimental study examines its effects on first-year Japanese university EFL students’ accuracy, fluency, and complexity. Results show significant gains in accuracy and fluency, with increased clausal complexity, suggesting context-specific developmental patterns in foreign language writing instruction.
This study examines a genre-based, technology-integrated pedagogy for supporting scientific writing in EMI secondary classrooms in Hong Kong. The intervention improved students’ genre awareness, writing quality, and confidence. The study highlights the role of teachers as mediators of disciplinary meaning-making in technology-supported writing environments.
This mixed-methods study examines the role of artificial intelligence (AI)-assisted learning in academic writing for Chinese as a Second Language (CSL) students in a Chinese university context. Writing samples from fifty international students were evaluated using established scoring rubrics for Chinese academic writing.
This study examines how graduate EFL students’ AI-mediated autonomy and AI dependence develop across three summary-writing tasks. Using questionnaires, AI interaction logs, and student texts, it explores changes in AI use and identifies trajectories suggesting increasing autonomy, persistent dependence, or mixed patterns.
This study examines how multilingual undergraduate writers enact genre awareness when engaging with AI-generated feedback in a genre-based writing course. Drawing on ecological and sociocultural perspectives, it analyzes uptake decisions and justificatory discourse to show how genre awareness mediates writers’ regulation of AI suggestions in socially situated writing contexts.
This study investigated a six-week prompt-writing instruction to enhance L2 writers’ prompt literacy in a GAI-supported classroom. Using a mixed method approach, results suggested improvement in prompt development, strategic GAI interaction and incorporation, and revision practices, demonstrating the effectiveness of structured pedagogical framework in fostering prompt literacy and improving overall writing quality.
This study examines how university language teachers in Taiwan assess multimodal composing in second language classrooms. Using a qualitative multiple-case approach, it explores teachers’ assessment literacy, evaluative criteria, and decision-making, including responses to AI-mediated composing, with the aim of informing more sustainable multimodal assessment practices.
This presentation examines how a first-year writing program redesigned analytical synthesis and case analysis assignments in response to AI-mediated writing environments. By emphasizing discernment, oral outline defense, and process-based assessment, the redesign shifts evaluation from textual products to students’ reasoning, judgment, and accountability in academic writing.
This study examines how Korean EFL students craft prompts for AI feedback and how teacher guidance shapes evaluative labor in revision. Thematic analysis identified three prompt foci and recurring construction gaps. Findings show that teacher-guided prompt design functions as relational scaffolding in human-centered AI-mediated L2 writing revision.
I’m a university English educator and researcher in South Korea who is fascinated by what happens when language learners, teachers, and AI meet in the classroom. My current work explores AI-mediated L2 writing, prompt literacy, and how learners can move from simply "using AI" to... Read More →
Drawing from fifty years of hand-written bilingual journals and a memoir translated into four languages, Guy Giard argues that life writing is a pedagogical practice preserving human presence in the classroom. While AI generates fluent text, it cannot replicate the lived experience, embodied memory, or ethical weight of personal testimony.
Author of "Love's Healing Journey" CHP, Speaker, Coach, 3 Pillars of HAPPINESS
Guy Giard is a typical Renaissance man. Born in French speaking province of Quebec, Canada, he has lived many years in Europe and travelled on three continents. Completing university degrees in visual arts he unveiled his first public sculpture by the age of twenty, followed by a... Read More →
This panel explores entanglement as an onto-epistemological reorientation for L2/multilingual writing, demonstrated through analyses of diverse material and digital sites, both in the classroom and beyond.
This study examines whether combining corpus consultation with guided ChatGPT interaction enhances learners’ academic collocational competence and use in writing. Conducted with 16 Vietnamese English majors, it employed a pre-,while-, and post-intervention design within an academic writing course at a public university.
This mixed-methods study examines how EFL students in Argumentative Writing classes, where GenAI use is permitted, perceive teacher support across pre-writing, drafting, and revising stages. Surveys (M = 2.75/4) show that teacher scaffolding remains valued, especially during drafting and revision. Interviews will uncover how students balance teacher guidance with ChatGPT.
This qualitative case study examines how poetry writing supports the development of L2 writer voice in a Japanese undergraduate EFL context. Analysis of a student’s poems and interview data shows how expressive writing fostered identity reflection, emotional engagement, and ownership of English, highlighting the human dimensions of L2 writing instruction in the age of AI.
This paper examines how AI prompting practices construct “human-like” writing by invoking roles such as editors, researchers, and tutors. Drawing on the concepts of prompted humanity and repackaged pedagogical labour, the paper explores how these practices reproduce elements of EAP teachers’ pedagogical labour and considers how prompting discourse may inform genre awareness and pedagogy in EAP classrooms.
This presentation examines how an ESL graduate teaching assistant Zahra enacted her agency through the critical use of generative artificial intelligence (GenAI) in teaching freshman composition at a U.S. university. The presentation draws on longitudinal data collected from the first year of Zahra’s graduate study and examines three teaching-related critical incidents in which GenAI use played a significant role in facilitating writing and communication.
This mixed-methods study examines how secondary teachers and multilingual students use generative AI across Hebrew, Arabic, and English in the EFL classroom. It explores translanguaging practices in AI-supported writing and investigates teacher and student perceptions of its benefits and limitations, highlighting how to sustain human-centered pedagogy and support home languages.
I am an Assistant Professor, Head of the Language & Communication Lab, and former Head of the Academic Writing Program and Vice Dean at the Department of Humanities & Arts, Technion. My research focuses on digital and AI-based pedagogies, particularly the integration of AI in STEM... Read More →
This study integrates corpus-based genre analysis into a graduate EAP writing course to enhance students’ disciplinary research writing. Findings show that the approach improved rhetorical awareness, organization, and confidence, offering a practical, discipline-sensitive framework for supporting advanced academic writing and strengthening students’ understanding of disciplinary conventions.
This study found that an MT-integrated writing intervention, incorporating pre-editing, post-editing, and back-translation, significantly improved Japanese university EFL students’ writing quality. After approximately two months, participants scored higher in vocabulary, grammar and syntax, organization and development, and task fulfillment, indicating gains in both local and global dimensions of L2 writing.
This study investigates how L2 writers engage with simultaneous teacher and automated writing evaluation (AWE) feedback on the same draft. Using think-aloud protocols, revision analysis, surveys, and interviews, it examines behavioral, cognitive, and affective engagement, highlighting how learners negotiate trust, authority, and feedback completeness in dual-feedback environments.
Using a lesson study approach, the study explores how two novice EFL teachers developed and applied Technological Pedagogical Content Knowledge (TPACK) through GenAI-mediated writing instruction. The study sheds light on the interplay between GenAI and teachers’ evolving TPACK as they integrate technological, pedagogical, and content knowledge through iterative cycles of planning, enactment, and reflection in writing classrooms.
This case study explores how four first-year EAL students experienced linguistic prejudice toward “GenAI-style” writing. Findings show polished writing was often viewed suspiciously, promoting disclosure management, stylistic re-voicing, and epistemic vigilance. The study advocates inclusive pedagogy that treats GenAI-style as a learnable resource while supporting ethical use, agency, and voice.
This presentation offers an in-depth tour of a new AI-powered teaching application developed in The College called VibeCheck. The presenters will describe the problem that informed the application’s development, demonstrate how the application’s design addressed this problem, provide success stories from the initial rounds of BETA testing, and project how the application’s infrastructure makes future developments possible.
The theme of SSLW 2026 invites us to reconsider what it means to teach writing as artificial intelligence (AI) transforms writing practices. In this talk, I explore the humanity of L2 writing education from two perspectives: learners and teachers. Sustaining this humanity requires recognizing learners as whole persons whose development is shaped by multilingual resources and social contexts, while supporting teachers’ agency and well-being as they navigate AI-related challenges. The first part presents three insights from research on L2 writing development that foreground learner humanity, framed within a non-deficit, socially situated, whole-person view of multilingual learners. Research on machine translation as feedback shows that multilingual resources, including learners’ first languages, function as productive tools rather than deficits. Studies of AI-mediated writing show that learners can appropriate AI as a mediational tool while developing writer agency. Longitudinal research shows that L1 and L2 writing development unfold through interactions between personal goals and social contexts. Together, these studies reconceptualize learners as agentive, socially embedded individuals whose development extends beyond language alone. The second part turns to writing teachers and examines how this reconceptualization of humanity may be taken up in practice. Although applied linguistics research often proposes pedagogical implications, little is known about whether such ideas influence teachers’ thinking or professional flourishing. With this in mind, I report on a pilot intervention study with Japanese university teachers of English L2 writing. Over four months, participants read and reflected on practitioner-oriented articles based on a non-deficit view of learners, attention to social context, and a whole-person perspective, as well as their implications for L2 writing pedagogy, including AI-supported practices. By bringing together learner humanity, teacher humanity, and AI-mediated writing, this talk argues that the future of L2 writing education lies not in resisting technological change but in reframing how teachers and learners enact human agency, expanding multilingual resources, and fostering purposeful communication.
