This presentation examines what happens when a game-integrated Pedagogy of Multiliteracies project prevails in terms of learning and research outcomes, but fails as sustainable practice. Drawing on design-based action research across two Japanese university cohorts, I reflect on a DGBLLT design that used board and digital games, student-as-researcher tasks, and mixed-methods data to support language, literacy, participation, and well-being. The project produced strong outcomes, including gains in off-list vocabulary, grammar, speech acts, and students’ self-rated curiosity and happiness. However, these gains came at a cost. More than 1000 hours of design, implementation, feedback, and analysis created recurring pressure points, including grading overload, data avalanches, uneven group dynamics, and physical and emotional strain. One major lesson was that rich instrumentation can support valuable evidence of learning while also making a project difficult to sustain. In response, I propose a “permaculture” approach to DGBLLT: reusing open materials, simplifying research and assessment routines, embracing constraints, and protecting space for play. The session argues that the key question is not only whether game-based teaching succeeds, but whether it can be maintained, adapted, and shared without exhausting teachers. Participants will leave with practical heuristics and tools for redesigning CALL projects for both impact and sustainability.

Generative AI offers new ways to adapt course materials to students’ language levels and disciplinary needs. In this presentation, I share how I used generative AI (e.g., Gemini for content creation and code generation) in an undergraduate English for Specific Purposes (ESP) economics course for non-native English-speaking students to support their understanding of key economic concepts while remaining sensitive to linguistic challenges. After briefly outlining how AI helped me tailor materials in this context, the talk focuses on how AI allowed me to move beyond traditional, text-based resources. I will demonstrate the development of interactive, scenario-based simulations inspired by narrative adventure games. Developed using AI for both content creation and coding, these simulations allow students to explore economic situations, make policy choices, and immediately see how their decisions affect outcomes, encouraging active engagement and reflection on economic trade-offs. The session will conclude with a live demonstration of the custom-built tool and a discussion of its classroom use. Overall, the presentation aims to show how AI can help make economics more interactive, accessible, and even enjoyable, perhaps challenging its long-standing reputation as the “dismal science,” while offering practical ideas that participants can adapt for their own teaching contexts.

The rapid proliferation of large language models (LLMs) has opened new horizons for personalized, AI‑augmented learning. The ability to design new kinds of educational interactions can provide language practice opportunities that previously did not exist. For example, the language of persuasion, AI chatbots offer the unique ability to craft interactions with a high degree of authenticity related to the social purpose of the interaction. Enter Luigi: a chatbot pizza lover who is vehemently opposed to the addition of pineapple on pizza. Your mission, should you choose to accept it, is to convince Luigi to at least try tasting pineapple on pizza (Hawaiian pizza). Students interacting with Luigi are provided with an interlocutory adversary who will not immediately acquiesce to the student's request, but rather will evenly provide opportunities to entire classes of students to use persuasive language. In this presentation, I will demonstrate how to achieve this, hosting LLMs locally using Ollama (no cloud services and free of cost), as well as how to download (pull) models and customize them to create unique learning interactions for educational use. I will also describe the difficulties encountered getting models to produce language that is appropriate for the task, level, and situation.

The role of digital technologies in language education has expanded considerably in recent years. Gamified language learning has been promoted as an innovative pedagogical approach, particularly for its potential to enhance learner motivation and engagement through interactive learning experiences. However, comparative analyses of different gamified learning conditions remain underexplored in empirical research, with none focusing on Japanese EFL learners. Grounded in social interdependence theory and sociocultural theory, this study explores the effectiveness of different social structures on students’ motivation and learning achievement in gamified contexts. Sixty Japanese undergraduate students participated in a 14-week intervention using Quizlet. Questionnaires and pre-posttests measured participants’ learning gains and motivation, while interviews further explored their perceptions of learning experiences. Preliminary findings suggest that students in the cooperative condition significantly outperformed their peers in the posttest and showed the highest motivational intensity. Since data analysis is ongoing, implications and additional findings will be presented at the conference. Aligning with JALTCALL’s theme, rather than treating gamification as an inherently effective approach, the study investigates the conditions under which gamified environments support or hinder sustained motivation and learning gains. This offers a balanced reflection on both the pedagogical potential and limitations of gamification in technology-enhanced language learning.

This presentation reflects on a pedagogical failure that ultimately reshaped my approach to game-based language teaching. In an early attempt to integrate games through a rushed, flipped-learning model, I treated play as the core in-class activity with minimal scaffolding, and an overreliance on students doing the bulk of work outside class. While technologically convenient, this approach resulted in shallow engagement, fragmented learning, and teacher frustration. Drawing on my earlier work conceptualizing ludic language pedagogy through the metaphor of *ｖａｐｏｒｗａｖｅ* (slow, reflective, and aesthetically intentional) this talk traces how abandoning speed and efficiency became the turning point. By slowing down, expanding pre- and post-game pedagogical framing, and legitimizing languaging practices such as L1 use and reflection, games shifted from "maximum student talk time" to meaningful learning spaces. Framed candidly as a journey from failure to recovery, this presentation highlights practical lessons for teachers navigating educational technologies: when innovation prioritizes pace over pedagogy, learning suffers, but when we slow down deliberately, both teachers and students can prevail.

Recent advances in automatic speech recognition (ASR) and generative AI have enabled new forms of oral language practice beyond traditional, test-oriented speaking tasks. This paper reports on the design and classroom use of a gamified ASR-based oral practice platform developed with Google AI Studio for elementary-level ESL learners. The system integrates ASR into a fast-paced pronunciation game inspired by falling-block mechanics. Learners practice words, phrases, and sentences by speaking aloud: accurately pronounced items disappear, while inaccurate attempts cause items to fall and accumulate as “bricks,” ending the game once a preset height is reached.

The platform was rapidly prototyped using Google AI Studio to manage ASR processing, pronunciation tolerance thresholds, and prompt-based feedback, allowing flexible refinement without complex backend development. The web-based game was piloted in an elementary classroom setting.

Questionnaire data and classroom observations indicate generally positive learner responses, including high engagement, increased willingness to repeat pronunciation attempts, and reduced speaking anxiety compared with traditional drill-based activities. Teachers also reported sustained attention and voluntary practice. Although no quantitative pronunciation gains were measured, the findings suggest that gamified ASR environments can serve as effective supplementary tools for young learners and highlight the pedagogical potential of generative AI for CALL development.

This workshop introduces the design process and core mechanics of a mobile digital game developed for workplace-situated language learning (https://workdplays.com). Originally created for migrant workers in Danish slaughterhouses, the platform has since been expanded to support additional labor industries with high proportions of migrant employees, as well as multiple target languages. A key challenge in workplace integration for many migrant workers lies in persistent communication barriers, particularly in contexts where formal language education is inaccessible or insufficient for highly task-specific communicative needs. Drawing on principles from serious games, the game simulates authentic workplace interactions within a safe, scaffolded digital environment. During the workshop, participants will explore the game firsthand and examine how ethnographically informed design decisions are operationalized through concrete gameplay mechanics. The workshop will also present findings from quantitative analyses conducted at multiple factory sites in Denmark, which demonstrate measurable improvements in learners’ acquisition of workplace-relevant Danish vocabulary following gameplay. By combining hands-on exploration with discussion of design rationale and learning outcomes, the workshop provides practical insights into how mobile, game-based platforms can be designed and adapted to support language learning in real-world workplace contexts.

This presentation reports on a research-and-development project conducted in a Danish slaughterhouse where migrant workers constitute a substantial portion of the workforce and where language and communication difficulties are a persistent feature of everyday work practices. For many employees, formal Danish language education has not been accessible or sufficient to meet highly situated, task-specific communicative demands. To address this gap, a digital, game-based language learning application was developed based on extended ethnomethodological fieldwork. Language learning activities were embedded within a virtual slaughterhouse environment that reflects workers’ procedural and interactional realities, enabling engagement with vocabulary directly tied to daily tasks. The presentation focuses on both the ethnographic foundations of the design process and preliminary findings from implementation. Quantitative analyses of in-game interaction data and pre- and post-test vocabulary measures indicate significant vocabulary development following gameplay. Regression analyses identify pre-test proficiency, in-game performance, task difficulty, and the temporal distribution of gameplay as significant predictors of vocabulary gains, while clustering analyses suggest that learners with lower initial proficiency benefited most from more widely spaced gameplay. Overall, the findings demonstrate how ethnographically informed, performance-dependent, and temporally distributed game-based interactions can support meaningful workplace vocabulary development across proficiency levels.

Extensive reading has a well-documented history of support in second language education research, but some of today's learners may be reluctant to engage with traditional print-based reading materials outside of the classroom. This poster presentation introduces extensive RPGing as an approach that includes narrative-driven role-playing video games as a digitally mediated option for students engaging in extensive reading activities. In many RPGs, reading is an essential part of the play experience, with players needing to read and understand dialogue, menus, item descriptions, quest instructions, and other text in order to progress the story. The poster explains what extensive RPGing is, how it compares to more traditional extensive reading approaches, and draws on observations and student-generated data from early classroom implementations. While students who chose to participate reported high engagement, participation itself was limited. Challenges included students who do not play video games, skepticism toward games as learning materials, and uncertainty about selecting appropriate titles. Rather than arguing to replace other methods and materials, extensive RPGing invites participants to consider learners’ existing media consumption habits and whether these habits can be leveraged to support language learning among interested students.