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| Desain Metode Campuran Dominan Kuantitatif untuk Intervensi× | Desain Metode Campuran Sekuensial Eksplanatori× | |
|---|---|---|
| Bidang | Desain Penelitian | Desain Penelitian |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2007–2011 (codified in Creswell & Plano Clark editions) | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Pencetus≠ | Creswell & Plano Clark (intervention MMD); weighting framework systematized in mixed methods typologies | John W. Creswell & Vicki L. Plano Clark |
| Tipe | Mixed methods research design | Mixed methods research design |
| Sumber perintis | 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 |
| Alias | QUAN-dominant intervention MMD, quantitatively weighted intervention mixed methods, QUAN+qual intervention design, quantitative-priority intervention mixed methods | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Terkait | 6 | 6 |
| Ringkasan≠ | Quantitative-dominant intervention mixed methods design embeds a qualitative component within a predominantly quantitative intervention study — typically a randomized controlled trial or quasi-experiment — where the quantitative strand carries the primary weight in determining efficacy, while the qualitative strand explains the processes, mechanisms, or participant experiences that illuminate why and how the intervention works. | 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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