Digital multimodal composing in post-secondary L2 settings: a review of the empirical landscape

Abstract

Driven by the digital revolution in second language (L2) classrooms and broadened views on literacy, digital multimodal composing (DMC) has gained a robust growth of interests in the past decade. To illuminate the empirical landscape of this budding field, this paper provides a substantive and methodological review of 60 empirical L2 studies on DMC in tertiary settings from 2005 to 2020. Each study was coded for characteristics regarding research context, methodology, study setup features, analyses performed, and the methodological practices. Our findings suggest that with a combination of flourishing qualitative observational research and emerging interventionist studies, this domain features (a) great attention to DMC in language classes, (b) an underrepresentation of non-English classrooms, (c) a preference for video projects over visual projects, and (d)immense efforts in exploring the potential of DMC from learners’ perspectives. Also, using a broad range of data sources, this domain relies on analytic frameworks distinct from traditional monomodal L2 writing. Methodologically, we found a strength in the use of two validity strategies (i.e., a thick description and triangulation) and less-than-ideal practices in reporting reliability and learners’ proficiency level. We conclude the paper with a number of empirically grounded recommendations for future research efforts.

Supplemental data for this article is available online at https://doi.org/10.1080/09588221.2021.1942068.

Keywords:

• Digital composing
• L2 writing
• methodological synthesis
• multimodal writing
• systematic review

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The fuller representation of quantitative research likely relates to the fact that methodological reviews originated from meta-analysis (Norris & Ortega, 2000), a technique relying on numeric data.

2 In a few studies (e.g., Jiang, Yang, & Yu, 2020), the multimodal products were mentioned as a type of data source although they were not analyzed and only served as supplementary data sources.

Additional information

Notes on contributors

Meixiu Zhang

Meixiu Zhang (PhD., Northern Arizona University) is Assistant Professor of Applied Linguistics at Texas Tech University, where she teaches courses in applied linguistics to both graduate and undergraduate students. Her primary research areas include second language writing, corpus linguistics, and instructed second language acquisition. Her work has appeared in journals such as Journal of Second Language Writing, Language Teaching Research, System, and Corpora.

Miriam Akoto

Miriam Akoto is a PhD candidate in the Applied Linguistics program at Texas A&M University-Commerce. Her research interests are centered on second/foreign language writing and computer-assisted language learning. She is particularly interested in computer-mediated interaction, peer-assessment/feedback, collaborative writing and multimodal composition within the French as a FL context.

Mimi Li

Mimi Li, PhD., is an Assistant Professor of Applied Linguistics/TESOL in the Department of Literature and Languages at Texas A&M University-Commerce. Her main research areas are second language writing and CALL. She has conducted research projects on online collaborative writing, computer-based instructor and peer feedback, gamification and vocabulary learning, and multimodal pedagogy in teacher education. Her work has appeared in Journal of Second Language Writing, Computer Assisted Language Learning, Language Learning & Technology, Language Teaching, System, Computers & Education, and Computers and Composition, among others.