Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Preparing to teach in the age of AI: insights from pre-service English teachers
0
Zitationen
3
Autoren
2025
Jahr
Abstract
Artificial intelligence (AI) is rapidly transforming language education, prompting growing interest in how pre-service teachers adopt and reflect on its classroom applications. This study investigates how pre-service English language teachers in Türkiye engage with AI tools in their academic and instructional practices, with a focus on their usage patterns, pedagogical interpretations, and ethical considerations. A qualitative research design was employed, drawing on semi-structured interviews with pre-service English teachers enrolled in teacher education programs. Thematic analysis was conducted to identify key trends and critical insights. Findings reveal that participants widely used AI tools such as ChatGPT for generating lesson content, supporting academic writing, and enhancing classroom engagement. Many appreciated AI’s role in reducing workload, stimulating creativity, and providing personalized learning opportunities. However, participants also expressed concerns over AI’s accuracy, its potential to hinder learners’ critical thinking, and risks of over-dependence. Ethical dilemmas—especially regarding plagiarism, bias, and misinformation—were frequently noted. Participants emphasized the need for structured training that integrates both pedagogical and ethical dimensions of AI use. They consistently argued that AI should remain a supportive tool rather than a replacement for human teaching, reaffirming the teacher’s central role in facilitating responsible integration. The participants demonstrated both enthusiasm and critical awareness in their use of AI. Their reflections highlight an urgent need for AI literacy in teacher education—grounded not only in technical competence but also in ethical reasoning and pedagogical fit—to prepare them for the realities of AI-enhanced classrooms
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.