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| 평가 지향 혼합 방법 행렬× | 다단계 혼합 방법 설계× | |
|---|---|---|
| 분야 | 연구설계 | 연구설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2000s (Teddlie & Tashakkori 2009; Greene 2007) | 2007 (first edition of Designing and Conducting Mixed Methods Research) |
| 창시자≠ | Teddlie & Tashakkori (matrix framework); Greene (evaluation-oriented framing) | John W. Creswell & Vicki L. Plano Clark |
| 유형≠ | Mixed methods design variant | Mixed methods research design |
| 원전≠ | Teddlie, C., & Tashakkori, A. (2009). Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. Sage. ISBN: 978-0761930129 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483substitute |
| 별칭 | evaluation MMM, mixed methods display matrix for evaluation, evaluation-focused methods matrix, program evaluation mixed methods matrix | multiphase design, multiproject mixed methods, programmatic mixed methods, multistage mixed methods |
| 관련≠ | 5 | 6 |
| 요약≠ | The evaluation-oriented mixed methods matrix is a structured planning and display tool applied within program evaluation contexts. It maps evaluation questions against data sources, timing, and method types — quantitative and qualitative — in a grid format, making the integration logic explicit and auditable. Rooted in Greene's value-engaged mixed methods tradition and Teddlie and Tashakkori's matrix framework, it serves evaluators who must justify methodological choices to stakeholders while addressing multiple evaluation purposes simultaneously. | The multiphase mixed methods design is a sustained research program in which quantitative and qualitative strands are combined across three or more sequential phases — or across multiple related projects — to address a central program objective. Each phase builds on the prior phase's findings, making the design well-suited to long-term evaluation, intervention development, and large-scale program assessment where a single data-collection cycle cannot fully address the complexity of the research problem. |
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