Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Jaukto metožu matrica× | Jaukto metožu metainference× | |
|---|---|---|
| Nozare | Pētījuma dizains | Pētījuma dizains |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2003–2010 | 1998–2003 |
| Autors≠ | Tashakkori & Teddlie; Onwuegbuzie & Teddlie | Abbas Tashakkori & Charles Teddlie |
| Tips≠ | Research design classification and planning tool | Mixed methods integration procedure |
| Pirmavots≠ | Onwuegbuzie, A. J., & Teddlie, C. (2003). A framework for analyzing data in mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 351-383). Sage. link ↗ | 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 |
| Citi nosaukumi | MMR matrix, mixed-methods design matrix, research design classification matrix, mixed methods typology matrix | meta-inference, mixed methods overall inference, integrated inference, MMR meta-inference |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | The mixed methods matrix is a systematic framework for classifying, planning, and comparing mixed methods research designs along key dimensions such as timing (concurrent vs. sequential), priority (quantitative- vs. qualitative-dominant), and point of integration. It provides researchers with a structured map to make design decisions explicit, communicate choices transparently, and locate a study within the broader mixed methods typology. | Mixed methods meta-inference is the overarching conclusion drawn at the end of a mixed methods study by systematically combining and integrating the separate inferences produced by the quantitative and qualitative strands. It represents the highest-level interpretive act in mixed methods research: moving beyond strand-specific findings to produce a unified, coherent understanding of the research problem that neither strand could yield alone. |
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