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| Phương pháp hỗn hợp tập trung vào trường hợp, ưu tiên định lượng× | Thiết kế phương pháp hỗn hợp giải thích tuần tự× | |
|---|---|---|
| Lĩnh vực | Thiết kế nghiên cứu | Thiết kế nghiên cứu |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 2003–2007 | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Người khởi xướng≠ | Tashakkori & Teddlie (dominant-status typology); Creswell & Plano Clark (design taxonomy) | John W. Creswell & Vicki L. Plano Clark |
| Loại | Mixed methods research design | Mixed methods research design |
| Công trình gốc≠ | Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). Sage. ISBN: 978-1412972666 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Tên gọi khác≠ | QUAN-dominant case study MMR, quantitatively weighted case mixed methods, dominant-status case-centered mixed design | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | Quantitative-dominant case-focused mixed methods organizes a study around one or more clearly bounded cases while assigning primary weight and inferential authority to quantitative data. Qualitative data are collected within the same case boundaries and serve an augmenting, explanatory, or contextual role rather than an equal one. The design is ideal when a case (a school, organization, community, or patient cohort) is the unit of analysis and the core research questions require measurable outcomes that qualitative evidence then helps interpret or explain. | 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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