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Beyond the standard interview: the use of graphic elicitation and arts-based methods

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Bagnoli, Anna·2009·Qualitative Research

Abstract

This article reviews three visual methods based on drawing that I applied in my research on young people: the arts-based projective technique, the self-portrait, and the graphic elicitation methods of the relational map and the timeline. Examples of these methods are drawn from their application in two studies, the Narratives of Identity and Migration project, exploring young people and identities in England and Italy, and the Young Lives and Times. The article argues that applying these drawing methods in the context of an interview can open up participants’ interpretations of questions, and allow a creative way of interviewing that is responsive to participants’ own meanings and associations. The article discusses the analytical potential of graphic elicitation and arts-based methods, by making reference to the insights that they offered in the contextual analysis with more traditional text-based data. The efficacy of these methods is critically discussed, together with their limitations, and their potential within the context of qualitative longitudinal research.

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Metadata

Authors
Bagnoli, A.
Venue
Qualitative Research
Published
2009-11
Volume
9
Issue
5
Pages
547-570
ISSN
  • 1468-7941 (ISSN-L)
  • 1741-3109
OpenAlex
W2125156878
Cited by
910
References
19
FWCI
54.27
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Beyond the standard interview: the use of graphic elicitation and arts-based methods. https://app.cochat.ai/papers/10.1177/1468794109343625
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Bagnoli, A. (2009). Beyond the standard interview: the use of graphic elicitation and arts-based methods. Qualitative Research. https://doi.org/10.1177/1468794109343625

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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.