Data Saturation in Qualitative Research
Data saturation is a foundational principle in qualitative research describing the point at which data collection yields no new themes, codes, or insights—additional data becomes redundant. Introduced by Glaser and Strauss (1967) in their work on grounded theory, saturation guides decisions about sample size and when to stop recruiting participants. Saturation is not a fixed number but a dynamic endpoint determined by examining whether new data are adding substantively new information. The concept is central to claims of rigor and theoretical adequacy in qualitative research, signaling that the researcher has gathered sufficient data to understand the phenomenon in depth.
Catatan sumber
Kutipan disalin apa adanya dari catatan sumber metode. Tidak ada verifikasi tingkat klaim yang disimpulkan darinya.
- Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine. · ISBN 978-0202302560
- Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory (2nd ed.). SAGE Publications. · ISBN 978-0803959393
- Bowen, G. A. (2008). Naturalistic inquiry and saturation (S): Determining when enough is enough. Journal of Research in Education, 18(1), 137-152. · URL
- Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82. · DOI 10.1177/1525822X05279903
Klaim yang dikurasi
Klaim tersimpan dalam buku besar bukti, masing-masing dengan penilaiannya sendiri.
Tampilan ini tidak menciptakan penilaian klaim ketika buku besar tidak memilikinya.
Metode terkait
Dihasilkan dari grafik metode dan ditampilkan sebagai relasi yang disarankan mesin — tidak ada klaim bukti yang disimpulkan.