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Generative AI in career English integrated education for K-12 teacher training: Insights from university student feedback

  • Modern English Education
  • Abbr : MEESO
  • 2024, 25(), pp.343~360
  • Publisher : The Modern English Education Society
  • Research Area : Humanities > English Language and Literature > English Language Teaching
  • Received : August 31, 2024
  • Accepted : September 30, 2024
  • Published : November 7, 2024

HyeJin Lee 1 Im, Jae-hyun 2

1원광대학교
2대구교육대학교

Accredited

ABSTRACT

This study investigates the use of generative AI in career English integrated education for K-12 teacher training, carried out in two stages. In the first stage, university students with various majors participated in AI-based career English integrated lessons. Feedback from these students led to refinement of AI tools, including a shift from Poe AI to Mizou AI for better accessibility and functionality. In the second stage, various AI tools were introduced to elementary and secondary teachers, guiding them on personalizing career English integrated education. Results showed that elementary teachers responded more positively and consistently, while secondary teachers, in contrast, identified challenges, particularly with the rigid, grade-based evaluation systems. Specifically, elementary teachers rated career decision-making and subject interest higher than secondary teachers, although their differences were not statistically significant (p > 0.05). These results suggest that while AI tools can offer promising solutions for integrating career education into English teaching, their effectiveness is contingent on flexibility of existing evaluation systems and adapting AI tools to classroom-specific contexts. Additionally, this study highlights the need for ongoing professional training for teachers to better integrate AI technologies into their pedagogy, ensuring they can utilize these tools effectively across diverse educational settings.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.