The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to ‘seeing’ how science works Article Swipe
María Evagorou
,
Sibel Erduran
,
Terhi Mäntylä
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1186/s40594-015-0024-x
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1186/s40594-015-0024-x
The use of visual representations (i.e., photographs, diagrams, models) has been part of science, and their use makes it possible for scientists to interact with and represent complex phenomena, not observable in other ways. Despite a wealth of research in science education on visual representations, the emphasis of such research has mainly been on the conceptual understanding when using visual representations and less on visual representations as epistemic objects. In this paper, we argue that by positioning visual representations as epistemic objects of scientific practices, science education can bring a renewed focus on how visualization contributes to knowledge formation in science from the learners' perspective. This is a theoretical paper, and in order to argue about the role of visualization, we first present a case study, that of the discovery of the structure of DNA that highlights the epistemic components of visual information in science. The second case study focuses on Faraday's use of the lines of magnetic force. Faraday is known of his exploratory, creative, and yet systemic way of experimenting, and the visual reasoning leading to theoretical development was an inherent part of the experimentation. Third, we trace a contemporary account from science focusing on the experimental practices and how reproducibility of experimental procedures can be reinforced through video data. Our conclusions suggest that in teaching science, the emphasis in visualization should shift from cognitive understanding—using the products of science to understand the content—to engaging in the processes of visualization. Furthermore, we suggest that is it essential to design curriculum materials and learning environments that create a social and epistemic context and invite students to engage in the practice of visualization as evidence, reasoning, experimental procedure, or a means of communication and reflect on these practices. Implications for teacher education include the need for teacher professional development programs to problematize the use of visual representations as epistemic objects that are part of scientific practices.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s40594-015-0024-x
- https://stemeducationjournal.springeropen.com/counter/pdf/10.1186/s40594-015-0024-x
- OA Status
- gold
- Cited By
- 180
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1851436928
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W1851436928Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s40594-015-0024-xDigital Object Identifier
- Title
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The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to ‘seeing’ how science worksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-07-18Full publication date if available
- Authors
-
María Evagorou, Sibel Erduran, Terhi MäntyläList of authors in order
- Landing page
-
https://doi.org/10.1186/s40594-015-0024-xPublisher landing page
- PDF URL
-
https://stemeducationjournal.springeropen.com/counter/pdf/10.1186/s40594-015-0024-xDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://stemeducationjournal.springeropen.com/counter/pdf/10.1186/s40594-015-0024-xDirect OA link when available
- Concepts
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Visualization, Science education, Visual reasoning, Visual analytics, Computer science, Scientific visualization, Perspective (graphical), Epistemology, TRACE (psycholinguistics), Cognitive science, Data science, Mathematics education, Psychology, Artificial intelligence, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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180Total citation count in OpenAlex
- Citations by year (recent)
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2025: 25, 2024: 30, 2023: 28, 2022: 29, 2021: 20Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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