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

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March 13, 2026, 1:05 p.m.

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March 17, 2026, 1:36 a.m.

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March 17, 2026, 1:36 a.m.

access-status:

open.access

bitstream:

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bitstream_txt:

[['https://scholarspace.manoa.hawaii.edu/bitstreams/36a14096-e696-4716-bf2b-8069542354cd/download', 'full_text']]

collection:

Volume 30 Number 1, 2026

contributor.author:

Tang, Alexander Fukin Honeycutt, David Byron

contributor.editor:

Matt Kessler

date.accessioned:

2026-03-13T06:32:08Z

date.available:

2026-03-13T06:32:08Z

date.copyright:

2026

date.issued:

2026-03-16

description.abstract:

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.

endingpage:

13

format.extent:

13

identifier.citation:

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

identifier.doi:

https://doi.org/10.64152/10125/73671

identifier.issn:

1094-3501

identifier.uri:

https://hdl.handle.net/10125/73671

language:

eng

llt.topic:

Technology in Practice

number:

1

publicationname:

Language Learning & Technology

publisher:

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

rights.license:

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

rights.uri:

https://creativecommons.org/licenses/by-nc-nd/4.0/

site_url:

/item/10125-73671/

startingpage:

1

subject:

digital multimodal composing, English as a Second Language, generative artificial intelligence, L2 writing, multiliteracies

title:

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

type:

Column Text

volume:

30