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Cited by 329

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Fitting the Methodology with the Research: An exploration of narrative, self-study and auto-ethnography

Hamilton, Mary Lynn, Smith, Laura, Worthington, Kristen·2008·Studying Teacher Education

Abstract

Sharpening our approaches to methodology in self-study research can strengthen our work and clarify questions that arise for readers unfamiliar with this research genre. Our article considers three methodologies – narrative, auto-ethnography and self-study – that privilege self in the research design, believing that addressing self can contribute to our understandings about teaching and teacher education. We address two questions: In what ways, if any, does the methodological choice affect the inquiry of the researchers? When, if ever, might self-study be the best choice for inquiry? For this, we use one selected work to explore the critical elements of these methodologies to determine usefulness. This is not a discussion to determine which approach is better; rather it is a discussion to explore when one method might be privileged over another and why.

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Metadata

Authors
Hamilton, M. L., Smith, L., & Worthington, K.
Venue
Studying Teacher Education
Published
2008-05
Volume
4
Issue
1
Pages
17-28
ISSN
  • 1742-5964 (ISSN-L)
  • 1742-5972
OpenAlex
W2107839500
Cited by
329
References
49
FWCI
27.19
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fitting the Methodology with the Research: An exploration of narrative, self-study and auto-ethnography. https://app.cochat.ai/papers/10.1080/17425960801976321
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Hamilton, M. L., Smith, L., & Worthington, K. (2008). Fitting the Methodology with the Research: An exploration of narrative, self-study and auto-ethnography. Studying Teacher Education. https://doi.org/10.1080/17425960801976321

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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.