Fostering Fine‐Tuned Prompt Literacy for Multimodal Writing: A Systemic Functional Linguistics‐Informed Framework

Abstract The rise of GenAI‐powered image generation tools presents new opportunities for English learners to engage in digital multimodal composing (DMC) in both creative and critical ways. At the same time, it calls for a reconceptualization of DMC pedagogy in language education. In this article, we build on the concept of fine‐tuned prompt literacy (Kang & Yi, 2023) in the context of GenAI‐assisted multimodal writing and introduce a pedagogical framework informed by Systemic Functional Linguistics (SFL) to support its development and implementation. We conceptualize fine‐tuned prompt literacy at the intersection of multimodal literacy and GenAI literacy, emphasizing the need for students to envision meaningful GenAI outcomes and engage with GenAI tools critically and strategically. Drawing on our research on ESL students' photo essay creation with GenAI image generators, we show that separating instruction on multimodal and GenAI literacies may hinder students' process of creating multimodal resources in an intentional and rhetorically effective way. To address this gap, we present an SFL‐informed framework that guides students in designing prompts based on the ideational, interpersonal, and textual metafunctions. Teaching observation and students' writing from a first‐year ESL writing course illustrates the framework's potential to enhance GenAI‐integrated DMC instruction. This brief report offers both theoretical insights and practical strategies for teaching multimodal writing in the era of GenAI.