Communications in Humanities Research ISSN: 2753-7072
Home> Volumes> Volume CHR Vol.104> Article
Research Article

Artificial Intelligence in English Speaking Instruction: Learner Impacts and Teacher Role Reconstruction

Xinyu HuNanjing University of Science and Technology Ruotong QiuSoochow University*

* Corresponding author: [email protected]

Abstract

The rapid development of artificial intelligence, especially generative AI and intelligent voice technology, has profoundly reshaped the landscape of English oral language teaching. Increasing research indicates that using AI-assisted teaching can increase opportunities for oral practice, improve feedback efficiency, and alleviate learners' anxiety about oral expression. However, new research also points out persistent limitations in pragmatic depth, cultural context, interaction authenticity, and ethical issues. These mixed research results suggest that a systematic review of both positive and negative aspects has been conducted, focusing on its impact on learners' oral performance, learning experience, psychological factors, and self-regulation. This review reveals a dual influence model: AI effectively supports the development of basic oral skills and learning autonomy, but still has limitations in cultivating higher-level communicative and pragmatic abilities. Based on these findings at the learner level, this paper further explores how the integration of AI needs to fundamentally reshape the role of English oral language teachers. Specifically, it analyzes the evolution of teachers' roles as instructional designers, pragmatic ability assessors, emotional facilitators, and ethical guardians in the context of AI-assisted teaching. By integrating evidence from both learners' and teachers' perspectives, this review aims to provide theoretical insights for the responsible integration of AI in English oral language teaching and practical implications for the professional development of teachers in the era of human-AI collaboration.

Keywords: English speaking instruction; AI-assisted language learning; learner outcomes; teacher role reconstruction; human–AI collaboration
Published: February 24, 2026
DOI: 10.54254/2753-7064/2026.HT31925
Volume: CHR Vol.104
pp. 82-91
Download PDF

References

  1. Dai, D. W., Suzuki, S., & Chen, G. (2025). Generative AI for professional communication training in intercultural contexts: Where are we now and where are we heading? Applied Linguistics Review, 16(2), 763–774. https: //doi.org/10.1515/applirev-2023-XXXX
  2. Ding, D., & Yusof, M. B. (2025). Investigating the role of AI-powered conversation bots in enhancing L2 speaking skills and reducing speaking anxiety: A mixed methods study. Humanities and Social Sciences Communications, 12(1), 1–16. https: //doi.org/10.1057/s41599-024-XXXX
  3. Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 6–13.
  4. Holmes, J., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2021). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 31(4), 527–563. https: //doi.org/10.1007/s40593-021-00239-1
  5. Kang, H. (2022). Effects of artificial intelligence (AI) and native speaker interlocutors on ESL learners' speaking ability and affective aspects. Multimedia-Assisted Language Learning, 25(2).
  6. Latip, A., Robandi, B., Amaliah, A., Khakim, R. R., & Fatonah, N. (2023). Technical pedagogical content knowledge (TPACK) framework for science teachers' competences in facing global challenges and issues: A narrative literature review. International Journal of Pedagogy and Teacher Education, 7(1), 45–57. https: //doi.org/10.20961/ijpte.v0i0.74699
  7. Latip, N. H., Wardoyo, R., & Setyaningrum, R. (2023). Teacher pedagogical wisdom in AI-integrated language classrooms: Re-examining the TPACK framework. Journal of Educational Technology & Society, 26(3), 45–56. https: //doi.org/10.14789/jets.26.3.4
  8. Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https: //doi.org/10.1111/j.1467-9620.2006.00684.x
  9. Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: Illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14, 1255594. https: //doi.org/10.3389/fpsyg.2023.1255594
  10. Schiff, D. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https: //doi.org/10.1007/s40593-021-00270-2
  11. Wardoyo, R., Latip, N. H., & Setyaningrum, R. (2025). From tech users to ecosystem architects: Teacher roles in AI-supported language learning. Language Teaching Research, 29(1), 112–128. https: //doi.org/10.1177/1362168824123456
  12. Yan, Y., Liu, H., & Chau, T. (2025). A systematic review of AI ethics in education: Challenges, policy gaps, and future directions. Journal of Global Information Management, 33(1), 1–50.
  13. Zou, B., Du, Y., Wang, Z., Chen, J., & Zhang, W. (2023). An investigation into artificial intelligence speech evaluation programs with automatic feedback for developing EFL learners' speaking skills. SAGE Open, 13(3), 21582440231193818. https: //doi.org/10.1177/21582440231193818
  14. Zou, B., Liviero, S., Ma, Q., Zhang, W., Du, Y., & Xing, P. (2024). Exploring EFL learners' perceived promise and limitations of using an artificial intelligence speech evaluation system for speaking practice. System, 126, 103497. https: //doi.org/10.1016/j.system.2024.103497