Abstract: This presentation introduces a classroom-ready approach to using NotebookLM as a reflective tool to support oral fluency development in a university EFL context. Students record short audio journals several times per week, producing regular, low-stakes spoken output. They upload either a transcript or the audio file itself, which NotebookLM can transcribe; the resulting transcript serves as the basis for analysis. Best practices for generating accurate transcripts will be briefly outlined. While audio files may be uploaded directly, pre-generated transcripts are typically faster and more efficient for classroom use. Rather than requesting general corrections, students ask for feedback focused on recurring grammatical errors across their output. NotebookLM can analyze a single journal, a specific week, or all accumulated transcripts, allowing learners to control the scope of feedback. This flexibility helps students identify recurring problem areas, track changes over time, and select actionable points for reflection. By analyzing transcripts of their own spoken language, learners engage in metalinguistic reflection grounded in authentic L2 output. NotebookLM does not replace instruction or speaking practice but serves as a reflective guide, supporting a more intentional path toward oral fluency.
Abstract: Many language teaching tasks work better through structured AI workflows that coordinate multiple tools rather than relying on a single AI tool. For example, generating realistic multi-character conversations, providing scaffolded feedback that adapts to student responses, or managing feedback across many students often requires a sequence of coordinated AI actions. A typical workflow might allow students to record a spoken dialogue, have the audio automatically transcribed, receive targeted feedback on vocabulary, grammar, and fluency, and then obtain an overall evaluation or grade.
This practice-oriented session presents how teachers can build such workflows using AI tools to complete multi-step pedagogical tasks. Co-presented by a language teacher with no programming background and an app developer, the session presents classroom-tested examples including generating multi-character dialogues, building personalised feedback cycles for student writing, and managing scalable homework correction.
Participants will see how chaining instructions allows teachers to guide AI behaviour more reliably than relying on a single tool. The session also demonstrates how local tools can be combined with online services to improve privacy and reduce platform lock-in.
Participants will leave with practical examples and a simple framework they can adapt to their own teaching contexts.
Abstract: Recent discussion of AI in language education often focuses on generating code or single-prompt interactions with large language models (LLMs). In practice, however, effective use increasingly involves chaining instructions, managing context window limits, and combining multiple tools and services. This presentation introduces vibe coding—an approach that uses conversational instructions to orchestrate AI tools, treating LLMs not as code generators but as components in flexible, instruction-driven workflows.
The session is co-presented by a language professional with no programming background and a developer who builds educational applications. Together, we demonstrate how vibe coding enables teachers to design powerful AI-assisted workflows using natural-language instructions rather than traditional code. Examples relevant to JALT professionals include generating realistic multi-character conversations, providing personalised feedback at scale, and managing iterative tasks.
We also address what vibe coding is not: it does not require learning a programming language, nor does it depend on a single AI platform. Instead, it enables practitioners to combine local tools with online services, reducing vendor lock-in and improving privacy by keeping sensitive data under user control.
Participants will see practical demonstrations of simple workflows, learn how to judge when a task requires multiple steps, and choose appropriate tools for their context, such as generating realistic multi-character conversations or providing personalized feedback at scale. Attendees will leave with a framework for building AI workflows and concrete first steps that they can implement immediately. No prior programming experience is required.
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Abstract: Speech recognition and synthesis are perhaps the last stage in interface technology. For the language learner, the ability to speak to a device that can simultaneously play different roles and accents (female, male, old, young, Irish, Scottish, New Zealand, Fijian, Canadian, US etc.) is opening up speaking opportunities for L2 learners. However, the machine learning engines that allow such interactions are somewhat of a black box. In this study supported by a JSPS Kakenhi Grant as part of a Japanese MEXT Grants-in-Aid for Scientific Research, we look at the accuracy and use of such systems, and this presentation will give an outline of how the technology works, its future, and the preliminary results of this ongoing study.
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Abstract: In recent years the increase in the availability of computerized speech recognition and speech synthesis has led to exciting possibilities in the field of foreign language learning. Traditionally learning activities do not require students to vocalize their responses. This paper presentation will show an analysis of the effectiveness of speech recognition using online speaking on student reactions over 3 institutions as part of Kakenhi research.
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Abstract: Gary and Steve will have an informal discussion about using Edzil.la for your own conference. If you have any questions or would like to use the platform, please feel free to join us.
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Abstract: In recent years the increase in the availability of computerized speech recognition and speech synthesis has lead to exciting possibilities in the field of foreign language learning. Computerized speech essentially represents a final stage in the development of a human-computer interface, and in this context, it offers substantial advantages over traditional touch-based interfaces which can eschew language altogether. One activity where this is particularly pertinent is in spaced-learning activities where traditionally students do not need to vocalize their responses, and indeed the responses are often not available to instructors at all. Speech Recognition has further benefits in that every utterance is immediately displayed for students, giving them a more accurate indication of their success with the tested language constructs. The advantage to instructors is in the ability for utterances to be stored as text in a database allowing computer analysis of speech patterns to discern common errors. As the 3rd year of a four-year cross-institutional research grant from the Japanese Government (Kakenhi), this paper will present a speech recognition and speech synthesis system developed by the author within the context of a spaced learning program. We will further show (a) a pattern analysis of the accuracy of the system and patterns of learner usage, (b) an analysis of the effectiveness of spaced-learning using online speaking on student outcomes over 3 institutions, (c) student feedback and reactions on speaking to a machine, (d) how the system deals with pronunciation.
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Abstract: The team behind Eventzil.la, Gary Ross and Stephen Henneberry, will be giving an informal look at how you can use the system to host your own event, and some pointers and tips to make your event successful. We will be reflecting on the Kotesol2021, and talking about the improvements coming. Eventzil.la has successfully hosted over 1000 presentations and 10,000 participants from small seminars to large international events with hundreds of sessions. Invisible to attendees is the powerful and easy to use admin area that makes this possible, and this session will give also give a brief look at that in action.
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Victor Reeser, Rhea Metituk, Rhett BUrton, Aaron Jones, Gary Ross, & Stephen Henneberry
Abstract:
Due to the coronavirus pandemic, online teaching has moved from a position of tenuous acceptance and application into standard practice across the world. From parents to students to educators, everyone has undoubtedly struggled with this shift. In this panel, members of the Multimedia and CALL Special Interest Group (MCALL-SIG) as well as two invited speakers will review positive and negative experiences with online teaching; discuss the challenges of converting standardized offline classes to online classes; explore strategies to adapt offline teaching practices to online classes; and share insights into what it takes to succeed in education today.
The panel will also be prepared to engage with audience members on specific questions related to online education, using technology in their classes, and solutions and resources to assist educators with tech-related issues in their respective classrooms. Attendees will leave with a renewed perspective on online teaching as well as practical solutions to the challenges of teaching offline courses in an online setting.
Abstract: This presentation will demonstrate how to use Line with your students for more immediacy in your communication without compromising your personal Line ID. Making use of the free Line Official system, you can set up direct lines of contact with multiple courses without giving out your personal Line ID. In these times of Emergency Online Teaching, this is possibly the most effective way to push messages to students and be confident they will read them.
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