Exploring AIGC-Aided Approaches to Multimodal Journalistic Discourse Teaching

With the rapid development of artificial intelligence technology, multimodality has been increasingly applied in the field of foreign language education. Considering the potential of AI-based text-to-image generation, this paper explores methods and pathways to optimize multimodal foreign language teaching, addressing the challenges in the application of multimodal discourse teaching in foreign language classrooms. For instance, some interpretive images are generated from text meanings in sociocultural discourse in order to design the multimodal interactive scenarios for teaching. This approach aims to create a richer, more intuitive and more lively experience of discourse meaning for both teachers and learners. The AI-based image-text interaction presented in this article can help deepen learners’ understanding of discourse and provide a useful reference for improving the effectiveness of multimodal teaching.