Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Mbinu Mseto ya Uingiliaji× | Muundo wa Mbinu Mchanganyiko wa Maelezo Mfululizo× | |
|---|---|---|
| Nyanja | Muundo wa Utafiti | Muundo wa Utafiti |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2000s–2010s (systematised in Creswell & Plano Clark, 2011–2018) | 2007 (formalized in Creswell & Plano Clark's mixed methods typology) |
| Mwanzilishi | John W. Creswell & Vicki L. Plano Clark | John W. Creswell & Vicki L. Plano Clark |
| Aina | Mixed methods research design | Mixed methods research design |
| Chanzo asilia | 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 |
| Majina mbadala | intervention MMR design, mixed methods intervention study, intervention-embedded mixed design, trial-embedded mixed methods | explanatory sequential design, QUAN → qual design, two-phase explanatory design, sequential explanatory design |
| Zinazohusiana | 6 | 6 |
| Muhtasari≠ | Intervention mixed methods design embeds qualitative data collection within an experimental or quasi-experimental study so that process, mechanism, and participant experience are captured alongside outcome measurement. The quantitative strand tests whether the intervention works; the qualitative strand explains how and why it works — or does not. The two strands may be sequenced before, during, or after the intervention phase, or run concurrently, depending on the research questions. | 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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