This poster presentation aims to explain how the transcription-translation platform TurboScribe is used in conjunction with the latest Chat GPT-4o AI model to help students practice for the speaking component of the IELTS test. The participants are first-year undergraduate students in the International Studies Department at a college of liberal arts in Western Japan. One year of study abroad is mandatory for these students, so they need to take the IELTS test to qualify for programs in North America, Europe, Southeast Asia, and Australia. The students’ transcripts have been analyzed to check how they incorporated the advice received from the AI into their speaking practice. The students` perceptions and thoughts about using the AI, as well as the successes and challenges we encountered in our classroom instruction are discussed.

This poster session will detail the design and development of an innovative AI-Powered Virtual Reality Chatbot, specifically created for English-speaking practice. The VR simulation application aims to provide an immersive and interactive platform for EFL learners to enhance their English communication skills without a need for an English speaking human partner. This VR simulation can be applied to any speaking scenario. Here, we created a VR medical environment for the purpose of training for interviewing a patient in English, where the chatbot will play the role of the patient.

The poster covers key aspects of the development process, including the integration of text-to-speech and speech-to-text technology to successfully communicate with the AI (ChatGPT) patient, the creation of the 3D VR environment, the implementation of user-friendly controls, and design decisions based on feedback from experts in medical education. Preliminary user testing results and feedback are shared, highlighting the application's potential to improve medical English proficiency, to address the lack of human speaking practice partners and to reduce language learning anxiety.

Participants will have the opportunity to experience the simulation themselves.

This study explores Taiwanese elementary school teachers' perspectives on integrating ChatGPT into English as a Foreign Language (EFL) teaching. While ChatGPT offers potential benefits, such as enhancing lesson planning, generating teaching materials, and improving language accuracy, its adoption remains limited due to concerns about information reliability, student media literacy, and the challenge of crafting precise prompts. Using the Technology Acceptance Model (TAM) as a framework, this study examines teachers’ perceptions of ChatGPT’s perceived usefulness and ease of use. A mixed-methods approach was employed, gathering data through a survey with 13 in-service elementary school English teachers. Results indicate that teachers generally view ChatGPT as a moderately useful and accessible tool, particularly for reducing workload and enhancing creativity in lesson design. However, limitations such as ChatGPT’s inability to provide personalized feedback and concerns over potential misinformation remain key challenges. Teachers strongly support AI training programs to improve their ability to integrate ChatGPT effectively. This study highlights the importance of equipping teachers with the necessary skills to leverage AI tools while ensuring a balanced approach that prioritizes human interaction and critical thinking in EFL classrooms. Future research should explore broader teacher perspectives and classroom implementation strategies.

Developing intercultural awareness can be challenging for many Japanese students, particularly those who have limited opportunities to study abroad. However, advancements in EdTech now enable educators to create interactive, multimedia-based virtual learning experiences that immerse students in cross-cultural exchange without leaving the classroom. This interactive poster presentation will demonstrate how to design and implement immersive media using ThingLink, a platform that integrates 360° and flat images and videos, text and audio to create interactive learning scenarios. Attendees will gain practical insights into the process of developing virtual tours, as well as strategies for incorporating them into language learning curricula to foster intercultural communication. A joint project launched at the presenter’s university successfully utilized ThingLink to support student-generated virtual tours as a means of bridging cultural gaps. Japanese students engaged in these virtual experiences demonstrated increased confidence in initiating conversations with international students. By virtually exploring cultural landmarks and daily life in other countries, they were able to generate more meaningful discussions and ask more in-depth follow-up questions. This poster will provide examples of ThingLink-based activities and discuss the pedagogical implications of integrating immersive media into language education.

The use of generative AI in language learning tasks offers potential benefits, such as enabling personalized learning and fostering autonomous learning. However, if students are unaware of GenAI’s full potential as a learning tool—treating it as an “answering machine” rather than an interactive assistant—certain task formats may inadvertently encourage AI use for answer retrieval rather than cognitive engagement. This ongoing study addresses this issue by focusing on two key aspects: i) raising students’ awareness of GenAI’s mechanisms, which is crucial for preventing overreliance, and ii) designing tasks that enable students to leverage AI’s learning support while avoiding passive answer retrieval. The study involves preliminary observations of beginning EFL learners, examining how they respond to AI awareness-raising efforts and engage with GenAI-integrated tasks during the early stages of implementation in two different instructional contexts: in-person courses (Fall 2024 and Spring 2025) and an on-demand course (Spring 2025). This preliminary report will present emerging patterns related to shifts in student perceptions of AI, responses to task design adjustments, and unintended effects of AI integration. Findings will inform strategies for designing AI-integrated assignments that support beginning EFL learners across different course formats, promoting personalized learning rather than passive answer-seeking.

Grant writing is a critical academic endeavor across disciplines, yet the grant genre remains less explored due to its restricted accessibility. Existing research has primarily examined grant proposals based on limited datasets, with little focus on their phraseological features. Among these features are lexical frames, or discontinuous multi-word sequences (e.g., to * the impact of), often regarded as “important building blocks in discourse” (Biber & Barbieri, 2007, p. 270). However, no published studies have analyzed how lexical frames function in the rhetorical move-steps of grant proposal abstracts (GPAs). This study addresses this gap by exploring the form-function connection in GPAs across three social science disciplines (i.e., Anthropology, Linguistics, and Sociology) and analyzing variations in the distribution and use of recurrent frames and move-steps. Our dataset consists of 1,500 GPAs from National Science Foundation (NSF) grant recipients in the U.S. All texts were annotated for rhetorical move-steps, using a coding scheme adapted from Cotos (2019) and Lu et al., (2021). A corpus-driven analytic approach was used to extract frequently occurring 5-word frames. The results revealed significant disciplinary differences in both the distribution of rhetorical move-steps and the lexical frames used to realize them. Implications for discipline-specific grant writing pedagogy are discussed.

This practical poster session will demonstrate how to configure Google Colab with a Gemini API to efficiently assess speaking assignments in bulk. Participants will learn how to record student pairwork or presentation tasks, upload them to Google Drive, and use AI to transcribe and evaluate the audio. Sample Gemini AI prompts incorporating speech assessment rubrics will be introduced, covering both text-based criteria (e.g., grammar accuracy and content) and speech-based criteria (e.g., intonation, stress, and rhythm).

This study expands on Lee and Drajati’s (2019) scale of willingness to communicate in a second language (L2 WTC) in digital and non-digital EFL contexts to include virtual exchange (VE) contexts. The original scale comprises eleven items across three factors: L2 WTC inside the classroom, L2 WTC outside the classroom, and L2 WTC in the context of informal digital learning of English. Two items related to VE were added to L2 WTC inside the classroom factor: one for speaking with non-native speakers and another for native speakers of the participant’s L2. Additionally, the items in the third factor were changed to reference social media rather than Facebook. The revised L2 WTC was administered to first-year STEM majors at a small Japanese university (n=195). Cronbach’s alpha demonstrated high internal reliability, and the confirmatory factor analysis confirmed that the additions and changes to items still fit the three-factor model. These results validate the L2 WTC scale in the Japanese context and offer a new tool for researchers examining changes in WTC with VE. Attendees can scan a QR code to access the questions and stay updated with ongoing research.

Collaborative online international learning (COIL) exchanges have become increasingly prevalent in tertiary educational settings. These exchanges aim to promote intercultural understanding and awareness through offering opportunities for students from different countries to engage in authentic collaborative interactions while also practicing communicative language skills. Our poster focuses on the second year of an annual short-term synchronous COIL exchange between university students in Japan and Taiwan. We describe the process of implementing this exchange at our universities, including the student demographics, the activities they engaged in, and the technologies used to facilitate the collaboration. The poster also explores the outcomes of the exchange, examining how students from different cultural and language backgrounds interacted, challenges faced, and benefits gained. Additionally, we discuss the logistical aspects encountered as exchange organizers and provide suggestions for refining and sustaining future exchanges. Finally, we offer a general outline for university educators interested in creating short-term synchronous COIL exchanges incorporating meaningful international and intercultural learning experiences for their students.

This poster presentation explores the integration of artificial intelligence (AI) with instructional design principles, specifically L. Dee Fink’s framework for creating Significant Learning Experiences, in a Content and Language Integrated Learning (CLIL) program. The program is designed for Japanese university non-English majors. By leveraging generative AI in curriculum development, course design, materials creation, and assessment protocols, the program effectively addresses challenges in motivation and language acquisition among students with diverse proficiency levels. Key applications include AI-generated course materials tailored to disciplinary content, dynamic assessment tools that provide immediate and personalized feedback, and streamlined workflows for course planning and evaluation. Preliminary findings from the program’s implementation indicate increased learner engagement, improved comprehension of subject matter, and enhanced language proficiency. The presentation will provide practical insights for educators and researchers interested in harnessing generative AI to create meaningful and impactful CALL interventions, contributing to the broader discourse on CALL for All.

Language learning theories have long shaped the design of interactive CALL systems. For example, many of the earliest platforms provided both multiple choice quizzes around comprehensible input and gap fill tasks promoting output. More recently, the emergence of generative AI has led to debates about whether a CALL system could be a human-like learning partner.

This poster demonstrates how fine-tuning through ChatGPT's API can be carried out to create an AI-based interactive CALL system for real-time feedback on learners’ academic writing. Fine-tuning is carried out based on teacher’s insights into students' academic writing capabilities and writing needs, here demonstrated with ICNALE corpus data. The AI is integrated into a CALL system designed to facilitate in-class discussions on academic writing.

Fine-tuning allows the system to reflect the teacher’s understanding of their students' needs, improving its responsiveness and feedback quality. The goal of this work is to demonstrate how current AI systems can be rewired using teachers' insights to create an environment where AI not only provides feedback but also supports classroom-based discussions on academic writing. This is a useful demonstration towards exploring more specialized, responsive systems.

Interdisciplinary learning is widely acknowledged as a crucial educational strategy, allowing students to integrate knowledge from different domains. Natural Language Processing (NLP), for example, is a highly interdisciplinary field involving computer science and linguistics, often requiring learners to develop computational skills such as programming and data analysis (Joshi, 1991). The growth of generative AI (GenAI) has further catalyzed this integration and expanded the possibilities for humanities students to learn computational skills traditionally considered outside their domain. However, limited research has examined how humanities students use AI tools in interdisciplinary learning and their attitudes toward the approach. Therefore, applying questionnaires, semi-structured interviews, and reflections from 29 undergraduate English majors taking an Introduction to NLP course in a Taiwanese university, this study explores how these students leverage GenAI to support computational competencies acquisition and their attitudes regarding AI-assisted interdisciplinary learning. Preliminary findings suggest that while students found GenAI useful for debugging, they struggled when its responses failed to meet their expectations or task requirements. Despite challenges, they generally view GenAI as an empowering tool that facilitates their computational tasks. By leveraging AI tools to navigate NLP-related tasks, this study highlights the potential for integrating AI into humanities curricula.

We introduce an innovative approach to adaptive language learning using embodied intelligent virtual agents as personalized tutors within an immersive extended reality environment. At the core of our innovation is the use of real-time biosignals, specifically heart rate data collected through wearable devices like the Samsung Watch 7, to personalize educational interactions. By continuously monitoring changes in the learner's emotional and cognitive states, indicated through fluctuations in heart rate, the virtual tutor can adapt its instructional approach. For example, if a Japanese learner's heart rate increases when correcting written errors, indicating possible stress or difficulty, the tutor might slow down speech or simplify language tasks to help the learner remain comfortable and engaged. Currently, our adaptation method primarily uses average heart rate data, but we are also exploring more detailed analyses, such as examining heartbeat intervals over time and detecting patterns in specific heart rhythm frequencies. Additionally, we are investigating how additional biosignals such as electrocardiogram and photoplethysmography can further improve the accuracy of stress prediction. Our comprehensive system integrates digital human tutors powered by ConvAI, advanced language models, XR environments, and efficient data handling. Early results demonstrate significant potential for enhancing language learning through personalized, engaging, and responsive experiences.

This poster presentation explores the use of Gimkit as a gamified vocabulary review tool in ESL and TOEIC preparation courses at a Japanese university. Traditionally, vocabulary instruction in these courses has relied on printed word lists, quizzes, and standardized testing — methods which often result in low engagement and limited retention.

As an exploratory classroom project, this study examines how Gimkit — a gamified quiz-based platform — supports vocabulary review through repetition, self-paced practice, and interactive game elements. While Gimkit is not a game in the traditional sense, its point systems, power-ups, and competitive modes fostered noticeably higher student motivation, engagement, and autonomy compared to previous vocabulary learning approaches used in the same courses.

Students engaged with word lists derived from the New General Service List (NGSL) and TOEIC Service List (TSL), encountering approximately 1,000 words over a 15-week course. Accessing Gimkit via mobile devices allowed for flexible review outside of class. Informal student feedback and classroom observations suggest that Gimkit made vocabulary study more interactive and enjoyable, helping students to reinforce known words, strengthen partial knowledge, and gain exposure to new vocabulary.

This poster will present key classroom insights, implementation strategies, and practical takeaways for educators interested in gamified vocabulary learning.

While Learning Management Systems (LMS) like Google Classroom have become ubiquitous in educational settings, research examining their specific implementation in language teaching contexts remains limited. Although Kassim (2021) found generally positive student attitudes toward Google Classroom, little research has explored how language learners specifically want these platforms to be utilised to enhance their language learning experience. This research addresses this gap by investigating university students' experiences and preferences regarding Google Classroom implementation.

Through qualitative and quantitative data from approximately 100 students from a range of majors, this poster presentation will analyse responses from two perspectives: students’ perceptions of how Google Classroom supported their experience on the course, and their recommendations for more effective implementation of LMS platforms to support their learning.

The poster will show the results of the research and provide practical recommendations for optimising LMSs as Computer-Assisted Language Learning (CALL) tools. These recommendations could potentially lower students' affective filters and create more engaging computer-mediated language learning environments. This research will be of interest to language educators and practitioners seeking to enhance their CALL implementation through more student-centred approaches to LMS usage.

English grammar learning is challenging for elementary students, as rote memorization often leads to disengagement. This study investigates how integrating songwriting with AI-generated music can enhance English grammar understanding and engagement among Grade 6 students in a Thai primary school. The instructional design involves students writing original English song lyrics that emphasize key grammar structures (e.g., tenses, sentence patterns), then generating accompanying music using AI tools such as Soundraw or Suno. Students present their songs in class and reflect on the grammar used, reinforcing learning through context and repetition.

An experimental research design will be used, comparing an experimental group (using the songwriting-AI process) with a control group receiving traditional grammar instruction. Research instruments include grammar-focused pre- and post-tests, student feedback questionnaires, and semi-structured interviews.

It is expected that the experimental group will show greater grammar improvement and learning motivation due to the affective engagement of music, the cognitive depth of composition, and the personalized experience enabled by AI. The study offers a novel CALL-based approach that combines creativity, technology, and learner-generated content to support grammar learning in young learners.

To enhance fluency and understanding of English reading materials, vocabulary instructions are given to learners as a pre-reading session. However, since not all materials include vocabulary lists and explanations, students may struggle to identify which words to learn without textbooks or teacher guidance. AI is considered to be capable of generating tailored content based on prompts, serving as the possibility of making vocabulary lists according to any given articles.Therefore, this study explores the potential of AI-generated vocabulary lists to enhance reading comprehension for EFL learners, focusing on Taiwanese senior high school students at B1 level. Thirty participants were divided into textbook and ChatGPT list groups. Both groups read the same passage with wordlists from AI or textbook, followed by a comprehension test and survey for data analysis. The results manifested AI-selected vocabulary highly overlapped textbook lists. Additionally, the scores from the tests and surveys showed no statistically significant difference between two groups, which indicated the effectiveness of AI-generated vocabulary lists. Survey responses also showed AI vocabulary lists were helpful, though the AI group reported some unfamiliar words. Clear prompts can be made to improve AI-generated lists, enabling AI to support reading comprehension as effectively as expert-made lists.

Effective content-based instruction (CBI) requires consideration of the program’s context, teaching methods, and available resources (Goto-Butler, 2005). I considered these criteria when creating a digital literacy course as part of an advanced communication training course at Ochanomizu University. I was already familiar with digital literacy, as I have been interested in it for a long time. This prior knowledge helped me create materials that were engaging and relevant. The course was designed for advanced students from various majors who had completed basic English classes. It covered topics like safe social media use and maintaining a healthy digital mindset. AI models like Co-Pilot, Perplexity AI, and Leo generated ideas and provided links to resources, while GPT-3 adjusted language for better comprehension and helped level down materials. Additionally, GPT-3 assisted with brainstorming activities, such as scenarios where students advised a friend on securing online activities and participated in a digital tribalism simulation. Miroboard was also used to give feedback at the end of each class. A total of eight students enrolled. A survey showed that seven out of eight students enjoyed the materials, and all would recommend the course. While the content was challenging, most students did not find it too difficult.

The rapid advancement of large language models (LLMs) like ChatGPT has transformed educational practices, particularly in English for Academic Purposes (EAP) instruction. This study explores effective prompt crafting strategies that uphold student agency in LLM-assisted writing. Key research questions address how rhetorical strategies in prompt design can affect the writing process and enhance learning experiences for both novice and professional EAP writers. Conducted in a university-level EAP course, the research involved two student groups: one used LLM-generated prompts designed with rhetorical strategies, while the control group utilized standard prompts. Data were collected through surveys, writing samples, and interviews to evaluate the prompts' effectiveness in fostering critical thinking and creativity. Preliminary results indicate that students using tailored prompts reported increased engagement and confidence, along with a better grasp of genre conventions. This presentation will highlight the implications of writer-centered prompt design, showcasing practical strategies that educators can adopt to improve EAP writers' skills while preserving critical thinking in an increasingly digital landscape.

This study intends to explore the use of AI to assist twenty EFL Taiwanese university students in cultivating empathy and examine whether this skill development can improve the quality of their collaborative written works. It adopts a mixed-methods approach to collect data, including learners' pre- and post- self-report empathy scales, pre-test and post-test collaborative written works, and peer feedback. Content analysis is used to analyze the written data and peer feedback. The learners complete five collaborative writing tasks as part of their writing course throughout the semester. Before each task, they receive guidance on empathetic communication from the researcher working with AI to create written scenarios illustrating the empathetic discourses being taught. Throughout the study, it is anticipated that the learners can cultivate empathy, foster mutual trust and collaboration, which in turn is expected to enhance their collaborative writing. The findings of the study will be presented at the conference.

Traditional tutoring typically encompasses one-on-one interactions between students and their instructors. While this method affords the opportunity for detailed feedback, it presents significant challenges when attempting to reach larger student population and personalize the experience for each individual. With generative artificial intelligence joining forces with tutoring, the proposed project aims to develop an AI-assisted tutoring system based on two Large Language Models (LLM) for students in the Chinese University of Hong Kong, Shenzhen. The system will be specifically designed to support the English for Academic Purposes (EAP) course, targeting primarily Year 2 students from diverse academic disciplines such as finance, marketing, computer science, biology, and etc. The intelligent system is guided by course learning outcomes and comprises two components: an analyzer and a tutor. The analyzer accurately tracks students’ progress and identifies individual strengths and weaknesses, while the tutor provides personalized learning support and focused assistance at the points where students’ learning requires enhancement. Additionally, the AI tutor aids instructors in analyzing class-wide progress towards attaining learning outcomes, beyond what can be accomplished by human instructors alone. The LLM implementation and deployment solutions developed in this project will be open-sourced to facilitate intelligent teaching in other courses.

This systematic review analyses empirical studies on the implementation of Generative Artificial Intelligence (GenAI) in language education to highlight its impact on promoting inclusivity and bridging educational gaps. The review encompasses quantitative, qualitative, and mixed-methods research, with a focus on inclusivity and educational equity accelerated by GenAI across multiple language education contexts, ranging from K-12 to higher education. Analysis shows that GenAI has the potential to substantially increase learner motivation and confidence by providing real-time feedback and generating engaging learning materials. Such tools can adapt to individual learner needs, support students with special education requirements, and empower economically disadvantaged learners. Furthermore, GenAI facilitates intercultural competence by incorporating diverse cultural contents into language learning. At the same time, it was also identified that GenAI could exacerbate equity issues due to economic disparities among students. By synthesizing current research, this review delineates a comprehensive understanding of GenAI’s role in creating equitable and inclusive language education landscapes, thereby guiding future research, educational practices, teacher training, and policymaking.

This poster presentation describes how young learners improve their intercultural communicative competence (ICC), gain motivation and responsibility in the global project in the small private school. The Japanese students (n=12) aged 12-15 engaged in the project from 2022 to 2024, inviting the students in Ukraine, Norway, and Sweden. This project aims for students to raise awareness of foreign cultures, increase interest in language learning, and develop their ICC, therefore, the two-year-long research was launched. The exchange of hand-writing letters, and questions on the Padlet are the tools for them to expand their curiosities toward the different cultures, popular movies, and fashions by comparing their lifestyles to their counterparts. The students' Foreign Language Anxiety Scales (FLAS） were analyzed to examine their feelings and an interview was conducted to learn about their specific interests in the project. As a result, most students increased their ICC and gained motivation and responsibilities in the project, showing positive comments and expanding their curiosities about foreign countries. The research results and students' works are shown on this poster and implicate why the students-students virtual exchange is important.

Creating a Padlet as an interactive hub for study-abroad information significantly boosts students' engagement with course content and enhances their interaction with peers. Teachers can foster a collaborative space for classes to document their aspirations around a future study-abroad experience. And by incorporating interactive and visually engaging Padlet centered activities into their classrooms educators can support the development of a student’s future L2 self by encouraging them to set clear, specific goals related to their upcoming study-abroad. Educators can reinforce language targets while encouraging class members to share useful resources they've discovered about specific locations. Activities such as researching local food and culture, discussing language needs for various situations, and reflecting on the type of L2 speaker they hope to become can boost students’ motivation and help them visualize how they will soon use classroom English in real-world contexts.

This poster presents the results from a survey of university students' attitudes to studying English in both classroom and online environments. It specifically focuses on EFL classes that used a communicative language teaching (CLT) approach. The questionnaire survey was administered to 327 non-English major students at a science and engineering university in northern Japan. The questionnaire included an open response section asking students to write about their experiences of learning communicative English both online and in the classroom. A total of 43 valid responses were received. Thematic content analysis was used to identify seven main themes from the written data: Advantages of classroom classes; Technical issues; Study materials; Breakout rooms – benefits; Breakout rooms – problems; Student health and welfare; and Preferred learning environment. This analysis of the written responses showed that students considered the classroom-based pedagogy to be more effective, particularly in terms of peer involvement and interaction. However, students also highlighted certain benefits of online learning, particularly access to materials and opportunities to interact with a diverse array of students. Findings from the survey have significant implications for how students experience communicative language learning and how teachers can best enhance this experience.

Large class sizes can require a large amount of time and administration. This presentation offers a simple and practical way to take attendance quickly using QR codes and Google Forms. This presentation will also provide ways to automatically pull grades and other information from classwork done via Google Forms into attendance records or gradebooks created in Google Sheets. No prior experience is required, as formulae will be provided and explained. After this presentation, attendees will be able to create their own attendance system, understand the formulae used in the process, and also move data around within the Google ecosystem.

Study abroad (SA) is traditionally seen as the most effective method for language and cultural learning, yet it faces challenges like language barriers, cultural misunderstandings, and social integration issues (Borràs and Llanes, 2019; Lee and Song, 2019). Students often struggle to engage socially and form friendships, leading to loneliness (Alghamdi and Otte, 2016). Virtual exchange (VE) offers authentic language practice and intercultural interaction (Helm, 2010; O’Dowd, 2016). This pilot study explores VE's potential in complementing SA for international students in Norway learning Norwegian as a second language (N2), paired with native Norwegian speakers for online interactions. The focus is on enhancing intercultural competence: What are the perceived benefits of participating in VE while studying abroad? A qualitative approach involved five N2 and five Norwegian students in a three-week online project. Data from post-questionnaires and interviews revealed varied experiences. Two N2 students reported positive outcomes, citing effective communication and strong relationships that enhanced cultural understanding and motivation. Conversely, one N2 student experienced minimal gains due to poor communication and partner disengagement. The study highlights the importance of quality interactions in VE for successful intercultural learning and its potential to supplement SA, despite its small-scale limiting generalizability

Owing to the recent exponential advancement in machine translation (MT) technologies, integrating these resources by students in tertiary educational settings has become a widespread practice worldwide. In language education, however, issues have emerged among teachers concerning the reliability of their output and the maintenance of ethical standards. As studies have suggested (e.g., Lee, 2021), this has led to MT technology being considered as unacceptable and unnecessary in the language classroom especially for lower-proficiency students. This quantitative and qualitative small-scale study aims to examine university students’ use of MT technologies and the benefits and challenges they encounter through the English language learning process. Data for this study was collected through a questionnaire with undergraduate students enrolled in spoken communication courses at universities in Japan. The findings of this study suggest that students are accustomed to various MT technologies, with most recognizing their advantages, especially in enhancing confidence in using the target language and improving overall language proficiency. The results also indicate that the majority of students recognize the benefits of using MT as an instructional assistant and critically evaluate its output by applying self-regulated learning strategies developed through the educational training they have received in the past.

This study investigates the integration of AI tools in developing teaching materials for an English for Specific Academic Purposes (ESAP) module tailored for Engineering students at Xi’an Jiaotong Liverpool University, a Sino-British institution and EMI university. The module enrolls approximately 600 students, with around 120 directly taught by the presenter in groups of about 20 each. The focus is on utilizing AI technologies—such as ChatGPT or DeepSeek—and voice tools like MURF AI to design reading and listening exercises that meet the specific needs of students specializing in fields such as big data and microelectronics. Students are expected to achieve a B2+ level on the Common European Framework of Reference (CEFR) after one year of study. The poster will demonstrate the process of incorporating advanced AI technology into lesson planning by presenting a detailed example of a complete lesson plan that illustrates the development of effective prompts and the generation of materials aligned with targeted learning outcomes and discipline-relevant topics. Employing a reflective approach, this study provides insights into the potential of AI in language teaching for specialized disciplines and offers a teacher’s perspective on the practical applications and challenges of integrating AI in the classroom.

This presentation gives an overview of an English Listening and Speaking course focused on digital literacy. The different software and programs used in the 16 week course will be explained, including student assessments, where many of these techniques and skills come together in a final presentation. Some of the tools used are; bots, video editing, podcasting, and programming. The presentation does not give an in-depth explanation to each of the programs or software but shows how they can be brought together to enhance projects, and give students the confidence to try out and use different technologies in their life.

Japanese learners of English often excel in reading comprehension because of years of preparation for university entrance exams, emphasizing grammar and vocabulary. However, their listening skills often lag, presenting a significant challenge in language acquisition. A primary reason for this disparity is the lack of exposure to an immersive English environment. While many universities require English proficiency for graduation, traditional classroom instruction alone does not provide enough input for students to develop strong listening skills. Given the limited opportunities for real-life practice, learners need to seek additional resources to enhance their abilities. Online learning platforms offer a practical and accessible way for students to engage in self-directed practice beyond the classroom. Through listening exercises and speech recognition technology, learners can improve their listening comprehension at their own pace. This study explores the integration of English Central to enhance college-level students’ listening proficiency. With limitations such as the number of participants, the results indicate that some participants showed measurable improvements in their TOEIC listening and reading scores. The presenter discusses key findings and the implications for educators incorporating technology-driven approaches to support English listening comprehension. This research aims to share effective teaching methods, not for commercial purposes.

Generative artificial intelligence (GenAI) is transforming educational practices by offering novel tools for English language teaching and learning (Kohnke et al., 2023). As digital role models, teachers must equip students with the skills to engage with AI (Moorhouse & Kohnke, 2024; Moorhouse et al., 2024). Pre-service teachers, however, face the challenge of acquiring AI literacy and competencies in an environment characterized by GenAI’s rapid evolution and diverse applications (Cervera & Caena, 2022; Ng et al., 2023). Consequently, many pre- and in-service educators struggle to harness GenAI’s full potential. Microlearning offers a promising solution by delivering content in concise, targeted segments that minimize cognitive overload while enhancing retention (Corbeil et al., 2021; Kohnke, 2023). This approach facilitates self-directed professional development with clear learning objectives (Zhang & West, 2019) and boosts overall engagement (Kohnke et al., 2024a). By merging time-tested pedagogical practices with digital innovation, microlearning equips pre-service teachers with practical strategies for seamlessly integrating emerging technologies (Kohnke et al., 2024b; Kohnke & Moorhouse, 2024). This poster summarizes insights from a pre-service teacher education course where GenAI and microlearning converge. It highlights practical examples, participants’ reflections, and an inclusive framework that offers actionable guidance for empowering educators in the digital age.

As online interviews become increasingly common in CALL research, particularly in studies involving virtual exchanges, online language learning environments, and technology-mediated communication, new ethical challenges are emerging that demand careful attention. While online interviews offer greater accessibility and flexibility, they also raise important concerns around data security, participant privacy, informed consent, and shifting power dynamics in virtual spaces (Deakin & Wakefield, 2014; Guo et al., 2024).

This poster explores how digital affordances shape researcher-participant interactions and introduce new ethical considerations specific to CALL contexts. Challenges are addressed, including navigating consent in online platforms, ensuring participant anonymity in multimodal environments, and managing the evolving power dynamics when participants can control their visibility or disengage at any time. These issues are especially pertinent in CALL studies where participants may be learners or teachers working across different cultural and institutional contexts.

The poster will offer CALL researchers practical strategies to address these ethical concerns. For example, designing more transparent digital consent procedures, selecting secure communication platforms, and adopting reflexive practices to account for asymmetries in digital communication. The session will foster interactive discussions on how CALL researchers can ethically design and conduct online interviews responding to the complexities of digital research ecologies.