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| 설계 기반 다층 혼합 방법론× | 설계 기반 개입 혼합 방법론× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2000s–2010s | 2003–2010s (convergence of DBR and mixed methods traditions) |
| 창시자≠ | Synthesized from Design-Based Research Collective (2003) and Creswell & Plano Clark multilevel mixed methods typology | Design-Based Research Collective; Creswell & Plano Clark (mixed methods framework) |
| 유형≠ | Mixed methods research design | Mixed methods research design variant |
| 원전 | 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 Publications. ISBN: 978-1483344452 |
| 별칭 | DB-MLMM, multilevel design-based mixed methods, design-based multilevel research, DBR multilevel mixed design | DBR intervention mixed methods, design-based intervention study, design experiment with mixed methods, intervention design-based mixed methods |
| 관련≠ | 3 | 6 |
| 요약≠ | Design-based multilevel mixed methods combines the iterative, context-sensitive logic of design-based research (DBR) with the analytical power of multilevel data structures and the explanatory depth of mixed methods research. It is used predominantly in educational and organizational research where participants are nested within settings (e.g., students within classrooms within schools) and where a designed intervention must be tested, refined, and understood at multiple organizational levels simultaneously. | Design-based intervention mixed methods is a research design that embeds both quantitative and qualitative data collection within iterative intervention cycles drawn from design-based research (DBR). The approach systematically tests and refines a practical intervention — typically an educational program, curriculum, or organizational solution — while using qualitative data to explain why and how the intervention works, and quantitative data to assess its measurable impact. Iteration between design, testing, and revision is the hallmark of this approach. |
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