Integration Pathways of AI-Generated Tools and Cultivation of Instructional Innovation Competencies in Pre-Service Teacher Preparation: A Literature Review and Practical Implications

Abstract

With the rapid iteration of generative artificial intelligence technology, AI-generated tools have become a core variable reshaping the education ecosystem and have also placed new demands on the competency structure of pre-service teachers. This study, based on domestic and international literature on the application of AI-generated tools in pre-service teacher education, employs an integrative literature review approach to examine existing research findings from four aspects: the connotation of core concepts, the current state of cognitive application, curriculum integration paths, and competency development dimensions. Given the rapidly evolving nature of the topic and the limited pool of empirical studies available, an integrative review design was chosen over a full systematic review to allow for critical synthesis of both empirical and conceptual works.The study finds that the academic community has formed a hierarchical conceptual system of AI literacy and AI competency, constructing three typical integration paths: curriculum embedding, workshop intervention, and practical penetration. However, pre-service teachers generally suffer from low levels of AI application, a disconnect between theoretical understanding and teaching practice, and insufficient ethical critical thinking. Based on these findings, this paper proposes practical strategies such as a hierarchical and progressive competency development system and a closed-loop “theory-practice-reflection” training model.