Purposeful remixing with generative AI: Constructing designer voice in multimodal composing

Abstract

In multimodal writing, students can mobilize both linguistic and non-linguistic resources to express their real or imagined identities. But at the same time, when students are limited to choosing from available online resources, their voices might be compromised due to the incompatibility between their authorial intentions and the materials available to them. This study, therefore, investigates whether the use of generative AI tools could help student authors construct a more consistent voice in multimodal writing. In this study, we have designed a photo essay assignment where students recount a story in the form of photo essays and prompt AI image-generating tools to create photos for their storytelling. Drawing on interview data, written reflections, written annotations, and multimodal products from seven focal participants, we have identified two remixing practices–layering and blending–through which students attempted to establish a coherent and unique voice in writing. The study sheds light on the intentional and discursive nature of multimodal writing with AI as afforded by the technological flexibility, while also highlighting the practical and ethical challenges that could be attributed to students’ insufficient prompt and multimodal literacy and the innate limitations of AI systems. This study provides important implications for incorporating AI tools in designing multimodal writing tasks.