Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sekvenciālas intervences jauktās metodes× | Diferencētā secīgā jauktās metodes dizains× | |
|---|---|---|
| Nozare | Pētījuma dizains | Pētījuma dizains |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2000s–2010s | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Autors≠ | Creswell & Plano Clark (intervention design framework); extended by health and evaluation researchers | John W. Creswell & Vicki L. Plano Clark |
| Tips | Mixed methods research design | Mixed methods research design |
| Pirmavots≠ | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications. ISBN: 978-1483344379 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Citi nosaukumi | sequential intervention MMR, intervention-embedded sequential design, sequential mixed methods intervention study, sequential clinical trial mixed methods | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | Sequential intervention mixed methods is a research design in which quantitative and qualitative data collection phases are arranged in sequence — one after the other — within the context of a planned intervention or experimental study. The sequencing allows each phase to build on the other: quantitative data may establish whether an intervention works, while qualitative data explain how and why it works (or does not) for specific participants or contexts. | The explanatory sequential mixed methods design is a two-phase research approach in which a quantitative study is conducted first, and qualitative data are then collected specifically to help explain or elaborate the initial quantitative results. The quantitative phase carries greater priority; the qualitative phase is purposefully built around the findings — such as surprising results, outliers, or statistically significant relationships — that need deeper interpretation. |
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