Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Количественно-приоритетный смешанный метод× | Объяснительный последовательный дизайн смешанных методов× | |
|---|---|---|
| Область | Дизайн исследования | Дизайн исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2003–2009 | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Автор метода≠ | Creswell & Plano Clark; Teddlie & Tashakkori | 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. 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 | QUAN-dominant mixed methods, quantitative-dominant mixed methods, quan-priority design, quantitative-first mixed methods | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Связанные | 6 | 6 |
| Сводка≠ | Quantitative-priority mixed methods design is a research approach in which quantitative data and analysis carry the primary explanatory weight, while qualitative data play a supplementary or corroborating role. The researcher collects and analyzes quantitative data first (or concurrently with greater emphasis), then uses qualitative findings to elaborate, explain, or contextualize the statistical results. Priority and sequence together define where integration occurs and how each strand informs the other. | 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 ↗ |
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