Building knowledge through images in physics

Bibliographic Data

ID12700151
AuthorsYJ Doran (The University of Sydney, corresponding author)
Year2018
Volume18
Issue2
Pages251-277
Publication date2018-03-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueVisual Communication (JOURNAL)
Journal identifiersISSN: 1470-3572 • E-ISSN: 1741-3214
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/1470357218759825
OpenAlexW2791118303
LanguageEN
Citations received9
References cited13

This article considers the role of images in physics. Utilizing the Systemic Functional Linguistic dimension of field it shows that diagrams that present large classification and composition taxonomies as well as long sequences of activities can be overlaid upon graphs that show arrays of ordered data. Through an analysis using the concepts of semantic density and semantic gravity from Legitimation Code Theory, it is argued that this allows images to present large degrees of meaning in a single snapshot whilst also linking abstracted theory to specific instances of data. That is, the analysis shows that images play a significant role in developing technical physics knowledge through abstractions away from the empirical world. This article contributes to the growing body of research focusing on the structuring of knowledge and the non-linguistic semiotic resources used to organize it

Body of knowledge · Data science · Epistemology · Field (mathematics · Knowledge management · Legitimation · Linguistics · Semiotics · Structuring · Computer Science · Discourse Analysis in Language Studies · Educational Theory and Curriculum Studies · Mathematics · Second Language Learning and Teaching · Artificial Intelligence

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