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Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Σχεδιασμός Μικτών Μεθόδων με Ταυτόχρονη Τριγωνοποίηση× | Σχεδιασμός Επεξηγηματικών Διαδοχικών Μεικτών Μεθόδων× | |
|---|---|---|
| Πεδίο | Ερευνητικός Σχεδιασμός | Ερευνητικός Σχεδιασμός |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 2007 (formally named in Creswell & Plano Clark, 1st ed.) | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Δημιουργός | John W. Creswell & Vicki L. Plano Clark | John W. Creswell & Vicki L. Plano Clark |
| Τύπος | Mixed methods research design | Mixed methods research design |
| Θεμελιώδης πηγή≠ | Creswell, J. W., & Plano Clark, V. L. (2011). Designing and Conducting Mixed Methods Research (2nd ed.). Sage. ISBN: 978-1412975179 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Εναλλακτικές ονομασίες | convergent parallel design, triangulation design, QUAN+QUAL concurrent design, simultaneous triangulation | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Συναφείς≠ | 5 | 6 |
| Σύνοψη≠ | 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. | 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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