Oct 2026· International Journal of Instruction· 0 citations· 52 references
TL;DR
To advance CDMC as an integral part of EFL teaching and bridge the research-practice divide, this review calls for systemic support through targeted teacher development, curriculum and assessment reform, and inclusive infrastructure planning in the field.
Abstract
This systematic review investigates the integration of collaborative digital multimodal composing (CDMC) in EFL classrooms. Following the PRISMA guidelines, a systematic literature search was conducted in Scopus, Social Sciences Citation Index (SSCI), and EBSCO databases to identify 45 empirical studies published between 2013 and 2024. Data were extracted and synthesized using thematic synthesis. This paper identifies key trends, learning outcomes, and implementation challenges in diverse educational contexts. Findings reveal a significant increase in CDMC studies since 2020, predominantly in East Asian tertiary contexts. Task designs have evolved from digital storytelling to more complex multimedia and AI-enhanced compositions. Reported learning outcomes include improved writing proficiency, enhanced genre awareness, development of multimodal and digital literacy, and stronger collaborative skills. However, its implementation is hindered by insufficient teacher training in digital pedagogy, technological and infrastructural obstacles, curricular misalignments with traditional assessment, and complexities in managing student collaboration. To advance CDMC as an integral part of EFL teaching and bridge the research-practice divide, this review calls for systemic support through targeted teacher development, curriculum and assessment reform, and inclusive infrastructure planning in the field. While offering a synthesis of CDMC research, the review is limited by the absence of a formal risk-of-bias assessment and potential publication bias. Finally, it outlines directions for future research, including the investigation of the collaborative process through multimodal conversation analysis, the integration of AI, and the need for longitudinal studies.
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