השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| הסקה מטא-מעורבת דומיננטית-איכותנית× | עיצוב מחקר מעורב שיטתי חלוצי× | |
|---|---|---|
| תחום | תכנון מחקר | תכנון מחקר |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 2003–2010 | 1990s–2000s (codified by ~2007) |
| הוגה השיטה≠ | Abbas Tashakkori & Charles Teddlie | John W. Creswell & Vicki L. Plano Clark |
| סוג≠ | Mixed methods integration strategy | Mixed methods research design |
| מקור מכונן≠ | 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 |
| כינויים | QUAL-dominant meta-inference, qualitative-priority meta-inference, qual-dominant MMR meta-inference, qualitative-weighted mixed methods integration | QUAL → QUAN design, exploratory sequential design, instrument-development design, theory-building mixed methods |
| קשורות | 6 | 6 |
| תקציר≠ | Qualitative-dominant mixed methods meta-inference is the overarching inference-drawing process in a mixed methods study where qualitative findings carry primary explanatory weight. Meta-inference — the integrated conclusion drawn by combining qualitative and quantitative strands — is anchored to and interpreted through the richer, theoretically foregrounded qualitative findings, with quantitative results serving a supplementary, corroborating, or contextualizing function. | The exploratory sequential mixed methods design is a two-phase research framework in which a qualitative phase is conducted first to explore a poorly understood phenomenon, and the findings then inform a subsequent quantitative phase — typically to develop and test a survey instrument, measure a theory, or generalize qualitative insights to a larger population. The qualitative strand guides what is measured; the quantitative strand tests or extends those findings at scale. |
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