Constructing translanguaging spaces through GenAI-assisted digital multimodal composing: a virtual ethnography on platform language teacherpreneurs

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Authors: Yunan Zhang, Lianjiang Jiang
Cited by: 1
References: 44

Abstract

Recent years have witnessed the emergence of language teachers who engage in piecemeal and digitally mediated work on online platforms, referred to as platform language teacherpreneurs, who have received little scholarly attention. Addressing this gap, this study conceptualises the video-making practices of online language teachers as digital multimodal composing (DMC) and examines how they engage in GenAI-assisted DMC. We conducted a virtual ethnography of the GenAI-assisted DMC practices of two teachers on a Chinese digital platform, within which GenAI assisted multimodal production of online videos. Findings revealed that the two teacherpreneurs have translanguaged through GenAI, remixed local cultural resources, and crafted metaphorical cultural figures: an AI-generated child figure and AI-voiced historical characters. They have then constructed a GenAI-empowered translanguaging space and branded themselves respectively as a child English teacher with AI-Generated Content (AIGC) expertise and a ‘Zhenhuan’ scholar for joyful learning. Yet, combined with the viewers’ comments, our analysis suggests that the translanguaging space is more for attention-grabbing and entertaining than for pedagogical effectiveness. These practices suggest that GenAI-assisted DMC functions not only as a pedagogical tool but increasingly as a platformised branding practice and call for attention to balancing the pedagogical values and marketing purposes when engaging with GenAI-assisted DMC in the online language teaching industry.

Fields of Study & Subjects

Multilingual Education and Policy Literacy Media and Education Second Language Learning and Teaching

Publication details

Journal / source
Journal of Multilingual and Multicultural Development
Publisher
Informa UK Limited
Pages
1–26
Publication date
19 May 2026
Language
EN