Сравнение на методи
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| Смесени методи със секвенциална интервенция× | Обяснителен последователен смесен метод× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2000s–2010s | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Създател≠ | Creswell & Plano Clark (intervention design framework); extended by health and evaluation researchers | John W. Creswell & Vicki L. Plano Clark |
| Тип | Mixed methods research design | Mixed methods research design |
| Основополагащ източник≠ | 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 |
| Други названия | 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 |
| Свързани≠ | 5 | 6 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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