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March 20, 2024System210 citationsOpen Access

The effects of generative AI on initial language teacher education: The perceptions of teacher educators

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BMBenjamin Luke MoorhouseLKLucas Kohnke

Key Points

  • Generative AI tools significantly impact the initial language teacher education curriculum, instruction, and assessment.
  • Thirteen teacher educators from Hong Kong universities provided insights through interviews, revealing their perceptions.
  • The study highlights a lack of confidence among educators to address generative AI implications effectively and adapt ILTE accordingly. Further research is necessary to enhance their skills and understanding of this technology's influence.

Abstract

Since the public release of ChatGPT in November 2022, generative AI tools—capable of creating human-like content such as audio, code, images, text, simulations, 3D objects, and videos—have gained significant attention. While the impact of these tools on language teaching and learning has been widely speculated, the perspective of language teacher educators concerning their influence on initial language teacher education (ILTE) remains unexplored. This study investigates how teacher educators, who play a crucial role in adapting ILTE to technological advancements, perceive the effects of generative AI tools on ILTE. Data were collected through in-depth interviews with thirteen English language teacher educators from all four Hong Kong government-funded universities offering ILTE. Findings reveal that participants believe generative AI tools will substantially affect the ILTE curriculum, instruction, and assessment. However, most participants believed they lacked the confidence and competence to address the implications of generative AI tools effectively. This study highlights the need for further research and training to support teacher educators in adapting ILTE to the emerging influence of generative AI.

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Cite This Study

Moorhouse et al. (2024) studied this question.

synapsesocial.com/papers/68e732b8b6db6435876aba47https://doi.org/10.1016/j.system.2024.103290
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