EMPOWERING FUTURE ENGLISH TEACHERS WITH AI LANGUAGE MODELS: ENHANCING TEACHING COMPETENCE AND LEARNER ENGAGEMENT
Keywords:
Pre-service English teachers, AI language models, teaching competence, learner engagement, personalized learningAbstract
As the demand for effective English language education grows, it is crucial to equip pre-service English teachers with the skills and tools necessary to facilitate meaningful learning experiences. This paper explores the potential of AI language models, such as Claude, to enhance the teaching competence of future English teachers by providing them with innovative, learner-centered teaching strategies and resources. By leveraging the advanced natural language processing capabilities of these models, pre-service teachers can engage in authentic, contextualized language interactions, develop a deeper understanding of learner needs, and create personalized, interactive learning experiences. The paper discusses the key principles of effective language teaching, including fostering learner autonomy, promoting authentic communication, and providing targeted feedback. It also addresses common challenges faced by novice English teachers and how AI language models can help them develop the skills and confidence needed to overcome these challenges. While the integration of AI in teacher education is still an emerging field, initial research suggests that it has the potential to significantly improve pre-service teachers' pedagogical knowledge, technological competence, and ability to engage diverse learners. The paper concludes by outlining future directions for the integration of AI language models in English teacher education and the importance of collaboration between teacher educators, researchers, and AI developers to ensure the effective and ethical implementation of these technologies.
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