Bridging the AI Gap: A Needs Analysis of Chinese Pre-Service EFL Teachers in Developing Intelligent-Technological Pedagogical Content Knowledge

Abstract

This study explores the readiness and learning needs of Chinese pre-service English as a Foreign Language teachers in developing Intelligent-Technological Pedagogical Content Knowledge for the effective integration of AI in English Language Teaching. Using a mixed-methods approach, quantitative data were collected from 253 pre-service English teachers, while qualitative insights were obtained from semistructured interviews with eight participants. The findings show strong levels of Intelligent-Technological Knowledge and Intelligent-Technological Pedagogical Knowledge, but moderate levels in Intelligent-Technological Content Knowledge, Intelligent-Pedagogical Content Knowledge, and ethics. Key learning needs include increasing familiarity with AI tools, designing personalized instruction, incorporating AI into English speaking and listening tasks, and developing cohesive AI-supported pedagogy. Ethical concerns, such as fairness, transparency, and data security, were also highlighted. The study underscores the importance of tailored training programs that integrate AI technologies, pedagogical methods, and ethical considerations to prepare teachers for AI-driven educational environments. While contributing to the growing discourse on AI in teacher education, the study is limited by a small qualitative sample and its focus on Chinese pre-service teachers, which may limit broader applicability. Future research should expand sample sizes, incorporate cross-cultural comparisons, and examine the long-term impact of AI training on teacher competencies and practices.

Keywords: AI readiness, English language teaching, ethics, Intelligent-Technological Pedagogical Content Knowledge, needs analysis, pre-service EFL teachers, teacher education