Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Meta wa Mbinu Zilizochanganywa kwa Leng Lengo la Tathmini× | Muundo wa Mchanganyiko wa Mabadiliko× | |
|---|---|---|
| Nyanja | Muundo wa Utafiti | Muundo wa Utafiti |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2000s–2010s | 2003–2009 |
| Mwanzilishi≠ | 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 |
| Aina≠ | Mixed methods research design variant | Mixed methods research design |
| Chanzo asilia≠ | 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 |
| Majina mbadala | 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 |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | 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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