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Lookup NU author(s): Dr Müge SatarORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Multimodal (inter)action analysis offers a powerful and robust methodology for the study of action and interaction between social actors, their environment, and the objects and tools within. Yet its implementation in the analysis of synchronous multimodal online data sets, e.g. (inter)actions via videoconferencing, is limited. Drawing on our research in understanding teacher-learner (inter)actions in instruction-giving fragments in synchronous multimodal online language lessons, we describe and illustrate the ways in which we adapted and extended some of the methodological and analytical tools. These include (1) the use of a grounded theory approach in delineating and identifying higher-level actions, (2) the embodiment and disembodiment of frozen actions, (3) electronic print mode, (4) semiotic lag, (5) semiotic (mis)alignment, (6) modal density (mis)alignment, and (7) how modal density can be achieved by brisk modal shifts in addition to through modal intensity and complexity. We conclude by a call for further educational research in online teaching platforms using the framework to have richer understandings of the (inter)actions between social actors with particular roles and identities (teachers-learners), their environment, and the objects and tools within, which bring their “own material properties, feel and techniques of use, affordances and limitations” (Chun, Kern, & Smith 2016: 65).
Author(s): Wigham CR, Satar M
Publication type: Article
Publication status: Published
Journal: Multimodal Communication
Year: 2024
Pages: ePub ahead of Print
Online publication date: 08/08/2024
Acceptance date: 19/07/2024
Date deposited: 22/07/2024
ISSN (print): 2230-6579
ISSN (electronic): 2230-6587
Publisher: De Gruyter Mouton
URL: https://doi.org/10.1515/mc-2024-0048
DOI: 10.1515/mc-2024-0048
Data Access Statement: Full size image for Extract 1 are available at https://doi.org/10.25405/data.ncl.20315142, see Extract 4.3
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