This study examines English language teachers’ perceptions of artificial intelligence (AI) tools in El Salvador, exploring their awareness, usage, benefits, challenges, and concerns. In December 2024, a survey was distributed to 1,570 preservice and in-service teachers in Teachers Up, a nationwide professional network supporting English language educators in El Salvador, yielding 136 responses. Additionally, 12 teachers participated in focus groups. Findings indicate that while 57% of respondents are somewhat familiar with AI in language teaching, only 39% have integrated AI tools into their practice. Teachers recognize AI’s potential to create content and provide feedback, yet they express concerns about student over-reliance, the accuracy of AI-generated content. Most teachers view AI as a complementary tool rather than a replacement for human instruction, recommend always reviewing AI-generated materials before use, and emphasize the need for professional development and methodological guidelines. Additionally, they highlight issues with repetitive AI-generated content, the ease of identifying AI-produced work, and the need for critical evaluation of AI outputs. Finally, a lack of institutional training and clear policies further limits AI’s effective implementation. This presentation benefits English language teachers, teacher educators, policymakers, CALL developers, and researchers.

This study examines how students enrolled in 2024-25 academic year courses in English for Academic Purposes responded to pre-recorded video presentations of either group or individual projects using Padlet and online evaluation methods using Google Forms in a virtual learning environment. The students majored in English Language Communication (n=115 in four classes) and Image Arts & Science (n=109 in four classes) at a private university. By analyzing engagement levels, comprehension, and assessment performance, this study explored the attention span, interaction, and perceived effectiveness of asynchronous learning. The results indicate that while pre-recorded videos offer flexibility and accessibility, student engagement varies based on content delivery style and video length. Additionally, online evaluations influence test-taking behavior, with factors such as question format and time constraints affecting performance. These findings provide insight into optimizing digital learning strategies to enhance student outcomes.

In the age of AI, student motivation to write original essays is of paramount importance. In this study, multimodality and ChatGPT were used to motivate students to write their own original essays. This presentation will show the results of a study conducted with 48 first-year English majors at a Japanese foreign language university during the first semester of the 2024-25 school year. At the beginning of the semester, students were tasked with doing an audio recording of their pre-writing tasks for their first essay and then surveyed on their motivation to write essays. For the second essay, students were taught how to use ChatGPT as a writing assistant. At the end of the semester, students were surveyed on their use of AI and their overall motivation. Results showed that students enjoyed the pre-writing tasks using multimodality. In addition, student motivation to write their own original essays increased. However, results also showed that some of the essays turned in were far from original. Although multimodality and ChatGPT can be used as motivators in the Freshman EFL composition classroom, more understanding is needed to get students to rely less on AI and focus more on their own original work.

In recent years, the integration of data-driven learning (DDL), particularly corpus technology, has gained attention for its ability to steer language learners (LLs) toward independent learning. This 25-minute presentation explores the evolving attitudes and perceptions of digital-native LLs toward direct corpus use and its associated technology. First, I will differentiate between corpus-informed (indirect use) and corpus-based (direct use) approaches. Next, I will outline key findings from previous studies on LLs’ perceptions of corpus technology. Then, I will describe two teaching contexts in which I have integrated direct corpus use and summarize my LLs’ perceptions using a short, structured questionnaire. Finally, this presentation concludes with an open discussion about the perceived challenges surrounding corpus technology and potential creative workarounds.

Active participation and deeper engagement are essential elements of effective language learning. In the digital age, adopting innovative technological tools creates interactive learning environments that enhance student immersion. This study explores the role of Padlet, a cloud-based platform, in fostering greater engagement in English learning activities among Information Technology (IT) and Finance first-year students at a private Vietnamese university. The primary objective was to assess how Padlet facilitates active learning and identify the features most valued by students for boosting their participation. A mixed-methods approach was employed, gathering data from 70 students through structured questionnaires, follow-up interviews with 8 participants, and two 45-minute classroom observations. The results indicated that Padlet positively impacted student motivation and collaboration through real-time posting and commenting. Quantitative data revealed engagement patterns, while qualitative responses highlighted the platform's collaborative features. Despite the overall positive impact, participants reported technical issues and initial unfamiliarity with the platform. The study emphasizes Padlet's potential as an effective tool for enhancing engagement and collaboration in language learning and offers practical recommendations for its use in specific educational contexts.

The rapid rise of AI tools in education presents an ongoing challenge on understanding how students perceive the ethical boundaries of AI use in academic settings, especially in the realm of EFL education. While previous research has explored both the potential and the limitations of AI in language education, further investigation is needed to reveal how student perceptions evolve alongside advancements of AI tools. Building on our 2023 study involving 543 first-year students (Neff, Arciaga, & Burri, 2024), the present study analyzes data from a new cohort of 522 first-year students surveyed in 2024 at the same national university. Using the same questionnaire, participants evaluated AI-related scenarios on a 4-point Likert scale. This study offers a year-on-year comparison, which is expected to reveal some degree of continuity and shift to an extent. These findings may provide insight into emerging trends in student attitudes and emphasize the need to promote ethical awareness in EFL education. The presentation will explore how these results can inform educators in developing ethical guidelines and effective pedagogical practices for English language programs in Japan and beyond.

Main author: Kasumi Arciaga (myself) Co-author #1: Joel Neff (who can attend the conference) Co-author #2: Mike Burri (who cannot make it to the presentation)

The rapid advancement of technology can negatively impact students’ psychological well-being, leading to a phenomenon known as technostress. The introduction of generative artificial intelligence (AI) has further raised concerns about its potential to increase technostress among language students. This presentation reports on a study that explored technostress among English as a foreign language (EFL) students at two Japanese universities. The study assessed the levels of technostress related to generative AI among the participants and examined the relationship between English language proficiency and AI-related technostress. An adapted survey (Kohnke et al., 2024; Niu et al., 2020) consisting of Likert-scale questions and open-ended items was developed and administered to participating students during the fall 2024 semester. A total of 100 students provided informed consent and fully completed the survey. While the quantitative results indicate that the participants did not exhibit a high level of technostress, the qualitative results suggest a more nuanced picture of the impact of AI-related technostress on Japanese EFL students. The full results of the study and its implications will be discussed during the presentation.

Since ChatGPT’s 2023 release, AI tools have become increasingly available to language learners, yet their adoption remains underexplored. This study surveyed 163 students at a national university in western Japan in Fall 2024, complemented by teacher observations, to investigate students’ use of AI, preferred tools, targeted tasks, concerns, and expected AI use guidelines. Results show ChatGPT as the leading tool, followed by DeepL and Google Translate, with 93% of students using AI for translation, grammar, writing, and vocabulary. Usage frequency varies, with only 5% using AI daily and 53% occasionally. Students expressed moderate concern about over-reliance on AI and its impact on critical thinking (mean: 3.03/5) and were ambivalent about AI-assisted homework constituting dishonesty (mean: 2.55/5). Many noted insufficient instructor guidance on ethical AI use. This study highlights the need for pedagogical strategies to ensure responsible AI integration in language learning. A qualitative analysis of student comments, processed with NVivo, further enriches these findings, offering deeper insights into student perspectives.

Teaching Intercultural Communicative Competence (ICC) to EFL learners from the Natural Sciences is akin to swimming against the current: on one end, they are being trained by their majors to see reality in objective terms; but on the other end, ICC development requires them to focus on the subjective nuances of how culture mediates language. This workshop describes an ICC teaching approach for tackling this challenge: First, by explaining the basic theoretical foundations that guide it. Second, by showcasing GenAI-based strategies developed for triggering in students the necessary self-reflective processes that may lead towards ICC development. Participants will be given hands-on access to a chatbot that was prompt-engineered for eliciting conversations on the intersectionalities between the objective and subjective aspects of certain natural phenomena. The interactions focus first on the objective components of these phenomena, and then slowly guide students towards the realization that what they thought is an “objective” reality from the viewpoint of Physics, Chemistry or Mathematics, is really a “subjective” one once we factor in how different cultures around the world perceive those same phenomena. As a result, a feasible strategy for using GenAI as a stepping stone for developing certain foundational ICC-related skills will be demonstrated.

This study investigates how English teachers with different first languages (L1 English, L1 Japanese, and L1 Other) and varying levels of AI experience implement generative AI in their speaking classes. Through collaborative action research, three teachers will document their experiences and perceptual changes while implementing standardized AI-enhanced speaking tasks. The research employs a qualitative approach focusing on teacher narratives, structured reflection journals, and bi-weekly collaborative reflection meetings. Data collection will occur over a 12-week period (February-May 2025), capturing the evolution of teachers' attitudes, concerns, and pedagogical adaptations. This research contributes to understanding how teachers' linguistic backgrounds, educational experiences, and prior AI exposure influence their approaches to AI integration in language education and provides practical insights for teacher training and professional development.

This study investigates the relationship between Generative AI (GenAI) literacy and English language learning motivation (ELLM) among Japanese high school students. The integration of GenAI tools, such as ChatGPT, into language education has shown potential to personalize and enrich the learning experience (Kohnke et al., 2025). While Japan has long faced challenges in fostering communicative competence in English (Wilkins & Peet, 2024), recent research continues to highlight motivation as a key factor influencing language learning outcomes (Taguchi, 2025). In classroom settings where instruction often emphasizes grammar and vocabulary over communicative use, GenAI may offer new opportunities to position English as a meaningful communication tool (Huang & Mizumoto, 2024; Moybeka et al., 2023; Wang & Xue, 2024). This study hypothesizes that GenAI literacy (GAIL)—defined across dimensions of awareness, usage, evaluation, and ethics—affects students’ ELLM, including intrinsic motivation, introjected regulation, and external regulation. Using a survey comprising two instruments—the GenAI Literacy (GAIL) Scale and the English Language Learning Motivation (ELLM) Scale—the study collected data from 200 Japanese high school students. Regression and multiple regression analyses were conducted to examine the relationships between variables. The findings aim to provide insights into the role of GenAI literacy in enhancing motivation and informing effective AI-integrated language instruction. This study hopes to contribute to the growing discourse on AI in education, offering actionable recommendations for ethical and motivationally supportive GenAI integration in English language classrooms.

Awareness of collocations is essential for vocabulary learning, as they form a fundamental part of natural spoken and written English. This study examined the impact of original CALL tools on collocation acquisition. Over seven weeks, 136 Japanese EFL university students used an online tool to read short passages, each containing 10 collocations, while their reading speed was tracked. The tool evaluated collocation knowledge through multiple-choice quizzes (recognition) and blank-fill exercises (production) based on the passages. To reinforce learning, students practiced these collocations using online flashcards for homework and were tested on them the following week. Pre- and post-tests evaluated overall collocation knowledge and learning gains. Results showed that students’ reading speed increased over the seven weeks and their collocation quiz scores improved, culminating in significantly higher post-test scores. More frequent flashcard use was also positively correlated with better weekly test performance. The findings indicate that digital tools and flashcards can effectively enhance collocation learning, improving both recognition and production skills. This study highlights the potential of CALL-based interventions to optimize vocabulary acquisition and offers some insights for designing more effective digital learning strategies.

This presentation is a call for culturally responsive technology integration. Despite the fact that technology in education is ubiquitous, effective integration remains difficult. I argue that one of the reasons why integration is so challenging is due to cultural differences in the way technology is used. My argument is supported by data obtained through qualitative research investigating the technological implementation of native English teachers in Japanese EFL classrooms. The talk begins by introducing the technological pedagogical content knowledge (TPACK) (Mishra & Koehler, 2006) model. TPACK is one of the most widely used frameworks for technology integration in education. However, this presentation provides evidence for its critical limitations in intercultural contexts. The findings from my research indicate Cultural Knowledge (CK) acts as a separate but interdependent dimension within TPACK. As such, I call for the TPACK model to be revised to include CK as a separate dimension to address the importance of cultural knowledge in technological integration–TPACCK. This presentation is aimed at those working with technology in intercultural contexts. Attendees will learn how cultural filters mediate technology use and how technology can be used to overcome barriers to language learning in Japanese EFL settings. Implications in other contexts are also discussed.