AI-Generated Culturally Adaptive Visual Aids in Vocabulary Learning and Retention among Iranian High School EFL Learners: A Conceptual Framework

This conceptual paper suggests a framework for understanding the role of culturally adaptive AI-generated visual aids in vocabulary learning and retention among Iranian high school EFL learners. Drawing on Dual Coding Theory, Schema Theory, and the Cognitive Theory of Multimedia Learning, this paper argues that using culturally familiar images generated by AI may facilitate vocabulary learning by activating learners' prior knowledge and strengthening their verbal and visual memory representations, thereby reducing cognitive load and enhancing engagement with learning materials. The paper also explores how the recent developments of generative AI have made it possible for teachers to produce high-quality culturally responsive content for instruction that would have been hard to create using traditional media. The paper draws on the recent research literature in the fields of AI in language learning, culturally responsive pedagogy, and multimedia learning to describe the theoretical mechanisms by which culturally adaptive AI-generated visuals might improve vocabulary acquisition and retention. Finally, the paper discusses implications for EFL teachers and materials developers. It also suggests possible directions for future empirical research that could further explore the use of AI-generated content in vocabulary learning within the framework of culturally adaptive pedagogy.

Keywords:

AI-generated visuals , culturally adaptive materials , vocabulary learning , vocabulary retention , schema theory , EFL