Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Inferenza Meta Orientata alla Valutazione con Metodi Misti× | Progettazione Trasformativa a Metodi Misti× | |
|---|---|---|
| Campo | Disegno della ricerca | Disegno della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 2000s–2010s | 2003–2009 |
| Ideatore≠ | Abbas Tashakkori and Charles Teddlie (meta-inference); evaluation-oriented framing associated with Donna M. Mertens and Jennifer C. Greene | Donna M. Mertens; John W. Creswell & Vicki L. Plano Clark |
| Tipo≠ | Mixed methods research design variant | Mixed methods research design |
| Fonte seminale≠ | Tashakkori, A., & Teddlie, C. (Eds.). (2010). SAGE Handbook of Mixed Methods in Social and Behavioral Research (2nd ed.). SAGE Publications. ISBN: 978-1412972666 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Alias | evaluation MMR meta-inference, evaluation-focused meta-inference, mixed methods evaluation inference, meta-inference in evaluation research | transformative design, advocacy mixed methods, emancipatory mixed methods, social-justice mixed methods |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | Evaluation-oriented mixed methods meta-inference is a rigorous concluding process in program evaluation research in which the researcher integrates inferences drawn from both quantitative and qualitative strands of a mixed methods study into a single, coherent, higher-order conclusion. This meta-inference is explicitly anchored to evaluation questions — such as program worth, merit, or impact — and is judged by dual quality criteria: inferential consistency and interpretive consistency across strands. | Transformative mixed methods design embeds a social-justice or advocacy theoretical framework — such as feminism, critical race theory, disability studies, or indigenous worldviews — as the overarching lens that guides every decision about data collection, integration, and use. Both quantitative and qualitative strands serve the goal of advancing equity, challenging power structures, and producing actionable knowledge for marginalized communities. |
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