Achieving saturation in thematic analysis: development and refinement of a codebook.
By H. Ando, R. Cousins, C. Young. 2014
551 citations recorded by the source corpus.
Reaching a saturation point in thematic analysis is important to validity in qualitative studies, yet the process of achieving saturation is often left ambiguous. The lack of information about the process creates uncertainty in the timing of recruitment closure. This exploratory study was conducted to demonstrate a rigorous approach to reaching saturation through two-stage establishment of a codebook used for thematic analysis. The codebook development involved inductive analysis with six interviews, followed by a refinement of the coding system by applying them to an additional 33 interviews. These findings are discussed in relation to plausible pattern in code occurrence rate and suggested sample sizes for thematic analysis. Read More: http://www.amsciepub.com/doi/abs/10.2466/03.CP.3.4
Subfields: Education, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/dcbd41c8db7c093add7f56cca18b9941f323fedf
How researchers see this paper
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In Education
- B. Saunders
- J. Sim
- Thomas K. F. Chiu
- Tom Kingstone
- Ching Sing Chai
- J. Waterfield
- Favourate Sebele Mpofu
In Sociology and Political Science
- B. Saunders
- J. Sim
- Thomas K. F. Chiu
- Tom Kingstone
- Ching Sing Chai
- J. Waterfield
- Favourate Sebele Mpofu
Citations in the corpus
- The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney (2023, unknown): “Moreover, the sample size of 88 in this study is su ffi cient to generate codes for thematic analysis (Ando et al., 2014).”
- The Programmer’s Assistant: Conversational Interaction with a Large Language Model for Software Development (2023, unknown): “We conducted periodic reviews to determine whether we were learning something new from each participant or if we had reached the point of saturation [7].”
- Can sample size in qualitative research be determined a priori? (2018, methodology): “Similarly, empirical studies, such as those by Ando et al. (2014), Francis et al. (2010) and Guest et al. (2006, 2017), are conducted in particular contexts, with specific samples: Ando et al. (2014) interviewed individuals with multiple sclerosis, whilst Guest et al.”
- Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective (2020, methodology): “The sample size of 24 has been recommended by Ando, Cousins and Young [20] as sufficient to generate codes for thematic analysis.”