The Qualitative Report· 2015Q1
Are We There Yet? Data Saturation in Qualitative Research
- 4,423citations
- Q1SCImago
- 2015year
Short summary
Qualitative research quality hinges on reaching data saturation, defined as achieving sufficient information for replication and ceasing new coding, which is influenced by study size.
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Key points
- Data saturation is crucial for research quality and content validity.
- Saturation is achieved when a study is replicable and no new information or coding is possible.
- Study size influences the rate at which data saturation is reached.
- The article critiques two qualitative studies regarding their data saturation practices.
AI-generated from the title and abstract; the full text is not read.
Abstract
Failure to reach data saturation has an impact on the quality of the research conducted and hampers content validity. The aim of a study should include what determines when data saturation is achieved, for a small study will reach saturation more rapidly than a larger study. Data saturation is reached when there is enough information to replicate the study when the ability to obtain additional new information has been attained, and when further coding is no longer feasible. The following article critiques two qualitative studies for data saturation: Wolcott (2004) and Landau and Drori (2008). Failure to reach data saturation has a negative impact on the validity on one’s research. The intended audience is novice student researchers.
The authors' abstract, as published at the source. The Qualitative Report, 2015 · DOI ↗
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Field: Education
EducationSocial Sciences