Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Матрица за смесени методи× | Обяснителен последователен смесен метод× | |
|---|---|---|
| Област | Дизайн на изследването | Дизайн на изследването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2003–2010 | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Създател≠ | Tashakkori & Teddlie; Onwuegbuzie & Teddlie | John W. Creswell & Vicki L. Plano Clark |
| Тип≠ | Research design classification and planning tool | Mixed methods research design |
| Основополагащ източник≠ | Onwuegbuzie, A. J., & Teddlie, C. (2003). A framework for analyzing data in mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 351-383). Sage. link ↗ | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Други названия | MMR matrix, mixed-methods design matrix, research design classification matrix, mixed methods typology matrix | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Свързани | 6 | 6 |
| Резюме≠ | The mixed methods matrix is a systematic framework for classifying, planning, and comparing mixed methods research designs along key dimensions such as timing (concurrent vs. sequential), priority (quantitative- vs. qualitative-dominant), and point of integration. It provides researchers with a structured map to make design decisions explicit, communicate choices transparently, and locate a study within the broader mixed methods typology. | 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 ↗ |
|
|