Published June 21, 2025 | Version v1

TEACHERS' PERCEPTIONS OF AI TOOLS IN ENGLISH LANGUAGE EDUCATION: OPPORTUNITIES AND ETHICAL CONCERNS

  • 1. 3rd year student, Foreign language and literature (English), faculty of Languages, Termez state pedagogical institute

Description

The integration of Artificial Intelligence (AI) tools in English Language Education
(ELE) presents numerous opportunities for enhancing teaching and learning processes. This study
explores teachers’ perceptions regarding the benefits and ethical challenges associated with AI
implementation in ELE. Using a mixed-methods approach, findings reveal that while educators
acknowledge AI’s potential to personalize learning and provide instant feedback, concerns about data
privacy, bias, and teacher roles persist. The paper concludes with recommendations for balanced AI
integration respecting pedagogical and ethical standards. This study also explores the influence of
cultural and institutional factors on teachers' acceptance of AI tools. It reveals a generational divide
in attitudes, with younger educators showing greater enthusiasm and adaptability towards technology
integration. Ultimately, the research provides actionable insights for policymakers, curriculum
developers, and teacher trainers aiming to foster ethical and effective AI adoption in English language
classrooms

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References

  • 1. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
  • 2. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson.
  • 3. Zhang, J., & Chen, L. (2020). Ethical challenges of artificial intelligence in education: A review. Technology, Knowledge and Learning, 25(4), 575–588
  • 4. Wu, Y., & Wang, H. (2021). Teachers' attitudes towards AI-powered language learning tools: A case study. Computer Assisted Language Learning, 34(7), 806–825
  • 5. Williamson, B., & Piattoeva, N. (2020). Objectivity as standardization in data-scientific educational governance: Grasping the global through the local. Research in Education, 101(1), 60–81.