Fostering Interactional Competence through AI-Based Virtual Dialogue: Task Awareness Transformation in Japanese Pre-service Elementary School Teachers

Takayoshi Sako, Naoyuki Kiryu

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.

Keywords


Generative AI, grounded theory approach, interactional competence, teacher education

Full Text:

PDF

References


Badiee, F., & Kaufman, D. (2015). Design evaluation of a simulation for teacher education. SAGE Open, 5(2). https://doi.org/10.1177/2158244015592454

Bose, S. (2021). Using grounded theory approach for examining the problems faced by teachers enrolled in a distance education programme. Open Praxis, 13(2), 160–171. https://doi.org/10.5944/openpraxis.13.2.128

Dai, C.-P. (2023). Designing learning support for simulation-based preservice teacher learning with artificial intelligence-powered virtual agents. International Journal for Educational Media and Technology, 17(2), 31–39.

Dai, C.-P., Ke, F., Zhang, N., Barrett, A., West, L., Bhowmik, S., Southerland, S. A., & Yuan, X. (2024). Designing conversational agents to support student teacher learning in virtual reality simulation: A case study. Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (Article 513). ACM. https://doi.org/10.1145/3613905.3637145

Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 227, 105224. https://doi.org/10.1016/j.compedu.2024.105224

Dung, L. Q. (2024). The effectiveness of the integration of ChatGPT into flipped classrooms from teachers’ and learners’ perspectives. English Language Teaching, 17(7), 38–49. https://doi.org/10.5539/elt.v17n7p38

Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.

Galaczi, E., & Taylor, L. (2018). Interactional competence: Conceptualisations, operationalisations, and outstanding questions. Language Assessment Quarterly, 15(3), 219–236. https://doi.org/10.1080/15434303.2018.1453816

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine.

Hong, S., Moon, J., Eom, T., Awoyemi, I. D., & Hwang, J. (2025). Generative AI-enhanced virtual reality simulation for pre-service teacher education: A mixed-methods analysis of usability and instructional utility for course integration. Education Sciences, 15(8), 997. https://doi.org/10.3390/educsci15080997

Johnston, O., Wildy, H., & Shand, J. (2024). A grounded theory about how teachers communicated high expectations to their secondary school students. European Journal of Psychology of Education, 39, 211–235. https://doi.org/10.1007/s10212-023-00689-2

Karakaya, K., Alpat, M. F., Uçar, H., Karakaya, Ö., & Bozkurt, A. (2025). Preparing teachers for the algorithmic educational landscape: A critical mapping of generative AI integration in language teacher education. Technology in Language Teaching & Learning, 7(2), 102841. https://doi.org/10.29140/tltl.v7n2.102841

Lee, D., Son, T., & Yeo, S. (2025). Impacts of interacting with an AI chatbot on preservice teachers’ responsive teaching skills in math education. Journal of Computer Assisted Learning, 41(1), e13091. https://doi.org/10.1111/jcal.13091

Liu, Z., & Zhang, W. (2024). A qualitative analysis of Chinese higher education students’ intentions and influencing factors in using ChatGPT: A grounded theory approach. Scientific Reports, 14(1), Article 18100. https://doi.org/10.1038/s41598-024-65226-7

Matsunaga, M., & Tanabe, Y. (2025). Challenges in English proficiency and teaching skills identified through self-evaluations of elementary school teachers: Implications for teacher training. JASTEC Journal, 44, 129-144.

Mezirow, J. (1991). Transformative dimensions of adult learning. Jossey-Bass.

Ministry of Education, Culture, Sports, Science and Technology (MEXT). (2019). Foreign language (English) core curriculum.

Ministry of Education, Culture, Sports, Science and Technology (MEXT). (2024). Results of the fiscal year 2023 survey on the implementation of English education.

Moorhouse, B. L., Wan, Y., Wu, C., Kohnke, L., Ho, T. Y., & Kwong, T. (2024). Developing language teachers’ professional generative AI competence: An intervention study in an initial language teacher education course. System, 125, 103399. https://doi.org/10.1016/j.system.2024.103399

Prilop, C. N., Mah, D.-K., Jacobsen, L. J., Hansen, R. R., Weber, K. E., & Hoya, F. (2025). Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI-enhanced methods. Computers and Education: Artificial Intelligence, 9, 100471. https://doi.org/10.1016/j.caeai.2025.100471

Sakai, H., & Uchino, S. (2018). A questionnaire survey of university students in a primary school teacher training program: Identifying core curricula achievement gaps. JES Journal, 18, 100–115.

Schonberg, C., Becker, M. H., An, X., & Bashkov, B. M. (2025). Spaced learning supports productive struggle in an online learning platform. Technology, Knowledge and Learning. Advance online publication. https://doi.org/10.1007/s10758-025-09914-x

Shimatani, H., & Okazaki, S. (2024). Anxiety factors of teacher training course students in teaching elementary school English. Bulletin of the Faculty of Education, Kumamoto University, 73, 69-76.

Son, T., Yeo, S., & Lee, D. (2024). Exploring elementary preservice teachers’ responsive teaching in mathematics through an artificial intelligence-based chatbot. Teaching and Teacher Education, 146, 104640. https://doi.org/10.1016/j.tate.2024.104640

Sugianto, A., & Khoirunnisa, S. F. (2024). From teacher talk to embodied actions: Investigating an EFL primary school teacher’s classroom interactional competence. Journal of English Language Teaching and Linguistics, 9(3), 269–285.

Tegero, M. C., & Mabini, J. P. (2025). AI chatbot simulations in teacher training: Core teaching competencies developed through virtual practice. Journal of Teaching and Learning, 19(4), 216–232. https://doi.org/10.22329/jtl.v19i4.10087

Toi, K., & Yamauchi, Y. (2022). Instructions to introduce language activities in elementary school English: An investigation of pre-service teachers. JASTEC Journal, 41, 113-124.

Vazquez, S. R., Ermeling, B. A., & Ramirez, G. (2020). Parental beliefs on the efficacy of productive struggle and their relation to homework-helping behavior. Journal for Research in Mathematics Education, 51(2), 179–203.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Williams, K., & Murray, D. (2025). Proposing grounded theory as a method to facilitate and extend reflective practice. Higher Education. Advance online publication. https://doi.org/10.1007/s10734-025-01516-x

Xia, Q., Li, W., Yang, Y., Weng, X., & Chiu, T. K. F. (2025). A systematic review and meta-analysis of the effectiveness of generative artificial intelligence (GenAI) on students’ motivation and engagement. Computers and Education: Artificial Intelligence, 9, Article 100455. https://doi.org/10.1016/j.caeai.2025.100455

Yonezaki, M., Tara, S., & Tsukuda, Y. (2016). Primary school teachers’ anxiety about teaching English as a compulsory subject and teaching English to middle-grade students: Structuring and transition. JES Journal, 16, 132-146.




DOI: http://dx.doi.org/10.21462/jeltl.v11i1.1929

Refbacks

  • There are currently no refbacks.




JELTL (Journal of English Language Teaching and Linguistics); Web: www.jeltl.org; Email: journal.eltl@gmail.com

Creative Commons License
JELTL by http://www.jeltl.org is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License


Indexed and Abstracted BY: