Exploring prompt iteration process through generative AI image creation in EFL vocabulary learning

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초록

Amid the growing use of GenAI in second language education and its emerging multimodality, this study investigated how Korean undergraduates studying EFL enacted prompt iteration with a text-to-image generator to support multimodal vocabulary learning. Participants read etymology-rich word stories, sketched visualizations, and iteratively refined prompts until the images aligned with their intentions. Data included AI-generated artworks, reflective papers documenting the process, and a vocabulary learning strategies survey. Overall, learners reported high use of strategies after the task. Analysis of artworks and reflections revealed a metacognitive-strategic cycle: learners monitored and evaluated outputs, then strategically varied contextual features to negotiate meaning and achieve nuanced imagery. Framed as both a prompt-engineering technique and a literacy practice involving planning, monitoring, and evaluation, prompt iteration emerged as central to GenAI-mediated vocabulary learning, highlighting learners' agency in exploring word meanings.

키워드

artificial intelligence literacygenerative artificial intelligenceprompt iterationvocabulary learning strategiesSTRATEGIESLANGUAGECOMPREHENSIONACQUISITIONGLOSSES
제목
Exploring prompt iteration process through generative AI image creation in EFL vocabulary learning
저자
Hwang, YohanLee, Jang HoShin, Dongkwang
DOI
10.1515/iral-2025-0089
발행일
2025-11
유형
Article; Early Access
저널명
IRAL - International Review of Applied Linguistics in Language Teaching