Multiliteracies for generative artificial intelligence-assisted digital multimodal composing: A technology-in-practice approach

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University of Hawaii National Foreign Language Resource Center
Center for Language & Technology

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Language Learning & Technology

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30

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1

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1

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13

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With recent trends toward integrating generative artificial intelligence (GenAI) in the second language (L2) classroom, there has been a surge of research on using chatbots for language learning and teaching. However, GenAI chatbots are now starting to be examined in digital multimodal composing (DMC). DMC has been explored markedly over the past decade and provides an opportunity to examine how multiliteracies can be integrated in GenAI-assisted DMC. In this technology in practice forum, the benefits and challenges of integrating GenAI-assisted DMC are reported. Implemented in an American university-based intensive English program in the Pacific context, the GenAI-assisted DMC project was employed in a eight-week upper-beginning English as a Second Language class through a multiliteracies framework–consisting of situated practice, overt instruction, critical framing, and transformed practice–drawing on pedagogical components for storytelling. The students created artifacts for future participants in the program. Reflections from the students indicate that engagement was sustained throughout the DMC process. However, the learners struggled with prompting the GenAI chatbot of their choice during the DMC task. By reflecting on opportunities to integrate GenAI-assisted DMC, this forum provides an example of how GenAI can be implemented in classrooms and the procedural steps involved in such a process. Lessons learned from this process are also discussed, which can be improved upon by future iterations.

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Tang, A. F., & Honeycutt, D. B. (2026). Multiliteracies for generative artificial intelligence-assisted digital multimodal composing: A technology-in-practice approach. Language Learning & Technology, 30(1), 1–13. https://doi.org/10.64152/10125/73671

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13

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