Abstract Summary/Description
In the field of teaching English as a second language, generative AI systems are increasingly being positioned as a “solution” to pedagogical problems. While these systems claim to increase the efficiency of teaching, their potential to resolve the core dilemmas of ESL educators, to facilitate meaningful peer interaction and support mixed-level classes, remains unclear. The study employed an environmental scan to catalog generative AI tools designed for English language teaching and qualitative thematic analysis of claims about their benefits made in selected promotional materials. These claims were compared with existing studies of dilemmas in language teaching. Preliminary results suggest that while these systems prioritize efficiency and customizability in content generation, they often rely on generalized templates and outputs, which may fail to accommodate the linguistic diversity and unique contexts of classrooms. For instance, while certain online platforms and tools can generate teaching materials based on instructors’ needs, it is questionable whether they can resolve issues arising from the students of different proficiency levels and linguistic backgrounds. Moreover, this reliance on AI-generated materials risks promoting generic content and reinforces a standardized and franchised approach to language education. Accordingly, critical AI literacy among language teachers is essential to mitigate the risks associated with overusing formulaic, AI-generated materials as a replacement for teachers’ expertise. Generative AI systems should also be adapted to the domain specific challenges of language teaching. This study challenges educators to reconsider the role of AI as a partner in addressing-not bypassing-complex teaching challenges.
