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| Μήτρα Συνδυασμένων Μεθόδων× | Σχεδιασμός Επεξηγηματικών Διαδοχικών Μεικτών Μεθόδων× | |
|---|---|---|
| Πεδίο | Ερευνητικός Σχεδιασμός | Ερευνητικός Σχεδιασμός |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 2000s–2010s | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Δημιουργός≠ | Teddlie & Tashakkori; Creswell & Plano Clark | John W. Creswell & Vicki L. Plano Clark |
| Τύπος | Mixed methods research design | Mixed methods research design |
| Θεμελιώδης πηγή≠ | 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 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Εναλλακτικές ονομασίες | concurrent MM matrix, simultaneous mixed methods matrix, parallel mixed methods matrix, concurrent matrix mixed design | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Συναφείς | 6 | 6 |
| Σύνοψη≠ | The concurrent mixed methods matrix is a mixed methods design in which quantitative and qualitative data strands are collected simultaneously and organized within a structured matrix framework. The matrix maps design dimensions — such as research questions, data sources, priority, and integration points — across rows and columns, making the logical architecture of the study explicit and auditable. Both strands are analyzed independently before being merged through a matrix-guided integration step. | The explanatory sequential mixed methods design is a two-phase research approach in which a quantitative study is conducted first, and qualitative data are then collected specifically to help explain or elaborate the initial quantitative results. The quantitative phase carries greater priority; the qualitative phase is purposefully built around the findings — such as surprising results, outliers, or statistically significant relationships — that need deeper interpretation. |
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