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All Journal Journal of English Language Teaching and Linguistics ENGLISH EDUCATION: JOURNAL OF ENGLISH TEACHING AND RESEARCH
Sako, Takayoshi
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Education Languange, Linguistic, Communication & Media

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How Did Students Perceive Classroom Learning under Strict COVID-19 Pandemic Closures and Restrictions? Sako, Takayoshi
English Education:Journal of English Teaching and Research Vol 6 No 2 (2021): English education
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/jetar.v6i2.16394

Abstract

The COVID-19 pandemic of 2020 required strict infection prevention measures worldwide, including school closure. After school reopened, we implemented Japan’s strict COVID measures, under which close contact in pairs or groups, as well as vocalizing in unison, was proscribed, with students having to remain quiet and face the blackboard. This study’s aim is to answer the question of how students felt about learning under such extreme constraints. One of the most noticeable findings from the responses to the survey of the 2020 class was that they felt the lack of collaborative learning experiences; hence, in 2021, we implemented changes that would allow for more collaboration while still adhering to COVID prevention guidelines. Among the various collaborative learning activities in the classroom, students reported that they found value in debate activities that challenged their English language skills and critical thinking. Overall, however, students found comfort and value in a semblance of learning with their peers. It was concluded that even in a volatile and uncertain situation, such as a pandemic, it is crucial to improve environments for collaborative learning. In the future, quantitative study of the impact of collaborative learning on students’ English proficiency will be a useful follow-up study.
Fostering Interactional Competence through AI-Based Virtual Dialogue: Task Awareness Transformation in Japanese Pre-service Elementary School Teachers Sako, Takayoshi; Kiryu, Naoyuki
Journal of English Language Teaching and Linguistics Journal of English Language Teaching and Linguistics, 11(1), April 2026
Publisher : Yayasan Visi Intan Permata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21462/jeltl.v11i1.1929

Abstract

Developing interactional competence (IC) remains a significant challenge in Japanese elementary English teacher education, where pre-service teachers tend to prioritize linguistic accuracy over pedagogical facilitation. This pilot study investigates how a generative AI-based virtual dialogue environment—one specifically designed to introduce “friction” through unpredictable and incomplete responses—may reshape pre-service teachers' task awareness. Two university students took part in a two-week intervention using ChatGPT’s voice mode, assuming the role of teachers interacting with an AI “child.” Semi-structured interview data were analyzed using a Grounded Theory Approach (GTA). The analysis reveals a four-stage process: (1) initial difficulty arising from the gap between expectations and reality, (2) a shift in awareness from self-oriented linguistic anxiety toward learner-focused facilitation, (3) the concretization of perceived classroom conflicts, and (4) an emerging desire for pedagogical support. A central finding is that AI-mediated “friction” serves as a productive catalyst for professional learning, destabilizing existing frames of reference and prompting participants to redefine IC as the co-construction of meaning. The study carries several implications for teacher education and AI design. It proposes the principle of “intentional imperfection” in AI behavior, suggesting that rather than providing flawless models, AI for teacher training should generate manageable interactional trouble to elicit pedagogical judgment. The findings also highlight the necessity of embedding such simulations within a scaffolded framework that provides diagnostic feedback and links virtual practice to real-world professional vision. Together, these contributions offer a conceptual foundation for utilizing AI to prepare teachers for the interactional complexities of the language classroom.
Co-Authors Kiryu, Naoyuki