Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Disseny mixt seqüencial amb prioritat qualitativa× | Disseny explicatiu seqüencial de mètodes mixts× | |
|---|---|---|
| Camp | Disseny de recerca | Disseny de recerca |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 2000s–2010s | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Autor original≠ | Creswell & Plano Clark; Teddlie & Tashakkori | John W. Creswell & Vicki L. Plano Clark |
| Tipus | Mixed methods research design | Mixed methods research design |
| Font seminal | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 | Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Sage. ISBN: 978-1483344379 |
| Àlies | QUAL-priority sequential design, qualitative-dominant sequential design, qual-first sequential mixed methods, sequential exploratory qualitative-priority design | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Relacionats≠ | 5 | 6 |
| Resum≠ | Sequential qualitative-priority mixed design is a two-phase mixed methods approach in which a qualitative strand is conducted first and carries greater weight in the overall study. The quantitative phase follows and serves to extend, test, or generalize the qualitative findings. The QUAL-first, QUAL-dominant logic makes this design well suited to exploratory research where theory or instruments are underdeveloped and must be grounded in participants' own words before being scaled up. | 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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