Teacher Perceptions of GenAI ‐Integrated Digital Storytelling for Refugee‐Background Youth

Abstract Digital storytelling (DST), the composing of 2–3 minute first‐person digital multimodal narratives, integrating photographs, video clips, voice‐over, text, and music related to personal experiences, is arguably one of the most powerful forms of digital multimodal composing (DMC). Expanding the range of modes (e.g., images, sounds, multiple languages) through which they can share their personal experiences, DST can be particularly transformative for refugee‐background youth. As GenAI is increasingly integrated into DMC practices, its potential impact on DST, particularly for refugee‐background youth, needs to be examined. Guided by sociomaterial and multimodal approaches to literacies, this empirical, qualitative case study examines the perceptions of seven Canadian English as an Additional Language teachers regarding GenAI‐integrated DST for the education of refugee‐background youth, through engaging the teachers in their own GenAI‐integrated DST. Our reflexive thematic analysis resulted in two key themes: (1) A reimagined, transformative composing process; (2) concerns about human–AI entanglement in DST. Teachers highlighted how GenAI‐integrated DST with refugee‐background learners, while holding transformative potential, requires carefully sequenced and critically scaffolded pedagogy that begins from learners' own voices, languages, experiences, and relationships, prioritizing their sense of identity, safety, and human connection. We discuss results and implications for educators, teacher educators, and researchers.

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Publication Details

Journal
TESOL Quarterly
Published
2026-08-24
DOI
https://doi.org/10.1002/tesq.70217
Primary Topic
Digital Storytelling and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Teacher Perceptions of GenAI ‐Integrated Digital Storytelling for Refugee‐Background Youth

Amir Michalovich, Shawn Porteous
TESOL Quarterly
Digital Storytelling and Education
article

Teacher Perceptions of GenAI ‐Integrated Digital Storytelling for Refugee‐Background Youth

Amir Michalovich, Shawn Porteous
article en

Abstract

Abstract Digital storytelling (DST), the composing of 2–3 minute first‐person digital multimodal narratives, integrating photographs, video clips, voice‐over, text, and music related to personal experiences, is arguably one of the most powerful forms of digital multimodal composing (DMC). Expanding the range of modes (e.g., images, sounds, multiple languages) through which they can share their personal experiences, DST can be particularly transformative for refugee‐background youth. As GenAI is increasingly integrated into DMC practices, its potential impact on DST, particularly for refugee‐background youth, needs to be examined. Guided by sociomaterial and multimodal approaches to literacies, this empirical, qualitative case study examines the perceptions of seven Canadian English as an Additional Language teachers regarding GenAI‐integrated DST for the education of refugee‐background youth, through engaging the teachers in their own GenAI‐integrated DST. Our reflexive thematic analysis resulted in two key themes: (1) A reimagined, transformative composing process; (2) concerns about human–AI entanglement in DST. Teachers highlighted how GenAI‐integrated DST with refugee‐background learners, while holding transformative potential, requires carefully sequenced and critically scaffolded pedagogy that begins from learners' own voices, languages, experiences, and relationships, prioritizing their sense of identity, safety, and human connection. We discuss results and implications for educators, teacher educators, and researchers.

TESOL Quarterly
Red River College (CA), University of Manitoba (CA)
Social Sciences and Humanities Research Council of Canada
Quality Education
Openalex Percentile: Top 7%
Digital Storytelling and Education
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Teacher Perceptions of GenAI ‐Integrated Digital Storytelling for Refugee‐Background Youth — Amir Michalovich, Shawn Porteous · TESOL Quarterly (2026) | TGRS Research Map | TGRS