大橋 ルイーズ

Teachers globally recognise the potential of artificial intelligence (AI) to aid and disrupt language learning, but there is a lack of up-to-date practiced-based research within L2 education due to AI’s rapid evolution. Despite the need for such research, few teachers are ready to empirically evaluate the impact of their interventions through pre- and post-intervention data collection, limiting the publication of practice-based studies. A partial solution lies in exploratory action research (AR), which prefaces the conventional AR ‘reflect-plan-act-observe’ cycle (Kemmis/McTaggart 1988) with a period of reflection, planning, and observation to identify problems without impacting everyday teaching (Smith 2015). This article presents an exploratory AR project on a university course designed to help students build AI literacy in order to critically and creatively use AI for L2 learning. The stages presented are course design (reflection and planning), course implementation (observation and reflection), and post-course identification of issues to address in future planning (reflection for future course design). Thus, the present study ends at the beginning of the conventional AR cycle. The article makes a valuable contribution by demonstrating how emerging technologies in L2 education can be explored through exploratory AR and offers practice-related findings that may help educators design activities and courses suited to their own contexts.

The recent proliferation of generative AI (GenAI) applications and the sharp rise in their language capabilities have led to widespread experimentation and adoption within language education. As empirical studies in this book demonstrate, GenAI has the potential to aid L2 teachers and students, but caution must be exerted to ensure it is used in appropriate ways. In this chapter, we explore GenAI ethics with the goal of steering teachers towards responsible use of this valuable educational tool. We not only identify potential problems, but also suggest ways to mitigate them. First, we discuss academic misuse of GenAI by students, including cheating and over-reliance, and consider the importance of guidelines and teacher modeling. Second, we look at issues surrounding privacy and data protection, highlighting risks and raising awareness about responsible use and consent. Next, we turn to the built-in biases in GenAI, providing suggestions to reduce the perpetuation of stereotypes and address disparities in the representation of different demographic groups. Then, we draw attention to the environmental impact of GenAI and highlight factors that should be considered for sustainable use. Finally, we consolidate these issues to offer seven emerging principles for teachers to consider when adopting GenAI into language education. Importantly, this chapter also provides guidance for teacher educators and institutions. It emphasizes their co-responsibility with teachers for the necessary initial upskilling in GenAI and GenAI ethics, as well as for teachers’ continuous professional development with this rapidly changing technology.

In this introductory chapter, Louise Ohashi situates the emergence of generative AI (GenAI) in language education within a rapidly changing technological and pedagogical landscape. Reflecting on her experience as Chair of EUROCALL’s AI SIG during the release of ChatGPT, she documents the swift adoption of AI tools among L2 educators worldwide and their transformative potential for teaching and learning. The chapter explores both the opportunities and challenges of integrating GenAI into language education, highlighting its multimodal and multilingual affordances while urging critical, ethical, and informed use. It sets the stage for the book’s exploration of how AI is reshaping L2 skill development, ethics, engagement, and teacher practice.

<jats:p>This chapter explores the adoption of artificial intelligence (AI) within language education from the perspective of teacher-driven action. It draws on the Community of Practice framework (Lave &amp; Wenger, 1991) to highlight the vital role of teacher communities in raising teachers’ AI literacy and facilitating AI integration. This framework comprises three central elements: the domain, the community, and the practice. The chapter outlines key issues within the domain of AI in language education, introduces various types of teacher communities that address this domain, and shares common practices they undertake. The chapter also integrates personal narratives and encourages readers to reflect on their own roles within teacher communities. It ends with a call to action, with suggestions for readers at all stages of the AI novice-expert spectrum.</jats:p>

Machine Translation (MT) is receiving increasing attention within language education due to both its affordances and the potential it offers for academic misconduct. To understand more about teachers’ views and practices, a survey was conducted with 153 foreign language (L2) educators who teach at Japanese universities. The survey examined their; (1) use of MT to assist with L2 reading, writing, speaking, and listening, both personally and in their courses; (2) views on MT in language education; and (3) knowledge of how to help students use MT effectively and their willingness to learn about this. The results indicated that most teachers supported the use of MT as a learning tool, but many had concerns over its misuse. Few felt they had enough knowledge to guide students toward effective use and the vast majority wanted to learn more about how to do so. These findings highlight a need for teacher support and underscore the necessity of more research and workplace discussions on the integration and regulation of MT within L2 education.

This article reports on research and teaching methods related to self-directed learning (SDL) that were presented by four SDL teachers in a forum at JALT2020. There is growing interest in the role teachers and institutions can play in fostering learner autonomy (Blidi, 2017; Lai, 2017; Murray, 2014; Ohashi, 2018, 2019). This article addresses the need for greater transparency in the practical aspects of aiding students to take charge of their learning within and beyond classrooms. It shows different ways each author approached the same SDL course that they taught at a university in Tokyo, by introducing language learning histories, future self exploration, planning-action-reflection cycles, negotiated goal contracts, learning logs, and asynchronous peer interaction. Through sharing their experiences, insights, and research outcomes, the authors hope to contribute knowledge of practical ways in which SDL can be approached by teachers and institutions.本稿では、自己主導型学習（self-directed learning、以下SDL）の授業を担当する4名の教師がJALT2020のフォーラムで発表したSDLに関する研究と教授方法を報告する。学習者の自律性の育成において、教師や教育機関が果たせる役割への関心が高まっている（Blidi, 2017; Lai, 2017; Murray, 2014; Ohashi, 2018, 2019）。本稿は、学生が授業内外で学習に主体的に取り組むための実践的な支援方法の透明性を高めるニーズに応える。著者らは東京の同じ大学で同一科目SDLを担当し、それぞれが言語学習ヒストリー、将来の自分探し、計画―実行―省察サイクル、交渉した目標の契約、学習ログ、非同期ピア・インタラクションという異なるアプローチを実践した。本稿ではこれらの経験、洞察、研究成果を共有し、教師や教育機関によるSDL支援方法に関する知見を提供する。

This article reports on an autoethnography by two authors who analysed the interrelationship of their experiences as foreign language learners, educators, and researchers. Both participant-researchers had taken advantage of the accessibility of online learning resources to learn new languages, had incorporated digital tools into their teaching practices, and had researched how technology could be used as a learning aid for students inside and outside the classroom. In this collaborative autoethnography, they turned the research lens upon themselves and each other to develop understandings of the way their experiences as language learners and researchers impacted upon their teacher cognition and teaching practices.