Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Concurrent Multiphase Mixed Methods× | Объяснительный последовательный дизайн смешанных методов× | |
|---|---|---|
| Область | Дизайн исследования | Дизайн исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2000s–2010s | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Автор метода≠ | Creswell & Plano Clark; Tashakkori & Teddlie | John W. Creswell & Vicki L. Plano Clark |
| Тип | Mixed methods research design | Mixed methods research design |
| Основополагающий источник≠ | 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 |
| Другие названия | concurrent-multiphase design, simultaneous multiphase MMR, parallel multiphase mixed methods, concurrent multistrand design | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Concurrent multiphase mixed methods design combines the structural complexity of multiphase research — spanning several distinct project phases — with concurrent (simultaneous) data collection within each phase. At each stage, quantitative and qualitative data strands are gathered and analyzed in parallel rather than sequentially, and findings are integrated across phases to address a program of interrelated research questions over time. | 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 данных ↗ |
|
|