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Challenging anthropocentric analysis of visual data: a relational materialist methodological approach to educational research

Hultman, Karin, Lenz Taguchi, Hillevi·2010·International Journal of Qualitative Studies in Education

Abstract

The purpose of this paper is to challenge the habitual anthropocentric gaze we use when analysing educational data, which takes human beings as the starting point and centre, and gives humans a self‐evident higher position above other matter in reality. By enacting analysis of photographic images from a preschool playground, using a relational materialist methodological approach, we put to work concepts that open up possibilities to understand the child as emergent in a relational field, where non‐human forces are equally at play in constituting children's becomings. In the second part of the paper, we discuss how the decentring of the child may also be applied to researchers as producers of knowledge. Such a decentring, where the data itself is considered to have a constitutive force and be working upon the researcher as much as the researcher works upon the data, has both methodological and ethical consequences for research.

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Metadata

Authors
Hultman, K., & Lenz Taguchi, H.
Venue
International Journal of Qualitative Studies in Education
Published
2010-09
Volume
23
Issue
5
Pages
525-542
ISSN
  • 0951-8398 (ISSN-L)
  • 1366-5898
OpenAlex
W2061627790
Cited by
549
References
40
FWCI
472.68
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Challenging anthropocentric analysis of visual data: a relational materialist methodological approach to educational research. https://app.cochat.ai/papers/10.1080/09518398.2010.500628
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Hultman, K., & Lenz Taguchi, H. (2010). Challenging anthropocentric analysis of visual data: a relational materialist methodological approach to educational research. International Journal of Qualitative Studies in Education. https://doi.org/10.1080/09518398.2010.500628

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.