Designing Knowledge Dissemination in a Digital Era – Analysing TED Talk’s Multimodal Orchestration

Authors

  • Jingxin Jiang Chongqing Open University
  • Fei Victor Lim Nanyang Technological University

DOI:

https://doi.org/10.21432/cjlt28263

Keywords:

online learning, TED talks, speech, images, gestures, multimodal discourse analysis

Abstract

Online learning has gained increasing attention during the COVID-19 pandemic. Teachers face social exigencies to design ways of knowledge dissemination in online instruction. We posit that understanding how knowledge can be represented in successful online academic genres can inform teachers on how they can design students’ online learning experiences. This study examined how scientific knowledge is disseminated in one of the most widespread academic genres, TED Talks, which share discoursal similarities with other academic genres such as online lectures. This study adopted a systemic functional multimodal discourse analysis approach to explore how a presenter used speech, images, and gestures to disseminate knowledge. The analysis shows that a presenter orchestrates speech, images, and gestures strategically to clarify the scientific ideas and engage the audience. Based on understanding how the three semiotic modes are used to disseminate scientific knowledge in accessible and engaging ways, this paper discusses how insights on multimodal orchestration can function as a heuristic tool to inform design in online learning.

Author Biographies

Jingxin Jiang, Chongqing Open University

Jingxin Jiang is an Associate Professor at Chongqing Open University, China, and Ph.D. candidate at the National Institute of Education, Nanyang Technological University, Singapore. Her research interest is multimodal discourse analysis, multiliteracy, and online learning.

Fei Victor Lim, Nanyang Technological University

Fei Victor Lim is an Assistant Professor at the National Institute of Education, Nanyang Technological University, Singapore. He researches and teaches on multiliteracies, multimodal discourse analyses, and digital learning.

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Published

2022-11-29