方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 实用主义混合方法设计× | 解释性顺序混合方法设计× | |
|---|---|---|
| 领域 | 研究设计 | 研究设计 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | Early 2000s (formalised); pragmatism as philosophy late 19th–early 20th century | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| 提出者≠ | John W. Creswell & Vicki L. Plano Clark (formalised); philosophical grounding in William James, John Dewey, Richard Rorty | John W. Creswell & Vicki L. Plano Clark |
| 类型 | Mixed methods research design | Mixed methods research design |
| 开创性文献≠ | 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 |
| 别名 | pragmatic MMR, pragmatism-guided mixed methods, pragmatic inquiry design, practical mixed methods | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| 相关 | 6 | 6 |
| 摘要≠ | Pragmatic mixed methods design is a research approach that selects and combines quantitative and qualitative methods based on what best answers the research question, rather than adhering to a single philosophical paradigm. Rooted in the philosophical tradition of pragmatism — associated with William James, John Dewey, and later Richard Rorty — it treats methodological fit and practical utility as the primary criteria for design decisions. The approach is endorsed by leading mixed methods scholars including Creswell and Plano Clark as the most common philosophical worldview underpinning mixed methods work. | 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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