This forum brings together three presenters exploring the intersection of language learning and technology, each offering unique insights into how digital tools can support learner engagement, autonomy, and innovation. Nicolas Vassilenko investigates how game-based environments leveraging fictional languages can simulate immersive acquisition experiences. Asad Delawalla presents findings from a qualitative study on students' perspectives and ethical concerns surrounding AI in second language writing. Sarah Deutchman shares initiatives and research focused on data-driven learning, learner autonomy, and AI applications in education. Together, these talks offer a thought-provoking look at how technology continues to reshape language education.

Effective use of spreadsheets in CALL classrooms can not only assist with basic classroom management tasks but also support the creation of interactive, dynamic lessons tailored to language learning. This workshop demonstrates practical applications for spreadsheet programming in instructional contexts. While it highlights Mac Numbers, due to its unique layout and native integration with Pages and Keynote for seamless content creation across Apple platforms, the workshop emphasizes transferable skills relevant to cross-platform tools such as Google Sheets and Microsoft Excel. Given the widespread market penetration of the Apple iPhone in Japan, educators can also distribute Numbers-based files compatible with most student devices. Attendees will explore how Numbers Formula Language, in conjunction with AppleScript and JavaScript, can be used to automate grading, design language-focused games, manage classrooms, and enhance learner engagement. Although Mac Numbers is the primary tool demonstrated, the workshop's pedagogical strategies are adaptable to other spreadsheet environments, making it relevant to all educators interested in integrating programmable spreadsheets into CALL. All attendees are encouraged to bring smartphones (any OS welcome), as the session includes interactive, QR code-based activities.

As automated writing assessment tools gain popularity in supporting independent learning, understanding their role in L2 writing development is essential. This study examines how Automated Essay Scoring (AES), specifically Write & Improve (W&I), supports students’ writing practice and influences their performance and perceptions in a Japanese university EFL course.

Twenty-one students (B1 CEFR) completed nine writing tasks using W&I. A mixed-methods approach analyzed (1) relationships between task scores and final writing performance, (2) score differences between higher- and lower-level essay groups, and (3) patterns in students’ self-reflection comments. A Spearman’s rank-order correlation analysis showed no significant relationship between regular practice and final writing performance in either group. However, a Mann-Whitney U test revealed significant differences in narrative writing scores (p < .05), suggesting that essay genre had a more substantial impact on student performance than gradual writing development. Additionally, self-reflection data indicated that while many students found AI feedback helpful for identifying mechanical errors such as spelling, lower-level students grew frustrated when their scores did not improve despite repeated revisions.

This presentation will discuss how AES tools can support L2 writing instruction, highlighting both their potential and the challenges of integrating more advanced AI feedback into writing practice.

More and more research surfaces around the use of AI for writing assignments in an EFL classroom. For those who accept the benefits and decide to adopt the practice, the question often remains as to how exactly to implement the practice in the classroom.

This action research looks at the use of AI tools in two modalities in a writing classroom. One modality – using AI before writing activities, with students evaluating and adding onto the basic structure provided by AI. Another – using AI post writing, to supplement and review original human work. The debate around originality of thought and quality of work continues to surge when AI support is involved, and this research will provide insights regarding how each manner of AI use affects the final product.

The research involves 60 first year students at a Japanese university with varied levels of English proficiency. The results of the study are based on three writing samples of the students written on different topics: without AI, with AI used first, and with AI used post writing. The writing samples are evaluated on linguistic features, structure and organization, originality, and learning impact. The results will clarify the effect of AI on student’s work.

This study examines the educational impact of AI translation on English writing and explores effective instructional approaches for its integration. While AI-powered translation tools offer learners immediate access to appropriate English expressions, uncritical reliance on them does not necessarily improve writing proficiency. Despite growing interest in AI translation for foreign language education, research on its pedagogical impact remains limited. This study involved four Japanese university students who completed writing tasks using DeepL over approximately two months during the semester. Learning outcomes were assessed through pre- and post-writing tasks analyzed with ChatGPT, supplemented by semi-structured interviews that provided qualitative insights into learners’ perceptions and revision strategies. Findings suggest that AI translation, when used appropriately, can enhance lexical precision, syntactic diversity, and content coherence. However, challenges in grammatical accuracy, lexical accuracy, and fluency persist. The results indicate that AI translation can be an effective tool for improving writing quality, provided learners receive proper guidance and ongoing feedback. Guiding learners to critically engage with AI-assisted writing can maximize its educational benefits.

The age of AI is finally with us, and brings with it far-reaching implications for language teachers and learners around the world. But how do we utilize the affordances of Large Language Models (LLMs) and other AI-powered technologies for the best English language learning outcomes? While the technology may have changed, the pedagogy in many respects remains the same. Students still need lots of exposure to comprehensible input, and they still need to produce a lot of meaningful output. It’s still a challenge for some students to find the opportunity to use the language productively, and it’s still a challenge for many teachers to give extensive personalized feedback to every individual in large speaking and writing classes. In the context of English language learning in Japan, many students still fall way below the recommended 2500+ hours of engagement with English by the time they graduate from college. Eigo.AI aims to assist and enhance this human-centric English language teaching and learning process. It offers a library of lessons on a wide range of topics, from historical events and figures to important scientific discoveries and much more. It combines OpenAI's cutting-edge LLMs with human proof-reading to provide engaging materials in beginner, intermediate, and advanced levels. Students receive AI-powered feedback on their speaking and writing skills, and all their progress and engagement can be easily tracked and monitored by teachers. Eigo.AI provides students with that all-important extra exposure to English and helps solve some age-old pedagogical problems with the latest advances in AI.

As AI tools like ChatGPT become increasingly integrated into language learning education, this study investigates how these tools affect first-year ESL learners’ writing skills over two semesters. One group used ChatGPT for brainstorming, organization, and grammar checks, while a control group relied on teacher-led workshops, peer-review sessions, and textbook-based grammar practice. Data from pre- and post-tests, level assessments, and self-efficacy surveys indicate stronger improvements in writing fluency, organization, and confidence among those using ChatGPT, especially across different proficiency levels. However, findings also highlight potential pitfalls, including over-reliance on AI outputs and confusion around academic integrity despite the introduction of ethical AI use guidelines. This presentation discusses the benefits and challenges of integrating ChatGPT in first-year ESL writing instruction, emphasizing the need for structured guidance so students can effectively enhance their writing skills while developing responsible AI usage habits. Attendees will gain insights for balancing innovative technologies with foundational writing instruction, thereby promoting both language proficiency and ethical accountability.

AI presents new challenges to evaluating writing that must be addressed critically. Language teachers are now encountering AI-produced submissions to an increasing degree. Although there are some benefits to gain with a critical eye and a trained ability to focus on language forms corrected by AI, AI tools have also raised teachers' concerns about academic integrity, particularly AI-facilitated cheating. This presentation will highlight one approach that can foster favorable outcomes for their students' development as language learners. To ensure students remain focused on their own personal growth as language learners, the presenter’s grading scheme for written assignments has evolved to prioritize students' abilities to produce presentation plans in writing. The evaluation of this assignment has also evolved to focus more on the writing process and the students' deliveries of their final presentations. In this way, students can more honestly produce level-appropriate reports that can be presented with confidence. Also, AI-produced presentations that are too difficult for the students to present confidently will be poorly evaluated. Throughout the presentation, discussions will also be opened to the audience to explore how everyone's approaches to evaluating writing have evolved with the development of AI tools.

In the age of generative artificial intelligence (GenAI), graduate-level L2 writers have been reported to encounter its limitation in generating discipline-specific discourse (Ou et al., 2024). Yet, effective pedagogical approaches for discipline-specific L2 writing remain underexplored. Theoretically guided by Genre Theory principles (Tardy et al., 2020) and Critical GenAI Literacy framework (Ou et al., 2024), this study examines the efficacy of integrating traditional genre-based writing pedagogies with collaborative GenAI output evaluation activities to enhance critical GenAI literacy in the context of discipline-specific research paper writing. It was conducted in an advanced academic writing course at a university in Japan with 18 engineering graduate students, focusing on the Introduction section (i.e., background information with literature review, followed by a summary of the study and its significance) due to its rhetorical complexity and susceptibility to GenAI hallucinations. The students first analyzed sample Introductions using Swales’ Create-a-Research-Space model (2004), and then engaged in joint and independent construction of their own Introduction. This was followed by collaborative critical evaluation of their own Introduction’s revisions generated by ChatGPT. The assignment drafts, weekly surveys, and interview results revealed the significance of scaffolded evaluation of GenAI outputs for the development of discipline-specific critical GenAI literacy.

This presentation explores how English-as-a-second-language (ESL) learners in an English-Medium-Instruction (EMI) context in Hong Kong navigate the complexities of developing their academic voice amidst the increasing reliance on Generative AI (GenAI) tools such as Google Translate, Grammarly, and ChatGPT. Multilingual writers have long faced challenges in asserting their voice within academic discourse, then recent advancements in GenAI provide both support and potential conflict. While GenAI tools are increasingly capable of helping students overcome English barriers in their English academic writing, the tools often produce direct and authoritative voices that clash with the struggling voice expected in student writing. Drawing on Canagarajah's (2004) conceptualization of voice development as a negotiation among historical identities, institutional roles, and ideological subjectivities, this study examines the writing process of students in an Academic English course. Through analysis of student drafts, revisions, and interview data, the study sheds light on how learners reconcile AI-generated language with their own voice, offering insights into the evolving dynamics of voice construction in the age of AI-assisted writing.

Reference Canagarajah, S. (2004). Multilingual writers and the struggle for voice in academic discourse. In A. Pavlenko & A. Blackledge (Eds.), Negotiation of identities in multilingual contexts (pp. 266-289). Multilingual Matters.

This workshop explores the potential of AI-powered tools in providing instant, personalized feedback on writing and speaking tasks. Participants will have hands-on experience with tools such as ChatGPT, Gemini, Deep Seek, and Write & Improve for writing, as well as Read Along, TOEFL TestReady, and Speak & Improve for speaking tasks. The session will feature demonstrations, guided activities, and group discussions on how to effectively incorporate these tools into language teaching.

By the end of the workshop, participants will be familiar with AI-powered tools for automated writing and speaking feedback, understand how to use these tools to enhance language learning outcomes, have practical ideas for integrating automated feedback into their teaching practices, and leave with actionable strategies and resources to implement in their classrooms.

This paper examines a pedagogical approach to fostering information literacy among second language learners in academic writing courses at a Japanese university. The study utilizes the Trump Twitter Archive, a searchable database containing all of U.S. President Donald Trump’s posts on X (formerly Twitter), as a tool to explore how social media can not only support academic research but also provide students with a practical framework for developing information literacy by engaging with real-world sources of information. The research addresses three key areas: 1) how students identify and assess the credibility and biases in online sources; 2) how students leverage online information to contextualize their research, explore diverse viewpoints, and organize data to construct coherent, persuasive arguments; and 3) metacognitive insights into how students apply these skills to future writing tasks. The findings suggest that analyzing social media sources, such as tweets, enhances students’ understanding of rhetoric, sharpens their ability to critically evaluate source credibility, and strengthens their skills in identifying bias and rhetorical intent. Student reflections reveal significant gains in their capacity to recognize biases and integrate online sources into academic writing, ultimately improving their ability to produce nuanced, evidence-based arguments.

Second language (L2) instructors face a challenge when incorporating AI tools into their writing lessons concerning the preservation of the writer’s voice. This presentation briefly explains the meaning and development of voice before covering two contrasting scenarios that potentially play out in L2 writing classrooms. In the first, L2 writers may become over reliant on AI-generated assistance, leading to a dilution of their personal style and expression. In this instance, algorithms and templates provided by AI may homogenize writing, with authentic language being replaced by standardized, computationally optimized phrases, resulting in a loss of individuality and originality. In the second, responsible use of AI can support L2 writers by offering assistance without reducing their original style. In this case, with guidance, AI can assist grammar correction and offer stylistic suggestions while allowing writers to retain control over their narratives and individuality as L2 writers. Teachers can play a central role in helping students preserve their authenticity, individuality, and voice by providing guidance on the responsible use of AI tools, along with directed instruction and constructive feedback.

The growing use of Artificial Intelligence (AI) tools such as ChatGPT in academic writing is reshaping how students ideate, organize, and refine their work in higher education. While these tools offer efficiencies and can elevate the quality of writing, they also pose risks to students’ intellectual independence and critical thinking. Overreliance on AI may suppress original thought and reduce students' engagement with the creative and analytical dimensions of writing. To address this, the study presents a literature-based investigation of how AI and human intelligence (HI) intersect in academic writing. It explores AI’s influence on cognitive processes, authorship, and the development of academic arguments. Based on this review, the study proposes a conceptual framework that supports the balanced integration of AI and HI. This framework aims to preserve the integrity of students’ ideas while leveraging AI for support and enhancement. The proposed framework serves as a foundation for instructional design and further empirical research on guiding students to navigate the evolving relationship between AI tools and original academic thought. By proposing a framework for integrating AI and human intelligence, this study offers insights into how both educators and students can navigate the evolving landscape of academic writing with AI tools.

This presentation examines the integration of ChatGPT into an academic writing curriculum within a year-long honors program at a university in Japan’s Kanto region. The program selects students based on their potential contributions to global society rather than English proficiency, resulting in diverse language abilities. The curriculum fosters critical thinking and confidence in English expression through a fluency-first approach, followed by accuracy-focused refinement.

Students engage in structured writing activities centered on three self-selected Sustainable Development Goals (SDGs), producing three distinct academic essays per semester. Each class begins with an SDG-related news article, prompting structured discussion and freewriting. Technology plays a key role in refining student output, with initial language adjustments made using DeepL and later ChatGPT. In formal essay development, students use ChatGPT to generate C1- and C2-level rewrites, accompanied by AI-generated explanations of linguistic modifications. By comparing outputs, students refine their understanding of tone, accuracy, and nuance. This AI-enhanced process encourages self-editing, peer review, and collaborative learning, allowing instructors to adopt a facilitative rather than directive role. The integration of ChatGPT not only strengthens students’ writing and editing skills but also deepens their critical engagement with language and content.