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	Meta-zaključivanje mešovitih metoda orijentisano na evaluaciju	Dizajn mešovitih metoda sa istovremenom triangulacijom
Oblast	Dizajn istraživanja	Dizajn istraživanja
Porodica	Process / pipeline	Process / pipeline
Godina nastanka	2000s–2010s	2007 (formally named in Creswell & Plano Clark, 1st ed.)
Tvorac	Abbas Tashakkori and Charles Teddlie (meta-inference); evaluation-oriented framing associated with Donna M. Mertens and Jennifer C. Greene	John W. Creswell & Vicki L. Plano Clark
Tip	Mixed methods research design variant	Mixed methods research design
Temeljni izvor	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. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179
Drugi nazivi	evaluation MMR meta-inference, evaluation-focused meta-inference, mixed methods evaluation inference, meta-inference in evaluation research	convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation
Srodne	5	5
Sažetak	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.	The concurrent triangulation mixed methods design collects quantitative and qualitative data simultaneously, analyzes each strand independently, and then merges the results to assess whether the two data sources corroborate one another. Often called the convergent parallel design, it is one of the foundational configurations in mixed methods research and is chosen specifically when the researcher wants to cross-validate or triangulate findings from two distinct methodological traditions.